diff --git a/CHANGELOG.md b/CHANGELOG.md
index 6e46f53d..44d379c3 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,6 +1,6 @@
 # @vladmandic/human  
 
-Version: **1.3.4**  
+Version: **1.3.5**  
 Description: **Human: AI-powered 3D Face Detection, Face Description & Recognition, Body Pose Tracking, Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction & Gesture Recognition**  
 
 Author: **Vladimir Mandic <mandic00@live.com>**  
@@ -9,7 +9,7 @@ Repository: **<git+https://github.com/vladmandic/human.git>**
 
 ## Changelog
 
-### **HEAD -> main** 2021/04/06 mandic00@live.com
+### **1.3.5** 2021/04/06 mandic00@live.com
 
 - add dynamic viewport and fix web worker
 - add cdn links
diff --git a/demo/index.html b/demo/index.html
index 79db69e7..8d2124eb 100644
--- a/demo/index.html
+++ b/demo/index.html
@@ -11,6 +11,7 @@
     <link rel="manifest" href="./manifest.webmanifest">
     <link rel="shortcut icon" href="../favicon.ico" type="image/x-icon">
     <link rel="apple-touch-icon" href="../assets/icon.png">
+    <!-- <script src="../node_modules/@tensorflow/tfjs/dist/tf.es2017.js"></script> -->
     <script src="./index.js" type="module"></script>
     <style>
       @font-face { font-family: 'Lato'; font-display: swap; font-style: normal; font-weight: 100; src: local('Lato'), url('../assets/lato-light.woff2') }
diff --git a/demo/index.js b/demo/index.js
index 3c1665e0..5471f67b 100644
--- a/demo/index.js
+++ b/demo/index.js
@@ -1,5 +1,6 @@
+/* global tf */
 import Human from '../dist/human.esm.js'; // equivalent of @vladmandic/human
-// import Human from '../src/human'; // import sources directly
+// import Human from '../dist/human.esm-nobundle.js'; // this requires that tf is loaded manually and bundled before human can be used
 import Menu from './helpers/menu.js';
 import GLBench from './helpers/gl-bench.js';
 
@@ -28,8 +29,6 @@ const userConfig = {
 };
 */
 
-const human = new Human(userConfig);
-
 // ui options
 const ui = {
   baseBackground: 'rgba(50, 50, 50, 1)', // 'grey'
@@ -90,6 +89,12 @@ function status(msg) {
   if (div) div.innerText = msg;
 }
 
+const human = new Human(userConfig);
+if (typeof tf !== 'undefined') {
+  log('TensorFlow external version:', tf.version);
+  human.tf = tf; // use externally loaded version of tfjs
+}
+
 const compare = { enabled: false, original: null };
 async function calcSimmilariry(result) {
   document.getElementById('compare-container').style.display = compare.enabled ? 'block' : 'none';
@@ -190,7 +195,7 @@ async function setupCamera() {
   if (ui.busy) return null;
   ui.busy = true;
   const viewportScale = Math.min(1, Math.round(100 * window.outerWidth / 700) / 100);
-  log('demo viewport scale:', viewportScale);
+  // log('demo viewport scale:', viewportScale);
   document.querySelector('meta[name=viewport]').setAttribute('content', `width=device-width, shrink-to-fit=no; initial-scale=${viewportScale}`);
   const video = document.getElementById('video');
   const canvas = document.getElementById('canvas');
diff --git a/dist/human.esm-nobundle.js b/dist/human.esm-nobundle.js
index 9ebc5ad3..0a96f543 100644
--- a/dist/human.esm-nobundle.js
+++ b/dist/human.esm-nobundle.js
@@ -5,14 +5,14 @@
   author: <https://github.com/vladmandic>'
   */
 
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I0=[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],Z0=[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],L0=[33,133,362,263,1,78,308],hr=I0.map(t=>le[t]),ir=Z0.map(t=>le[t]),ar=L0.map(t=>le[t]);var Pt=Y.leftEyeLower0,vt=Y.rightEyeLower0,se={leftBounds:[Pt[0],Pt[Pt.length-1]],rightBounds:[vt[0],vt[vt.length-1]]},Ve={count:468,mouth:13,symmetryLine:[13,Y.midwayBetweenEyes[0]]},P1={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},he={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function He(t,e,n,c){for(let r=0;r<Tt.length;r++){let{key:o,indices:_}=Tt[r],s=Y[`${n}${o}`];if(!c||c.includes(o))for(let h=0;h<_.length;h++){let a=_[h];t[s[h]]=[e[a][0],e[a][1],(e[a][2]+t[s[h]][2])/2]}}}var Mt=class{constructor(e,n,c){var r,o;this.storedBoxes=[],this.boundingBoxDetector=e,this.meshDetector=n,this.irisModel=c,this.boxSize=((r=e==null?void 0:e.model)==null?void 0:r.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((o=e==null?void 0:e.model)==null?void 0:o.inputs[0].shape[2]),this.irisSize=(c==null?void 0:c.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(e,n,c,r){let o=we({startPoint:n.startPoint,endPoint:n.endPoint}),_=e.map(i=>[o[0]/this.meshSize*(i[0]-this.meshSize/2),o[1]/this.meshSize*(i[1]-this.meshSize/2),i[2]]),s=c!==0?Le(c,[0,0]):Ze,h=c!==0?_.map(i=>[...T1(i,s),i[2]]):_,a=c!==0?g1(r):Ze,x=[..._e({startPoint:n.startPoint,endPoint:n.endPoint}),1];return h.map(i=>[i[0]+D(x,a[0]),i[1]+D(x,a[1]),i[2]])}getLeftToRightEyeDepthDifference(e){let n=e[se.leftBounds[0]][2],c=e[se.rightBounds[0]][2];return n-c}getEyeBox(e,n,c,r,o=!1){let _=Ie(Oe(this.calculateLandmarksBoundingBox([e[c],e[r]]),this.irisEnlarge)),s=we(_),h=A.image.cropAndResize(n,[[_.startPoint[1]/this.meshSize,_.startPoint[0]/this.meshSize,_.endPoint[1]/this.meshSize,_.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return o&&A.ENV.flags.IS_BROWSER&&(h=A.image.flipLeftRight(h)),{box:_,boxSize:s,crop:h}}getEyeCoords(e,n,c,r=!1){let o=[];for(let _=0;_<he.numCoordinates;_++){let s=e[_*3],h=e[_*3+1],a=e[_*3+2];o.push([(r?1-s/this.irisSize:s/this.irisSize)*c[0]+n.startPoint[0],h/this.irisSize*c[1]+n.startPoint[1],a])}return{rawCoords:o,iris:o.slice(he.index)}}getAdjustedIrisCoords(e,n,c){let r=e[Y[`${c}EyeUpper0`][he.upperCenter]][2],o=e[Y[`${c}EyeLower0`][he.lowerCenter]][2],_=(r+o)/2;return n.map((s,h)=>{let a=_;return h===2?a=r:h===4&&(a=o),[s[0],s[1],a]})}async predict(e,n){let c=!1,r;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(r=await this.boundingBoxDetector.getBoundingBoxes(e),this.skipped=0),n.videoOptimized&&this.skipped++,!n.videoOptimized||r&&r.boxes&&(!n.face.mesh.enabled||r.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let _ of r.boxes)this.storedBoxes.push({startPoint:_.box.startPoint.dataSync(),endPoint:_.box.endPoint.dataSync(),landmarks:_.landmarks,confidence:_.confidence});this.storedBoxes.length>0&&(c=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),c){if(!r||!r.boxes||r.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let _=0;_<this.storedBoxes.length;_++){let s=p1({startPoint:this.storedBoxes[_].startPoint,endPoint:this.storedBoxes[_].endPoint},r.scaleFactor),h=Oe(s),a=Ie(h),x=this.storedBoxes[_].landmarks.arraySync(),i=this.storedBoxes[_].confidence;this.storedBoxes[_]={...a,confidence:i,landmarks:x}}}r&&r.boxes&&r.boxes.forEach(_=>{_.box.startPoint.dispose(),_.box.endPoint.dispose(),_.landmarks.dispose()});let o=A.tidy(()=>this.storedBoxes.map((_,s)=>{let h=_.confidence,a,x=0,i;if(n.face.detector.rotation&&n.face.mesh.enabled&&A.ENV.flags.IS_BROWSER){let[g,d]=_.landmarks.length>=Ve.count?Ve.symmetryLine:P1.symmetryLine;x=gt(_.landmarks[g],_.landmarks[d]);let T=_e({startPoint:_.startPoint,endPoint:_.endPoint}),M=[T[0]/e.shape[2],T[1]/e.shape[1]],E=A.image.rotateWithOffset(e,x,0,M);i=Le(-x,T),n.face.mesh.enabled?a=oe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.meshSize,this.meshSize]).div(255):a=oe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.boxSize,this.boxSize]).div(255)}else{i=Ze;let g=e.clone();n.face.mesh.enabled?a=oe({startPoint:_.startPoint,endPoint:_.endPoint},g,[this.meshSize,this.meshSize]).div(255):a=oe({startPoint:_.startPoint,endPoint:_.endPoint},g,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:_,faceConfidence:null,boxConfidence:h,confidence:_.confidence,image:a};let[,w,u]=this.meshDetector.predict(a),b=w.dataSync()[0];if(b<n.face.detector.minConfidence)return null;let m=A.reshape(u,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:g,boxSize:d,crop:T}=this.getEyeBox(m,a,se.leftBounds[0],se.leftBounds[1],!0),{box:M,boxSize:E,crop:N}=this.getEyeBox(m,a,se.rightBounds[0],se.rightBounds[1]),Z=this.irisModel.predict(A.concat([T,N])).dataSync(),rt=Z.slice(0,he.numCoordinates*3),{rawCoords:Te,iris:ee}=this.getEyeCoords(rt,g,d,!0),a0=Z.slice(he.numCoordinates*3),{rawCoords:s1,iris:x0}=this.getEyeCoords(a0,M,E),h1=this.getLeftToRightEyeDepthDifference(m);Math.abs(h1)<30?(He(m,Te,"left",null),He(m,s1,"right",null)):h1<1?He(m,Te,"left",["EyeUpper0","EyeLower0"]):He(m,s1,"right",["EyeUpper0","EyeLower0"]);let y0=this.getAdjustedIrisCoords(m,ee,"left"),w0=this.getAdjustedIrisCoords(m,x0,"right");m=m.concat(y0).concat(w0)}let p=this.transformRawCoords(m,_,x,i);_=Oe(this.calculateLandmarksBoundingBox(p),1.5);let v=A.tensor2d(p);if(n.face.detector.rotation&&n.face.mesh.enabled&&(n.face.description.enabled||n.face.embedding.enabled)&&A.ENV.flags.IS_BROWSER){let[g,d]=_.landmarks.length>=Ve.count?Ve.symmetryLine:P1.symmetryLine;x=gt(_.landmarks[g],_.landmarks[d]);let T=_e({startPoint:_.startPoint,endPoint:_.endPoint}),M=[T[0]/e.shape[2],T[1]/e.shape[1]],E=A.image.rotateWithOffset(e,x,0,M);i=Le(-x,T),a=oe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.meshSize,this.meshSize]).div(255)}let R={coords:v,box:_,faceConfidence:b,boxConfidence:h,image:a,rawCoords:m},j=Ie(_);return this.storedBoxes[s]={...j,landmarks:p,confidence:_.confidence,faceConfidence:b},R}));return o=o.filter(_=>_!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(_=>_.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=o.length,o}calculateLandmarksBoundingBox(e){let n=e.map(_=>_[0]),c=e.map(_=>_[1]),r=[Math.min(...n),Math.min(...c)],o=[Math.max(...n),Math.max(...c)];return{startPoint:r,endPoint:o,landmarks:e}}};var Et=class{constructor(e,n,c,r){this.facePipeline=new Mt(e,n,c),this.config=r}async estimateFaces(e,n){let c=await this.facePipeline.predict(e,n),r=[];for(let o of c||[]){if(o.isDisposedInternal)continue;let _=o.coords?o.coords.arraySync():[],s=_.map(i=>[i[0]/e.shape[2],i[1]/e.shape[1],i[2]/this.facePipeline.meshSize]),h={};if(_&&_.length>0)for(let i of Object.keys(Y))h[i]=Y[i].map(w=>_[w]);let a=o.box?[Math.max(0,o.box.startPoint[0]),Math.max(0,o.box.startPoint[1]),Math.min(e.shape[2],o.box.endPoint[0])-Math.max(0,o.box.startPoint[0]),Math.min(e.shape[1],o.box.endPoint[1])-Math.max(0,o.box.startPoint[1])]:0,x=o.box?[o.box.startPoint[0]/e.shape[2],o.box.startPoint[1]/e.shape[1],(o.box.endPoint[0]-o.box.startPoint[0])/e.shape[2],(o.box.endPoint[1]-o.box.startPoint[1])/e.shape[1]]:[];r.push({confidence:Math.round(100*o.faceConfidence||100*o.boxConfidence||0)/100,boxConfidence:Math.round(100*o.boxConfidence)/100,faceConfidence:Math.round(100*o.faceConfidence)/100,box:a,boxRaw:x,mesh:_,meshRaw:s,annotations:h,image:o.image?o.image.clone():null}),o.coords&&o.coords.dispose(),o.image&&o.image.dispose()}return r}},re=[null,null,null];async function Rt(t){re=await Promise.all([!re[0]&&t.face.enabled?m1(t):null,!re[1]&&t.face.mesh.enabled?A.loadGraphModel(t.face.mesh.modelPath,{fromTFHub:t.face.mesh.modelPath.includes("tfhub.dev")}):null,!re[2]&&t.face.iris.enabled?A.loadGraphModel(t.face.iris.modelPath,{fromTFHub:t.face.iris.modelPath.includes("tfhub.dev")}):null]);let e=new Et(re[0],re[1],re[2],t);return t.face.mesh.enabled&&t.debug&&P(`load model: ${t.face.mesh.modelPath.match(/\/(.*)\./)[1]}`),t.face.iris.enabled&&t.debug&&P(`load model: ${t.face.iris.modelPath.match(/\/(.*)\./)[1]}`),e}var v1=ne,M1=le;var Vt={};F(Vt,{PoseNet:()=>Ht,load:()=>Xt});function V0(t){let[e,n,c,r]=t;return{offsets:e,heatmap:n,displacementFwd:c,displacementBwd:r}}var St=class{constructor(e){this.model=e}predict(e){return A.tidy(()=>{let c=e.toFloat().div(127.5).sub(1).expandDims(0),o=this.model.predict(c).map(s=>s.squeeze([0])),_=V0(o);return{heatmapScores:_.heatmap.sigmoid(),offsets:_.offsets,displacementFwd:_.displacementFwd,displacementBwd:_.displacementBwd}})}dispose(){this.model.dispose()}};function jt(t){return Math.floor(t/2)}var Wt=class{constructor(e,n){this.priorityQueue=new Array(e),this.numberOfElements=-1,this.getElementValue=n}enqueue(e){this.priorityQueue[++this.numberOfElements]=e,this.swim(this.numberOfElements)}dequeue(){let e=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,e}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(e){for(;e>0&&this.less(jt(e),e);)this.exchange(e,jt(e)),e=jt(e)}sink(e){for(;2*e<=this.numberOfElements;){let n=2*e;if(n<this.numberOfElements&&this.less(n,n+1)&&n++,!this.less(e,n))break;this.exchange(e,n),e=n}}getValueAt(e){return this.getElementValue(this.priorityQueue[e])}less(e,n){return this.getValueAt(e)<this.getValueAt(n)}exchange(e,n){let c=this.priorityQueue[e];this.priorityQueue[e]=this.priorityQueue[n],this.priorityQueue[n]=c}};function H0(t,e,n,c,r,o){let[_,s]=o.shape,h=!0,a=Math.max(n-r,0),x=Math.min(n+r+1,_);for(let i=a;i<x;++i){let w=Math.max(c-r,0),u=Math.min(c+r+1,s);for(let b=w;b<u;++b)if(o.get(i,b,t)>e){h=!1;break}if(!h)break}return h}function z1(t,e,n){let[c,r,o]=n.shape,_=new Wt(c*r*o,({score:s})=>s);for(let s=0;s<c;++s)for(let h=0;h<r;++h)for(let a=0;a<o;++a){let x=n.get(s,h,a);x<t||H0(a,x,s,h,e,n)&&_.enqueue({score:x,part:{heatmapY:s,heatmapX:h,id:a}})}return _}var ie=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],ae=ie.length,de=ie.reduce((t,e,n)=>(t[e]=n,t),{}),X0=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],Er=X0.map(([t,e])=>[de[t],de[e]]),E1=[["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 kt(t,e,n,c){return{y:c.get(t,e,n),x:c.get(t,e,n+ae)}}function Xe(t,e,n){let{heatmapY:c,heatmapX:r,id:o}=t,{y:_,x:s}=kt(c,r,o,n);return{x:t.heatmapX*e+s,y:t.heatmapY*e+_}}function Nt(t,e,n){return t<e?e:t>n?n:t}function R1(t,e,n,c){let r=n-t,o=c-e;return r*r+o*o}function Ot(t,e){return{x:t.x+e.x,y:t.y+e.y}}function S1(t,e){let n=e.shape[0],c=new Float32Array(n);for(let r=0;r<n;r++){let o=e.get(r,0),_=e.get(r,1);c[r]=t.get(o,_,r)}return c}function F0(t,e,n,c){return{y:c.get(t,e,n),x:c.get(t,e,n+ae)}}function q0(t,e){let n=[];for(let c=0;c<ae;c++){let r=t.get(c,0).valueOf(),o=t.get(c,1).valueOf(),{x:_,y:s}=F0(r,o,c,e);n.push(s),n.push(_)}return A.tensor2d(n,[ae,2])}function j1(t,e,n){return A.tidy(()=>t.toTensor().mul(A.scalar(e,"int32")).toFloat().add(q0(t,n)))}function C0(t,e){return A.tidy(()=>{let n=t.div(A.scalar(e,"int32"));return t.sub(n.mul(A.scalar(e,"int32")))})}function W1(t){let[e,n,c]=t.shape;return A.tidy(()=>{let o=t.reshape([e*n,c]).argMax(0),_=o.div(A.scalar(n,"int32")).expandDims(1),s=C0(o,n).expandDims(1);return A.concat([_,s],1)})}var k1=E1.map(([t,e])=>[de[t],de[e]]),It=k1.map(([,t])=>t),N1=k1.map(([t])=>t),B0=16;function Y0(t,e,n){let c=n.shape[2]/2;return{y:n.get(e.y,e.x,t),x:n.get(e.y,e.x,c+t)}}function Zt(t,e,n,c){return{y:Nt(Math.round(t.y/e),0,n-1),x:Nt(Math.round(t.x/e),0,c-1)}}function O1(t,e,n,c,r,o,_,s=2){let[h,a]=c.shape,x=Zt(e.position,o,h,a),i=Y0(t,x,_),u=Ot(e.position,i);for(let m=0;m<s;m++){let p=Zt(u,o,h,a),v=kt(p.y,p.x,n,r);u=Ot({x:p.x*o,y:p.y*o},{x:v.x,y:v.y})}let b=Zt(u,o,h,a),y=c.get(b.y,b.x,n);return{position:u,part:ie[n],score:y}}function I1(t,e,n,c,r,o){let _=e.shape[2],s=It.length,h=new Array(_),{part:a,score:x}=t,i=Xe(a,c,n);h[a.id]={score:x,part:ie[a.id],position:i};for(let w=s-1;w>=0;--w){let u=It[w],b=N1[w];h[u]&&!h[b]&&(h[b]=O1(w,h[u],b,e,n,c,o))}for(let w=0;w<s;++w){let u=N1[w],b=It[w];h[u]&&!h[b]&&(h[b]=O1(w,h[u],b,e,n,c,r))}return h}async function Z1(t,e,n){let c=0,r=W1(t),o=await Promise.all([t.buffer(),e.buffer(),r.buffer()]),_=o[0],s=o[1],h=o[2],a=j1(h,B0,s),x=await a.buffer(),w=Array.from(S1(_,h)).map((b,y)=>(c+=b,{position:{y:x.get(y,0),x:x.get(y,1)},part:ie[y],score:b})),u=w.filter(b=>b.score>n);return r.dispose(),a.dispose(),{keypoints:u,score:c/w.length}}var J0=1,L1=16;function V1(t,e,{x:n,y:c},r){return t.some(({keypoints:o})=>{let _=o[r].position;return R1(c,n,_.y,_.x)<=e})}function K0(t,e,n){return n.reduce((r,{position:o,score:_},s)=>(V1(t,e,o,s)||(r+=_),r),0)/n.length}function H1(t,e,n,c,r,o,_){let s=[],h=z1(_,J0,t),a=r^2;for(;s.length<o&&!h.empty();){let x=h.dequeue(),i=Xe(x.part,L1,e);if(V1(s,a,i,x.part.id))continue;let w=I1(x,t,e,L1,n,c),u=K0(s,a,w);u>_&&s.push({keypoints:w,score:Math.round(100*u)/100})}return s}async function X1(t){return Promise.all(t.map(e=>e.buffer()))}function U0(t,e,n){return{score:t.score,keypoints:t.keypoints.map(({score:c,part:r,position:o})=>({score:c,part:r,position:{x:Math.trunc(o.x*n),y:Math.trunc(o.y*e)}}))}}function F1(t,[e,n]){let c=t.squeeze(0),r=c.resizeBilinear([e,n]);return c.dispose(),r}function Lt(t,[e,n],[c,r]){return t.map(_=>U0(_,e/c,n/r))}async function D0(t,e,n,c){return new Promise(async r=>{let o=await X1([e.heatmapScores,e.offsets,e.displacementFwd,e.displacementBwd]),_=o[0],s=o[1],h=o[2],a=o[3],x=await H1(_,s,h,a,n.body.nmsRadius,n.body.maxDetections,n.body.scoreThreshold),i=Lt(x,[t.shape[1],t.shape[2]],[c,c]);r(i)})}async function G0(t,e,n,c){return new Promise(async r=>{let o=await Z1(e.heatmapScores,e.offsets,n.body.scoreThreshold),_=Lt([o],[t.shape[1],t.shape[2]],[c,c]);r(_)})}var Ht=class{constructor(e){this.baseModel=e,this.inputSize=e.model.inputs[0].shape[1],this.inputSize<128&&(this.inputSize=257)}async estimatePoses(e,n){let c=F1(e,[this.inputSize,this.inputSize]),r=this.baseModel.predict(c,n),o=n.body.maxDetections<2?await G0(e,r,n,this.inputSize):await D0(e,r,n,this.inputSize);return r.heatmapScores.dispose(),r.offsets.dispose(),r.displacementFwd.dispose(),r.displacementBwd.dispose(),c.dispose(),o}dispose(){this.baseModel.dispose()}};async function Xt(t){let e=await A.loadGraphModel(t.body.modelPath),n=new St(e);return t.debug&&P(`load model: ${t.body.modelPath.match(/\/(.*)\./)[1]}`),new Ht(n)}var Yt={};F(Yt,{HandPose:()=>Kt,load:()=>Ut});function Fe(t){return[Math.abs(t.endPoint[0]-t.startPoint[0]),Math.abs(t.endPoint[1]-t.startPoint[1])]}function fe(t){return[t.startPoint[0]+(t.endPoint[0]-t.startPoint[0])/2,t.startPoint[1]+(t.endPoint[1]-t.startPoint[1])/2]}function q1(t,e,n){let c=e.shape[1],r=e.shape[2],o=[[t.startPoint[1]/c,t.startPoint[0]/r,t.endPoint[1]/c,t.endPoint[0]/r]];return A.image.cropAndResize(e,o,[0],n)}function C1(t,e){let n=[t.startPoint[0]*e[0],t.startPoint[1]*e[1]],c=[t.endPoint[0]*e[0],t.endPoint[1]*e[1]],r=t.palmLandmarks.map(o=>[o[0]*e[0],o[1]*e[1]]);return{startPoint:n,endPoint:c,palmLandmarks:r,confidence:t.confidence}}function qe(t,e=1.5){let n=fe(t),c=Fe(t),r=[e*c[0]/2,e*c[1]/2],o=[n[0]-r[0],n[1]-r[1]],_=[n[0]+r[0],n[1]+r[1]];return{startPoint:o,endPoint:_,palmLandmarks:t.palmLandmarks}}function Ce(t){let e=fe(t),n=Fe(t),r=Math.max(...n)/2,o=[e[0]-r,e[1]-r],_=[e[0]+r,e[1]+r];return{startPoint:o,endPoint:_,palmLandmarks:t.palmLandmarks}}var Ft=class{constructor(e,n,c){this.model=e,this.anchors=c.map(r=>[r.x_center,r.y_center]),this.anchorsTensor=A.tensor2d(this.anchors),this.inputSize=n,this.inputSizeTensor=A.tensor1d([n,n]),this.doubleInputSizeTensor=A.tensor1d([n*2,n*2])}normalizeBoxes(e){return A.tidy(()=>{let 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n=e.map(_=>_[0]),c=e.map(_=>_[1]),r=[Math.min(...n),Math.min(...c)],o=[Math.max(...n),Math.max(...c)];return{startPoint:r,endPoint:o}}};var 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Q1=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],$1=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var H;async function Gt(t){return H||(H=await A.loadGraphModel(t.body.modelPath),H.width=parseInt(H.signature.inputs["input_1:0"].tensorShape.dim[2].size),H.height=parseInt(H.signature.inputs["input_1:0"].tensorShape.dim[1].size),t.debug&&P(`load model: ${t.body.modelPath.match(/\/(.*)\./)[1]}`)),H}async function Qt(t,e){if(!H||!e.body.enabled)return null;let n={width:t.shape[2],height:t.shape[1]},c=A.image.resizeBilinear(t,[H.width,H.height],!1),r=A.div(c,[255]);c.dispose();let o;if(e.profile){let x=await A.profile(()=>H.predict(r));o=x.result.find(i=>i.size===195||i.size===155).dataSync(),x.result.forEach(i=>i.dispose()),I("blazepose",x)}else{let x=await H.predict(r);o=x.find(i=>i.size===195||i.size===155).dataSync(),x.forEach(i=>i.dispose())}r.dispose();let _=[],s=o.length===195?Q1:$1,h=5;for(let 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I0=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],Z0=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],L0=[33,133,362,263,1,78,308],cr=I0.map(t=>le[t]),Ar=Z0.map(t=>le[t]),_r=L0.map(t=>le[t]);var Pt=Y.leftEyeLower0,vt=Y.rightEyeLower0,se={leftBounds:[Pt[0],Pt[Pt.length-1]],rightBounds:[vt[0],vt[vt.length-1]]},Ve={count:468,mouth:13,symmetryLine:[13,Y.midwayBetweenEyes[0]]},R1={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},he={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function He(t,e,n,c){for(let r=0;r<Tt.length;r++){let{key:o,indices:_}=Tt[r],s=Y[`${n}${o}`];if(!c||c.includes(o))for(let h=0;h<_.length;h++){let a=_[h];t[s[h]]=[e[a][0],e[a][1],(e[a][2]+t[s[h]][2])/2]}}}var Mt=class{constructor(e,n,c){var r,o;this.storedBoxes=[],this.boundingBoxDetector=e,this.meshDetector=n,this.irisModel=c,this.boxSize=((r=e==null?void 0:e.model)==null?void 0:r.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((o=e==null?void 0:e.model)==null?void 0:o.inputs[0].shape[2]),this.irisSize=(c==null?void 0:c.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(e,n,c,r){let o=we({startPoint:n.startPoint,endPoint:n.endPoint}),_=e.map(i=>[o[0]/this.meshSize*(i[0]-this.meshSize/2),o[1]/this.meshSize*(i[1]-this.meshSize/2),i[2]]),s=c!==0?Le(c,[0,0]):Ze,h=c!==0?_.map(i=>[...E1(i,s),i[2]]):_,a=c!==0?z1(r):Ze,x=[..._e({startPoint:n.startPoint,endPoint:n.endPoint}),1];return h.map(i=>[i[0]+D(x,a[0]),i[1]+D(x,a[1]),i[2]])}getLeftToRightEyeDepthDifference(e){let n=e[se.leftBounds[0]][2],c=e[se.rightBounds[0]][2];return n-c}getEyeBox(e,n,c,r,o=!1){let _=Ie(Oe(this.calculateLandmarksBoundingBox([e[c],e[r]]),this.irisEnlarge)),s=we(_),h=A.image.cropAndResize(n,[[_.startPoint[1]/this.meshSize,_.startPoint[0]/this.meshSize,_.endPoint[1]/this.meshSize,_.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return o&&A.ENV.flags.IS_BROWSER&&(h=A.image.flipLeftRight(h)),{box:_,boxSize:s,crop:h}}getEyeCoords(e,n,c,r=!1){let o=[];for(let _=0;_<he.numCoordinates;_++){let s=e[_*3],h=e[_*3+1],a=e[_*3+2];o.push([(r?1-s/this.irisSize:s/this.irisSize)*c[0]+n.startPoint[0],h/this.irisSize*c[1]+n.startPoint[1],a])}return{rawCoords:o,iris:o.slice(he.index)}}getAdjustedIrisCoords(e,n,c){let r=e[Y[`${c}EyeUpper0`][he.upperCenter]][2],o=e[Y[`${c}EyeLower0`][he.lowerCenter]][2],_=(r+o)/2;return n.map((s,h)=>{let a=_;return h===2?a=r:h===4&&(a=o),[s[0],s[1],a]})}async predict(e,n){let c=!1,r;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(r=await this.boundingBoxDetector.getBoundingBoxes(e),this.skipped=0),n.videoOptimized&&this.skipped++,!n.videoOptimized||r&&r.boxes&&(!n.face.mesh.enabled||r.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let _ of r.boxes)this.storedBoxes.push({startPoint:_.box.startPoint.dataSync(),endPoint:_.box.endPoint.dataSync(),landmarks:_.landmarks,confidence:_.confidence});this.storedBoxes.length>0&&(c=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),c){if(!r||!r.boxes||r.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let _=0;_<this.storedBoxes.length;_++){let s=P1({startPoint:this.storedBoxes[_].startPoint,endPoint:this.storedBoxes[_].endPoint},r.scaleFactor),h=Oe(s),a=Ie(h),x=this.storedBoxes[_].landmarks.arraySync(),i=this.storedBoxes[_].confidence;this.storedBoxes[_]={...a,confidence:i,landmarks:x}}}r&&r.boxes&&r.boxes.forEach(_=>{_.box.startPoint.dispose(),_.box.endPoint.dispose(),_.landmarks.dispose()});let o=A.tidy(()=>this.storedBoxes.map((_,s)=>{let h=_.confidence,a,x=0,i;if(n.face.detector.rotation&&n.face.mesh.enabled&&A.ENV.flags.IS_BROWSER){let[g,d]=_.landmarks.length>=Ve.count?Ve.symmetryLine:R1.symmetryLine;x=gt(_.landmarks[g],_.landmarks[d]);let T=_e({startPoint:_.startPoint,endPoint:_.endPoint}),M=[T[0]/e.shape[2],T[1]/e.shape[1]],E=A.image.rotateWithOffset(e,x,0,M);i=Le(-x,T),n.face.mesh.enabled?a=oe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.meshSize,this.meshSize]).div(255):a=oe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.boxSize,this.boxSize]).div(255)}else{i=Ze;let g=e.clone();n.face.mesh.enabled?a=oe({startPoint:_.startPoint,endPoint:_.endPoint},g,[this.meshSize,this.meshSize]).div(255):a=oe({startPoint:_.startPoint,endPoint:_.endPoint},g,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:_,faceConfidence:null,boxConfidence:h,confidence:_.confidence,image:a};let[,w,u]=this.meshDetector.predict(a),b=w.dataSync()[0];if(b<n.face.detector.minConfidence)return null;let m=A.reshape(u,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:g,boxSize:d,crop:T}=this.getEyeBox(m,a,se.leftBounds[0],se.leftBounds[1],!0),{box:M,boxSize:E,crop:N}=this.getEyeBox(m,a,se.rightBounds[0],se.rightBounds[1]),Z=this.irisModel.predict(A.concat([T,N])).dataSync(),rt=Z.slice(0,he.numCoordinates*3),{rawCoords:Te,iris:ee}=this.getEyeCoords(rt,g,d,!0),d0=Z.slice(he.numCoordinates*3),{rawCoords:s1,iris:f0}=this.getEyeCoords(d0,M,E),h1=this.getLeftToRightEyeDepthDifference(m);Math.abs(h1)<30?(He(m,Te,"left",null),He(m,s1,"right",null)):h1<1?He(m,Te,"left",["EyeUpper0","EyeLower0"]):He(m,s1,"right",["EyeUpper0","EyeLower0"]);let m0=this.getAdjustedIrisCoords(m,ee,"left"),p0=this.getAdjustedIrisCoords(m,f0,"right");m=m.concat(m0).concat(p0)}let p=this.transformRawCoords(m,_,x,i);_=Oe(this.calculateLandmarksBoundingBox(p),1.5);let v=A.tensor2d(p);if(n.face.detector.rotation&&n.face.mesh.enabled&&(n.face.description.enabled||n.face.embedding.enabled)&&A.ENV.flags.IS_BROWSER){let[g,d]=_.landmarks.length>=Ve.count?Ve.symmetryLine:R1.symmetryLine;x=gt(_.landmarks[g],_.landmarks[d]);let T=_e({startPoint:_.startPoint,endPoint:_.endPoint}),M=[T[0]/e.shape[2],T[1]/e.shape[1]],E=A.image.rotateWithOffset(e,x,0,M);i=Le(-x,T),a=oe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.meshSize,this.meshSize]).div(255)}let R={coords:v,box:_,faceConfidence:b,boxConfidence:h,image:a,rawCoords:m},j=Ie(_);return this.storedBoxes[s]={...j,landmarks:p,confidence:_.confidence,faceConfidence:b},R}));return o=o.filter(_=>_!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(_=>_.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=o.length,o}calculateLandmarksBoundingBox(e){let n=e.map(_=>_[0]),c=e.map(_=>_[1]),r=[Math.min(...n),Math.min(...c)],o=[Math.max(...n),Math.max(...c)];return{startPoint:r,endPoint:o,landmarks:e}}};var Et=class{constructor(e,n,c,r){this.facePipeline=new Mt(e,n,c),this.config=r}async estimateFaces(e,n){let c=await this.facePipeline.predict(e,n),r=[];for(let o of c||[]){if(o.isDisposedInternal)continue;let _=o.coords?o.coords.arraySync():[],s=_.map(i=>[i[0]/e.shape[2],i[1]/e.shape[1],i[2]/this.facePipeline.meshSize]),h={};if(_&&_.length>0)for(let i of Object.keys(Y))h[i]=Y[i].map(w=>_[w]);let a=o.box?[Math.max(0,o.box.startPoint[0]),Math.max(0,o.box.startPoint[1]),Math.min(e.shape[2],o.box.endPoint[0])-Math.max(0,o.box.startPoint[0]),Math.min(e.shape[1],o.box.endPoint[1])-Math.max(0,o.box.startPoint[1])]:0,x=o.box?[o.box.startPoint[0]/e.shape[2],o.box.startPoint[1]/e.shape[1],(o.box.endPoint[0]-o.box.startPoint[0])/e.shape[2],(o.box.endPoint[1]-o.box.startPoint[1])/e.shape[1]]:[];r.push({confidence:Math.round(100*o.faceConfidence||100*o.boxConfidence||0)/100,boxConfidence:Math.round(100*o.boxConfidence)/100,faceConfidence:Math.round(100*o.faceConfidence)/100,box:a,boxRaw:x,mesh:_,meshRaw:s,annotations:h,image:o.image?o.image.clone():null}),o.coords&&o.coords.dispose(),o.image&&o.image.dispose()}return r}},re=[null,null,null];async function Rt(t){re=await Promise.all([!re[0]&&t.face.enabled?T1(t):null,!re[1]&&t.face.mesh.enabled?A.loadGraphModel(t.face.mesh.modelPath,{fromTFHub:t.face.mesh.modelPath.includes("tfhub.dev")}):null,!re[2]&&t.face.iris.enabled?A.loadGraphModel(t.face.iris.modelPath,{fromTFHub:t.face.iris.modelPath.includes("tfhub.dev")}):null]);let e=new Et(re[0],re[1],re[2],t);return t.face.mesh.enabled&&t.debug&&P(`load model: ${t.face.mesh.modelPath.match(/\/(.*)\./)[1]}`),t.face.iris.enabled&&t.debug&&P(`load model: ${t.face.iris.modelPath.match(/\/(.*)\./)[1]}`),e}var S1=ne,j1=le;var Vt={};F(Vt,{PoseNet:()=>Ht,load:()=>Xt});function V0(t){let[e,n,c,r]=t;return{offsets:e,heatmap:n,displacementFwd:c,displacementBwd:r}}var St=class{constructor(e){this.model=e}predict(e){return A.tidy(()=>{let c=e.toFloat().div(127.5).sub(1).expandDims(0),o=this.model.predict(c).map(s=>s.squeeze([0])),_=V0(o);return{heatmapScores:_.heatmap.sigmoid(),offsets:_.offsets,displacementFwd:_.displacementFwd,displacementBwd:_.displacementBwd}})}dispose(){this.model.dispose()}};function jt(t){return Math.floor(t/2)}var Wt=class{constructor(e,n){this.priorityQueue=new Array(e),this.numberOfElements=-1,this.getElementValue=n}enqueue(e){this.priorityQueue[++this.numberOfElements]=e,this.swim(this.numberOfElements)}dequeue(){let e=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,e}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(e){for(;e>0&&this.less(jt(e),e);)this.exchange(e,jt(e)),e=jt(e)}sink(e){for(;2*e<=this.numberOfElements;){let n=2*e;if(n<this.numberOfElements&&this.less(n,n+1)&&n++,!this.less(e,n))break;this.exchange(e,n),e=n}}getValueAt(e){return this.getElementValue(this.priorityQueue[e])}less(e,n){return this.getValueAt(e)<this.getValueAt(n)}exchange(e,n){let c=this.priorityQueue[e];this.priorityQueue[e]=this.priorityQueue[n],this.priorityQueue[n]=c}};function H0(t,e,n,c,r,o){let[_,s]=o.shape,h=!0,a=Math.max(n-r,0),x=Math.min(n+r+1,_);for(let i=a;i<x;++i){let w=Math.max(c-r,0),u=Math.min(c+r+1,s);for(let b=w;b<u;++b)if(o.get(i,b,t)>e){h=!1;break}if(!h)break}return h}function W1(t,e,n){let[c,r,o]=n.shape,_=new Wt(c*r*o,({score:s})=>s);for(let s=0;s<c;++s)for(let h=0;h<r;++h)for(let a=0;a<o;++a){let x=n.get(s,h,a);x<t||H0(a,x,s,h,e,n)&&_.enqueue({score:x,part:{heatmapY:s,heatmapX:h,id:a}})}return _}var ie=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],ae=ie.length,de=ie.reduce((t,e,n)=>(t[e]=n,t),{}),X0=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],Tr=X0.map(([t,e])=>[de[t],de[e]]),k1=[["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 kt(t,e,n,c){return{y:c.get(t,e,n),x:c.get(t,e,n+ae)}}function Xe(t,e,n){let{heatmapY:c,heatmapX:r,id:o}=t,{y:_,x:s}=kt(c,r,o,n);return{x:t.heatmapX*e+s,y:t.heatmapY*e+_}}function Nt(t,e,n){return t<e?e:t>n?n:t}function N1(t,e,n,c){let r=n-t,o=c-e;return r*r+o*o}function Ot(t,e){return{x:t.x+e.x,y:t.y+e.y}}function O1(t,e){let n=e.shape[0],c=new Float32Array(n);for(let r=0;r<n;r++){let o=e.get(r,0),_=e.get(r,1);c[r]=t.get(o,_,r)}return c}function F0(t,e,n,c){return{y:c.get(t,e,n),x:c.get(t,e,n+ae)}}function q0(t,e){let n=[];for(let c=0;c<ae;c++){let r=t.get(c,0).valueOf(),o=t.get(c,1).valueOf(),{x:_,y:s}=F0(r,o,c,e);n.push(s),n.push(_)}return A.tensor2d(n,[ae,2])}function I1(t,e,n){return A.tidy(()=>t.toTensor().mul(A.scalar(e,"int32")).toFloat().add(q0(t,n)))}function C0(t,e){return A.tidy(()=>{let n=t.div(A.scalar(e,"int32"));return t.sub(n.mul(A.scalar(e,"int32")))})}function Z1(t){let[e,n,c]=t.shape;return A.tidy(()=>{let o=t.reshape([e*n,c]).argMax(0),_=o.div(A.scalar(n,"int32")).expandDims(1),s=C0(o,n).expandDims(1);return A.concat([_,s],1)})}var L1=k1.map(([t,e])=>[de[t],de[e]]),It=L1.map(([,t])=>t),V1=L1.map(([t])=>t),B0=16;function Y0(t,e,n){let c=n.shape[2]/2;return{y:n.get(e.y,e.x,t),x:n.get(e.y,e.x,c+t)}}function Zt(t,e,n,c){return{y:Nt(Math.round(t.y/e),0,n-1),x:Nt(Math.round(t.x/e),0,c-1)}}function H1(t,e,n,c,r,o,_,s=2){let[h,a]=c.shape,x=Zt(e.position,o,h,a),i=Y0(t,x,_),u=Ot(e.position,i);for(let m=0;m<s;m++){let p=Zt(u,o,h,a),v=kt(p.y,p.x,n,r);u=Ot({x:p.x*o,y:p.y*o},{x:v.x,y:v.y})}let b=Zt(u,o,h,a),y=c.get(b.y,b.x,n);return{position:u,part:ie[n],score:y}}function X1(t,e,n,c,r,o){let _=e.shape[2],s=It.length,h=new Array(_),{part:a,score:x}=t,i=Xe(a,c,n);h[a.id]={score:x,part:ie[a.id],position:i};for(let w=s-1;w>=0;--w){let u=It[w],b=V1[w];h[u]&&!h[b]&&(h[b]=H1(w,h[u],b,e,n,c,o))}for(let w=0;w<s;++w){let u=V1[w],b=It[w];h[u]&&!h[b]&&(h[b]=H1(w,h[u],b,e,n,c,r))}return h}async function F1(t,e,n){let c=0,r=Z1(t),o=await Promise.all([t.buffer(),e.buffer(),r.buffer()]),_=o[0],s=o[1],h=o[2],a=I1(h,B0,s),x=await a.buffer(),w=Array.from(O1(_,h)).map((b,y)=>(c+=b,{position:{y:x.get(y,0),x:x.get(y,1)},part:ie[y],score:b})),u=w.filter(b=>b.score>n);return r.dispose(),a.dispose(),{keypoints:u,score:c/w.length}}var J0=1,q1=16;function C1(t,e,{x:n,y:c},r){return t.some(({keypoints:o})=>{let _=o[r].position;return N1(c,n,_.y,_.x)<=e})}function K0(t,e,n){return n.reduce((r,{position:o,score:_},s)=>(C1(t,e,o,s)||(r+=_),r),0)/n.length}function B1(t,e,n,c,r,o,_){let s=[],h=W1(_,J0,t),a=r^2;for(;s.length<o&&!h.empty();){let x=h.dequeue(),i=Xe(x.part,q1,e);if(C1(s,a,i,x.part.id))continue;let w=X1(x,t,e,q1,n,c),u=K0(s,a,w);u>_&&s.push({keypoints:w,score:Math.round(100*u)/100})}return s}async function Y1(t){return Promise.all(t.map(e=>e.buffer()))}function U0(t,e,n){return{score:t.score,keypoints:t.keypoints.map(({score:c,part:r,position:o})=>({score:c,part:r,position:{x:Math.trunc(o.x*n),y:Math.trunc(o.y*e)}}))}}function J1(t,[e,n]){let c=t.squeeze(0),r=c.resizeBilinear([e,n]);return c.dispose(),r}function Lt(t,[e,n],[c,r]){return t.map(_=>U0(_,e/c,n/r))}async function D0(t,e,n,c){return new Promise(async r=>{let o=await Y1([e.heatmapScores,e.offsets,e.displacementFwd,e.displacementBwd]),_=o[0],s=o[1],h=o[2],a=o[3],x=await B1(_,s,h,a,n.body.nmsRadius,n.body.maxDetections,n.body.scoreThreshold),i=Lt(x,[t.shape[1],t.shape[2]],[c,c]);r(i)})}async function G0(t,e,n,c){return new Promise(async r=>{let o=await F1(e.heatmapScores,e.offsets,n.body.scoreThreshold),_=Lt([o],[t.shape[1],t.shape[2]],[c,c]);r(_)})}var Ht=class{constructor(e){this.baseModel=e,this.inputSize=e.model.inputs[0].shape[1],this.inputSize<128&&(this.inputSize=257)}async estimatePoses(e,n){let c=J1(e,[this.inputSize,this.inputSize]),r=this.baseModel.predict(c,n),o=n.body.maxDetections<2?await G0(e,r,n,this.inputSize):await D0(e,r,n,this.inputSize);return r.heatmapScores.dispose(),r.offsets.dispose(),r.displacementFwd.dispose(),r.displacementBwd.dispose(),c.dispose(),o}dispose(){this.baseModel.dispose()}};async function Xt(t){let e=await A.loadGraphModel(t.body.modelPath),n=new St(e);return t.debug&&P(`load model: ${t.body.modelPath.match(/\/(.*)\./)[1]}`),new Ht(n)}var Yt={};F(Yt,{HandPose:()=>Kt,load:()=>Ut});function Fe(t){return[Math.abs(t.endPoint[0]-t.startPoint[0]),Math.abs(t.endPoint[1]-t.startPoint[1])]}function fe(t){return[t.startPoint[0]+(t.endPoint[0]-t.startPoint[0])/2,t.startPoint[1]+(t.endPoint[1]-t.startPoint[1])/2]}function K1(t,e,n){let c=e.shape[1],r=e.shape[2],o=[[t.startPoint[1]/c,t.startPoint[0]/r,t.endPoint[1]/c,t.endPoint[0]/r]];return A.image.cropAndResize(e,o,[0],n)}function U1(t,e){let n=[t.startPoint[0]*e[0],t.startPoint[1]*e[1]],c=[t.endPoint[0]*e[0],t.endPoint[1]*e[1]],r=t.palmLandmarks.map(o=>[o[0]*e[0],o[1]*e[1]]);return{startPoint:n,endPoint:c,palmLandmarks:r,confidence:t.confidence}}function qe(t,e=1.5){let n=fe(t),c=Fe(t),r=[e*c[0]/2,e*c[1]/2],o=[n[0]-r[0],n[1]-r[1]],_=[n[0]+r[0],n[1]+r[1]];return{startPoint:o,endPoint:_,palmLandmarks:t.palmLandmarks}}function Ce(t){let e=fe(t),n=Fe(t),r=Math.max(...n)/2,o=[e[0]-r,e[1]-r],_=[e[0]+r,e[1]+r];return{startPoint:o,endPoint:_,palmLandmarks:t.palmLandmarks}}var Ft=class{constructor(e,n,c){this.model=e,this.anchors=c.map(r=>[r.x_center,r.y_center]),this.anchorsTensor=A.tensor2d(this.anchors),this.inputSize=n,this.inputSizeTensor=A.tensor1d([n,n]),this.doubleInputSizeTensor=A.tensor1d([n*2,n*2])}normalizeBoxes(e){return A.tidy(()=>{let 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n=e.map(_=>_[0]),c=e.map(_=>_[1]),r=[Math.min(...n),Math.min(...c)],o=[Math.max(...n),Math.max(...c)];return{startPoint:r,endPoint:o}}};var 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r0=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],c0=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var H;async function Gt(t){return H||(H=await A.loadGraphModel(t.body.modelPath),H.width=parseInt(H.signature.inputs["input_1:0"].tensorShape.dim[2].size),H.height=parseInt(H.signature.inputs["input_1:0"].tensorShape.dim[1].size),t.debug&&P(`load model: ${t.body.modelPath.match(/\/(.*)\./)[1]}`)),H}async function Qt(t,e){if(!H||!e.body.enabled)return null;let n={width:t.shape[2],height:t.shape[1]},c=A.image.resizeBilinear(t,[H.width,H.height],!1),r=A.div(c,[255]);c.dispose();let o;if(e.profile){let x=await A.profile(()=>H.predict(r));o=x.result.find(i=>i.size===195||i.size===155).dataSync(),x.result.forEach(i=>i.dispose()),I("blazepose",x)}else{let x=await H.predict(r);o=x.find(i=>i.size===195||i.size===155).dataSync(),x.forEach(i=>i.dispose())}r.dispose();let _=[],s=o.length===195?r0:c0,h=5;for(let 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"))}c.rotation&&c.rotation.angle&&c.rotation.angle.roll&&r.push(`roll: ${Math.trunc(100*c.rotation.angle.roll)/100} yaw:${Math.trunc(100*c.rotation.angle.yaw)/100} pitch:${Math.trunc(100*c.rotation.angle.pitch)/100}`),r.length===0&&r.push("face"),n.fillStyle=f.color;for(let o=r.length-1;o>=0;o--){let _=Math.max(c.box[0],0),s=o*f.lineHeight+c.box[1];f.shadowColor&&f.shadowColor!==""&&(n.fillStyle=f.shadowColor,n.fillText(r[o],_+5,s+16)),n.fillStyle=f.labelColor,n.fillText(r[o],_+4,s+15)}if(n.lineWidth=1,c.mesh&&c.mesh.length>0){if(f.drawPoints)for(let o of c.mesh)De(n,o[0],o[1],o[2]);if(f.drawPolygons){n.lineWidth=1;for(let o=0;o<ne.length/3;o++){let _=[ne[o*3+0],ne[o*3+1],ne[o*3+2]].map(s=>c.mesh[s]);o1(n,_)}if(c.annotations&&c.annotations.leftEyeIris){n.strokeStyle=f.useDepth?"rgba(255, 200, 255, 0.3)":f.color,n.beginPath();let o=Math.abs(c.annotations.leftEyeIris[3][0]-c.annotations.leftEyeIris[1][0])/2,_=Math.abs(c.annotations.leftEyeIris[4][1]-c.annotations.leftEyeIris[2][1])/2;n.ellipse(c.annotations.leftEyeIris[0][0],c.annotations.leftEyeIris[0][1],o,_,0,0,2*Math.PI),n.stroke(),f.fillPolygons&&(n.fillStyle=f.useDepth?"rgba(255, 255, 200, 0.3)":f.color,n.fill())}if(c.annotations&&c.annotations.rightEyeIris){n.strokeStyle=f.useDepth?"rgba(255, 200, 255, 0.3)":f.color,n.beginPath();let o=Math.abs(c.annotations.rightEyeIris[3][0]-c.annotations.rightEyeIris[1][0])/2,_=Math.abs(c.annotations.rightEyeIris[4][1]-c.annotations.rightEyeIris[2][1])/2;n.ellipse(c.annotations.rightEyeIris[0][0],c.annotations.rightEyeIris[0][1],o,_,0,0,2*Math.PI),n.stroke(),f.fillPolygons&&(n.fillStyle=f.useDepth?"rgba(255, 255, 200, 0.3)":f.color,n.fill())}}}}}var Q=[];async function o0(t,e){if(!e||!t||!(t instanceof HTMLCanvasElement))return;let n=t.getContext("2d");if(!!n){n.lineJoin="round";for(let c=0;c<e.length;c++){if(!Q[c]&&f.bufferedOutput&&(Q[c]={...e[c]}),n.strokeStyle=f.color,n.lineWidth=f.lineWidth,f.drawPoints)for(let r=0;r<e[c].keypoints.length;r++)n.fillStyle=f.useDepth&&e[c].keypoints[r].position.z?`rgba(${127.5+2*e[c].keypoints[r].position.z}, ${127.5-2*e[c].keypoints[r].position.z}, 255, 0.5)`:f.color,f.bufferedOutput?(Q[c].keypoints[r][0]=(Q[c].keypoints[r][0]+e[c].keypoints[r].position.x)/2,Q[c].keypoints[r][1]=(Q[c].keypoints[r][1]+e[c].keypoints[r].position.y)/2,De(n,Q[c].keypoints[r][0],Q[c].keypoints[r][1])):De(n,e[c].keypoints[r].position.x,e[c].keypoints[r].position.y);if(f.drawLabels&&(n.font=f.font,e[c].keypoints))for(let r of e[c].keypoints)n.fillStyle=f.useDepth&&r.position.z?`rgba(${127.5+2*r.position.z}, ${127.5-2*r.position.z}, 255, 0.5)`:f.color,n.fillText(`${r.part}`,r.position.x+4,r.position.y+4);if(f.drawPolygons&&e[c].keypoints){let r,o=[];o.length=0,r=e[c].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),pe(n,o),o.length=0,r=e[c].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightHip"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftHip"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),o.length===4&&o1(n,o),o.length=0,r=e[c].keypoints.find(_=>_.part==="leftHip"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftKnee"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftAnkle"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftHeel"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftFoot"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),pe(n,o),o.length=0,r=e[c].keypoints.find(_=>_.part==="rightHip"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightKnee"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightAnkle"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightHeel"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightFoot"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),pe(n,o),o.length=0,r=e[c].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftElbow"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftWrist"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftPalm"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),pe(n,o),o.length=0,r=e[c].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightElbow"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightWrist"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightPalm"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),pe(n,o)}}}}async function s0(t,e){if(!e||!t||!(t instanceof HTMLCanvasElement))return;let n=t.getContext("2d");if(!!n){n.lineJoin="round",n.font=f.font;for(let c of e){if(f.drawBoxes&&(n.strokeStyle=f.color,n.fillStyle=f.color,f.useRawBoxes?xe(n,t.width*c.boxRaw[0],t.height*c.boxRaw[1],t.width*c.boxRaw[2],t.height*c.boxRaw[3]):xe(n,c.box[0],c.box[1],c.box[2],c.box[3]),f.drawLabels&&(f.shadowColor&&f.shadowColor!==""&&(n.fillStyle=f.shadowColor,n.fillText("hand",c.box[0]+3,1+c.box[1]+f.lineHeight,c.box[2])),n.fillStyle=f.labelColor,n.fillText("hand",c.box[0]+2,0+c.box[1]+f.lineHeight,c.box[2])),n.stroke()),f.drawPoints&&c.landmarks&&c.landmarks.length>0)for(let r of c.landmarks)n.fillStyle=f.useDepth?`rgba(${127.5+2*r[2]}, ${127.5-2*r[2]}, 255, 0.5)`:f.color,De(n,r[0],r[1]);if(f.drawPolygons){let r=o=>{if(!!o)for(let _=0;_<o.length;_++)n.lineWidth=f.lineWidth,n.beginPath(),n.strokeStyle=f.useDepth?`rgba(${127.5+2*o[_][2]}, ${127.5-2*o[_][2]}, 255, 0.5)`:f.color,n.moveTo(o[_>0?_-1:0][0],o[_>0?_-1:0][1]),n.lineTo(o[_][0],o[_][1]),n.stroke()};r(c.annotations.indexFinger),r(c.annotations.middleFinger),r(c.annotations.ringFinger),r(c.annotations.pinky),r(c.annotations.thumb)}}}}async function h0(t,e){if(!e||!t||!(t instanceof HTMLCanvasElement))return;let n=t.getContext("2d");if(!!n){n.lineJoin="round",n.font=f.font;for(let c of e)if(f.drawBoxes){if(n.strokeStyle=f.color,n.fillStyle=f.color,f.useRawBoxes?xe(n,t.width*c.boxRaw[0],t.height*c.boxRaw[1],t.width*c.boxRaw[2],t.height*c.boxRaw[3]):xe(n,c.box[0],c.box[1],c.box[2],c.box[3]),f.drawLabels){let r=`${Math.round(100*c.score)}% ${c.label}`;f.shadowColor&&f.shadowColor!==""&&(n.fillStyle=f.shadowColor,n.fillText(r,c.box[0]+3,1+c.box[1]+f.lineHeight,c.box[2])),n.fillStyle=f.labelColor,n.fillText(r,c.box[0]+2,0+c.box[1]+f.lineHeight,c.box[2])}n.stroke()}}}async function on(t,e){if(!t||!e||!(t instanceof HTMLCanvasElement)||!(e instanceof HTMLCanvasElement))return;let n=t.getContext("2d");n==null||n.drawImage(t,0,0)}async function sn(t,e){!e||!t||t instanceof HTMLCanvasElement&&(_0(t,e.face),o0(t,e.body),s0(t,e.hand),A0(t,e.gesture),h0(t,e.object))}var Ge=`
+`)}var Ue=2048,W=null,O=null,k=null;function A1(t,e){let n;if(!t)throw new Error("Human: Input is missing");if(!(t instanceof A.Tensor)&&!(typeof Image!="undefined"&&t instanceof Image)&&!(typeof ImageData!="undefined"&&t instanceof ImageData)&&!(typeof ImageBitmap!="undefined"&&t instanceof ImageBitmap)&&!(typeof HTMLImageElement!="undefined"&&t instanceof HTMLImageElement)&&!(typeof HTMLMediaElement!="undefined"&&t instanceof HTMLMediaElement)&&!(typeof HTMLVideoElement!="undefined"&&t instanceof HTMLVideoElement)&&!(typeof HTMLCanvasElement!="undefined"&&t instanceof HTMLCanvasElement)&&!(typeof OffscreenCanvas!="undefined"&&t instanceof OffscreenCanvas))throw new Error("Human: Input type is not recognized");if(t instanceof A.Tensor)n=A.clone(t);else{let r=t.naturalWidth||t.videoWidth||t.width||t.shape&&t.shape[1]>0,o=t.naturalHeight||t.videoHeight||t.height||t.shape&&t.shape[2]>0,_=r,s=o;if(_>Ue&&(_=Ue,s=_*o/r),s>Ue&&(s=Ue,_=s*r/o),e.filter.width>0?_=e.filter.width:e.filter.height>0&&(_=r*(e.filter.height/o)),e.filter.height>0?s=e.filter.height:e.filter.width>0&&(s=o*(e.filter.width/r)),!_||!s)throw new Error("Human: Input cannot determine dimension");(!W||W.width!==_||W.height!==s)&&(W=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(_,s):document.createElement("canvas"),W.width!==_&&(W.width=_),W.height!==s&&(W.height=s));let h=W.getContext("2d");if(t instanceof ImageData?h.putImageData(t,0,0):h.drawImage(t,0,0,r,o,0,0,W.width,W.height),e.filter.enabled){if((!k||!O||W.width!==O.width||W.height!==O.height)&&(O=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(W.width,W.height):document.createElement("canvas"),O.width!==W.width&&(O.width=W.width),O.height!==W.height&&(O.height=W.height),k=A.ENV.flags.IS_BROWSER?new h0({canvas:O}):null),!k)return{tensor:null,canvas:W};k.reset(),k.addFilter("brightness",e.filter.brightness),e.filter.contrast!==0&&k.addFilter("contrast",e.filter.contrast),e.filter.sharpness!==0&&k.addFilter("sharpen",e.filter.sharpness),e.filter.blur!==0&&k.addFilter("blur",e.filter.blur),e.filter.saturation!==0&&k.addFilter("saturation",e.filter.saturation),e.filter.hue!==0&&k.addFilter("hue",e.filter.hue),e.filter.negative&&k.addFilter("negative"),e.filter.sepia&&k.addFilter("sepia"),e.filter.vintage&&k.addFilter("brownie"),e.filter.sepia&&k.addFilter("sepia"),e.filter.kodachrome&&k.addFilter("kodachrome"),e.filter.technicolor&&k.addFilter("technicolor"),e.filter.polaroid&&k.addFilter("polaroid"),e.filter.pixelate!==0&&k.addFilter("pixelate",e.filter.pixelate),k.apply(W)}else O=W,k&&(k=null);let a;if(O.data){let i=[O.height,O.width,3];a=A.tensor3d(O.data,i,"int32")}else if(O instanceof ImageData)a=A.browser.fromPixels(O);else if(e.backend==="webgl"||e.backend==="humangl"){let i=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(_,s):document.createElement("canvas");i.width=_,i.height=s;let w=i.getContext("2d");w==null||w.drawImage(O,0,0),a=A.browser.fromPixels(i)}else{let i=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(_,s):document.createElement("canvas");i.width=_,i.height=s;let w=i.getContext("2d");w==null||w.drawImage(O,0,0);let u=w==null?void 0:w.getImageData(0,0,_,s);a=A.browser.fromPixels(u)}let x=a.toFloat();n=x.expandDims(0),a.dispose(),x.dispose()}let c=e.filter.return?O:null;return{tensor:n,canvas:c}}var _1={};F(_1,{all:()=>sn,body:()=>x0,canvas:()=>on,drawOptions:()=>f,face:()=>a0,gesture:()=>i0,hand:()=>y0,object:()=>w0});var S={backend:"webgl",wasmPath:"../assets/",debug:!0,async:!0,profile:!1,deallocate:!1,scoped:!1,videoOptimized:!0,warmup:"face",filter:{enabled:!0,width:0,height:0,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:"../models/blazeface-back.json",rotation:!1,maxFaces:10,skipFrames:21,skipInitial:!1,minConfidence:.2,iouThreshold:.1,scoreThreshold:.2,return:!1},mesh:{enabled:!0,modelPath:"../models/facemesh.json"},iris:{enabled:!0,modelPath:"../models/iris.json"},description:{enabled:!0,modelPath:"../models/faceres.json",skipFrames:31},emotion:{enabled:!0,minConfidence:.1,skipFrames:32,modelPath:"../models/emotion.json"},age:{enabled:!1,modelPath:"../models/age.json",skipFrames:33},gender:{enabled:!1,minConfidence:.1,modelPath:"../models/gender.json",skipFrames:34},embedding:{enabled:!1,modelPath:"../models/mobileface.json"}},body:{enabled:!0,modelPath:"../models/posenet.json",maxDetections:10,scoreThreshold:.3,nmsRadius:20},hand:{enabled:!0,rotation:!1,skipFrames:12,skipInitial:!1,minConfidence:.1,iouThreshold:.1,scoreThreshold:.5,maxHands:1,landmarks:!0,detector:{modelPath:"../models/handdetect.json"},skeleton:{modelPath:"../models/handskeleton.json"}},object:{enabled:!1,modelPath:"../models/nanodet.json",minConfidence:.2,iouThreshold:.4,maxResults:10,skipFrames:41}};var f={color:"rgba(173, 216, 230, 0.3)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",font:'small-caps 16px "Segoe UI"',lineHeight:20,lineWidth:6,pointSize:2,roundRect:28,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawPolygons:!0,fillPolygons:!1,useDepth:!0,useCurves:!1,bufferedOutput:!1,useRawBoxes:!1};function De(t,e,n,c=null){t.fillStyle=f.useDepth&&c?`rgba(${127.5+2*(c||0)}, ${127.5-2*(c||0)}, 255, 0.3)`:f.color,t.beginPath(),t.arc(e,n,f.pointSize,0,2*Math.PI),t.fill()}function xe(t,e,n,c,r){if(t.beginPath(),f.useCurves){let o=(e+e+c)/2,_=(n+n+r)/2;t.ellipse(o,_,c/2,r/2,0,0,2*Math.PI)}else t.lineWidth=f.lineWidth,t.moveTo(e+f.roundRect,n),t.lineTo(e+c-f.roundRect,n),t.quadraticCurveTo(e+c,n,e+c,n+f.roundRect),t.lineTo(e+c,n+r-f.roundRect),t.quadraticCurveTo(e+c,n+r,e+c-f.roundRect,n+r),t.lineTo(e+f.roundRect,n+r),t.quadraticCurveTo(e,n+r,e,n+r-f.roundRect),t.lineTo(e,n+f.roundRect),t.quadraticCurveTo(e,n,e+f.roundRect,n),t.closePath();t.stroke()}function o1(t,e=[]){if(!(e===void 0||e.length===0)){t.beginPath(),t.moveTo(e[0][0],e[0][1]);for(let n of e)t.strokeStyle=f.useDepth&&n[2]?`rgba(${127.5+2*n[2]}, ${127.5-2*n[2]}, 255, 0.3)`:f.color,t.fillStyle=f.useDepth&&n[2]?`rgba(${127.5+2*n[2]}, ${127.5-2*n[2]}, 255, 0.3)`:f.color,t.lineTo(n[0],parseInt(n[1]));t.stroke(),f.fillPolygons&&(t.closePath(),t.fill())}}function pe(t,e=[]){if(!(e===void 0||e.length===0)){if(!f.useCurves||e.length<=2){o1(t,e);return}t.moveTo(e[0][0],e[0][1]);for(let n=0;n<e.length-2;n++){let c=(e[n][0]+e[n+1][0])/2,r=(e[n][1]+e[n+1][1])/2;t.quadraticCurveTo(e[n][0],e[n][1],c,r)}t.quadraticCurveTo(e[e.length-2][0],e[e.length-2][1],e[e.length-1][0],e[e.length-1][1]),t.stroke(),f.fillPolygons&&(t.closePath(),t.fill())}}async function i0(t,e){if(!e||!t||!(t instanceof HTMLCanvasElement))return;let n=t.getContext("2d");if(!n)return;n.font=f.font,n.fillStyle=f.color;let c=1;for(let r=0;r<e.length;r++){let o=[],_=[];if([o,_]=Object.entries(e[r]),_.length>1&&_[1].length>0){let s=o[1]>0?`#${o[1]}`:"",h=`${o[0]} ${s}: ${_[1]}`;f.shadowColor&&f.shadowColor!==""&&(n.fillStyle=f.shadowColor,n.fillText(h,8,2+c*f.lineHeight)),n.fillStyle=f.labelColor,n.fillText(h,6,0+c*f.lineHeight),c+=1}}}async function a0(t,e){if(!e||!t||!(t instanceof HTMLCanvasElement))return;let n=t.getContext("2d");if(!!n)for(let c of e){n.font=f.font,n.strokeStyle=f.color,n.fillStyle=f.color,f.drawBoxes&&(f.useRawBoxes?xe(n,t.width*c.boxRaw[0],t.height*c.boxRaw[1],t.width*c.boxRaw[2],t.height*c.boxRaw[3]):xe(n,c.box[0],c.box[1],c.box[2],c.box[3]));let r=[];if(r.push(`face confidence: ${Math.trunc(100*c.confidence)}%`),c.genderConfidence&&r.push(`${c.gender||""} ${Math.trunc(100*c.genderConfidence)}% confident`),c.age&&r.push(`age: ${c.age||""}`),c.iris&&r.push(`iris distance: ${c.iris}`),c.emotion&&c.emotion.length>0){let o=c.emotion.map(_=>`${Math.trunc(100*_.score)}% ${_.emotion}`);r.push(o.join(" "))}c.rotation&&c.rotation.angle&&c.rotation.angle.roll&&r.push(`roll: ${Math.trunc(100*c.rotation.angle.roll)/100} yaw:${Math.trunc(100*c.rotation.angle.yaw)/100} pitch:${Math.trunc(100*c.rotation.angle.pitch)/100}`),r.length===0&&r.push("face"),n.fillStyle=f.color;for(let o=r.length-1;o>=0;o--){let _=Math.max(c.box[0],0),s=o*f.lineHeight+c.box[1];f.shadowColor&&f.shadowColor!==""&&(n.fillStyle=f.shadowColor,n.fillText(r[o],_+5,s+16)),n.fillStyle=f.labelColor,n.fillText(r[o],_+4,s+15)}if(n.lineWidth=1,c.mesh&&c.mesh.length>0){if(f.drawPoints)for(let o of c.mesh)De(n,o[0],o[1],o[2]);if(f.drawPolygons){n.lineWidth=1;for(let o=0;o<ne.length/3;o++){let _=[ne[o*3+0],ne[o*3+1],ne[o*3+2]].map(s=>c.mesh[s]);o1(n,_)}if(c.annotations&&c.annotations.leftEyeIris){n.strokeStyle=f.useDepth?"rgba(255, 200, 255, 0.3)":f.color,n.beginPath();let o=Math.abs(c.annotations.leftEyeIris[3][0]-c.annotations.leftEyeIris[1][0])/2,_=Math.abs(c.annotations.leftEyeIris[4][1]-c.annotations.leftEyeIris[2][1])/2;n.ellipse(c.annotations.leftEyeIris[0][0],c.annotations.leftEyeIris[0][1],o,_,0,0,2*Math.PI),n.stroke(),f.fillPolygons&&(n.fillStyle=f.useDepth?"rgba(255, 255, 200, 0.3)":f.color,n.fill())}if(c.annotations&&c.annotations.rightEyeIris){n.strokeStyle=f.useDepth?"rgba(255, 200, 255, 0.3)":f.color,n.beginPath();let o=Math.abs(c.annotations.rightEyeIris[3][0]-c.annotations.rightEyeIris[1][0])/2,_=Math.abs(c.annotations.rightEyeIris[4][1]-c.annotations.rightEyeIris[2][1])/2;n.ellipse(c.annotations.rightEyeIris[0][0],c.annotations.rightEyeIris[0][1],o,_,0,0,2*Math.PI),n.stroke(),f.fillPolygons&&(n.fillStyle=f.useDepth?"rgba(255, 255, 200, 0.3)":f.color,n.fill())}}}}}var Q=[];async function x0(t,e){if(!e||!t||!(t instanceof HTMLCanvasElement))return;let n=t.getContext("2d");if(!!n){n.lineJoin="round";for(let c=0;c<e.length;c++){if(!Q[c]&&f.bufferedOutput&&(Q[c]={...e[c]}),n.strokeStyle=f.color,n.lineWidth=f.lineWidth,f.drawPoints)for(let r=0;r<e[c].keypoints.length;r++)n.fillStyle=f.useDepth&&e[c].keypoints[r].position.z?`rgba(${127.5+2*e[c].keypoints[r].position.z}, ${127.5-2*e[c].keypoints[r].position.z}, 255, 0.5)`:f.color,f.bufferedOutput?(Q[c].keypoints[r][0]=(Q[c].keypoints[r][0]+e[c].keypoints[r].position.x)/2,Q[c].keypoints[r][1]=(Q[c].keypoints[r][1]+e[c].keypoints[r].position.y)/2,De(n,Q[c].keypoints[r][0],Q[c].keypoints[r][1])):De(n,e[c].keypoints[r].position.x,e[c].keypoints[r].position.y);if(f.drawLabels&&(n.font=f.font,e[c].keypoints))for(let r of e[c].keypoints)n.fillStyle=f.useDepth&&r.position.z?`rgba(${127.5+2*r.position.z}, ${127.5-2*r.position.z}, 255, 0.5)`:f.color,n.fillText(`${r.part}`,r.position.x+4,r.position.y+4);if(f.drawPolygons&&e[c].keypoints){let r,o=[];o.length=0,r=e[c].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),pe(n,o),o.length=0,r=e[c].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightHip"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftHip"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),o.length===4&&o1(n,o),o.length=0,r=e[c].keypoints.find(_=>_.part==="leftHip"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftKnee"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftAnkle"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftHeel"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftFoot"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),pe(n,o),o.length=0,r=e[c].keypoints.find(_=>_.part==="rightHip"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightKnee"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightAnkle"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightHeel"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightFoot"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),pe(n,o),o.length=0,r=e[c].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftElbow"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftWrist"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="leftPalm"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),pe(n,o),o.length=0,r=e[c].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightElbow"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightWrist"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),r=e[c].keypoints.find(_=>_.part==="rightPalm"),r&&r.score>S.body.scoreThreshold&&o.push([r.position.x,r.position.y]),pe(n,o)}}}}async function y0(t,e){if(!e||!t||!(t instanceof HTMLCanvasElement))return;let n=t.getContext("2d");if(!!n){n.lineJoin="round",n.font=f.font;for(let c of e){if(f.drawBoxes&&(n.strokeStyle=f.color,n.fillStyle=f.color,f.useRawBoxes?xe(n,t.width*c.boxRaw[0],t.height*c.boxRaw[1],t.width*c.boxRaw[2],t.height*c.boxRaw[3]):xe(n,c.box[0],c.box[1],c.box[2],c.box[3]),f.drawLabels&&(f.shadowColor&&f.shadowColor!==""&&(n.fillStyle=f.shadowColor,n.fillText("hand",c.box[0]+3,1+c.box[1]+f.lineHeight,c.box[2])),n.fillStyle=f.labelColor,n.fillText("hand",c.box[0]+2,0+c.box[1]+f.lineHeight,c.box[2])),n.stroke()),f.drawPoints&&c.landmarks&&c.landmarks.length>0)for(let r of c.landmarks)n.fillStyle=f.useDepth?`rgba(${127.5+2*r[2]}, ${127.5-2*r[2]}, 255, 0.5)`:f.color,De(n,r[0],r[1]);if(f.drawPolygons){let r=o=>{if(!!o)for(let _=0;_<o.length;_++)n.lineWidth=f.lineWidth,n.beginPath(),n.strokeStyle=f.useDepth?`rgba(${127.5+2*o[_][2]}, ${127.5-2*o[_][2]}, 255, 0.5)`:f.color,n.moveTo(o[_>0?_-1:0][0],o[_>0?_-1:0][1]),n.lineTo(o[_][0],o[_][1]),n.stroke()};r(c.annotations.indexFinger),r(c.annotations.middleFinger),r(c.annotations.ringFinger),r(c.annotations.pinky),r(c.annotations.thumb)}}}}async function w0(t,e){if(!e||!t||!(t instanceof HTMLCanvasElement))return;let n=t.getContext("2d");if(!!n){n.lineJoin="round",n.font=f.font;for(let c of e)if(f.drawBoxes){if(n.strokeStyle=f.color,n.fillStyle=f.color,f.useRawBoxes?xe(n,t.width*c.boxRaw[0],t.height*c.boxRaw[1],t.width*c.boxRaw[2],t.height*c.boxRaw[3]):xe(n,c.box[0],c.box[1],c.box[2],c.box[3]),f.drawLabels){let r=`${Math.round(100*c.score)}% ${c.label}`;f.shadowColor&&f.shadowColor!==""&&(n.fillStyle=f.shadowColor,n.fillText(r,c.box[0]+3,1+c.box[1]+f.lineHeight,c.box[2])),n.fillStyle=f.labelColor,n.fillText(r,c.box[0]+2,0+c.box[1]+f.lineHeight,c.box[2])}n.stroke()}}}async function on(t,e){if(!t||!e||!(t instanceof HTMLCanvasElement)||!(e instanceof HTMLCanvasElement))return;let n=t.getContext("2d");n==null||n.drawImage(t,0,0)}async function sn(t,e){!e||!t||t instanceof HTMLCanvasElement&&(a0(t,e.face),x0(t,e.body),y0(t,e.hand),i0(t,e.gesture),w0(t,e.object))}var Ge=`
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-2Q==`;var i0="1.3.4";var ye,ue,be,ce,$e,ge,et,tt,nt,hn=class{constructor(e={}){ye.set(this,void 0);ue.set(this,void 0);be.set(this,void 0);ce.set(this,void 0);this.analyze=(...e)=>{if(!V(this,ue))return;let n=this.tf.engine().state.numTensors,c=V(this,ye);te(this,ye,n);let r=n-c;r!==0&&P(...e,r)};$e.set(this,e=>{if(!V(this,be))return null;if(!e)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(e instanceof A.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});ge.set(this,async(e=!1)=>{if(this.config.backend&&this.config.backend!==""&&e||this.tf.getBackend()!==this.config.backend){let n=z();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.tf.ENV.flags.IS_BROWSER&&this.config.backend==="tensorflow"&&(this.config.backend="webgl"),this.tf.ENV.flags.IS_NODE&&(this.config.backend==="webgl"||this.config.backend==="wasm")&&(this.config.backend="tensorflow"),this.config.debug&&P("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&P("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let c=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),r=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&P(`wasm execution: ${c?"SIMD":"no SIMD"} ${r?"multithreaded":"singlethreaded"}`),c||P("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&y1();try{await this.tf.setBackend(this.config.backend)}catch(c){P("error: cannot set backend:",this.config.backend,c)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"||this.tf.getBackend()==="humangl"){this.tf.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),this.tf.ENV.set("WEBGL_PACK_DEPTHWISECONV",!0),this.config.deallocate&&(P("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let c=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&P(`gl version:${c.getParameter(c.VERSION)} renderer:${c.getParameter(c.RENDERER)}`)}await this.tf.ready(),this.perf.backend=Math.trunc(z()-n)}});et.set(this,async()=>{let e=(r,o="application/octet-stream")=>fetch(`data:${o};base64,${r}`).then(_=>_.blob()),n,c;switch(this.config.warmup){case"face":n=await e(Ge);break;case"full":n=await e(Qe);break;default:n=null}if(n){let r=await createImageBitmap(n);c=await this.detect(r,this.config),r.close()}return c});tt.set(this,async()=>new Promise(e=>{let n,c=0;switch(this.config.warmup){case"face":c=256,n="data:image/jpeg;base64,"+Ge;break;case"full":case"body":c=1200,n="data:image/jpeg;base64,"+Qe;break;default:n=null}let r=new Image;r.onload=async()=>{let o=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(c,c):document.createElement("canvas");o.width=r.naturalWidth,o.height=r.naturalHeight;let _=o.getContext("2d");_==null||_.drawImage(r,0,0);let s=await this.detect(o,this.config);e(s)},n?r.src=n:e(null)}));nt.set(this,async()=>{let e=_=>Buffer.from(_,"base64"),n=this.config.warmup==="face"?e(Ge):e(Qe),c=A.node.decodeJpeg(n),r=c.expandDims(0);this.tf.dispose(c);let o=await this.detect(r,this.config);return this.tf.dispose(r),o});this.tf=A,this.draw=_1,this.version=i0,this.config=Ae(S,e),this.state="idle",te(this,ye,0),te(this,ue,!1),te(this,be,!1),te(this,ce,!0),this.perf={},this.models={face:null,posenet:null,blazepose:null,efficientpose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null,faceres:null},this.image=n=>A1(n,this.config),this.classes={facemesh:zt,age:ct,gender:_t,emotion:at,faceres:ft,body:this.config.body.modelPath.includes("posenet")?Vt:Dt,hand:Yt,nanodet:t1},this.faceTriangulation=v1,this.faceUVMap=M1,this.sysinfo=x1()}profileData(){return this.config.profile?Pe:{}}similarity(e,n){return this.config.face.description.enabled?pt(e,n):this.config.face.embedding.enabled?w1(e,n):0}enhance(e){return ut(e)}match(e,n,c=0){return l1(e,n,c)}async load(e={}){this.state="load";let n=z();e&&(this.config=Ae(this.config,e)),V(this,ce)&&(this.config.debug&&P(`version: ${this.version}`),this.config.debug&&P(`tfjs version: ${this.tf.version_core}`),this.config.debug&&P("platform:",this.sysinfo.platform),this.config.debug&&P("agent:",this.sysinfo.agent),await V(this,ge).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&P("configuration:",this.config),this.config.debug&&P("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.efficientpose,this.models.nanodet,this.models.faceres]=await Promise.all([this.models.face||(this.config.face.enabled?Rt(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?At(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?it(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?wt(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?lt(this.config):null),this.models.handpose||(this.config.hand.enabled?Ut(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?Xt(this.config):null),this.models.blazepose||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?Gt(this.config):null),this.models.efficientpose||(this.config.body.enabled&&this.config.body.modelPath.includes("efficientpose")?$t(this.config):null),this.models.nanodet||(this.config.object.enabled?r1(this.config):null),this.models.faceres||(this.config.face.enabled&&this.config.face.description.enabled?mt(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await Rt(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await At(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await it(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await wt(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await lt(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await Ut(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await Xt(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await Gt(this.config)),this.config.body.enabled&&!this.models.efficientpose&&this.config.body.modelPath.includes("efficientpose")&&(this.models.efficientpose=await $t(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await r1(this.config)),this.config.face.enabled&&this.config.face.description.enabled&&!this.models.faceres&&(this.models.faceres=await mt(this.config))),V(this,ce)&&(this.config.debug&&P("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),te(this,ce,!1));let c=Math.trunc(z()-n);c>(this.perf.load||0)&&(this.perf.load=c)}async detect(e,n={}){return new Promise(async c=>{var y,m,p,v;this.state="config";let r;this.config=Ae(this.config,n),this.state="check";let o=V(this,$e).call(this,e);o&&(P(o,e),c({error:o}));let _=z();await V(this,ge).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),this.analyze("Start Scope:"),r=z();let s=A1(e,this.config);if(!s||!s.tensor){P("could not convert input to tensor"),c({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(z()-r),this.analyze("Get Image:");let h,a,x,i,w;this.config.async?(x=this.config.face.enabled?bt(this,s.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",r=z(),x=this.config.face.enabled?await bt(this,s.tensor):[],w=Math.trunc(z()-r),w>0&&(this.perf.face=w)),this.analyze("Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?h=this.config.body.enabled?(y=this.models.posenet)==null?void 0:y.estimatePoses(s.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?h=this.config.body.enabled?Qt(s.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(h=this.config.body.enabled?e1(s.tensor,this.config):[]),this.perf.body&&delete this.perf.body):(this.state="run:body",r=z(),this.config.body.modelPath.includes("posenet")?h=this.config.body.enabled?await((m=this.models.posenet)==null?void 0:m.estimatePoses(s.tensor,this.config)):[]:this.config.body.modelPath.includes("blazepose")?h=this.config.body.enabled?await Qt(s.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(h=this.config.body.enabled?await e1(s.tensor,this.config):[]),w=Math.trunc(z()-r),w>0&&(this.perf.body=w)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(a=this.config.hand.enabled?(p=this.models.handpose)==null?void 0:p.estimateHands(s.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",r=z(),a=this.config.hand.enabled?await((v=this.models.handpose)==null?void 0:v.estimateHands(s.tensor,this.config)):[],w=Math.trunc(z()-r),w>0&&(this.perf.hand=w)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.config.async?(i=this.config.object.enabled?c1(s.tensor,this.config):[],this.perf.object&&delete this.perf.object):(this.state="run:object",r=z(),i=this.config.object.enabled?await c1(s.tensor,this.config):[],w=Math.trunc(z()-r),w>0&&(this.perf.object=w)),this.analyze("End Object:"),this.config.async&&([x,h,a,i]=await Promise.all([x,h,a,i])),s.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),this.analyze("End Scope:");let u=[];this.config.gesture.enabled&&(r=z(),u=[...t0(x),...e0(h),...r0(a),...n0(x)],this.config.async?this.perf.gesture&&delete this.perf.gesture:this.perf.gesture=Math.trunc(z()-r)),this.perf.total=Math.trunc(z()-_),this.state="idle";let b={face:x,body:h,hand:a,gesture:u,object:i,performance:this.perf,canvas:s.canvas};c(b)})}async warmup(e={}){let n=z();e&&(this.config=Ae(this.config,e));let c=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await V(this,et).call(this):typeof Image!="undefined"?r=await V(this,tt).call(this):r=await V(this,nt).call(this),this.config.videoOptimized=c;let o=z();return this.config.debug&&P("Warmup",this.config.warmup,Math.round(o-n),"ms",r),r}};ye=new WeakMap,ue=new WeakMap,be=new WeakMap,ce=new WeakMap,$e=new WeakMap,ge=new WeakMap,et=new WeakMap,tt=new WeakMap,nt=new WeakMap;export{hn as Human,hn as default};
+2Q==`;var l0="1.3.5";var ye,ue,be,ce,$e,ge,et,tt,nt,hn=class{constructor(e={}){ye.set(this,void 0);ue.set(this,void 0);be.set(this,void 0);ce.set(this,void 0);this.analyze=(...e)=>{if(!V(this,ue))return;let n=this.tf.engine().state.numTensors,c=V(this,ye);te(this,ye,n);let r=n-c;r!==0&&P(...e,r)};$e.set(this,e=>{if(!V(this,be))return null;if(!e)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(e instanceof A.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});ge.set(this,async(e=!1)=>{if(this.config.backend&&this.config.backend!==""&&e||this.tf.getBackend()!==this.config.backend){let n=z();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.tf.ENV.flags.IS_BROWSER&&this.config.backend==="tensorflow"&&(this.config.backend="webgl"),this.tf.ENV.flags.IS_NODE&&(this.config.backend==="webgl"||this.config.backend==="wasm")&&(this.config.backend="tensorflow"),this.config.debug&&P("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&P("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let c=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),r=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&P(`wasm execution: ${c?"SIMD":"no SIMD"} ${r?"multithreaded":"singlethreaded"}`),c||P("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&m1();try{await this.tf.setBackend(this.config.backend)}catch(c){P("error: cannot set backend:",this.config.backend,c)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"||this.tf.getBackend()==="humangl"){this.tf.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),this.tf.ENV.set("WEBGL_PACK_DEPTHWISECONV",!0),this.config.deallocate&&(P("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let c=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&P(`gl version:${c.getParameter(c.VERSION)} renderer:${c.getParameter(c.RENDERER)}`)}await this.tf.ready(),this.perf.backend=Math.trunc(z()-n)}});et.set(this,async()=>{let e=(r,o="application/octet-stream")=>fetch(`data:${o};base64,${r}`).then(_=>_.blob()),n,c;switch(this.config.warmup){case"face":n=await e(Ge);break;case"full":n=await e(Qe);break;default:n=null}if(n){let r=await createImageBitmap(n);c=await this.detect(r,this.config),r.close()}return c});tt.set(this,async()=>new Promise(e=>{let n,c=0;switch(this.config.warmup){case"face":c=256,n="data:image/jpeg;base64,"+Ge;break;case"full":case"body":c=1200,n="data:image/jpeg;base64,"+Qe;break;default:n=null}let r=new Image;r.onload=async()=>{let o=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(c,c):document.createElement("canvas");o.width=r.naturalWidth,o.height=r.naturalHeight;let _=o.getContext("2d");_==null||_.drawImage(r,0,0);let s=await this.detect(o,this.config);e(s)},n?r.src=n:e(null)}));nt.set(this,async()=>{let e=_=>Buffer.from(_,"base64"),n=this.config.warmup==="face"?e(Ge):e(Qe),c=A.node.decodeJpeg(n),r=c.expandDims(0);this.tf.dispose(c);let o=await this.detect(r,this.config);return this.tf.dispose(r),o});this.tf=A,this.draw=_1,this.version=l0,this.config=Ae(S,e),this.state="idle",te(this,ye,0),te(this,ue,!1),te(this,be,!1),te(this,ce,!0),this.perf={},this.models={face:null,posenet:null,blazepose:null,efficientpose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null,faceres:null},this.image=n=>A1(n,this.config),this.classes={facemesh:zt,age:ct,gender:_t,emotion:at,faceres:ft,body:this.config.body.modelPath.includes("posenet")?Vt:Dt,hand:Yt,nanodet:t1},this.faceTriangulation=S1,this.faceUVMap=j1,this.sysinfo=x1()}profileData(){return this.config.profile?Pe:{}}similarity(e,n){return this.config.face.description.enabled?pt(e,n):this.config.face.embedding.enabled?p1(e,n):0}enhance(e){return ut(e)}match(e,n,c=0){return u1(e,n,c)}async load(e={}){this.state="load";let n=z();e&&(this.config=Ae(this.config,e)),V(this,ce)&&(this.config.debug&&P(`version: ${this.version}`),this.config.debug&&P(`tfjs version: ${this.tf.version_core}`),this.config.debug&&P("platform:",this.sysinfo.platform),this.config.debug&&P("agent:",this.sysinfo.agent),await V(this,ge).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&P("configuration:",this.config),this.config.debug&&P("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.efficientpose,this.models.nanodet,this.models.faceres]=await Promise.all([this.models.face||(this.config.face.enabled?Rt(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?At(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?it(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?wt(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?lt(this.config):null),this.models.handpose||(this.config.hand.enabled?Ut(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?Xt(this.config):null),this.models.blazepose||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?Gt(this.config):null),this.models.efficientpose||(this.config.body.enabled&&this.config.body.modelPath.includes("efficientpose")?$t(this.config):null),this.models.nanodet||(this.config.object.enabled?r1(this.config):null),this.models.faceres||(this.config.face.enabled&&this.config.face.description.enabled?mt(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await Rt(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await At(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await it(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await wt(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await lt(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await Ut(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await Xt(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await Gt(this.config)),this.config.body.enabled&&!this.models.efficientpose&&this.config.body.modelPath.includes("efficientpose")&&(this.models.efficientpose=await $t(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await r1(this.config)),this.config.face.enabled&&this.config.face.description.enabled&&!this.models.faceres&&(this.models.faceres=await mt(this.config))),V(this,ce)&&(this.config.debug&&P("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),te(this,ce,!1));let c=Math.trunc(z()-n);c>(this.perf.load||0)&&(this.perf.load=c)}async detect(e,n={}){return new Promise(async c=>{var y,m,p,v;this.state="config";let r;this.config=Ae(this.config,n),this.state="check";let o=V(this,$e).call(this,e);o&&(P(o,e),c({error:o}));let _=z();await V(this,ge).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),this.analyze("Start Scope:"),r=z();let s=A1(e,this.config);if(!s||!s.tensor){P("could not convert input to tensor"),c({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(z()-r),this.analyze("Get Image:");let h,a,x,i,w;this.config.async?(x=this.config.face.enabled?bt(this,s.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",r=z(),x=this.config.face.enabled?await bt(this,s.tensor):[],w=Math.trunc(z()-r),w>0&&(this.perf.face=w)),this.analyze("Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?h=this.config.body.enabled?(y=this.models.posenet)==null?void 0:y.estimatePoses(s.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?h=this.config.body.enabled?Qt(s.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(h=this.config.body.enabled?e1(s.tensor,this.config):[]),this.perf.body&&delete this.perf.body):(this.state="run:body",r=z(),this.config.body.modelPath.includes("posenet")?h=this.config.body.enabled?await((m=this.models.posenet)==null?void 0:m.estimatePoses(s.tensor,this.config)):[]:this.config.body.modelPath.includes("blazepose")?h=this.config.body.enabled?await Qt(s.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(h=this.config.body.enabled?await e1(s.tensor,this.config):[]),w=Math.trunc(z()-r),w>0&&(this.perf.body=w)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(a=this.config.hand.enabled?(p=this.models.handpose)==null?void 0:p.estimateHands(s.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",r=z(),a=this.config.hand.enabled?await((v=this.models.handpose)==null?void 0:v.estimateHands(s.tensor,this.config)):[],w=Math.trunc(z()-r),w>0&&(this.perf.hand=w)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.config.async?(i=this.config.object.enabled?c1(s.tensor,this.config):[],this.perf.object&&delete this.perf.object):(this.state="run:object",r=z(),i=this.config.object.enabled?await c1(s.tensor,this.config):[],w=Math.trunc(z()-r),w>0&&(this.perf.object=w)),this.analyze("End Object:"),this.config.async&&([x,h,a,i]=await Promise.all([x,h,a,i])),s.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),this.analyze("End Scope:");let u=[];this.config.gesture.enabled&&(r=z(),u=[..._0(x),...A0(h),...s0(a),...o0(x)],this.config.async?this.perf.gesture&&delete this.perf.gesture:this.perf.gesture=Math.trunc(z()-r)),this.perf.total=Math.trunc(z()-_),this.state="idle";let b={face:x,body:h,hand:a,gesture:u,object:i,performance:this.perf,canvas:s.canvas};c(b)})}async warmup(e={}){let n=z();e&&(this.config=Ae(this.config,e));let c=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await V(this,et).call(this):typeof Image!="undefined"?r=await V(this,tt).call(this):r=await V(this,nt).call(this),this.config.videoOptimized=c;let o=z();return this.config.debug&&P("Warmup",this.config.warmup,Math.round(o-n),"ms",r),r}};ye=new WeakMap,ue=new WeakMap,be=new WeakMap,ce=new WeakMap,$e=new WeakMap,ge=new WeakMap,et=new WeakMap,tt=new WeakMap,nt=new WeakMap;export{hn as Human,hn as default};
 //# sourceMappingURL=human.esm-nobundle.js.map
diff --git a/dist/human.esm-nobundle.js.map b/dist/human.esm-nobundle.js.map
index 40d234b1..5fd4377e 100644
--- a/dist/human.esm-nobundle.js.map
+++ b/dist/human.esm-nobundle.js.map
@@ -1,7 +1,7 @@
 {
   "version": 3,
   "sources": ["../src/helpers.ts", "../src/sysinfo.ts", "../src/tfjs/tf-browser.ts", "../src/tfjs/backend.ts", "../src/age/age.ts", "../src/profile.ts", "../src/gender/gender.ts", "../src/emotion/emotion.ts", "../src/embedding/embedding.ts", "../src/faceres/faceres.ts", "../src/faceall.ts", "../src/blazeface/facemesh.ts", "../src/blazeface/blazeface.ts", "../src/blazeface/box.ts", "../src/blazeface/util.ts", "../src/blazeface/coords.ts", "../src/blazeface/facepipeline.ts", "../src/posenet/posenet.ts", "../src/posenet/modelBase.ts", "../src/posenet/heapSort.ts", "../src/posenet/buildParts.ts", "../src/posenet/keypoints.ts", "../src/posenet/vectors.ts", "../src/posenet/decoders.ts", "../src/posenet/decodePose.ts", "../src/posenet/decodeMultiple.ts", "../src/posenet/util.ts", "../src/handpose/handpose.ts", "../src/handpose/box.ts", "../src/handpose/handdetector.ts", "../src/handpose/util.ts", "../src/handpose/handpipeline.ts", "../src/handpose/anchors.ts", "../src/blazepose/blazepose.ts", "../src/blazepose/annotations.ts", "../src/efficientpose/efficientpose.ts", "../src/nanodet/nanodet.ts", "../src/nanodet/labels.ts", "../src/gesture/gesture.ts", "../src/image/imagefx.js", "../src/image/image.ts", "../src/draw/draw.ts", "../src/config.ts", "../src/sample.ts", "../src/human.ts"],
-  "sourcesContent": ["// helper function: wrapper around console output\nexport function log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n\n// helper function: gets elapsed time on both browser and nodejs\nexport const now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nexport function mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n", "export function info(): { platform: string, agent: string } {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }\n\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export versions\nexport const version = {\n  tfjs: packageBundle.version,\n  'tfjs-core': packageCore.version,\n  'tfjs-data': packageData.version,\n  'tfjs-layers': packageLayers.version,\n  'tfjs-converter': packageConverter.version,\n  'tfjs-backend-cpu': version_cpu,\n  'tfjs-backend-webgl': version_webgl,\n  'tfjs-backend-wasm': version_wasm,\n};\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\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\nexport function register(): void {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 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    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './helpers';\n\nexport const data = {};\n\nexport function run(modelName: string, profileData: any): void {\n  if (!profileData || !profileData.kernels) return;\n  const maxResults = 5;\n  const time = profileData.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = profileData.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = profileData.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  data[modelName] = {\n    model: modelName,\n    newBytes: profileData.newBytes,\n    newTensors: profileData.newTensors,\n    peakBytes: profileData.peakBytes,\n    numKernelOps: profileData.kernels.length,\n    timeKernelOps: time,\n    slowestKernelOps: slowest,\n    largestKernelOps: largest,\n  };\n  log('profiler', modelName, data[modelName]);\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(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 = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      if (!Array.isArray(genderT)) {\n        const data = genderT.dataSync();\n        if (alternative) {\n          // returns two values 0..1, bigger one is prediction\n          if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n            obj.gender = data[0] > data[1] ? 'female' : 'male';\n            obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n          }\n        } else {\n          // returns one value 0..1, .5 is prediction threshold\n          const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n          if (confidence > config.face.gender.minConfidence) {\n            obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n            obj.confidence = Math.min(0.99, confidence);\n          }\n        }\n        genderT.dispose();\n      } else {\n        const gender = genderT[0].dataSync();\n        const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n        /*\n        let age = genderT[1].argMax(1).dataSync()[0];\n        const all = genderT[1].dataSync();\n        age = Math.round(all[age - 1] > all[age + 1] ? 10 * age - 100 * all[age - 1] : 10 * age + 100 * all[age + 1]) / 10;\n        const descriptor = genderT[1].dataSync();\n        */\n        genderT.forEach((t) => tf.dispose(t));\n      }\n    }\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\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\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\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    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = typeof tf.Tensor;\ntype DB = Array<{ name: string, source: string, embedding: number[] }>;\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function similarity(embedding1, embedding2, order = 2): number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<number>, db: DB, threshold = 0) {\n  let best = { similarity: 0, name: '', source: '', embedding: [] as number[] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = similarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.similarity) best = { ...f, similarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = 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    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\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    // 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    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\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\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([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: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\ntype Tensor = typeof tf.Tensor;\ntype DB = Array<{ name: string, source: string, embedding: number[] }>;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.description.modelPath);\n    if (config.debug) log(`load model: ${config.face.description.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function similarity(embedding1, embedding2, order = 2): number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = 4.0 * embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(0, 100 - distance) / 100.0;\n  return res;\n}\n\nexport function match(embedding: Array<number>, db: DB, threshold = 0) {\n  let best = { similarity: 0, name: '', source: '', embedding: [] as number[] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = similarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.similarity) best = { ...f, similarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    const tensor = input.image || input.tensor || input;\n    if (!(tensor instanceof tf.Tensor)) return null;\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    // const crop = tf.image.resizeBilinear(tensor, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\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    /*\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\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n    /*\n    // normalize brightness from 0..1\n    const darken = crop.sub(crop.min());\n    const lighten = darken.div(darken.max());\n    */\n    const norm = crop.mul(255);\n\n    return norm;\n  });\n  return image;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.description.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    // const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    // const enhanced = tf.mul(resize, [255.0]);\n    // tf.dispose(resize);\n    const enhanced = enhance(image);\n\n    let resT;\n    const obj = {\n      age: <number>0,\n      gender: <string>'unknown',\n      genderConfidence: <number>0,\n      descriptor: <number[]>[] };\n\n    if (!config.profile) {\n      if (config.face.description.enabled) resT = await model.predict(enhanced);\n    } else {\n      const profileDesc = config.face.description.enabled ? await tf.profile(() => model.predict(enhanced)) : {};\n      resT = profileDesc.result;\n      profile.run('faceres', profileDesc);\n    }\n    tf.dispose(enhanced);\n\n    if (resT) {\n      tf.tidy(() => {\n        const gender = resT.find((t) => t.shape[1] === 1).dataSync();\n        const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n          obj.genderConfidence = Math.min(0.99, confidence);\n        }\n        const age = resT.find((t) => t.shape[1] === 100).argMax(1).dataSync()[0];\n        const all = resT.find((t) => t.shape[1] === 100).dataSync();\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]);\n        // const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n        obj.descriptor = [...desc.dataSync()];\n      });\n      resT.forEach((t) => tf.dispose(t));\n    }\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log, now } from './helpers';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as faceres from './faceres/faceres';\n\ntype Tensor = typeof tf.Tensor;\n\nconst calculateFaceAngle = (face, image_size): { angle: { pitch: number, yaw: number, roll: number }, matrix: [number, number, number, number, number, number, number, number, number] } => {\n  // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n  const degrees = (theta) => (theta * 180) / Math.PI;\n  // const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n  const normalize = (v) => { // 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, b) => { // 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, b) => { // 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) => {\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; let thetaY; let thetaZ;\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    return { pitch: 2 * -thetaX, yaw: 2 * -thetaY, roll: 2 * -thetaZ };\n  };\n  // simple Euler angle calculation based existing 3D mesh\n  // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n  const meshToEulerAngle = (mesh) => {\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // pitch is face move up/down\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\n      // yaw is face turn left/right\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\n      // roll is face lean 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\n    };\n    return angle;\n  };\n\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] };\n\n  const size = Math.max(face.boxRaw[2] * image_size[0], face.boxRaw[3] * image_size[1]) / 1.5;\n  // top, bottom, left, right\n  const pts = [mesh[10], mesh[152], mesh[234], mesh[454]].map((pt) => [\n    // make the xyz coordinates proportional, independent of the image/box size\n    pt[0] * image_size[0] / size,\n    pt[1] * image_size[1] / size,\n    pt[2],\n  ]);\n\n  const y_axis = normalize(subVectors(pts[1], pts[0]));\n  let x_axis = normalize(subVectors(pts[3], pts[2]));\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  return { angle, matrix };\n};\n\nexport const detectFace = async (parent, input): Promise<any> => {\n  // run facemesh, includes blazeface and iris\n  // eslint-disable-next-line no-async-promise-executor\n  let timeStamp;\n  let ageRes;\n  let genderRes;\n  let emotionRes;\n  let embeddingRes;\n  let descRes;\n  const faceRes: Array<{\n      confidence: number,\n      boxConfidence: number,\n      faceConfidence: number,\n      box: [number, number, number, number],\n      mesh: Array<[number, number, number]>\n      meshRaw: Array<[number, number, number]>\n      boxRaw: [number, number, number, number],\n      annotations: Array<{ part: string, points: Array<[number, number, number]>[] }>,\n      age: number,\n      gender: string,\n      genderConfidence: number,\n      emotion: string,\n      embedding: number[],\n      iris: number,\n      rotation: {\n        angle: { pitch: number, yaw: number, roll: number },\n        matrix: [number, number, number, number, number, number, number, number, number]\n      },\n      tensor: Tensor,\n    }> = [];\n  parent.state = 'run:face';\n  timeStamp = now();\n  const faces = await parent.models.face?.estimateFaces(input, parent.config);\n  parent.perf.face = Math.trunc(now() - timeStamp);\n  if (!faces) return [];\n  for (const face of faces) {\n    parent.analyze('Get Face');\n\n    // is something went wrong, skip the face\n    if (!face.image || face.image.isDisposedInternal) {\n      log('Face object is disposed:', face.image);\n      continue;\n    }\n\n    const rotation = calculateFaceAngle(face, [input.shape[2], input.shape[1]]);\n\n    // run age, inherits face from blazeface\n    parent.analyze('Start Age:');\n    if (parent.config.async) {\n      ageRes = parent.config.face.age.enabled ? age.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:age';\n      timeStamp = now();\n      ageRes = parent.config.face.age.enabled ? await age.predict(face.image, parent.config) : {};\n      parent.perf.age = Math.trunc(now() - timeStamp);\n    }\n\n    // run gender, inherits face from blazeface\n    parent.analyze('Start Gender:');\n    if (parent.config.async) {\n      genderRes = parent.config.face.gender.enabled ? gender.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:gender';\n      timeStamp = now();\n      genderRes = parent.config.face.gender.enabled ? await gender.predict(face.image, parent.config) : {};\n      parent.perf.gender = Math.trunc(now() - timeStamp);\n    }\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Emotion:');\n    if (parent.config.async) {\n      emotionRes = parent.config.face.emotion.enabled ? emotion.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:emotion';\n      timeStamp = now();\n      emotionRes = parent.config.face.emotion.enabled ? await emotion.predict(face.image, parent.config) : {};\n      parent.perf.emotion = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Emotion:');\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Embedding:');\n    if (parent.config.async) {\n      embeddingRes = parent.config.face.embedding.enabled ? embedding.predict(face, parent.config) : [];\n    } else {\n      parent.state = 'run:embedding';\n      timeStamp = now();\n      embeddingRes = parent.config.face.embedding.enabled ? await embedding.predict(face, parent.config) : [];\n      parent.perf.embedding = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Embedding:');\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Description:');\n    if (parent.config.async) {\n      descRes = parent.config.face.description.enabled ? faceres.predict(face, parent.config) : [];\n    } else {\n      parent.state = 'run:description';\n      timeStamp = now();\n      descRes = parent.config.face.description.enabled ? await faceres.predict(face.image, parent.config) : [];\n      parent.perf.embedding = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Description:');\n\n    // if async wait for results\n    if (parent.config.async) {\n      [ageRes, genderRes, emotionRes, embeddingRes, descRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes, descRes]);\n    }\n\n    parent.analyze('Finish Face:');\n\n    // calculate iris distance\n    // iris: array[ center, left, top, right, bottom]\n    if (!parent.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n      delete face.annotations.leftEyeIris;\n      delete face.annotations.rightEyeIris;\n    }\n    const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n    /* average human iris size is 11.7mm */\n      ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n      : 0;\n\n    // combine results\n    faceRes.push({\n      ...face,\n      age: descRes.age || ageRes.age,\n      gender: descRes.gender || genderRes.gender,\n      genderConfidence: descRes.genderConfidence || genderRes.confidence,\n      embedding: descRes.descriptor || embeddingRes,\n      emotion: emotionRes,\n      iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n      rotation,\n      tensor: parent.config.face.detector.return ? face.image?.squeeze() : null,\n    });\n    // dispose original face tensor\n    face.image?.dispose();\n\n    parent.analyze('End Face');\n  }\n  parent.analyze('End FaceMesh:');\n  if (parent.config.async) {\n    if (parent.perf.face) delete parent.perf.face;\n    if (parent.perf.age) delete parent.perf.age;\n    if (parent.perf.gender) delete parent.perf.gender;\n    if (parent.perf.emotion) delete parent.perf.emotion;\n  }\n  return faceRes;\n};\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[2], prediction.box.endPoint[0]) - Math.max(0, prediction.box.startPoint[0]),\n        Math.min(input.shape[1], prediction.box.endPoint[1]) - Math.max(0, prediction.box.startPoint[1]),\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        prediction.box.startPoint[0] / input.shape[2],\n        prediction.box.startPoint[1] / input.shape[1],\n        (prediction.box.endPoint[0] - prediction.box.startPoint[0]) / input.shape[2],\n        (prediction.box.endPoint[1] - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: Math.round(100 * prediction.faceConfidence || 100 * prediction.boxConfidence || 0) / 100,\n        boxConfidence: Math.round(100 * prediction.boxConfidence) / 100,\n        faceConfidence: Math.round(100 * prediction.faceConfidence) / 100,\n        box,\n        boxRaw,\n        mesh,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config): Promise<MediaPipeFaceMesh> {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexport const triangulation = coords.TRI468;\nexport const uvmap = coords.UV468;\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\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++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\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 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]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\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];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\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 function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\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\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\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],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\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 MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\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 = [\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 = [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 = [\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 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\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 = [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 = [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", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\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], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  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.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\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.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\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 / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * 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.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${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\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (!config.videoOptimized || (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces)))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(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\n          // 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          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && (config.face.description.enabled || config.face.embedding.enabled) && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\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, landmarks };\n  }\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\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() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\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    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", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, 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(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.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 < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "export 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 NUM_KEYPOINTS = 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 const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\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", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\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 sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, 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 sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !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    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score: Math.round(100 * score) / 100 });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.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\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return 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: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, boxRaw: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - Math.max(0, prediction.box.topLeft[0]),\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - Math.max(0, prediction.box.topLeft[1]),\n      ] : [];\n      const boxRaw = [\n        (prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.topLeft[1]) / input.shape[1],\n        (prediction.box.bottomRight[0] - prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.bottomRight[1] - prediction.box.topLeft[1]) / input.shape[1],\n      ];\n      hands.push({ confidence: Math.round(100 * prediction.confidence) / 100, box, boxRaw, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config): Promise<HandPose> {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\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]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\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]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\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];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\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]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "export 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", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\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 box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.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 = [...box.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      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) 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.maxHands) || !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<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\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[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? 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 = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\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", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    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   x_center: 0.5625,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  const score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n  return [{ score, keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet keypoints: Array<any> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst bodyParts = ['head', 'neck', 'rightShoulder', 'rightElbow', 'rightWrist', 'chest', 'leftShoulder', 'leftElbow', 'leftWrist', 'pelvis', 'rightHip', 'rightKnee', 'rightAnkle', 'leftHip', 'leftKnee', 'leftAnkle'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\n// performs argmax and max functions on a 2d tensor\nfunction max2d(inputs, minScore) {\n  const [width, height] = inputs.shape;\n  return tf.tidy(() => {\n    // modulus op implemented in tf\n    const mod = (a, b) => tf.sub(a, tf.mul(tf.div(a, tf.scalar(b, 'int32')), tf.scalar(b, 'int32')));\n    // combine all data\n    const reshaped = tf.reshape(inputs, [height * width]);\n    // get highest score\n    const score = tf.max(reshaped, 0).dataSync()[0];\n    if (score > minScore) {\n      // skip coordinate calculation is score is too low\n      const coords = tf.argMax(reshaped, 0);\n      const x = mod(coords, width).dataSync()[0];\n      const y = tf.div(coords, tf.scalar(width, 'int32')).dataSync()[0];\n      return [x, y, score];\n    }\n    return [0, 0, score];\n  });\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.body.skipFrames) && config.videoOptimized && Object.keys(keypoints).length > 0) {\n    skipped++;\n    return keypoints;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const tensor = tf.tidy(() => {\n      const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n      const enhance = tf.mul(resize, 2);\n      const norm = enhance.sub(1);\n      return norm;\n    });\n\n    let resT;\n\n    if (!config.profile) {\n      if (config.body.enabled) resT = await model.predict(tensor);\n    } else {\n      const profileT = config.body.enabled ? await tf.profile(() => model.predict(tensor)) : {};\n      resT = profileT.result.clone();\n      profileT.result.dispose();\n      profile.run('body', profileT);\n    }\n    tensor.dispose();\n\n    if (resT) {\n      const parts: Array<{ id, score, part, position: { x, y }, positionRaw: { xRaw, yRaw} }> = [];\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, score] = max2d(stack[id], config.body.scoreThreshold);\n        if (score > config.body.scoreThreshold) {\n          parts.push({\n            id,\n            score: Math.round(100 * score) / 100,\n            part: bodyParts[id],\n            positionRaw: {\n              xRaw: x / model.inputs[0].shape[2], // x normalized to 0..1\n              yRaw: y / model.inputs[0].shape[1], // y normalized to 0..1\n            },\n            position: {\n              x: Math.round(image.shape[2] * x / model.inputs[0].shape[2]), // x normalized to input image size\n              y: Math.round(image.shape[1] * y / model.inputs[0].shape[1]), // y normalized to input image size\n            },\n          });\n        }\n      }\n      stack.forEach((s) => tf.dispose(s));\n      keypoints = parts;\n    }\n    const score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n    resolve([{ score, keypoints }]);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport { labels } from './labels';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let id = 0;\n  let results: Array<{ score: number, strideSize: number, class: number, label: string, center: number[], centerRaw: number[], box: number[], boxRaw: number[] }> = [];\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(() => { // 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 = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === labels.length))?.squeeze();\n      const featuresT = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] < labels.length))?.squeeze();\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 = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      const scores = scoresT.arraySync(); // 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 && 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) => 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 = [x, y, w, h]; // results normalized to range 0..1\n            boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // 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,\n              center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n              centerRaw: [cx, cy],\n              box: box.map((a) => Math.trunc(a)),\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);\n  const nmsScores = results.map((a) => a.score);\n  let nmsIdx: any[] = [];\n  if (nmsBoxes && nmsBoxes.length > 0) {\n    const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n    nmsIdx = nms.dataSync();\n    tf.dispose(nms);\n  }\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n    resize.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result;\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export 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", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\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.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) 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) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\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];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (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\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), 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, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\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  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\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  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\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    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\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    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\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;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\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)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\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  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\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  ].join('\\n');\n\n  _filter.brightness = function (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  _filter.saturation = function (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  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\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  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (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\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  _filter.desaturateLuminance = function () {\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  _filter.sepia = function () {\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  _filter.brownie = function () {\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  _filter.vintagePinhole = function () {\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  _filter.kodachrome = function () {\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  _filter.technicolor = function () {\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  _filter.polaroid = function () {\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  _filter.shiftToBGR = function () {\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  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\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  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\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  _filter.emboss = function (size) {\n    const s = size || 1;\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  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\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  _filter.blur.SHADER = [\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  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\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  ].join('\\n');\n}\n", "// @ts-nocheck\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\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 function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (!input) throw new Error('Human: Input is missing');\n  if (\n    !(input instanceof tf.Tensor)\n    && !(typeof Image !== 'undefined' && input instanceof Image)\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('Human: Input type is not recognized');\n  }\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\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    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) throw new Error('Human: Input cannot determine dimension');\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) { // if we have data, just convert to tensor\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if (outCanvas instanceof ImageData) { // if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else if (config.backend === 'webgl' || config.backend === 'humangl') { // tf kernel-optimized method to get imagedata\n      // we can use canvas as-is as it already has a context, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      pixels = tf.browser.fromPixels(tempCanvas);\n    } else { // cpu and wasm kernel does not implement efficient fromPixels method\n      // we can use canvas as-is as it already has a context, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "import { defaults } from '../config';\nimport { TRI468 as triangulation } from '../blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n  useRawBoxes: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n      else rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.rotation && f.rotation.angle && f.rotation.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.rotation.angle.roll) / 100} yaw:${Math.trunc(100 * f.rotation.angle.yaw) / 100} pitch:${Math.trunc(100 * f.rotation.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.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 (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.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 (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      if (result[i].keypoints) {\n        for (const pt of result[i].keypoints) {\n          ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n          ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons && result[i].keypoints) {\n      let part;\n      const points: any[] = [];\n      // shoulder line\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // torso main\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 4) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas: HTMLCanvasElement, outCanvas: HTMLCanvasElement) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas: HTMLCanvasElement, result:any) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\n/**\n * Configuration interface definition for **Human** library\n *\n * Contains all configurable parameters\n */\nexport interface Config {\n  backend: string,\n  wasmPath: string,\n  debug: boolean,\n  async: boolean,\n  profile: boolean,\n  deallocate: boolean,\n  scoped: boolean,\n  videoOptimized: boolean,\n  warmup: string,\n  filter: {\n    enabled: boolean,\n    width: number,\n    height: number,\n    return: boolean,\n    brightness: number,\n    contrast: number,\n    sharpness: number,\n    blur: number\n    saturation: number,\n    hue: number,\n    negative: boolean,\n    sepia: boolean,\n    vintage: boolean,\n    kodachrome: boolean,\n    technicolor: boolean,\n    polaroid: boolean,\n    pixelate: number,\n  },\n  gesture: {\n    enabled: boolean,\n  },\n  face: {\n    enabled: boolean,\n    detector: {\n      modelPath: string,\n      rotation: boolean,\n      maxFaces: number,\n      skipFrames: number,\n      skipInitial: boolean,\n      minConfidence: number,\n      iouThreshold: number,\n      scoreThreshold: number,\n      return: boolean,\n    },\n    mesh: {\n      enabled: boolean,\n      modelPath: string,\n    },\n    iris: {\n      enabled: boolean,\n      modelPath: string,\n    },\n    description: {\n      enabled: boolean,\n      modelPath: string,\n      skipFrames: number,\n    },\n    age: {\n      enabled: boolean,\n      modelPath: string,\n      skipFrames: number,\n    },\n    gender: {\n      enabled: boolean,\n      minConfidence: number,\n      modelPath: string,\n      skipFrames: number,\n    },\n    emotion: {\n      enabled: boolean,\n      minConfidence: number,\n      skipFrames: number,\n      modelPath: string,\n    },\n    embedding: {\n      enabled: boolean,\n      modelPath: string,\n    },\n  },\n  body: {\n    enabled: boolean,\n    modelPath: string,\n    maxDetections: number,\n    scoreThreshold: number,\n    nmsRadius: number,\n  },\n  hand: {\n    enabled: boolean,\n    rotation: boolean,\n    skipFrames: number,\n    skipInitial: boolean,\n    minConfidence: number,\n    iouThreshold: number,\n    scoreThreshold: number,\n    maxHands: number,\n    landmarks: boolean,\n    detector: {\n      modelPath: string,\n    },\n    skeleton: {\n      modelPath: string,\n    },\n  },\n  object: {\n    enabled: boolean,\n    modelPath: string,\n    minConfidence: number,\n    iouThreshold: number,\n    maxResults: number,\n    skipFrames: number,\n  },\n}\n\nconst config: Config = {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // 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    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    description: {\n      enabled: true,         // to improve accuracy of face description extraction it is\n                             // recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/faceres.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 32,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    age: {\n      enabled: false,        // obsolete, replaced by description module\n      modelPath: '../models/age.json',\n      skipFrames: 33,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: false,        // obsolete, replaced by description module\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 34,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    embedding: {\n      enabled: false,        // obsolete, replaced by description module\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet', 'blazepose' or 'efficientpose'\n                             // 'blazepose' and 'efficientpose' are experimental\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n                             // 'nanodet' is experimental\n    minConfidence: 0.20,     // threshold for discarding a prediction\n    iouThreshold: 0.40,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 41,          // how many frames to go without re-running the detector\n  },\n};\nexport { config as defaults };\n", "// data:image/jpeg;base64,\nexport const face = 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"import { log, now, mergeDeep } from './helpers';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as faceall from './faceall';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as faceres from './faceres/faceres';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as efficientpose from './efficientpose/efficientpose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image/image';\nimport * as draw from './draw/draw';\nimport * as profile from './profile';\nimport { Config, defaults } from './config';\nimport { Result } from './result';\nimport * as sample from './sample';\nimport * as app from '../package.json';\n\n/** Generic Tensor object type */\nexport type Tensor = typeof tf.Tensor;\nexport type { Config } from './config';\nexport type { Result } from './result';\n/** Defines all possible input types for **Human** detection */\nexport type Input = Tensor | typeof Image | ImageData | ImageBitmap | HTMLImageElement | HTMLMediaElement | HTMLVideoElement | HTMLCanvasElement | OffscreenCanvas;\n\n/** Error message */\nexport type Error = { error: string };\n/** Instance of TensorFlow/JS */\nexport type TensorFlow = typeof tf;\n/** Generic Model object type, holds instance of individual models */\ntype Model = Object;\n\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 */\nexport class Human {\n  version: string;\n  config: Config;\n  state: string;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: TensorFlow;\n  draw: {\n    drawOptions?: typeof draw.drawOptions,\n    gesture: typeof draw.gesture,\n    face: typeof draw.face,\n    body: typeof draw.body,\n    hand: typeof draw.hand,\n    canvas: typeof draw.canvas,\n    all: typeof draw.all,\n  };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | Model | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    efficientpose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n    faceres: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n    faceres: typeof faceres;\n  };\n  faceTriangulation: typeof facemesh.triangulation;\n  faceUVMap: typeof facemesh.uvmap;\n  sysinfo: { platform: string, agent: string };\n  perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: boolean;\n  #checkSanity: boolean;\n  #firstRun: boolean;\n  // definition end\n\n  constructor(userConfig: Config | Object = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.version = app.version;\n    this.config = mergeDeep(defaults, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      efficientpose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n      faceres: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Input) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      faceres,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    this.faceTriangulation = facemesh.triangulation;\n    this.faceUVMap = facemesh.uvmap;\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | string => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_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  similarity(embedding1: Array<number>, embedding2: Array<number>): number {\n    if (this.config.face.description.enabled) return faceres.similarity(embedding1, embedding2);\n    if (this.config.face.embedding.enabled) return embedding.similarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return faceres.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<number>, db: Array<{ name: string, source: string, embedding: number[] }>, threshold = 0): { name: string, source: string, similarity: number, embedding: number[] } {\n    return faceres.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Config | Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        // @ts-ignore\n        this.models.handpose,\n        // @ts-ignore false warning with latest @typescript-eslint\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.efficientpose,\n        this.models.nanodet,\n        this.models.faceres,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? <Promise<handpose.HandPose>>handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.blazepose || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.efficientpose || (this.config.body.enabled && this.config.body.modelPath.includes('efficientpose') ? efficientpose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n        this.models.faceres || ((this.config.face.enabled && this.config.face.description.enabled) ? faceres.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.body.enabled && !this.models.efficientpose && this.config.body.modelPath.includes('efficientpose')) this.models.efficientpose = await efficientpose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n      if (this.config.face.enabled && this.config.face.description.enabled && !this.models.faceres) this.models.faceres = await faceres.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.perf.load || 0)) this.perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        // force browser vs node backend\n        if (this.tf.ENV.flags.IS_BROWSER && this.config.backend === 'tensorflow') this.config.backend = 'webgl';\n        if (this.tf.ENV.flags.IS_NODE && (this.config.backend === 'webgl' || this.config.backend === 'wasm')) this.config.backend = 'tensorflow';\n\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      // this.tf.enableDebugMode();\n      if (this.tf.getBackend() === 'webgl' || this.tf.getBackend() === 'humangl') {\n        this.tf.ENV.set('CHECK_COMPUTATION_FOR_ERRORS', false);\n        this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  // main detect function\n  async detect(input: Input, userConfig: Config | Object = {}): Promise<Result | Error> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.perf.image = Math.trunc(now() - timeStamp);\n      this.analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n      let current;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? faceall.detectFace(this, process.tensor) : [];\n        if (this.perf.face) delete this.perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await faceall.detectFace(this, process.tensor) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.face = current;\n      }\n\n      // run body: can be posenet or blazepose\n      this.analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('blazepose')) bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('efficientpose')) bodyRes = this.config.body.enabled ? efficientpose.predict(process.tensor, this.config) : [];\n        if (this.perf.body) delete this.perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('blazepose')) bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('efficientpose')) bodyRes = this.config.body.enabled ? await efficientpose.predict(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.body = current;\n      }\n      this.analyze('End Body:');\n\n      // run handpose\n      this.analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.perf.hand) delete this.perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.hand = current;\n      }\n      this.analyze('End Hand:');\n\n      // run nanodet\n      this.analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.perf.object) delete this.perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.object = current;\n      }\n      this.analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.perf.gesture) delete this.perf.gesture;\n      }\n\n      this.perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      const result = {\n        face: faceRes,\n        body: bodyRes,\n        hand: handRes,\n        gesture: gestureRes,\n        object: objectRes,\n        performance: this.perf,\n        canvas: process.canvas,\n      };\n      // log('Result:', result);\n      resolve(result);\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\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 this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.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    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Config | Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\n/**\n * Class Human is also available as default export\n */\nexport { Human as default };\n"],
-  "mappings": 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+  "sourcesContent": ["// helper function: wrapper around console output\nexport function log(...msg) {\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')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n\n// helper function: gets elapsed time on both browser and nodejs\nexport const now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nexport function mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n", "export function info(): { platform: string, agent: string } {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1250, moduleBytes: 4013323, imports: 7, importBytes: 2255, outputBytes: 2991826, outputFiles: 'dist/tfjs.esm.js' }\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1253, moduleBytes: 4029357, imports: 7, importBytes: 2285, outputBytes: 2998298, outputFiles: 'dist/tfjs.esm.js' }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all - compiled\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all - sources\n/*\nexport * from '@tensorflow/tfjs-core/src/index';\nexport * from '@tensorflow/tfjs-layers/src/index';\nexport * from '@tensorflow/tfjs-converter/src/index';\nexport * as data from '@tensorflow/tfjs-data/src/index';\nexport * from '@tensorflow/tfjs-backend-cpu/src/index';\nexport * from '@tensorflow/tfjs-backend-webgl/src/index';\nexport * from '@tensorflow/tfjs-backend-wasm/src/index';\n*/\n\n// export versions\nexport const version = {\n  tfjs: packageBundle?.version || undefined,\n  'tfjs-core': packageCore?.version || undefined,\n  'tfjs-data': packageData?.version || undefined,\n  'tfjs-layers': packageLayers?.version || undefined,\n  'tfjs-converter': packageConverter?.version || undefined,\n  'tfjs-backend-cpu': version_cpu || undefined,\n  'tfjs-backend-webgl': version_webgl || undefined,\n  'tfjs-backend-wasm': version_wasm || undefined,\n};\n// export const version = {};\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\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\nexport function register(): void {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 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    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './helpers';\n\nexport const data = {};\n\nexport function run(modelName: string, profileData: any): void {\n  if (!profileData || !profileData.kernels) return;\n  const maxResults = 5;\n  const time = profileData.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = profileData.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = profileData.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  data[modelName] = {\n    model: modelName,\n    newBytes: profileData.newBytes,\n    newTensors: profileData.newTensors,\n    peakBytes: profileData.peakBytes,\n    numKernelOps: profileData.kernels.length,\n    timeKernelOps: time,\n    slowestKernelOps: slowest,\n    largestKernelOps: largest,\n  };\n  log('profiler', modelName, data[modelName]);\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(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 = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      if (!Array.isArray(genderT)) {\n        const data = genderT.dataSync();\n        if (alternative) {\n          // returns two values 0..1, bigger one is prediction\n          if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n            obj.gender = data[0] > data[1] ? 'female' : 'male';\n            obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n          }\n        } else {\n          // returns one value 0..1, .5 is prediction threshold\n          const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n          if (confidence > config.face.gender.minConfidence) {\n            obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n            obj.confidence = Math.min(0.99, confidence);\n          }\n        }\n        genderT.dispose();\n      } else {\n        const gender = genderT[0].dataSync();\n        const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n        /*\n        let age = genderT[1].argMax(1).dataSync()[0];\n        const all = genderT[1].dataSync();\n        age = Math.round(all[age - 1] > all[age + 1] ? 10 * age - 100 * all[age - 1] : 10 * age + 100 * all[age + 1]) / 10;\n        const descriptor = genderT[1].dataSync();\n        */\n        genderT.forEach((t) => tf.dispose(t));\n      }\n    }\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\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\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\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    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = typeof tf.Tensor;\ntype DB = Array<{ name: string, source: string, embedding: number[] }>;\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function similarity(embedding1, embedding2, order = 2): number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<number>, db: DB, threshold = 0) {\n  let best = { similarity: 0, name: '', source: '', embedding: [] as number[] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = similarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.similarity) best = { ...f, similarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = 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    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\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    // 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    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\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\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([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: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\ntype Tensor = typeof tf.Tensor;\ntype DB = Array<{ name: string, source: string, embedding: number[] }>;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.description.modelPath);\n    if (config.debug) log(`load model: ${config.face.description.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function similarity(embedding1, embedding2, order = 2): number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = 4.0 * embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(0, 100 - distance) / 100.0;\n  return res;\n}\n\nexport function match(embedding: Array<number>, db: DB, threshold = 0) {\n  let best = { similarity: 0, name: '', source: '', embedding: [] as number[] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = similarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.similarity) best = { ...f, similarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    const tensor = input.image || input.tensor || input;\n    if (!(tensor instanceof tf.Tensor)) return null;\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    // const crop = tf.image.resizeBilinear(tensor, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\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    /*\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\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n    /*\n    // normalize brightness from 0..1\n    const darken = crop.sub(crop.min());\n    const lighten = darken.div(darken.max());\n    */\n    const norm = crop.mul(255);\n\n    return norm;\n  });\n  return image;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.description.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    // const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    // const enhanced = tf.mul(resize, [255.0]);\n    // tf.dispose(resize);\n    const enhanced = enhance(image);\n\n    let resT;\n    const obj = {\n      age: <number>0,\n      gender: <string>'unknown',\n      genderConfidence: <number>0,\n      descriptor: <number[]>[] };\n\n    if (!config.profile) {\n      if (config.face.description.enabled) resT = await model.predict(enhanced);\n    } else {\n      const profileDesc = config.face.description.enabled ? await tf.profile(() => model.predict(enhanced)) : {};\n      resT = profileDesc.result;\n      profile.run('faceres', profileDesc);\n    }\n    tf.dispose(enhanced);\n\n    if (resT) {\n      tf.tidy(() => {\n        const gender = resT.find((t) => t.shape[1] === 1).dataSync();\n        const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n          obj.genderConfidence = Math.min(0.99, confidence);\n        }\n        const age = resT.find((t) => t.shape[1] === 100).argMax(1).dataSync()[0];\n        const all = resT.find((t) => t.shape[1] === 100).dataSync();\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]);\n        // const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n        obj.descriptor = [...desc.dataSync()];\n      });\n      resT.forEach((t) => tf.dispose(t));\n    }\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log, now } from './helpers';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as faceres from './faceres/faceres';\n\ntype Tensor = typeof tf.Tensor;\n\nconst calculateFaceAngle = (face, image_size): { angle: { pitch: number, yaw: number, roll: number }, matrix: [number, number, number, number, number, number, number, number, number] } => {\n  // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n  const degrees = (theta) => (theta * 180) / Math.PI;\n  // const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n  const normalize = (v) => { // 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, b) => { // 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, b) => { // 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) => {\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; let thetaY; let thetaZ;\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    return { pitch: 2 * -thetaX, yaw: 2 * -thetaY, roll: 2 * -thetaZ };\n  };\n  // simple Euler angle calculation based existing 3D mesh\n  // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n  const meshToEulerAngle = (mesh) => {\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // pitch is face move up/down\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\n      // yaw is face turn left/right\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\n      // roll is face lean 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\n    };\n    return angle;\n  };\n\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] };\n\n  const size = Math.max(face.boxRaw[2] * image_size[0], face.boxRaw[3] * image_size[1]) / 1.5;\n  // top, bottom, left, right\n  const pts = [mesh[10], mesh[152], mesh[234], mesh[454]].map((pt) => [\n    // make the xyz coordinates proportional, independent of the image/box size\n    pt[0] * image_size[0] / size,\n    pt[1] * image_size[1] / size,\n    pt[2],\n  ]);\n\n  const y_axis = normalize(subVectors(pts[1], pts[0]));\n  let x_axis = normalize(subVectors(pts[3], pts[2]));\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  return { angle, matrix };\n};\n\nexport const detectFace = async (parent, input): Promise<any> => {\n  // run facemesh, includes blazeface and iris\n  // eslint-disable-next-line no-async-promise-executor\n  let timeStamp;\n  let ageRes;\n  let genderRes;\n  let emotionRes;\n  let embeddingRes;\n  let descRes;\n  const faceRes: Array<{\n      confidence: number,\n      boxConfidence: number,\n      faceConfidence: number,\n      box: [number, number, number, number],\n      mesh: Array<[number, number, number]>\n      meshRaw: Array<[number, number, number]>\n      boxRaw: [number, number, number, number],\n      annotations: Array<{ part: string, points: Array<[number, number, number]>[] }>,\n      age: number,\n      gender: string,\n      genderConfidence: number,\n      emotion: string,\n      embedding: number[],\n      iris: number,\n      rotation: {\n        angle: { pitch: number, yaw: number, roll: number },\n        matrix: [number, number, number, number, number, number, number, number, number]\n      },\n      tensor: Tensor,\n    }> = [];\n  parent.state = 'run:face';\n  timeStamp = now();\n  const faces = await parent.models.face?.estimateFaces(input, parent.config);\n  parent.perf.face = Math.trunc(now() - timeStamp);\n  if (!faces) return [];\n  for (const face of faces) {\n    parent.analyze('Get Face');\n\n    // is something went wrong, skip the face\n    if (!face.image || face.image.isDisposedInternal) {\n      log('Face object is disposed:', face.image);\n      continue;\n    }\n\n    const rotation = calculateFaceAngle(face, [input.shape[2], input.shape[1]]);\n\n    // run age, inherits face from blazeface\n    parent.analyze('Start Age:');\n    if (parent.config.async) {\n      ageRes = parent.config.face.age.enabled ? age.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:age';\n      timeStamp = now();\n      ageRes = parent.config.face.age.enabled ? await age.predict(face.image, parent.config) : {};\n      parent.perf.age = Math.trunc(now() - timeStamp);\n    }\n\n    // run gender, inherits face from blazeface\n    parent.analyze('Start Gender:');\n    if (parent.config.async) {\n      genderRes = parent.config.face.gender.enabled ? gender.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:gender';\n      timeStamp = now();\n      genderRes = parent.config.face.gender.enabled ? await gender.predict(face.image, parent.config) : {};\n      parent.perf.gender = Math.trunc(now() - timeStamp);\n    }\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Emotion:');\n    if (parent.config.async) {\n      emotionRes = parent.config.face.emotion.enabled ? emotion.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:emotion';\n      timeStamp = now();\n      emotionRes = parent.config.face.emotion.enabled ? await emotion.predict(face.image, parent.config) : {};\n      parent.perf.emotion = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Emotion:');\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Embedding:');\n    if (parent.config.async) {\n      embeddingRes = parent.config.face.embedding.enabled ? embedding.predict(face, parent.config) : [];\n    } else {\n      parent.state = 'run:embedding';\n      timeStamp = now();\n      embeddingRes = parent.config.face.embedding.enabled ? await embedding.predict(face, parent.config) : [];\n      parent.perf.embedding = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Embedding:');\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Description:');\n    if (parent.config.async) {\n      descRes = parent.config.face.description.enabled ? faceres.predict(face, parent.config) : [];\n    } else {\n      parent.state = 'run:description';\n      timeStamp = now();\n      descRes = parent.config.face.description.enabled ? await faceres.predict(face.image, parent.config) : [];\n      parent.perf.embedding = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Description:');\n\n    // if async wait for results\n    if (parent.config.async) {\n      [ageRes, genderRes, emotionRes, embeddingRes, descRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes, descRes]);\n    }\n\n    parent.analyze('Finish Face:');\n\n    // calculate iris distance\n    // iris: array[ center, left, top, right, bottom]\n    if (!parent.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n      delete face.annotations.leftEyeIris;\n      delete face.annotations.rightEyeIris;\n    }\n    const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n    /* average human iris size is 11.7mm */\n      ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n      : 0;\n\n    // combine results\n    faceRes.push({\n      ...face,\n      age: descRes.age || ageRes.age,\n      gender: descRes.gender || genderRes.gender,\n      genderConfidence: descRes.genderConfidence || genderRes.confidence,\n      embedding: descRes.descriptor || embeddingRes,\n      emotion: emotionRes,\n      iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n      rotation,\n      tensor: parent.config.face.detector.return ? face.image?.squeeze() : null,\n    });\n    // dispose original face tensor\n    face.image?.dispose();\n\n    parent.analyze('End Face');\n  }\n  parent.analyze('End FaceMesh:');\n  if (parent.config.async) {\n    if (parent.perf.face) delete parent.perf.face;\n    if (parent.perf.age) delete parent.perf.age;\n    if (parent.perf.gender) delete parent.perf.gender;\n    if (parent.perf.emotion) delete parent.perf.emotion;\n  }\n  return faceRes;\n};\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[2], prediction.box.endPoint[0]) - Math.max(0, prediction.box.startPoint[0]),\n        Math.min(input.shape[1], prediction.box.endPoint[1]) - Math.max(0, prediction.box.startPoint[1]),\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        prediction.box.startPoint[0] / input.shape[2],\n        prediction.box.startPoint[1] / input.shape[1],\n        (prediction.box.endPoint[0] - prediction.box.startPoint[0]) / input.shape[2],\n        (prediction.box.endPoint[1] - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: Math.round(100 * prediction.faceConfidence || 100 * prediction.boxConfidence || 0) / 100,\n        boxConfidence: Math.round(100 * prediction.boxConfidence) / 100,\n        faceConfidence: Math.round(100 * prediction.faceConfidence) / 100,\n        box,\n        boxRaw,\n        mesh,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config): Promise<MediaPipeFaceMesh> {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexport const triangulation = coords.TRI468;\nexport const uvmap = coords.UV468;\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\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++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\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 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]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\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];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\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 function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\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\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\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],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\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 MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\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 = [\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 = [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 = [\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 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\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 = [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 = [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", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\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], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  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.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\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.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\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 / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * 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.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${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\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (!config.videoOptimized || (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces)))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(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\n          // 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          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && (config.face.description.enabled || config.face.embedding.enabled) && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\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, landmarks };\n  }\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\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() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\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    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", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, 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(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.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 < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "export 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 NUM_KEYPOINTS = 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 const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\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", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\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 sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, 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 sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !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    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score: Math.round(100 * score) / 100 });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.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\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return 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: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, boxRaw: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - Math.max(0, prediction.box.topLeft[0]),\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - Math.max(0, prediction.box.topLeft[1]),\n      ] : [];\n      const boxRaw = [\n        (prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.topLeft[1]) / input.shape[1],\n        (prediction.box.bottomRight[0] - prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.bottomRight[1] - prediction.box.topLeft[1]) / input.shape[1],\n      ];\n      hands.push({ confidence: Math.round(100 * prediction.confidence) / 100, box, boxRaw, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config): Promise<HandPose> {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\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]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\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]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\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];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\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]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "export 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", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\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 box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.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 = [...box.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      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) 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.maxHands) || !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<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\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[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? 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 = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\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", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.984375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.984375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    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   x_center: 0.5625,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  const score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n  return [{ score, keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet keypoints: Array<any> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst bodyParts = ['head', 'neck', 'rightShoulder', 'rightElbow', 'rightWrist', 'chest', 'leftShoulder', 'leftElbow', 'leftWrist', 'pelvis', 'rightHip', 'rightKnee', 'rightAnkle', 'leftHip', 'leftKnee', 'leftAnkle'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\n// performs argmax and max functions on a 2d tensor\nfunction max2d(inputs, minScore) {\n  const [width, height] = inputs.shape;\n  return tf.tidy(() => {\n    // modulus op implemented in tf\n    const mod = (a, b) => tf.sub(a, tf.mul(tf.div(a, tf.scalar(b, 'int32')), tf.scalar(b, 'int32')));\n    // combine all data\n    const reshaped = tf.reshape(inputs, [height * width]);\n    // get highest score\n    const score = tf.max(reshaped, 0).dataSync()[0];\n    if (score > minScore) {\n      // skip coordinate calculation is score is too low\n      const coords = tf.argMax(reshaped, 0);\n      const x = mod(coords, width).dataSync()[0];\n      const y = tf.div(coords, tf.scalar(width, 'int32')).dataSync()[0];\n      return [x, y, score];\n    }\n    return [0, 0, score];\n  });\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.body.skipFrames) && config.videoOptimized && Object.keys(keypoints).length > 0) {\n    skipped++;\n    return keypoints;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const tensor = tf.tidy(() => {\n      const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n      const enhance = tf.mul(resize, 2);\n      const norm = enhance.sub(1);\n      return norm;\n    });\n\n    let resT;\n\n    if (!config.profile) {\n      if (config.body.enabled) resT = await model.predict(tensor);\n    } else {\n      const profileT = config.body.enabled ? await tf.profile(() => model.predict(tensor)) : {};\n      resT = profileT.result.clone();\n      profileT.result.dispose();\n      profile.run('body', profileT);\n    }\n    tensor.dispose();\n\n    if (resT) {\n      const parts: Array<{ id, score, part, position: { x, y }, positionRaw: { xRaw, yRaw} }> = [];\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, score] = max2d(stack[id], config.body.scoreThreshold);\n        if (score > config.body.scoreThreshold) {\n          parts.push({\n            id,\n            score: Math.round(100 * score) / 100,\n            part: bodyParts[id],\n            positionRaw: {\n              xRaw: x / model.inputs[0].shape[2], // x normalized to 0..1\n              yRaw: y / model.inputs[0].shape[1], // y normalized to 0..1\n            },\n            position: {\n              x: Math.round(image.shape[2] * x / model.inputs[0].shape[2]), // x normalized to input image size\n              y: Math.round(image.shape[1] * y / model.inputs[0].shape[1]), // y normalized to input image size\n            },\n          });\n        }\n      }\n      stack.forEach((s) => tf.dispose(s));\n      keypoints = parts;\n    }\n    const score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n    resolve([{ score, keypoints }]);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport { labels } from './labels';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let id = 0;\n  let results: Array<{ score: number, strideSize: number, class: number, label: string, center: number[], centerRaw: number[], box: number[], boxRaw: number[] }> = [];\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(() => { // 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 = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === labels.length))?.squeeze();\n      const featuresT = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] < labels.length))?.squeeze();\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 = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      const scores = scoresT.arraySync(); // 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 && 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) => 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 = [x, y, w, h]; // results normalized to range 0..1\n            boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // 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,\n              center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n              centerRaw: [cx, cy],\n              box: box.map((a) => Math.trunc(a)),\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);\n  const nmsScores = results.map((a) => a.score);\n  let nmsIdx: any[] = [];\n  if (nmsBoxes && nmsBoxes.length > 0) {\n    const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n    nmsIdx = nms.dataSync();\n    tf.dispose(nms);\n  }\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n    resize.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result;\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export 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", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\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.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) 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) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\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];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (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\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), 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, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\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  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\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  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\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    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\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    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\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;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\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)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\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  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\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  ].join('\\n');\n\n  _filter.brightness = function (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  _filter.saturation = function (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  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\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  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (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\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  _filter.desaturateLuminance = function () {\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  _filter.sepia = function () {\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  _filter.brownie = function () {\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  _filter.vintagePinhole = function () {\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  _filter.kodachrome = function () {\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  _filter.technicolor = function () {\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  _filter.polaroid = function () {\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  _filter.shiftToBGR = function () {\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  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\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  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\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  _filter.emboss = function (size) {\n    const s = size || 1;\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  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\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  _filter.blur.SHADER = [\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  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\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  ].join('\\n');\n}\n", "// @ts-nocheck\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\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 function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (!input) throw new Error('Human: Input is missing');\n  if (\n    !(input instanceof tf.Tensor)\n    && !(typeof Image !== 'undefined' && input instanceof Image)\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('Human: Input type is not recognized');\n  }\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\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    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) throw new Error('Human: Input cannot determine dimension');\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) { // if we have data, just convert to tensor\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if (outCanvas instanceof ImageData) { // if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else if (config.backend === 'webgl' || config.backend === 'humangl') { // tf kernel-optimized method to get imagedata\n      // we can use canvas as-is as it already has a context, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      pixels = tf.browser.fromPixels(tempCanvas);\n    } else { // cpu and wasm kernel does not implement efficient fromPixels method\n      // we can use canvas as-is as it already has a context, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "import { defaults } from '../config';\nimport { TRI468 as triangulation } from '../blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n  useRawBoxes: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n      else rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.rotation && f.rotation.angle && f.rotation.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.rotation.angle.roll) / 100} yaw:${Math.trunc(100 * f.rotation.angle.yaw) / 100} pitch:${Math.trunc(100 * f.rotation.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.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 (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.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 (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      if (result[i].keypoints) {\n        for (const pt of result[i].keypoints) {\n          ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n          ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons && result[i].keypoints) {\n      let part;\n      const points: any[] = [];\n      // shoulder line\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // torso main\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 4) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas: HTMLCanvasElement, outCanvas: HTMLCanvasElement) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas: HTMLCanvasElement, result:any) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\n/**\n * Configuration interface definition for **Human** library\n *\n * Contains all configurable parameters\n */\nexport interface Config {\n  backend: string,\n  wasmPath: string,\n  debug: boolean,\n  async: boolean,\n  profile: boolean,\n  deallocate: boolean,\n  scoped: boolean,\n  videoOptimized: boolean,\n  warmup: string,\n  filter: {\n    enabled: boolean,\n    width: number,\n    height: number,\n    return: boolean,\n    brightness: number,\n    contrast: number,\n    sharpness: number,\n    blur: number\n    saturation: number,\n    hue: number,\n    negative: boolean,\n    sepia: boolean,\n    vintage: boolean,\n    kodachrome: boolean,\n    technicolor: boolean,\n    polaroid: boolean,\n    pixelate: number,\n  },\n  gesture: {\n    enabled: boolean,\n  },\n  face: {\n    enabled: boolean,\n    detector: {\n      modelPath: string,\n      rotation: boolean,\n      maxFaces: number,\n      skipFrames: number,\n      skipInitial: boolean,\n      minConfidence: number,\n      iouThreshold: number,\n      scoreThreshold: number,\n      return: boolean,\n    },\n    mesh: {\n      enabled: boolean,\n      modelPath: string,\n    },\n    iris: {\n      enabled: boolean,\n      modelPath: string,\n    },\n    description: {\n      enabled: boolean,\n      modelPath: string,\n      skipFrames: number,\n    },\n    age: {\n      enabled: boolean,\n      modelPath: string,\n      skipFrames: number,\n    },\n    gender: {\n      enabled: boolean,\n      minConfidence: number,\n      modelPath: string,\n      skipFrames: number,\n    },\n    emotion: {\n      enabled: boolean,\n      minConfidence: number,\n      skipFrames: number,\n      modelPath: string,\n    },\n    embedding: {\n      enabled: boolean,\n      modelPath: string,\n    },\n  },\n  body: {\n    enabled: boolean,\n    modelPath: string,\n    maxDetections: number,\n    scoreThreshold: number,\n    nmsRadius: number,\n  },\n  hand: {\n    enabled: boolean,\n    rotation: boolean,\n    skipFrames: number,\n    skipInitial: boolean,\n    minConfidence: number,\n    iouThreshold: number,\n    scoreThreshold: number,\n    maxHands: number,\n    landmarks: boolean,\n    detector: {\n      modelPath: string,\n    },\n    skeleton: {\n      modelPath: string,\n    },\n  },\n  object: {\n    enabled: boolean,\n    modelPath: string,\n    minConfidence: number,\n    iouThreshold: number,\n    maxResults: number,\n    skipFrames: number,\n  },\n}\n\nconst config: Config = {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // 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    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    description: {\n      enabled: true,         // to improve accuracy of face description extraction it is\n                             // recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/faceres.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 32,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    age: {\n      enabled: false,        // obsolete, replaced by description module\n      modelPath: '../models/age.json',\n      skipFrames: 33,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: false,        // obsolete, replaced by description module\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 34,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    embedding: {\n      enabled: false,        // obsolete, replaced by description module\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet', 'blazepose' or 'efficientpose'\n                             // 'blazepose' and 'efficientpose' are experimental\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n                             // 'nanodet' is experimental\n    minConfidence: 0.20,     // threshold for discarding a prediction\n    iouThreshold: 0.40,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 41,          // how many frames to go without re-running the detector\n  },\n};\nexport { config as defaults };\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import { log, now, mergeDeep } from './helpers';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as faceall from './faceall';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as faceres from './faceres/faceres';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as efficientpose from './efficientpose/efficientpose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image/image';\nimport * as draw from './draw/draw';\nimport * as profile from './profile';\nimport { Config, defaults } from './config';\nimport { Result } from './result';\nimport * as sample from './sample';\nimport * as app from '../package.json';\n\n/** Generic Tensor object type */\nexport type Tensor = typeof tf.Tensor;\nexport type { Config } from './config';\nexport type { Result } from './result';\n/** Defines all possible input types for **Human** detection */\nexport type Input = Tensor | typeof Image | ImageData | ImageBitmap | HTMLImageElement | HTMLMediaElement | HTMLVideoElement | HTMLCanvasElement | OffscreenCanvas;\n\n/** Error message */\nexport type Error = { error: string };\n/** Instance of TensorFlow/JS */\nexport type TensorFlow = typeof tf;\n/** Generic Model object type, holds instance of individual models */\ntype Model = Object;\n\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 */\nexport class Human {\n  version: string;\n  config: Config;\n  state: string;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: TensorFlow;\n  draw: {\n    drawOptions?: typeof draw.drawOptions,\n    gesture: typeof draw.gesture,\n    face: typeof draw.face,\n    body: typeof draw.body,\n    hand: typeof draw.hand,\n    canvas: typeof draw.canvas,\n    all: typeof draw.all,\n  };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | Model | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    efficientpose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n    faceres: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n    faceres: typeof faceres;\n  };\n  faceTriangulation: typeof facemesh.triangulation;\n  faceUVMap: typeof facemesh.uvmap;\n  sysinfo: { platform: string, agent: string };\n  perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: boolean;\n  #checkSanity: boolean;\n  #firstRun: boolean;\n  // definition end\n\n  constructor(userConfig: Config | Object = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.version = app.version;\n    this.config = mergeDeep(defaults, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      efficientpose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n      faceres: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Input) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      faceres,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    this.faceTriangulation = facemesh.triangulation;\n    this.faceUVMap = facemesh.uvmap;\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | string => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_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  similarity(embedding1: Array<number>, embedding2: Array<number>): number {\n    if (this.config.face.description.enabled) return faceres.similarity(embedding1, embedding2);\n    if (this.config.face.embedding.enabled) return embedding.similarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return faceres.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<number>, db: Array<{ name: string, source: string, embedding: number[] }>, threshold = 0): { name: string, source: string, similarity: number, embedding: number[] } {\n    return faceres.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Config | Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        // @ts-ignore\n        this.models.handpose,\n        // @ts-ignore false warning with latest @typescript-eslint\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.efficientpose,\n        this.models.nanodet,\n        this.models.faceres,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? <Promise<handpose.HandPose>>handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.blazepose || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.efficientpose || (this.config.body.enabled && this.config.body.modelPath.includes('efficientpose') ? efficientpose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n        this.models.faceres || ((this.config.face.enabled && this.config.face.description.enabled) ? faceres.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.body.enabled && !this.models.efficientpose && this.config.body.modelPath.includes('efficientpose')) this.models.efficientpose = await efficientpose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n      if (this.config.face.enabled && this.config.face.description.enabled && !this.models.faceres) this.models.faceres = await faceres.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.perf.load || 0)) this.perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        // force browser vs node backend\n        if (this.tf.ENV.flags.IS_BROWSER && this.config.backend === 'tensorflow') this.config.backend = 'webgl';\n        if (this.tf.ENV.flags.IS_NODE && (this.config.backend === 'webgl' || this.config.backend === 'wasm')) this.config.backend = 'tensorflow';\n\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      // this.tf.enableDebugMode();\n      if (this.tf.getBackend() === 'webgl' || this.tf.getBackend() === 'humangl') {\n        this.tf.ENV.set('CHECK_COMPUTATION_FOR_ERRORS', false);\n        this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  // main detect function\n  async detect(input: Input, userConfig: Config | Object = {}): Promise<Result | Error> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.perf.image = Math.trunc(now() - timeStamp);\n      this.analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n      let current;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? faceall.detectFace(this, process.tensor) : [];\n        if (this.perf.face) delete this.perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await faceall.detectFace(this, process.tensor) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.face = current;\n      }\n\n      // run body: can be posenet or blazepose\n      this.analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('blazepose')) bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('efficientpose')) bodyRes = this.config.body.enabled ? efficientpose.predict(process.tensor, this.config) : [];\n        if (this.perf.body) delete this.perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('blazepose')) bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('efficientpose')) bodyRes = this.config.body.enabled ? await efficientpose.predict(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.body = current;\n      }\n      this.analyze('End Body:');\n\n      // run handpose\n      this.analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.perf.hand) delete this.perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.hand = current;\n      }\n      this.analyze('End Hand:');\n\n      // run nanodet\n      this.analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.perf.object) delete this.perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.object = current;\n      }\n      this.analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.perf.gesture) delete this.perf.gesture;\n      }\n\n      this.perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      const result = {\n        face: faceRes,\n        body: bodyRes,\n        hand: handRes,\n        gesture: gestureRes,\n        object: objectRes,\n        performance: this.perf,\n        canvas: process.canvas,\n      };\n      // log('Result:', result);\n      resolve(result);\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\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 this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.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    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Config | Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\n/**\n * Class Human is also available as default export\n */\nexport { Human as default };\n"],
+  "mappings": 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   "names": []
 }
diff --git a/dist/human.esm.js b/dist/human.esm.js
index 56a68e03..9bf3583b 100644
--- a/dist/human.esm.js
+++ b/dist/human.esm.js
@@ -5,31 +5,31 @@
   author: <https://github.com/vladmandic>'
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r=++this.pendingBackendInitId,a=n.then(s=>r<this.pendingBackendInitId?!1:(this.registry[e]=s,this.pendingBackendInit=null,!0)).catch(s=>(r<this.pendingBackendInitId||(this.pendingBackendInit=null,console.warn(`Initialization of backend ${e} failed`),console.warn(s.stack||s.message)),!1));return this.pendingBackendInit=a,{success:a,asyncInit:!0}}else return this.registry[e]=n,{success:!0,asyncInit:!1}}catch(n){return console.warn(`Initialization of backend ${e} failed`),console.warn(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${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:r,asyncInit:a}=this.initializeBackend(n);if(a||r)return{name:n,asyncInit:a}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let n=this.state.tensorInfo.get(t),r=n.backend,a=this.readSync(t),s=r.refCount(t);r.disposeData(t,!0),n.backend=e,e.move(t,a,n.shape,n.dtype,s),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 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this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let r=this.backend.numDataIds(),a=0;n.forEach(o=>{a+=o.dtype==="complex64"?3:1});let s=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=r-t-a-s;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],r=this.isTapeOn(),a=this.state.numBytes,s=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let o,l=bf(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(bf(e)){let{kernelName:p,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let A=ad(p,this.backendName);M(A!=null,()=>`Cannot find registered kernel '${p}' for backend '${this.backendName}'`),i=()=>{let y=this.backend.numDataIds();o=A.kernelFunc({inputs:f,attrs:m,backend:this.backend});let g=Array.isArray(o)?o:[o];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(p,y,g);let w=g.map(b=>{if(b.rank!=null)return b;let{dataId:_,shape:x,dtype:N}=b;return this.makeTensorFromDataId(_,x,N)});if(r){let b=this.getTensorsForGradient(p,f,w);n=this.saveTensorsForBackwardMode(b)}return w}}else{let{forwardFunc:p}=e,f=m=>{!r||(n=m.map(A=>this.keep(this.clone(A))))};i=()=>{let m=this.backend.numDataIds();o=this.tidy(()=>p(this.backend,f));let A=Array.isArray(o)?o:[o];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,m,A),A}}let{inputs:c,attrs:u}=e,h=bf(e)?null:e.backwardsFunc,d;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(d=this.profiler.profileKernel(l,c,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),r&&this.addTapeNode(l,c,t,h,n,u),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-a,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-s,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(c).map(p=>c[p]!=null?c[p].shape:null),outputShapes:t.map(p=>p.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(t=>this.keep(this.clone(t)))}getTensorsForGradient(e,t,n){let r=pf(e);if(r!=null){let a=r.inputsToSave||[],s=r.outputsToSave||[],i;r.saveAllInputs?(M(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(l=>t[l])):i=a.map(l=>t[l]);let 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n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*sf(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 Du||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*sf(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(r=>r.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let r of 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n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*hf(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 $u||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*hf(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 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+          with dtype ${s.dtype}. `)}),n.length===1)return Rr(n[0]);let r=n,a={axis:t};return D.runKernel(io,r,a)}var rt=O({concat_:yS});function gS(e){let t={x:C(e,"x","sigmoid")};return D.runKernel(Us,t)}var Rn=O({sigmoid_:gS});function xS(e,t,n){let r=C(e,"x","slice","string_or_numeric");if(r.rank===0)throw new Error("Slicing scalar is not possible");let a={x:r},s={begin:t,size:n};return D.runKernel(Bo,a,s)}var Ce=O({slice_:xS});function bS(e){let t={x:C(e,"x","tanh")};return D.runKernel(Zs,t)}var ll=O({tanh_:bS});function wS(e,t,n,r,a,s){let i=C(e,"forgetBias","basicLSTMCell"),o=C(t,"lstmKernel","basicLSTMCell"),l=C(n,"lstmBias","basicLSTMCell"),c=C(r,"data","basicLSTMCell"),u=C(a,"c","basicLSTMCell"),h=C(s,"h","basicLSTMCell"),d=rt([c,h],1),p=Ge(d,o),f=se(p,l),m=f.shape[0],A=f.shape[1]/4,y=[m,A],g=Ce(f,[0,0],y),b=Ce(f,[0,A],y),w=Ce(f,[0,A*2],y),_=Ce(f,[0,A*3],y),x=se(P(Rn(g),ll(b)),P(u,Rn(se(i,w)))),N=P(ll(x),Rn(_));return[x,N]}var _S=O({basicLSTMCell_:wS});function vS(e,t,n){let r=C(e,"x","batchToSpaceND"),a=t.reduce((o,l)=>o*l);M(r.rank>=1+t.length,()=>`input rank is ${r.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(r.shape[0]%a==0,()=>`input tensor batch is ${r.shape[0]} but is not divisible by the product of the elements of blockShape ${t.join(" * ")} === ${a}`);let s={x:r},i={blockShape:t,crops:n};return D.runKernel(fu,s,i)}var ju=O({batchToSpaceND_:vS});function kS(e){let t;return e.rank===0||e.rank===1?t=H(e,[1,1,1,e.size]):e.rank===2?t=H(e,[1,1,e.shape[0],e.shape[1]]):e.rank===3?t=H(e,[1,e.shape[0],e.shape[1],e.shape[2]]):t=e,t}function IS(e,t,n,r,a,s){s==null&&(s=.001);let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),c;a!=null&&(c=C(a,"scale","batchNorm"));let u;r!=null&&(u=C(r,"offset","batchNorm")),M(o.rank===l.rank,()=>"Batch normalization gradient requires mean and variance to have equal 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${c.rank}.`),u!=null&&M(u.rank===2||u.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${u.rank}.`),ui(i,o,l,u,c,s)}var Fb=O({batchNorm2d_:NS});function SS(e,t,n,r,a,s){let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),c;a!=null&&(c=C(a,"scale","batchNorm"));let u;return r!=null&&(u=C(r,"offset","batchNorm")),M(i.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${i.rank}.`),M(o.rank===3||o.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${o.rank}.`),M(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`),c!=null&&M(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${c.rank}.`),u!=null&&M(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${u.rank}.`),ui(i,o,l,u,c,s)}var Db=O({batchNorm3d_:SS});function TS(e,t,n,r,a,s){let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),c;a!=null&&(c=C(a,"scale","batchNorm"));let u;return r!=null&&(u=C(r,"offset","batchNorm")),M(i.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${i.rank}.`),M(o.rank===4||o.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${o.rank}.`),M(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),c!=null&&M(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${c.rank}.`),u!=null&&M(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${u.rank}.`),ui(i,o,l,u,c,s)}var $b=O({batchNorm4d_:TS});function ES(e,t,n){let r=C(e,"x","bincount"),a=C(t,"weights","bincount");M(r.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${r.dtype}`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(a.size===r.size||a.size===0,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${r.shape}, weights shape: ${a.shape}.`);let s={x:r,weights:a},i={size:n};return D.runKernel(Ch,s,i)}var Ob=O({bincount_:ES});function CS(e,t){let n=C(e,"broadcastTo","x"),r=n.shape;if(t.some(l=>!(l>0)||l%1!=0))throw new Error(`broadcastTo(): Invalid broadcast shape [${t}].`);if(t.length<n.rank)throw new Error(`broadcastTo(): shape.length=${t.length} < input.rank=${n.rank}.`);if(t.length>n.rank){let l=n.shape.slice();for(;l.length<t.length;)l.unshift(1);n=H(n,l)}let a=n.shape,s=Array.from(t);for(let l=t.length-1;l>=0;l--)if(a[l]===t[l])s[l]=1;else if(n.shape[l]!==1)throw new Error(`broadcastTo(): [${r}] cannot be broadcast to [${t}].`);if(s.map((l,c)=>l>1?c:-1).filter(l=>l>=0).length===0)return Rr(n);let i={x:n},o={reps:s};return D.runKernel(Ia,i,o)}var Uu=O({broadcastTo_:CS});function RS(e){let t={x:C(e,"x","ceil")};return D.runKernel(hs,t)}var am=O({ceil_:RS});function MS(e,t,n){let r=C(e,"x","clipByValue");M(t<=n,()=>`Error in clip: min (${t}) must be less than or equal to max (${n}).`);let a={x:r},s={clipValueMin:t,clipValueMax:n};return D.runKernel(ka,a,s)}var wn=O({clipByValue_:MS});function FS(e){return rt(e,0)}var zb=O({concat1d_:FS});function DS(e,t){return rt(e,t)}var ul=O({concat2d_:DS});function $S(e,t){return rt(e,t)}var Pb=O({concat3d_:$S});function OS(e,t){return rt(e,t)}var Lb=O({concat4d_:OS});function zS(e,t,n,r,a="NHWC",s=[1,1],i){let o=C(e,"x","conv2d"),l=C(t,"filter","conv2d"),c=o,u=!1;o.rank===3&&(u=!0,c=H(o,[1,o.shape[0],o.shape[1],o.shape[2]])),M(c.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${c.rank}.`),M(l.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`),i!=null&&M(Vt(r),()=>`Error in conv2d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`);let h=a==="NHWC"?c.shape[3]:c.shape[1];M(h===l.shape[2],()=>`Error in conv2d: depth of input (${h}) must match input depth for filter ${l.shape[2]}.`),M(Fr(n,s),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${s}'`);let d={x:c,filter:l},p={strides:n,pad:r,dataFormat:a,dilations:s,dimRoundingMode:i},f=D.runKernel(ds,d,p);return u?H(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var na=O({conv2d_:zS});function PS(e,t,n,r,a="NWC",s=1,i){let o=C(e,"x","conv1d"),l=C(t,"filter","conv1d"),c=o,u=!1;o.rank===2&&(u=!0,c=H(o,[1,o.shape[0],o.shape[1]])),M(c.rank===3,()=>`Error in conv1d: input must be rank 3, but got rank ${c.rank}.`),M(l.rank===3,()=>`Error in conv1d: filter must be rank 3, but got rank ${l.rank}.`),i!=null&&M(Vt(r),()=>`Error in conv1d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`),M(c.shape[2]===l.shape[1],()=>`Error in conv1d: depth of input (${c.shape[2]}) must match input depth for filter ${l.shape[1]}.`),M(Fr(n,s),()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${n} and dilation '${s}'`),M(a==="NWC",()=>`Error in conv1d: got dataFormat of ${a} but only NWC is currently supported.`);let h=H(l,[1,l.shape[0],l.shape[1],l.shape[2]]),d=H(c,[c.shape[0],1,c.shape[1],c.shape[2]]),p=na(d,h,[1,n],r,"NHWC",[1,s],i);return u?H(p,[p.shape[2],p.shape[3]]):H(p,[p.shape[0],p.shape[2],p.shape[3]])}var yd=O({conv1d_:PS});function LS(e,t,n,r,a,s="NHWC",i){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let o=e,l=t,c=!1;t.rank===3&&(c=!0,l=H(t,[1,t.shape[0],t.shape[1],t.shape[2]]),o=[1,e[0],e[1],e[2]]),M(o.length===4,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${o.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 ${n.rank}`);let u=s==="NHWC"?o[3]:o[1],h=s==="NHWC"?l.shape[3]:l.shape[1];M(u===n.shape[2],()=>`Error in conv2dDerInput: depth of input (${u}) must match input depth for filter ${n.shape[2]}.`),M(h===n.shape[3],()=>`Error in conv2dDerInput: depth of output (${h}) must match output depth for filter ${n.shape[3]}.`),i!=null&&M(Vt(a),()=>`Error in conv2dDerInput: pad must be an integer when using, dimRoundingMode ${i} but got pad ${a}.`);let d={dy:l,filter:n},p={strides:r,pad:a,dataFormat:s,dimRoundingMode:i,inputShape:o},f=D.runKernel(ps,d,p);return c?H(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var sm=O({conv2DBackpropInput_:LS});function WS(e,t,n,r,a,s){let i=C(e,"x","conv2dTranspose"),o=C(t,"filter","conv2dTranspose");return sm(n,i,o,r,a,"NHWC",s)}var gd=O({conv2dTranspose_:WS});function BS(e,t,n,r,a="NDHWC",s=[1,1,1]){let i=C(e,"x","conv3d"),o=C(t,"filter","conv3d"),l=i,c=!1;i.rank===4&&(c=!0,l=H(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),M(l.rank===5,()=>`Error in conv3d: input must be rank 5, but got rank ${l.rank}.`),M(o.rank===5,()=>`Error in conv3d: filter must be rank 5, but got rank ${o.rank}.`),M(l.shape[4]===o.shape[3],()=>`Error in conv3d: depth of input (${l.shape[4]}) must match input depth for filter ${o.shape[3]}.`),M(Fr(n,s),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${n} and dilations '${s}'`),M(a==="NDHWC",()=>`Error in conv3d: got dataFormat of ${a} but only NDHWC is currently supported.`);let u={x:l,filter:o},h={strides:n,pad:r,dataFormat:a,dilations:s},d=D.runKernel(Au,u,h);return c?H(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var im=O({conv3d_:BS});function VS(e,t,n,r,a){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let s=e,i=t,o=!1;t.rank===4&&(o=!0,i=H(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),s=[1,e[0],e[1],e[2],e[3]]);let l=s[4],c=i.shape[4];M(s.length===5,()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${s.length}.`),M(i.rank===5,()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${i.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 ${n.shape[3]}.`),M(c===n.shape[4],()=>`Error in conv3dDerInput: depth of output (${c}) must match output depth for filter ${n.shape[4]}.`);let u={dy:i,filter:n},h={pad:a,strides:r,inputShape:s},d=D.runKernel(Dh,u,h);return o?H(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var Wb=O({conv3DBackpropInput_:VS});function jS(e,t,n,r,a){let s=C(e,"x","conv3dTranspose"),i=C(t,"filter","conv3dTranspose");return Wb(n,s,i,r,a)}var US=O({conv3dTranspose_:jS});function HS(e){let t={x:C(e,"x","cos")};return D.runKernel(fs,t)}var Hu=O({cos_:HS});function GS(e){let t={x:C(e,"x","cosh")};return D.runKernel(oo,t)}var xd=O({cosh_:GS});function qS(e,t=0,n=!1,r=!1){let a={x:C(e,"x","cumsum")},s={axis:t,exclusive:n,reverse:r};return D.runKernel(ms,a,s)}var bd=O({cumsum_:qS});function XS(e,t,n,r=!1){let a=C(e,"x","denseBincount"),s=C(t,"weights","denseBincount");M(a.dtype==="int32",()=>`Error in denseBincount: input dtype must be int32, but got ${a.dtype}`),M(a.rank<=2,()=>`Error in denseBincount: input must be at most rank 2, but got rank ${a.rank}.`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(s.size===a.size||s.size===0,()=>`Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${a.shape}, weights shape: ${s.shape}.`);let i={x:a,weights:s},o={size:n,binaryOutput:r};return D.runKernel($h,i,o)}var Bb=O({denseBincount_:XS});function KS(e,t,n="NHWC"){let r=C(e,"x","depthToSpace"),a=n==="NHWC"?r.shape[1]:r.shape[2],s=n==="NHWC"?r.shape[2]:r.shape[3],i=n==="NHWC"?r.shape[3]:r.shape[1];M(a*t>=0,()=>`Negative dimension size caused by overflow when multiplying
     ${a} and ${t}  for depthToSpace with input shape
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     ${s} and ${t} for depthToSpace with input shape
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s=a,i=!1;a.rank===3&&(i=!0,s=H(a,[1,a.shape[0],a.shape[1],a.shape[2]]));let[]=t,o={images:s},l={alignCorners:n,halfPixelCenters:r,size:t},c=D.runKernel(Iu,o,l);return i?H(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var bw=O({resizeNearestNeighbor_:IR});function NR(e,t,n="nearest",r="constant",a=0,s){let i=C(e,"image","transform","float32"),o=C(t,"transforms","transform","float32");M(i.rank===4,()=>`Error in transform: image must be rank 4,but got rank ${i.rank}.`),M(o.rank===2&&(o.shape[0]===i.shape[0]||o.shape[0]===1)&&o.shape[1]===8,()=>"Error in transform: Input transform should be batch x 8 or 1 x 8"),M(s==null||s.length===2,()=>`Error in transform: outputShape must be [height, width] or null, but got ${s}.`);let l={image:i,transforms:o},c={interpolation:n,fillMode:r,fillValue:a,outputShape:s};return D.runKernel(td,l,c)}var SR=O({transform_:NR});function TR(e,t,n){M(t%1==0,()=>`bandPart(): numLower must be an integer, got ${t}.`),M(n%1==0,()=>`bandPart(): numUpper must be an integer, 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a=C(e,"labels","hingeLoss"),s=C(t,"predictions","hingeLoss"),i=null;n!=null&&(i=C(n,"weights","hingeLoss")),nn(a.shape,s.shape,"Error in hingeLoss: ");let o=ge(1);a=Ae(P(ge(2),a),o);let l=zr(Ae(o,P(a,s)));return sa(l,i,r)}var WR=O({hingeLoss_:LR});function BR(e,t,n,r=1,a=cn.SUM_BY_NONZERO_WEIGHTS){let s=C(e,"labels","huberLoss"),i=C(t,"predictions","huberLoss"),o=null;n!=null&&(o=C(n,"weights","huberLoss")),nn(s.shape,i.shape,"Error in huberLoss: ");let l=ge(r),c=$t(Ae(i,s)),u=ml(c,l),h=Ae(c,u),d=se(P(ge(.5),it(u)),P(l,h));return sa(d,o,a)}var VR=O({huberLoss_:BR});function jR(e,t,n,r=1e-7,a=cn.SUM_BY_NONZERO_WEIGHTS){let s=C(e,"labels","logLoss"),i=C(t,"predictions","logLoss"),o=null;n!=null&&(o=C(n,"weights","logLoss")),nn(s.shape,i.shape,"Error in logLoss: ");let l=ge(1),c=ge(r),u=_t(P(s,Mn(se(i,c)))),h=P(Ae(l,s),Mn(se(Ae(l,i),c))),d=Ae(u,h);return sa(d,o,a)}var UR=O({logLoss_:jR});function HR(e,t,n,r=cn.SUM_BY_NONZERO_WEIGHTS){let 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MM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,scale:s,offset:i,mean:o,variance:l}=t;v.assert(o.shape.length===l.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||o.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(s==null||o.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks."),_e([a,o,l,s,i],"batchNorm");let{varianceEpsilon:c}=r;c==null&&(c=.001);let u=n.data.get(a.dataId).values,h=n.data.get(o.dataId).values,d=n.data.get(l.dataId).values,p=s?n.data.get(s.dataId).values:new Float32Array([1]),f=i?n.data.get(i.dataId).values:new Float32Array([0]),m=new Float32Array(u.length),A=f.length,y=p.length,g=d.length,w=h.length,b=0,_=0,x=0,N=0;for(let T=0;T<u.length;++T)m[T]=f[b++]+(u[T]-h[_++])*p[x++]/Math.sqrt(d[N++]+c),b>=A&&(b=0),_>=w&&(_=0),x>=y&&(x=0),N>=g&&(N=0);return n.makeTensorInfo(a.shape,a.dtype,m)}var FM={kernelName:bs,backendName:"cpu",kernelFunc:MM};function $M(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;_e([a],"batchToSpaceND");let o=s.reduce((y,g)=>y*g),l=R.getReshaped(a.shape,s,o),c=R.getPermuted(l.length,s.length),u=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(u,i,s.length),p=At({inputs:{x:a},backend:n,attrs:{shape:l}}),f=sr({inputs:{x:p},backend:n,attrs:{perm:c}}),m=At({inputs:{x:f},backend:n,attrs:{shape:u}}),A=yi({inputs:{x:m},backend:n,attrs:{begin:h,size:d}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),A}var DM={kernelName:fu,backendName:"cpu",kernelFunc:$M};function OM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.data.get(a.dataId).values,l=n.data.get(s.dataId).values,c=Fm(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var 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mF={kernelName:Oh,backendName:"cpu",kernelFunc:fF};function AF(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r;_e([a,s],"depthwiseConv2DNativeBackpropInput");let h=v.computeStrides(a.shape),d=v.computeStrides(s.shape),p=R.computeConv2DInfo(u,s.shape,i,o,l,c,!0),f=new $t(p.inShape,"float32"),m=f.values,[A,y,g]=f.strides,w=n.data.get(a.dataId).values,[b,_,x]=h,N=n.data.get(s.dataId).values,[T,E,F]=d,{batchSize:D,filterHeight:L,filterWidth:V,inChannels:U,inHeight:j,inWidth:X,outChannels:G,outHeight:ee,outWidth:Y,strideHeight:ae,strideWidth:te}=p,oe=L-1-p.padInfo.top,Q=V-1-p.padInfo.left,he=G/U;for(let le=0;le<D;++le)for(let fe=0;fe<U;++fe)for(let pe=0;pe<j;++pe){let ke=pe-oe,Se=Math.max(0,Math.ceil(ke/ae)),Me=Math.min(ee,(L+ke)/ae);for(let De=0;De<X;++De){let Fe=De-Q,Qe=Math.max(0,Math.ceil(Fe/te)),et=Math.min(Y,(V+Fe)/te),st=0;for(let Ke=Se;Ke<Me;++Ke){let dt=Ke*ae-ke;for(let Ve=Qe;Ve<et;++Ve){let 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i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=sr({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],R.assertAxesAreInnerMostDims("argMin",i,l.shape.length);let[u,h]=R.computeOutAndReduceShapes(l.shape,i),d=v.sizeFromShape(u),p=v.makeZerosTypedArray(d,"int32"),f=v.sizeFromShape(h),m=n.data.get(l.dataId).values;for(let A=0;A<p.length;++A){let y=A*f,g=m[y],b=0;for(let w=0;w<f;++w){let _=m[y+w];_<g&&(g=_,b=w)}p[A]=b}return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),n.makeTensorInfo(u,"int32",p)}var 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u=R.computePool3DInfo(s.shape,i,o,1,l,c),h=u.strideDepth,d=u.strideHeight,p=u.strideWidth,f=u.filterDepth,m=u.filterHeight,A=u.filterWidth,y=u.dilationDepth,g=u.dilationHeight,b=u.dilationWidth,w=u.effectiveFilterDepth,_=u.effectiveFilterHeight,x=u.effectiveFilterWidth,N=w-1-u.padInfo.front,T=x-1-u.padInfo.left,E=_-1-u.padInfo.top,F=Be(s.shape,"float32"),$=1/(f*m*A),L=n.bufferSync(a);for(let V=0;V<u.batchSize;++V)for(let j=0;j<u.inChannels;++j)for(let U=0;U<u.inDepth;++U)for(let X=0;X<u.inHeight;++X)for(let G=0;G<u.inWidth;++G){let ee=U-N,Y=X-E,ae=G-T,te=0;for(let oe=0;oe<w;oe+=y){let Q=(ee+oe)/h;if(!(Q<0||Q>=u.outDepth||Math.floor(Q)!==Q))for(let he=0;he<_;he+=g){let le=(Y+he)/d;if(!(le<0||le>=u.outHeight||Math.floor(le)!==le))for(let fe=0;fe<x;fe+=b){let pe=(ae+fe)/p;pe<0||pe>=u.outWidth||Math.floor(pe)!==pe||(te+=L.get(V,Q,le,pe,j))}}}F.set(te*$,V,U,X,G,j)}return n.makeTensorInfo(F.shape,F.dtype,F.values)}var uD={kernelName:Eh,backendName:"cpu",kernelFunc:lD};function cD(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;_e([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:c}=r,u=R.computePool2DInfo(i.shape,o,l,1,c),h=u.strideHeight,d=u.strideWidth,p=u.filterHeight,f=u.filterWidth,m=u.dilationHeight,A=u.dilationWidth,y=u.effectiveFilterHeight,g=u.effectiveFilterWidth,b=g-1-u.padInfo.left,w=y-1-u.padInfo.top,_=Be(i.shape,"float32"),x=1/(p*f),N=n.data.get(a.dataId).values,T=Be(a.shape,"float32",N);for(let E=0;E<u.batchSize;++E)for(let F=0;F<u.inChannels;++F)for(let $=0;$<u.inHeight;++$)for(let L=0;L<u.inWidth;++L){let V=$-w,j=L-b,U=0;for(let X=0;X<y;X+=m){let G=(V+X)/h;if(!(G<0||G>=u.outHeight||Math.floor(G)!==G))for(let ee=0;ee<g;ee+=A){let Y=(j+ee)/d;Y<0||Y>=u.outWidth||Math.floor(Y)!==Y||(U+=T.get(E,G,Y,F))}}_.set(U*x,E,$,L,F)}return n.makeTensorInfo(_.shape,_.dtype,_.values)}var hD={kernelName:Th,backendName:"cpu",kernelFunc:cD};function 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n.makeTensorInfo(a.shape,a.dtype,m)}var pD={kernelName:ws,backendName:"cpu",kernelFunc:dD};function fD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;_e([a],"batchToSpaceND");let o=s.reduce((y,g)=>y*g),l=R.getReshaped(a.shape,s,o),c=R.getPermuted(l.length,s.length),u=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(u,i,s.length),p=At({inputs:{x:a},backend:n,attrs:{shape:l}}),f=sr({inputs:{x:p},backend:n,attrs:{perm:c}}),m=At({inputs:{x:f},backend:n,attrs:{shape:u}}),A=yi({inputs:{x:m},backend:n,attrs:{begin:h,size:d}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),A}var mD={kernelName:fu,backendName:"cpu",kernelFunc:fD};function AD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.data.get(a.dataId).values,l=n.data.get(s.dataId).values,c=Pm(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var 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TD={kernelName:ps,backendName:"cpu",kernelFunc:SD};function ED(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r;_e([a,s],"conv3d");let c=R.computeConv3DInfo(a.shape,s.shape,i,l,o),{filterDepth:u,filterHeight:h,filterWidth:d,dilationDepth:p,dilationHeight:f,dilationWidth:m,padInfo:A}=c,y=A.front,g=A.left,b=A.top,w=new Dt(c.outShape,a.dtype),_=n.data.get(a.dataId).values,x=n.data.get(s.dataId).values,N=w.values,T=v.computeStrides(a.shape),E=v.computeStrides(s.shape);for(let F=0;F<c.batchSize;++F){let $=F*T[0],L=F*w.strides[0];for(let V=0;V<c.outDepth;++V){let j=L+V*w.strides[1],U=V*c.strideDepth-y;for(let X=0;X<u;++X){let G=U+X*p;if(G<0||G>=c.inDepth)continue;let ee=X*E[0],Y=$+G*T[1];for(let ae=0;ae<c.outHeight;++ae){let te=j+ae*w.strides[2],oe=ae*c.strideHeight-b;for(let Q=0;Q<h;++Q){let he=oe+Q*f;if(he<0||he>=c.inHeight)continue;let le=ee+Q*E[1],fe=Y+he*T[2];for(let pe=0;pe<c.outWidth;++pe){let ke=te+pe*c.outChannels,Se=pe*c.strideWidth-g;for(let 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jD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.data.get(a.dataId).values,c=n.data.get(s.dataId).values,u=Pm(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=Tw(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var UD={kernelName:$h,backendName:"cpu",kernelFunc:jD};function HD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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e=Re.getNumber("WEBGL_VERSION");return e===0?0:sb(e)});Re.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Re.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!zu.isMobile());Re.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>ib(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Re.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Re.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Re.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>ob(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_FENCE_API_ENABLED",()=>lb(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Re.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Re.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}.`)});Re.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>zu.isMobile()&&Re.getBool("IS_CHROME")?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 ${e}.`)});function hn(){let e,t,n,r,a,s,i,o,l,c;return J().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",r="in",a="texture",s="outputColor",i="out vec4 outputColor;",o=`
+`))}function k_(e){return oa(e,()=>e.createProgram(),"Unable to create WebGLProgram.")}function I_(e,t){if(be(e,()=>e.linkProgram(t)),e.getProgramParameter(t,e.LINK_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Failed to link vertex and fragment shaders.")}function sp(e,t){if(be(e,()=>e.validateProgram(t)),e.getProgramParameter(t,e.VALIDATE_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Shader program validation failed.")}function N_(e,t){let n=oa(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),be(e,()=>e.bufferData(e.ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function S_(e,t){let n=oa(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return be(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,n)),be(e,()=>e.bufferData(e.ELEMENT_ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function xP(){return J().getNumber("WEBGL_VERSION")===2?1:4}function T_(e){return oa(e,()=>e.createTexture(),"Unable to create WebGLTexture.")}function E_(e,t){let n=J().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(e<=0||t<=0){let r=`[${e}x${t}]`;throw new Error("Requested texture size "+r+" is invalid.")}if(e>n||t>n){let r=`[${e}x${t}]`,a=`[${n}x${n}]`;throw new Error("Requested texture size "+r+" greater than WebGL maximum on this browser / GPU "+a+".")}}function C_(e){return oa(e,()=>e.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function Jm(e,t,n,r,a,s,i){let o=e.getAttribLocation(t,n);return o===-1?!1:(be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,r)),be(e,()=>e.vertexAttribPointer(o,a,e.FLOAT,!1,s,i)),be(e,()=>e.enableVertexAttribArray(o)),!0)}function R_(e,t,n){j_(e,n),be(e,()=>e.activeTexture(e.TEXTURE0+n)),be(e,()=>e.bindTexture(e.TEXTURE_2D,t))}function bP(e,t){j_(e,t),be(e,()=>e.activeTexture(e.TEXTURE0+t)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function M_(e,t,n){return oa(e,()=>e.getUniformLocation(t,n),'uniform "'+n+'" not present in program.')}function F_(e,t,n){return e.getUniformLocation(t,n)}function D_(e,t,n,r){be(e,()=>R_(e,t,r)),be(e,()=>e.uniform1i(n,r))}function wP(e){be(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),be(e,()=>e.viewport(0,0,e.canvas.width,e.canvas.height)),be(e,()=>e.scissor(0,0,e.canvas.width,e.canvas.height))}function ip(e,t,n){be(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,n)),be(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0))}function Qm(e,t){be(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,t)),be(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,null,0))}function oc(e){let t=e.checkFramebufferStatus(e.FRAMEBUFFER);if(t!==e.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+$_(e,t))}function $_(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 ${t}`}}function oa(e,t,n){let r=be(e,()=>t());if(r==null)throw new Error(n);return r}function j_(e,t){let n=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,r=t+e.TEXTURE0;if(r<e.TEXTURE0||r>n){let a=`[gl.TEXTURE0, gl.TEXTURE${n}]`;throw new Error(`textureUnit must be in ${a}.`)}}function gi(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function xi(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 op(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[gi(e),...xi(e)]),t}function O_(e,t=!1){let n=J().getNumber("WEBGL_MAX_TEXTURE_SIZE");t&&(n=n*2,e=e.map((a,s)=>s>=e.length-2?v.nearestLargerEven(e[s]):e[s]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=v.squeezeShape(e).newShape);let r=v.sizeFromShape(e);if(e.length<=1&&r<=n)return[1,r];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 a=gi(e),s=2,i=2;return e.length&&([s,i]=xi(e)),r=a*(s/2)*(i/2),v.sizeToSquarishShape(r).map(o=>o*2)}return v.sizeToSquarishShape(r)}function up(e){return e%2==0}function lc(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],r=t.slice(-1)[0];if(n===r||up(n)&&up(r)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&up(e[0])&&up(t[0])}var cp,hp;function z_(e){if(cp==null){let t=Wr(e);cp=t.getParameter(t.MAX_TEXTURE_SIZE)}return cp}function _P(){cp=null}function vP(){hp=null}function P_(e){if(hp==null){let t=Wr(e);hp=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,hp)}function L_(e){if(e===0)return 0;let t,n=Wr(e);return qn(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:qn(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function qn(e,t){return e.getExtension(t)!=null}function eA(e){try{if(Wr(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function W_(e){if(e===0)return!1;let t=Wr(e);if(e===1){if(!qn(t,"OES_texture_float"))return!1}else if(!qn(t,"EXT_color_buffer_float"))return!1;return rA(t)}function B_(e){if(e===0)return!1;let t=Wr(e);if(e===1){if(!qn(t,"OES_texture_float")||!qn(t,"WEBGL_color_buffer_float"))return!1}else{if(qn(t,"EXT_color_buffer_float"))return rA(t);let n="EXT_color_buffer_half_float";if(qn(t,n)){let r=t.getExtension(n);return FP(t,r)}return!1}return rA(t)}function rA(e){let t=nA(e),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let r=1,a=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,r,a,0,t.textureFormatFloat,t.textureTypeFloat,null);let s=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,s),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(s),i}function FP(e,t){let n=nA(e,t),r=e.createTexture();e.bindTexture(e.TEXTURE_2D,r);let a=1,s=1;e.texImage2D(e.TEXTURE_2D,0,n.internalFormatHalfFloat,a,s,0,n.textureFormatFloat,n.textureTypeHalfFloat,null);let i=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,i),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,r,0);let o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(r),e.deleteFramebuffer(i),o}function V_(e){return e!==2?!1:Wr(e).fenceSync!=null}function kl(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 Re=J();Re.registerFlag("HAS_WEBGL",()=>Re.getNumber("WEBGL_VERSION")>0);Re.registerFlag("WEBGL_VERSION",()=>eA(2)?2:eA(1)?1:0);Re.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Re.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Re.get("WEBGL_VERSION")===2);Re.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Re.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Re.registerFlag("WEBGL_PACK",()=>Re.getBool("HAS_WEBGL"));Re.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_PACK_CLIP",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>!1);Re.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_PACK_REDUCE",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_LAZILY_UNPACK",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_CONV_IM2COL",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>z_(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>P_(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=Re.getNumber("WEBGL_VERSION");return e===0?0:L_(e)});Re.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Re.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!zu.isMobile());Re.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>W_(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Re.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Re.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Re.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>B_(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_FENCE_API_ENABLED",()=>V_(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Re.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Re.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}.`)});Re.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>zu.isMobile()&&Re.getBool("IS_CHROME")?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}.`)});function hn(){let e,t,n,r,a,s,i,o,l,c;return J().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",r="in",a="texture",s="outputColor",i="out vec4 outputColor;",o=`
       bool isnan_custom(float val) {
         return (val > 0.0 || val < 0.0) ? false : val != 0.0;
       }
@@ -74,11 +74,11 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       ivec4 round(vec4 value) {
         return ivec4(floor(value + vec4(0.5)));
       }
-    `),{version:e,attribute:t,varyingVs:n,varyingFs:r,texture2D:a,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:c}}function bi(e,t,n="index"){let r=v.computeStrides(t);return r.map((a,s)=>{let i=`int ${e[s]} = ${n} / ${a}`,o=s===r.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${a}`:`index -= ${e[s]} * ${a}`;return`${i}; ${o};`}).join("")}function Qm(e){let t=v.computeStrides(e).map(n=>n.toString());return`
+    `),{version:e,attribute:t,varyingVs:n,varyingFs:r,texture2D:a,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:c}}function wi(e,t,n="index"){let r=v.computeStrides(t);return r.map((a,s)=>{let i=`int ${e[s]} = ${n} / ${a}`,o=s===r.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${a}`:`index -= ${e[s]} * ${a}`;return`${i}; ${o};`}).join("")}function aA(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;
   }
-`}var cb=`
+`}var U_=`
   const float FLOAT_MAX = 1.70141184e38;
   const float FLOAT_MIN = 1.17549435e-38;
 
@@ -117,9 +117,9 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
     return c / 255.0;
   }
-`,ez=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=uc.DENSE;let t=hc(e),n=hn();this.outputShape=e,this.userCode=`
+`,DP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=uc.DENSE;let t=hc(e),n=hn();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
-        ${bi(["r","c","d"],e)}
+        ${wi(["r","c","d"],e)}
         return ivec3(r, c, d);
       }
 
@@ -138,9 +138,9 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${n.output} = result;
       }
-    `}},tz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=uc.DENSE;let t=hc(e),n=hn();this.outputShape=e,this.userCode=`
+    `}},$P=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=uc.DENSE;let t=hc(e),n=hn();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
-        ${bi(["r","c","d"],e)}
+        ${wi(["r","c","d"],e)}
         return ivec3(r, c, d);
       }
 
@@ -159,23 +159,23 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${n.output} = result;
       }
-    `}},nz=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Xn.DOWNLOAD;let t=hn();this.outputShape=e,this.userCode=`
-      ${cb}
+    `}},OP=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Xn.DOWNLOAD;let t=hn();this.outputShape=e,this.userCode=`
+      ${U_}
 
       void main() {
         float x = getAAtOutCoords();
         ${t.output} = encode_float(x);
       }
-    `}},rz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Xn.DOWNLOAD;let t=hn();this.outputShape=e,this.userCode=`
-      ${cb}
+    `}},zP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Xn.DOWNLOAD;let t=hn();this.outputShape=e,this.userCode=`
+      ${U_}
 
       void main() {
         ivec3 coords = getOutputCoords();
         float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
         ${t.output} = encode_float(x);
       }
-    `}},az=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=hn(),[a,s]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
-      ${Qm(e)}
+    `}},PP=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=hn(),[a,s]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
+      ${aA(e)}
 
       void main() {
         ivec3 coords = getOutputCoords();
@@ -204,7 +204,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${r.output} = vec4(${i}, 0., 0., 0.);
       }
-    `}},sz=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=hn(),[a,s]=t;this.outputShape=e;let i="",o="result";n&&(o="floor(result * 255. + 0.5)");for(let l=0;l<=1;l++)for(let c=0;c<=1;c++){let u=l*2+c;i+=`
+    `}},LP=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=hn(),[a,s]=t;this.outputShape=e;let i="",o="result";n&&(o="floor(result * 255. + 0.5)");for(let l=0;l<=1;l++)for(let c=0;c<=1;c++){let u=l*2+c;i+=`
           localCoords = coords;
           if(localCoords[2] + ${c} < ${e[2]}) {
             localCoords[2] += ${c};
@@ -233,7 +233,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
             }
           }
         `}this.userCode=`
-      ${Qm(e)}
+      ${aA(e)}
 
       void main() {
         ivec3 coords = getOutputCoords();
@@ -248,7 +248,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${r.output} = ${o};
       }
-    `}},hb={};Oe(hb,{bindVertexProgramAttributeStreams:()=>wb,createBufferFromOutputTexture:()=>vb,createFloat16MatrixTexture:()=>Ab,createFloat16PackedMatrixTexture:()=>xb,createFloat32MatrixTexture:()=>mb,createIndexBuffer:()=>fb,createPackedMatrixTexture:()=>gb,createUnsignedBytesMatrixTexture:()=>yb,createVertexBuffer:()=>pb,createVertexShader:()=>db,downloadByteEncodedFloatMatrixFromOutputTexture:()=>Ib,downloadFloat32MatrixFromBuffer:()=>kb,downloadMatrixFromPackedOutputTexture:()=>Sb,downloadPackedMatrixFromBuffer:()=>Nb,getInternalFormatForFloat16MatrixTexture:()=>tA,getInternalFormatForFloat16PackedMatrixTexture:()=>aA,getInternalFormatForFloat32MatrixTexture:()=>eA,getInternalFormatForPackedMatrixTexture:()=>rA,getInternalFormatForUnsignedBytesMatrixTexture:()=>nA,uploadDenseMatrixToTexture:()=>bb,uploadPixelDataToTexture:()=>_b});function db(e){let t=hn(),n=`${t.version}
+    `}},H_={};Me(H_,{bindVertexProgramAttributeStreams:()=>e3,createBufferFromOutputTexture:()=>r3,createFloat16MatrixTexture:()=>Z_,createFloat16PackedMatrixTexture:()=>Q_,createFloat32MatrixTexture:()=>K_,createIndexBuffer:()=>X_,createPackedMatrixTexture:()=>J_,createUnsignedBytesMatrixTexture:()=>Y_,createVertexBuffer:()=>q_,createVertexShader:()=>G_,downloadByteEncodedFloatMatrixFromOutputTexture:()=>s3,downloadFloat32MatrixFromBuffer:()=>a3,downloadMatrixFromPackedOutputTexture:()=>o3,downloadPackedMatrixFromBuffer:()=>i3,getInternalFormatForFloat16MatrixTexture:()=>iA,getInternalFormatForFloat16PackedMatrixTexture:()=>uA,getInternalFormatForFloat32MatrixTexture:()=>sA,getInternalFormatForPackedMatrixTexture:()=>lA,getInternalFormatForUnsignedBytesMatrixTexture:()=>oA,uploadDenseMatrixToTexture:()=>t3,uploadPixelDataToTexture:()=>n3});function G_(e){let t=hn(),n=`${t.version}
     precision highp float;
     ${t.attribute} vec3 clipSpacePos;
     ${t.attribute} vec2 uv;
@@ -257,22 +257,22 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
     void main() {
       gl_Position = vec4(clipSpacePos, 1);
       resultUV = uv;
-    }`;return Vw(e,n)}function pb(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 Gw(e,t)}function fb(e){let t=new Uint16Array([0,1,2,2,1,3]);return qw(e,t)}function dc(e,t,n,r,a,s){Kw(t,n);let i=Xw(e),o=e.TEXTURE_2D;return we(e,()=>e.bindTexture(o,i)),we(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),we(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),we(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),we(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),we(e,()=>e.texImage2D(o,0,r,t,n,0,a,s,null)),we(e,()=>e.bindTexture(e.TEXTURE_2D,null)),i}function eA(e){return e.internalFormatFloat}function mb(e,t,n,r){let[a,s]=cc(t,n);return dc(e,a,s,eA(r),r.textureFormatFloat,e.FLOAT)}function tA(e){return e.internalFormatHalfFloat}function Ab(e,t,n,r){let[a,s]=cc(t,n);return dc(e,a,s,tA(r),r.textureFormatFloat,r.textureTypeHalfFloat)}function nA(e){return e.downloadTextureFormat}function yb(e,t,n,r){let[a,s]=cc(t,n);return dc(e,a,s,nA(r),e.RGBA,e.UNSIGNED_BYTE)}function rA(e){return e.internalFormatPackedFloat}function gb(e,t,n,r){let[a,s]=Il(t,n);return dc(e,a,s,rA(r),e.RGBA,e.FLOAT)}function aA(e){return e.internalFormatPackedHalfFloat}function xb(e,t,n,r){let[a,s]=Il(t,n);return dc(e,a,s,aA(r),e.RGBA,r.textureTypeHalfFloat)}function wb(e,t,n){let r=0,a=3*4,s=3*4+2*4;return we(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),qm(e,t,"clipSpacePos",n,3,s,r)&&qm(e,t,"uv",n,2,s,a)}function bb(e,t,n,r,a,s){we(e,()=>e.bindTexture(e.TEXTURE_2D,t));let i,o,l;a instanceof Uint8Array?(i=new Uint8Array(n*r*4),o=e.UNSIGNED_BYTE,l=e.RGBA):(i=new Float32Array(n*r*4),o=e.FLOAT,l=s.internalFormatPackedFloat),i.set(a),we(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,r,0,e.RGBA,o,i)),we(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function _b(e,t,n){we(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?we(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):we(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),we(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function vb(e,t,n,r){let a=e.createBuffer();we(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,a));let s=4*4*t*n;return we(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),we(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),we(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),a}function kb(e,t,n){let r=e,a=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,t),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,a),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),a}function Ib(e,t,n,r){let[a,s]=cc(t,n),i=4,o=new Uint8Array(GO(t*n,i));return we(e,()=>e.readPixels(0,0,a,s,r.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function Nb(e,t,n,r,a,s,i,o){let l=e,c=new Float32Array(qO(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,c),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),c}function Sb(e,t,n){let r=new Float32Array(t*n*4);return we(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,r)),r}var dp=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=J().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,lp(t,e)):this.gl=Wr(t);let n="WEBGL_color_buffer_float",r="EXT_color_buffer_half_float";if(J().getNumber("WEBGL_VERSION")===1){let a="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=ic(this.gl,a),qn(this.gl,s))this.textureHalfFloatExtension=ic(this.gl,s);else if(J().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),qn(this.gl,r))this.colorBufferHalfFloatExtension=ic(this.gl,r);else if(J().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",qn(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(qn(this.gl,r))this.colorBufferHalfFloatExtension=this.gl.getExtension(r);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=pb(this.gl),this.indexBuffer=fb(this.gl),this.framebuffer=Zw(this.gl),this.textureConfig=Ym(this.gl,this.textureHalfFloatExtension)}get debug(){return J().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. 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+    }`;return __(e,n)}function q_(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 N_(e,t)}function X_(e){let t=new Uint16Array([0,1,2,2,1,3]);return S_(e,t)}function dc(e,t,n,r,a,s){E_(t,n);let i=T_(e),o=e.TEXTURE_2D;return be(e,()=>e.bindTexture(o,i)),be(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),be(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),be(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),be(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),be(e,()=>e.texImage2D(o,0,r,t,n,0,a,s,null)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null)),i}function sA(e){return e.internalFormatFloat}function K_(e,t,n,r){let[a,s]=cc(t,n);return dc(e,a,s,sA(r),r.textureFormatFloat,e.FLOAT)}function iA(e){return e.internalFormatHalfFloat}function Z_(e,t,n,r){let[a,s]=cc(t,n);return dc(e,a,s,iA(r),r.textureFormatFloat,r.textureTypeHalfFloat)}function oA(e){return e.downloadTextureFormat}function Y_(e,t,n,r){let[a,s]=cc(t,n);return dc(e,a,s,oA(r),e.RGBA,e.UNSIGNED_BYTE)}function lA(e){return e.internalFormatPackedFloat}function J_(e,t,n,r){let[a,s]=Il(t,n);return dc(e,a,s,lA(r),e.RGBA,e.FLOAT)}function uA(e){return e.internalFormatPackedHalfFloat}function Q_(e,t,n,r){let[a,s]=Il(t,n);return dc(e,a,s,uA(r),e.RGBA,r.textureTypeHalfFloat)}function e3(e,t,n){let r=0,a=3*4,s=3*4+2*4;return be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),Jm(e,t,"clipSpacePos",n,3,s,r)&&Jm(e,t,"uv",n,2,s,a)}function t3(e,t,n,r,a,s){be(e,()=>e.bindTexture(e.TEXTURE_2D,t));let i,o,l;a instanceof Uint8Array?(i=new Uint8Array(n*r*4),o=e.UNSIGNED_BYTE,l=e.RGBA):(i=new Float32Array(n*r*4),o=e.FLOAT,l=s.internalFormatPackedFloat),i.set(a),be(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,r,0,e.RGBA,o,i)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function n3(e,t,n){be(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?be(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):be(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function r3(e,t,n,r){let a=e.createBuffer();be(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,a));let s=4*4*t*n;return be(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),be(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),be(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),a}function a3(e,t,n){let r=e,a=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,t),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,a),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),a}function s3(e,t,n,r){let[a,s]=cc(t,n),i=4,o=new Uint8Array(NP(t*n,i));return be(e,()=>e.readPixels(0,0,a,s,r.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function i3(e,t,n,r,a,s,i,o){let l=e,c=new Float32Array(SP(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,c),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),c}function o3(e,t,n){let r=new Float32Array(t*n*4);return be(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,r)),r}var dp=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=J().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,lp(t,e)):this.gl=Wr(t);let n="WEBGL_color_buffer_float",r="EXT_color_buffer_half_float";if(J().getNumber("WEBGL_VERSION")===1){let a="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=ic(this.gl,a),qn(this.gl,s))this.textureHalfFloatExtension=ic(this.gl,s);else if(J().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),qn(this.gl,r))this.colorBufferHalfFloatExtension=ic(this.gl,r);else if(J().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",qn(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(qn(this.gl,r))this.colorBufferHalfFloatExtension=this.gl.getExtension(r);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=q_(this.gl),this.indexBuffer=X_(this.gl),this.framebuffer=C_(this.gl),this.textureConfig=nA(this.gl,this.textureHalfFloatExtension)}get debug(){return J().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;be(e,()=>e.finish()),be(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),be(e,()=>e.deleteFramebuffer(this.framebuffer)),be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),be(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),be(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),K_(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),Z_(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),Y_(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),n3(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,r){this.throwIfDisposed(),t3(this.gl,e,t,n,r,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),Q_(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),J_(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(Qm(this.gl,this.framebuffer),this.outputTexture=null),be(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>s3(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,r,a,s){return i3(this.gl,e,t,n,r,a,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return a3(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let r=r3(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),r}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,n;if(J().getBool("WEBGL_FENCE_API_ENABLED")){let r=e,a=r.fenceSync(r.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let s=r.clientWaitSync(a,0,0);return s===r.ALREADY_SIGNALED||s===r.CONDITION_SATISFIED},t=a}else J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>o3(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl,n=v_(t,e),r=G_(t),a=k_(t);return be(t,()=>t.attachShader(a,r)),be(t,()=>t.attachShader(a,n)),I_(t,a),this.debug&&sp(t,a),this.vertexAttrsAreBound||(this.setProgram(a),this.vertexAttrsAreBound=e3(t,this.program,this.vertexBuffer)),a}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&be(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&sp(this.gl,this.program),be(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?M_(this.gl,e,t):F_(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),be(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(),D_(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[r,a]=Il(t,n);this.setOutputMatrixTextureDriver(e,r,a)}setOutputMatrixWriteRegion(e,t,n,r){this.setOutputMatrixWriteRegionDriver(n,e,r,t)}setOutputPackedMatrixWriteRegion(e,t,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&sp(this.gl,this.program),oc(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),be(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),be(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=ic(this.gl,J().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(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,r=this.getQueryTimerExtensionWebGL2(),a=n.createQuery();return n.beginQuery(r.TIME_ELAPSED_EXT,a),a}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(J().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,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,J().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,r=this.getQueryTimerExtensionWebGL2(),a=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),a&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),r=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),r&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=WP(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(),ip(this.gl,e,this.framebuffer),this.debug&&oc(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(ip(this.gl,this.outputTexture,this.framebuffer),this.debug&&oc(this.gl)):Qm(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let n=t();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(e,t,n){this.throwIfDisposed();let r=this.gl;ip(r,e,this.framebuffer),this.debug&&oc(r),this.outputTexture=e,be(r,()=>r.viewport(0,0,t,n)),be(r,()=>r.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,r){this.throwIfDisposed(),be(this.gl,()=>this.gl.scissor(e,t,n,r))}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 WP(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{getBroadcastDims:l3}=R;function KP(e,t,n,r){let a=[];e.forEach(p=>{let f=v.sizeFromShape(p.shapeInfo.logicalShape);p.shapeInfo.isUniform?a.push(`uniform float ${p.name}${f>1?`[${f}]`:""};`):(a.push(`uniform sampler2D ${p.name};`),a.push(`uniform int offset${p.name};`))});let s=a.join(`
+`),i=e.map(p=>BP(p,t,r)).join(`
+`),o=t.texShape,l=hn(),c=UP(l),u,h,d=qP(l);return t.isPacked?(u=VP(t.logicalShape,o),h=GP(l)):(u=jP(t.logicalShape,o),h=HP(l)),r&&(d+=XP),[d,c,h,s,u,i,n].join(`
+`)}function Nl(e){let t=e.shapeInfo.logicalShape;switch(t.length){case 0:return ZP(e);case 1:return YP(e);case 2:return JP(e);case 3:return QP(e);case 4:return eL(e);case 5:return tL(e);case 6:return nL(e);default:throw new Error(`${t.length}-D input sampling is not yet supported`)}}function u3(e){switch(e.shapeInfo.logicalShape.length){case 0:return rL(e);case 1:return aL(e);case 2:return sL(e);case 3:return iL(e);default:return oL(e)}}function BP(e,t,n=!1){let r="";n?r+=u3(e):r+=Nl(e);let a=e.shapeInfo.logicalShape,s=t.logicalShape;return a.length<=s.length&&(n?r+=lL(e,t):r+=uL(e,t)),r}function VP(e,t){switch(e.length){case 0:return c3();case 1:return cL(e,t);case 2:return pL(e,t);case 3:return hL(e,t);default:return dL(e,t)}}function jP(e,t){switch(e.length){case 0:return c3();case 1:return fL(e,t);case 2:return xL(e,t);case 3:return mL(e,t);case 4:return AL(e,t);case 5:return yL(e,t);case 6:return gL(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function UP(e){return`
     float sampleTexture(sampler2D textureSampler, vec2 uv) {
       return ${e.texture2D}(textureSampler, uv).r;
     }
-  `}function hz(e){return`
+  `}function HP(e){return`
     void setOutput(float val) {
       ${e.output} = vec4(val, 0, 0, 0);
     }
-  `}function dz(e){return`
+  `}function GP(e){return`
     void setOutput(vec4 val) {
       ${e.output} = val;
     }
-  `}function pz(e){return`${e.version}
+  `}function qP(e){return`${e.version}
     precision highp float;
     precision highp int;
     precision highp sampler2D;
@@ -327,10 +327,10 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       return fract((p3.x + p3.y) * p3.z);
     }
 
-    ${Wz}
-    ${Bz}
-    ${Vz}
-  `}var Wz=`
+    ${bL}
+    ${wL}
+    ${_L}
+  `}var bL=`
 vec2 uvFromFlat(int texNumR, int texNumC, int index) {
   int texR = index / texNumC;
   int texC = index - texR * texNumC;
@@ -342,7 +342,7 @@ vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,Bz=`
+`,wL=`
 vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texNumC, int row, int col) {
   int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
@@ -350,7 +350,7 @@ vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,Vz=`
+`,_L=`
 vec2 packedUVfrom3D(int texNumR, int texNumC,
     int texelsInBatch, int texelsInLogicalRow, int b,
     int row, int col) {
@@ -359,7 +359,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   int texC = index - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,fz=`
+`,XP=`
   float getChannel(vec4 frag, vec2 innerDims) {
     vec2 modCoord = mod(innerDims, 2.);
     return modCoord.x == 0. ?
@@ -370,11 +370,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     float modCoord = mod(float(dim), 2.);
     return modCoord == 0. ? frag.r : frag.g;
   }
-`;function Cb(){return`
+`;function c3(){return`
     int getOutputCoords() {
       return 0;
     }
-  `}function Cz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?`
+  `}function cL(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?`
       int getOutputCoords() {
         return 2 * int(resultUV.x * ${n[1]}.0);
       }
@@ -388,7 +388,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${n[0]}, ${n[1]}));
       return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
     }
-  `}function $z(e,t){return t[0]===1?`
+  `}function fL(e,t){return t[0]===1?`
       int getOutputCoords() {
         return int(resultUV.x * ${t[1]}.0);
       }
@@ -402,7 +402,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${t[0]}, ${t[1]}));
       return resTexRC.x * ${t[1]} + resTexRC.y;
     }
-  `}function Rz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
+  `}function hL(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${n[0]}, ${n[1]}));
@@ -416,7 +416,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec3(b, r, c);
     }
-  `}function Dz(e,t){let n=bi(["r","c","d"],e);return`
+  `}function mL(e,t){let n=wi(["r","c","d"],e);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${t[0]}, ${t[1]}));
@@ -424,7 +424,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${n}
       return ivec3(r, c, d);
     }
-  `}function Mz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),s=a,i="",o="b, r, c";for(let l=2;l<e.length-1;l++)s*=e[e.length-l-1],i=`
+  `}function dL(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),s=a,i="",o="b, r, c";for(let l=2;l<e.length-1;l++)s*=e[e.length-l-1],i=`
       int b${l} = index / ${s};
       index -= b${l} * ${s};
     `+i,o=`b${l}, `+o;return`
@@ -443,7 +443,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec${e.length}(${o});
     }
-  `}function Oz(e,t){let n=bi(["r","c","d","d2"],e);return`
+  `}function AL(e,t){let n=wi(["r","c","d","d2"],e);return`
     ivec4 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${t[0]}, ${t[1]}));
@@ -451,7 +451,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${n}
       return ivec4(r, c, d, d2);
     }
-  `}function zz(e,t){let n=bi(["r","c","d","d2","d3"],e);return`
+  `}function yL(e,t){let n=wi(["r","c","d","d2","d3"],e);return`
     ivec5 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
                              ${t[1]}));
@@ -463,7 +463,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec5 outShape = ivec5(r, c, d, d2, d3);
       return outShape;
     }
-  `}function Pz(e,t){let n=bi(["r","c","d","d2","d3","d4"],e);return`
+  `}function gL(e,t){let n=wi(["r","c","d","d2","d3","d4"],e);return`
     ivec6 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${t[0]}, ${t[1]}));
@@ -474,7 +474,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec6 result = ivec6(r, c, d, d2, d3, d4);
       return result;
     }
-  `}function Fz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return`
+  `}function pL(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return`
       ivec2 getOutputCoords() {
         return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
       }
@@ -489,7 +489,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec2(r, c);
     }
-  `}function Lz(e,t){return v.arraysEqual(e,t)?`
+  `}function xL(e,t){return v.arraysEqual(e,t)?`
       ivec2 getOutputCoords() {
         return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
       }
@@ -516,11 +516,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       int c = index - r * ${e[1]};
       return ivec2(r, c);
     }
-  `}function _i(e){return`offset${e}`}function vz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=hn();return`
+  `}function _i(e){return`offset${e}`}function rL(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=hn();return`
     vec4 ${n}() {
       return ${r.texture2D}(${t}, halfCR);
     }
-  `}function Az(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${t};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
+  `}function ZP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${t};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
       float ${n}() {
         return sampleTexture(${t}, halfCR);
       }
@@ -529,13 +529,13 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${s}, ${i}, ${o});
       return sampleTexture(${t}, uv);
     }
-  `}function kz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=e.shapeInfo.texShape,a=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],s=hn();return`
+  `}function aL(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=e.shapeInfo.texShape,a=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],s=hn();return`
     vec4 ${n}(int index) {
       vec2 uv = packedUVfrom1D(
         ${a[0]}, ${a[1]}, index);
       return ${s.texture2D}(${t}, uv);
     }
-  `}function yz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
+  `}function YP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
       float ${n}(int index) {
         ${Sl(e)}
       }
@@ -558,7 +558,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${a}, ${s}, index + ${i});
       return sampleTexture(${t}, uv);
     }
-  `}function Iz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=a[0],i=a[1],o=hn();if(a!=null&&v.arraysEqual(t,a))return`
+  `}function sL(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=a[0],i=a[1],o=hn();if(a!=null&&v.arraysEqual(t,a))return`
       vec4 ${r}(int row, int col) {
         vec2 uv = (vec2(col, row) + halfCR) / vec2(${i}.0, ${s}.0);
 
@@ -569,7 +569,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = packedUVfrom2D(${c}, ${l[0]}, ${l[1]}, row, col);
       return ${o.texture2D}(${n}, uv);
     }
-  `}function gz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape;if(a!=null&&v.arraysEqual(t,a)){let h=a[0],d=a[1];return`
+  `}function JP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape;if(a!=null&&v.arraysEqual(t,a)){let h=a[0],d=a[1];return`
     float ${r}(int row, int col) {
       vec2 uv = (vec2(col, row) + halfCR) / vec2(${d}.0, ${h}.0);
       return sampleTexture(${n}, uv);
@@ -603,8 +603,8 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     vec2 uv = uvFromFlat(${l}, ${c}, index);
     return sampleTexture(${n}, uv);
   }
-`}function Nz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(t[0]===1){let h=t.slice(1),d=[1,2],p=Tl(e,h),f=["b","row","col"];return`
-        ${Eb(p)}
+`}function iL(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(t[0]===1){let h=t.slice(1),d=[1,2],p=Tl(e,h),f=["b","row","col"];return`
+        ${u3(p)}
         vec4 ${r}(int b, int row, int col) {
           return ${r}(${El(f,d)});
         }
@@ -614,7 +614,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         ${i}, ${o}, ${c}, ${l}, b, row, col);
       return ${u.texture2D}(${n}, uv);
     }
-  `}function xz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[1]*t[2],s=t[2],{newShape:i,keptDims:o}=v.squeezeShape(t),l=i;if(l.length<t.length){let f=Tl(e,l),m=["row","col","depth"];return`
+  `}function QP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[1]*t[2],s=t[2],{newShape:i,keptDims:o}=v.squeezeShape(t),l=i;if(l.length<t.length){let f=Tl(e,l),m=["row","col","depth"];return`
         ${Nl(f)}
         float ${r}(int row, int col, int depth) {
           return ${r}(${El(m,o)});
@@ -647,7 +647,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         vec2 uv = uvFromFlat(${u}, ${h}, index);
         return sampleTexture(${n}, uv);
       }
-  `}function Sz(e){let t=e.shapeInfo.logicalShape,n=t.length,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],o=i[0],l=i[1],c=Math.ceil(t[n-1]/2),u=c*Math.ceil(t[n-2]/2),h="int b, int row, int col",d=`b * ${u} + (row / 2) * ${c} + (col / 2)`;for(let f=2;f<n-1;f++)h=`int b${f}, `+h,u*=t[n-f-1],d=`b${f} * ${u} + `+d;let p=hn();return`
+  `}function oL(e){let t=e.shapeInfo.logicalShape,n=t.length,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],o=i[0],l=i[1],c=Math.ceil(t[n-1]/2),u=c*Math.ceil(t[n-2]/2),h="int b, int row, int col",d=`b * ${u} + (row / 2) * ${c} + (col / 2)`;for(let f=2;f<n-1;f++)h=`int b${f}, `+h,u*=t[n-f-1],d=`b${f} * ${u} + `+d;let p=hn();return`
     vec4 ${a}(${h}) {
       int index = ${d};
       int texR = index / ${l};
@@ -655,7 +655,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${l}, ${o});
       return ${p.texture2D}(${r}, uv);
     }
-  `}function wz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[3],s=t[2]*a,i=t[1]*s,{newShape:o,keptDims:l}=v.squeezeShape(t);if(o.length<t.length){let f=Tl(e,o),m=["row","col","depth","depth2"];return`
+  `}function eL(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[3],s=t[2]*a,i=t[1]*s,{newShape:o,keptDims:l}=v.squeezeShape(t);if(o.length<t.length){let f=Tl(e,o),m=["row","col","depth","depth2"];return`
       ${Nl(f)}
       float ${r}(int row, int col, int depth, int depth2) {
         return ${r}(${El(m,l)});
@@ -693,7 +693,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${h}, ${d}, index + ${p});
       return sampleTexture(${n}, uv);
     }
-  `}function bz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:c}=v.squeezeShape(t);if(l.length<t.length){let m=Tl(e,l),A=["row","col","depth","depth2","depth3"];return`
+  `}function tL(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:c}=v.squeezeShape(t);if(l.length<t.length){let m=Tl(e,l),A=["row","col","depth","depth2","depth3"];return`
       ${Nl(m)}
       float ${r}(int row, int col, int depth, int depth2, int depth3) {
         return ${r}(${El(A,c)});
@@ -734,7 +734,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${d}, ${p}, index);
       return sampleTexture(${n}, uv);
     }
-  `}function _z(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:a,keptDims:s}=v.squeezeShape(t);if(a.length<t.length){let A=Tl(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
+  `}function nL(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:a,keptDims:s}=v.squeezeShape(t);if(a.length<t.length){let A=Tl(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
       ${Nl(A)}
       float ${r}(int row, int col, int depth,
                     int depth2, int depth3, int depth4) {
@@ -790,7 +790,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         return ${t}[i];
       }
     }
-  `}function Tz(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=Tb(e.shapeInfo.logicalShape,t.logicalShape),l=ot(i),c=i-s,u,h=["x","y","z","w","u","v"];s===0?u="":i<2&&o.length>=1?u="coords = 0;":u=o.map(A=>`coords.${h[A+c]} = 0;`).join(`
+  `}function lL(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=l3(e.shapeInfo.logicalShape,t.logicalShape),l=ot(i),c=i-s,u,h=["x","y","z","w","u","v"];s===0?u="":i<2&&o.length>=1?u="coords = 0;":u=o.map(A=>`coords.${h[A+c]} = 0;`).join(`
 `);let d="";i<2&&s>0?d="coords":d=e.shapeInfo.logicalShape.map((A,y)=>`coords.${h[y+c]}`).join(", ");let p="return outputValue;",f=v.sizeFromShape(e.shapeInfo.logicalShape)===1,m=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!f&&!m)p=`
       return vec4(outputValue.xy, outputValue.xy);
     `;else if(f&&!m)i===1?p=`
@@ -804,22 +804,22 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec4 outputValue = get${r}(${d});
       ${p}
     }
-  `}function Ez(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
+  `}function uL(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
       float ${a}() {
         return sampleTexture(${n}, resultUV);
       }
-    `;let c=ot(l),u=Tb(e.shapeInfo.logicalShape,t.logicalShape),h=l-o,d,p=["x","y","z","w","u","v"];o===0?d="":l<2&&u.length>=1?d="coords = 0;":d=u.map(m=>`coords.${p[m+h]} = 0;`).join(`
+    `;let c=ot(l),u=l3(e.shapeInfo.logicalShape,t.logicalShape),h=l-o,d,p=["x","y","z","w","u","v"];o===0?d="":l<2&&u.length>=1?d="coords = 0;":d=u.map(m=>`coords.${p[m+h]} = 0;`).join(`
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     float ${a}() {
       ${c} coords = getOutputCoords();
       ${d}
       return get${r}(${f});
     }
-  `}function ot(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 ${e} is not yet supported`)}function Tl(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function El(e,t){return t.map(n=>e[n]).join(", ")}function Uz(e,t,n,r){let a=t.userCode,s=n.map((p,f)=>{let m={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(m.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[f],shapeInfo:m}}),i=s.map(p=>p.shapeInfo),o={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},l=mz(s,o,a,t.packedInputs),c=e.createProgram(l),u=null,h=e.getUniformLocation(c,"NAN",!1);J().getNumber("WEBGL_VERSION")===1&&(u=e.getUniformLocation(c,"INFINITY",!1));let d={};for(let p=0;p<t.variableNames.length;p++){let f=t.variableNames[p],m=!1;d[f]=e.getUniformLocation(c,f,m),d[`offset${f}`]=e.getUniformLocation(c,`offset${f}`,m)}return{program:t,source:l,webGLProgram:c,uniformLocations:d,inShapeInfos:i,outShapeInfo:o,infLoc:u,nanLoc:h}}function Rb(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,r)=>{let a=n.logicalShape,s=t[r],i=s.shape;if(!v.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function jz(e,t,n,r,a){Rb(t.inShapeInfos,n),Rb([t.outShapeInfo],[r]);let s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s,i[0],i[1]):e.setOutputMatrixTexture(s,i[0],i[1]),e.setProgram(t.webGLProgram),J().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,Infinity),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((o,l)=>{let c=t.program.variableNames[l],u=t.uniformLocations[c],h=t.uniformLocations[`offset${c}`];if(u!=null){if(o.isUniform){if(v.sizeFromShape(o.shape)<2)e.gl.uniform1f(u,o.uniformValues[0]);else{let d=o.uniformValues;d instanceof Float32Array||(d=new Float32Array(d)),e.gl.uniform1fv(u,d)}return}o.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,o.texData.slice.flatOffset),e.setInputMatrixTexture(o.texData.texture,u,l)}}),a!=null&&a(e,t.webGLProgram),e.executeProgram()}function Hz(e,t,n){let r="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0,l=i.isUniform?"uniform":i.texData.texShape;r+=`${i.shape}_${l}_${o}`});let a=e.userCode,s=e.constructor.name;return s+="_"+r+"_"+a,s}var{addImpl:Gz,bincountImpl:Mb,bincountReduceImpl:qz,ceilImpl:Xz,concatImpl:Kz,expImpl:Zz,expm1Impl:Yz,floorImpl:Jz,gatherV2Impl:Qz,greaterImpl:eP,lessImpl:tP,linSpaceImpl:nP,logImpl:rP,maxImpl:aP,maximumImpl:sP,minimumImpl:iP,multiplyImpl:oP,negImpl:lP,prodImpl:uP,rangeImpl:cP,rsqrtImpl:hP,simpleAbsImpl:Fb,sliceImpl:dP,stridedSliceImpl:pP,subImpl:fP,tileImpl:mP,topKImpl:AP,transposeImpl:sA,uniqueImpl:yP}=Mm;function $b(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function dn(e,t){return t===1?[e]:$b(e,t)}function gP(e,t){if(e===1)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}var _P=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
+  `}function ot(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 ${e} is not yet supported`)}function Tl(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function El(e,t){return t.map(n=>e[n]).join(", ")}function vL(e,t,n,r){let a=t.userCode,s=n.map((p,f)=>{let m={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(m.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[f],shapeInfo:m}}),i=s.map(p=>p.shapeInfo),o={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},l=KP(s,o,a,t.packedInputs),c=e.createProgram(l),u=null,h=e.getUniformLocation(c,"NAN",!1);J().getNumber("WEBGL_VERSION")===1&&(u=e.getUniformLocation(c,"INFINITY",!1));let d={};for(let p=0;p<t.variableNames.length;p++){let f=t.variableNames[p],m=!1;d[f]=e.getUniformLocation(c,f,m),d[`offset${f}`]=e.getUniformLocation(c,`offset${f}`,m)}return{program:t,source:l,webGLProgram:c,uniformLocations:d,inShapeInfos:i,outShapeInfo:o,infLoc:u,nanLoc:h}}function h3(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,r)=>{let a=n.logicalShape,s=t[r],i=s.shape;if(!v.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function kL(e,t,n,r,a){h3(t.inShapeInfos,n),h3([t.outShapeInfo],[r]);let s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s,i[0],i[1]):e.setOutputMatrixTexture(s,i[0],i[1]),e.setProgram(t.webGLProgram),J().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,Infinity),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((o,l)=>{let c=t.program.variableNames[l],u=t.uniformLocations[c],h=t.uniformLocations[`offset${c}`];if(u!=null){if(o.isUniform){if(v.sizeFromShape(o.shape)<2)e.gl.uniform1f(u,o.uniformValues[0]);else{let d=o.uniformValues;d instanceof Float32Array||(d=new Float32Array(d)),e.gl.uniform1fv(u,d)}return}o.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,o.texData.slice.flatOffset),e.setInputMatrixTexture(o.texData.texture,u,l)}}),a!=null&&a(e,t.webGLProgram),e.executeProgram()}function IL(e,t,n){let r="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0,l=i.isUniform?"uniform":i.texData.texShape;r+=`${i.shape}_${l}_${o}`});let a=e.userCode,s=e.constructor.name;return s+="_"+r+"_"+a,s}var{addImpl:NL,bincountImpl:d3,bincountReduceImpl:SL,ceilImpl:TL,concatImpl:EL,expImpl:CL,expm1Impl:RL,floorImpl:ML,gatherV2Impl:FL,greaterImpl:DL,lessImpl:$L,linSpaceImpl:OL,logImpl:zL,maxImpl:PL,maximumImpl:LL,minimumImpl:WL,multiplyImpl:BL,negImpl:VL,prodImpl:jL,rangeImpl:UL,rsqrtImpl:HL,simpleAbsImpl:p3,sliceImpl:GL,stridedSliceImpl:qL,subImpl:XL,tileImpl:KL,topKImpl:ZL,transposeImpl:cA,uniqueImpl:YL}=zm;function f3(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function dn(e,t){return t===1?[e]:f3(e,t)}function JL(e,t){if(e===1)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}var nW=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
         void main() {
           setOutput(vec4(getA(), 0., 0., 0.));
         }
-      `;else{let n=dn("rc",t),r=ot(t),a=xP(t,e,n),s=wP(t,e[e.length-1],e[e.length-2],n),i=bP(e,n);this.userCode=`
+      `;else{let n=dn("rc",t),r=ot(t),a=QL(t,e,n),s=eW(t,e[e.length-1],e[e.length-2],n),i=tW(e,n);this.userCode=`
         void main() {
           ${r} rc = getOutputCoords();
 
@@ -831,7 +831,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             setOutput(vec4(${i}));
           }
         }
-      `}}};function vP(e,t){let n=[];for(let r=0;r<=1;r++)for(let a=0;a<=1;a++){let s=`${r===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let i=2;i<e;i++)s=`${t[t.length-1-i]},`+s;n.push(s)}return n}function xP(e,t,n){if(e===1)return`rc > ${t[0]}`;let r="";for(let a=e-2;a<e;a++)r+=`${n[a]} >= ${t[a]}`,a<e-1&&(r+="||");return r}function wP(e,t,n,r){if(e===1)return"";let a=r.slice(-2);return`
+      `}}};function rW(e,t){let n=[];for(let r=0;r<=1;r++)for(let a=0;a<=1;a++){let s=`${r===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let i=2;i<e;i++)s=`${t[t.length-1-i]},`+s;n.push(s)}return n}function QL(e,t,n){if(e===1)return`rc > ${t[0]}`;let r="";for(let a=e-2;a<e;a++)r+=`${n[a]} >= ${t[a]}`,a<e-1&&(r+="||");return r}function eW(e,t,n,r){if(e===1)return"";let a=r.slice(-2);return`
     int r = ${a[0]};
     int c = ${a[1]};
     int rp1 = r + 1;
@@ -839,12 +839,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
     bool cEdge = cp1 >= ${t};
     bool rEdge = rp1 >= ${n};
-  `}function bP(e,t){let n=e.length,r=vP(n,t);return n===1?`getA(rc),
+  `}function tW(e,t){let n=e.length,r=rW(n,t);return n===1?`getA(rc),
             rc + 1 >= ${e[0]} ? 0. : getA(rc + 1),
             0, 0`:`getA(${r[0]}),
           cEdge ? 0. : getA(${r[1]}),
           rEdge ? 0. : getA(${r[2]}),
-          rEdge || cEdge ? 0. : getA(${r[3]})`}var Db=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let r=0;r<4;r++){let a="thisRC = rc;";r%2==1&&(a+="thisRC.z += 1;"),r>1&&(a+="thisRC.y += 1;"),n+=`
+          rEdge || cEdge ? 0. : getA(${r[3]})`}var m3=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let r=0;r<4;r++){let a="thisRC = rc;";r%2==1&&(a+="thisRC.z += 1;"),r>1&&(a+="thisRC.y += 1;"),n+=`
         ${a}
         ${r>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
           int flatIndex = getFlatIndex(thisRC);
@@ -856,8 +856,8 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
         ${r>0?"}":""}
       `}this.userCode=`
-      ${kP(t)}
-      ${Qm(e)}
+      ${aW(t)}
+      ${aA(e)}
 
       void main() {
         ivec3 rc = getOutputCoords();
@@ -872,12 +872,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function kP(e){return`
+    `}};function aW(e){return`
     ivec3 inputCoordsFromReshapedOutCoords(int index) {
-      ${bi(["r","c","d"],e)}
+      ${wi(["r","c","d"],e)}
       return ivec3(r, c, d);
     }
-  `}var IP=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let r=zb(t,n),a=Pb(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=Ob(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return r===en.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===en.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===en.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===en.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===en.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,r){if(this.freeTextures==null)return;let a=zb(n,r),s=Pb(t,a,r);s in this.freeTextures||(this.freeTextures[s]=[]);let i=Ob(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),o=J().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],c=l.indexOf(e);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${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)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function NP(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function Ob(e,t,n,r,a){let s=SP(t,r),i;if(a){let[l,c]=Il(e[0],e[1]);i=l*c}else{let[l,c]=cc(e[0],e[1]);i=l*c}let o=NP(n,s);return i*o}function SP(e,t){switch(e){case en.PACKED_2X2_FLOAT32:return rA(t);case en.PACKED_2X2_FLOAT16:return aA(t);case en.UNPACKED_FLOAT32:return eA(t);case en.UNPACKED_FLOAT16:return tA(t);case en.PACKED_4X1_UNSIGNED_BYTE:return nA(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function TP(e){return J().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?en.PACKED_2X2_FLOAT32:en.UNPACKED_FLOAT32:e?en.PACKED_2X2_FLOAT16:en.UNPACKED_FLOAT16}function zb(e,t){if(e===Xn.UPLOAD)return en.PACKED_2X2_FLOAT32;if(e===Xn.RENDER||e==null)return TP(t);if(e===Xn.DOWNLOAD||e===Xn.PIXELS)return en.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function Pb(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var La=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+  `}var sW=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let r=y3(t,n),a=g3(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=A3(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return r===en.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===en.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===en.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===en.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===en.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,r){if(this.freeTextures==null)return;let a=y3(n,r),s=g3(t,a,r);s in this.freeTextures||(this.freeTextures[s]=[]);let i=A3(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),o=J().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],c=l.indexOf(e);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${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)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function iW(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function A3(e,t,n,r,a){let s=oW(t,r),i;if(a){let[l,c]=Il(e[0],e[1]);i=l*c}else{let[l,c]=cc(e[0],e[1]);i=l*c}let o=iW(n,s);return i*o}function oW(e,t){switch(e){case en.PACKED_2X2_FLOAT32:return lA(t);case en.PACKED_2X2_FLOAT16:return uA(t);case en.UNPACKED_FLOAT32:return sA(t);case en.UNPACKED_FLOAT16:return iA(t);case en.PACKED_4X1_UNSIGNED_BYTE:return oA(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function lW(e){return J().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?en.PACKED_2X2_FLOAT32:en.UNPACKED_FLOAT32:e?en.PACKED_2X2_FLOAT16:en.UNPACKED_FLOAT16}function y3(e,t){if(e===Xn.UPLOAD)return en.PACKED_2X2_FLOAT32;if(e===Xn.RENDER||e==null)return lW(t);if(e===Xn.DOWNLOAD||e===Xn.PIXELS)return en.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function g3(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var La=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       float unaryOperation(float x) {
         ${t}
       }
@@ -888,11 +888,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}},gr="if (isnan(x)) return x;",EP="return x;",Lb="return abs(x);",CP="return (x >= 0.0) ? x : (exp(x) - 1.0);",RP=gr+`
+    `}},gr="if (isnan(x)) return x;",uW="return x;",x3="return abs(x);",cW="return (x >= 0.0) ? x : (exp(x) - 1.0);",hW=gr+`
   return (x < 0.0) ? 0.0 : x;
-`,MP=gr+`
+`,dW=gr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,pp="return x;",FP="return x;",$P=`
+`,pp="return x;",pW="return x;",fW=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -901,7 +901,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,DP=`
+`,mW=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -911,7 +911,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,OP=`
+`,AW=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -932,14 +932,14 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}},zP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=dn("rc",t),r=ot(t),a=gP(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
+    `}},yW=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=dn("rc",t),r=ot(t),a=JL(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
       void main() {
         ${r} rc = getOutputCoords();
         vec4 packedInput = getA(${a});
 
         setOutput(getChannel(packedInput, ${i}));
       }
-    `}},PP=Pr.whereImpl,LP=1e-7,WP=1e-4,iA={};function BP(e){return e in iA||(iA[e]={}),iA[e]}var VP=128,UP=600;function jP(){return J().global.screen==null?1024:J().global.screen.height*J().global.screen.width*window.devicePixelRatio*UP/1024/1024}var Rl=class extends uu{constructor(e){super();if(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.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!J().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Wr(J().getNumber("WEBGL_VERSION"));this.binaryCache=BP(J().getNumber("WEBGL_VERSION")),this.gpgpu=new dp(t),this.canvas=t.canvas,this.gpgpuCreatedLocally=!0}else this.gpgpu=e,this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=e.gl.canvas;this.textureManager=new IP(this.gpgpu),this.numMBBeforeWarning=jP(),this.texData=new _h(this,Mr())}nextDataId(){return Rl.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((J().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||J().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 r={id:this.nextDataId()};return this.texData.set(r,{shape:t,dtype:n,values:e,usage:Xn.UPLOAD,refCount:1}),r}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,r,a){if(J().getBool("DEBUG")&&this.checkNumericalProblems(t),r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:r,values:t,usage:Xn.UPLOAD,refCount:a})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:a,slice:s,shape:i,isPacked:o}=t;if(s!=null){let h;o?h=new Cl(i,pp):h=new La(i,pp);let d=this.runWebGLProgram(h,[{dataId:e,shape:i,dtype:r}],r),p=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(r==="string")return n;let l=this.activeTimers!=null,c;l&&(c=v.now());let u;if(r==="complex64"){let h=this.readSync(a.real.dataId),d=this.readSync(a.imag.dataId);u=R.mergeRealAndImagArrays(h,d)}else u=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-c),this.convertAndCacheOnCPU(e,u)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(f=>p.push(f))}let t=this.texData.get(e),{values:n,shape:r,slice:a,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(a!=null){let p;o?p=new Cl(r,pp):p=new La(r,pp);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&J().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,c;if(s!=="complex64"&&J().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let p=this.texData.get(c.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...hc(r))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let u;if(s==="complex64"){let p=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=p[0],m=p[1];u=R.mergeRealAndImagArrays(f,m)}else if(l==null)u=this.getValuesFromTexture(e);else{let p=v.sizeFromShape(r);u=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}c!=null&&this.disposeIntermediateTensorInfo(c);let h=this.convertAndCacheOnCPU(e,u),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(p=>p(h)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&Mr().removeDataId(e,this),this.pendingDeletes--),h}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return Be(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!Ww(n))throw J().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 ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),a=v.sizeFromShape(t);if(J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),d=this.texData.get(h.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(d.texture,...hc(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),p}let s=J().getBool("WEBGL_PACK")&&r===!0,i=s?op(t):t,o=s?new rz(i):new nz(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),c=this.texData.get(l.dataId),u=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture,c.texShape[0],c.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),u}timerAvailable(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,c)=>({name:s[c],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(J().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:r,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,s)));let c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return J().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Mr().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=VP){let n=this.getCPUBackend();return!J().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),n!=null&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){R.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return PP(e.shape,t)}packedUnaryOp(e,t,n){let r=new Cl(e.shape,t),a=this.compileAndRun(r,[e],n);return Mr().makeTensorFromDataId(a.dataId,a.shape,a.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let r=Fb(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,r)}if(J().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,Lb,e.dtype);let t=new La(e.shape,Lb),n=this.compileAndRun(t,[e]);return Mr().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let a=n.map(s=>v.encodeString(s));r=this.write(a,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:r}=this.makeTensorInfo(e,t,n);return Mr().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new zP(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new _P(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[gi(e.shape),...xi(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[gi(t),...xi(t)],s=new Db(a,n),i=!0,o=this.runWebGLProgram(s,[r],e.dtype,null,i);return{dataId:o.dataId,shape:t,dtype:o.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:r,dtype:a}=t,s=op(r),i;n?i=new tz(s):i=new ez(s);let o=!0,l=this.runWebGLProgram(i,[{shape:s,dtype:a,dataId:e}],a,null,o);return{dtype:a,shape:r,dataId:l.dataId}}runWebGLProgram(e,t,n,r,a=!1){let s=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(s.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===uc.DENSE){let m=hc(e.outputShape);i.texShape=m.map(A=>A*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(s.shape)===0)return i.values=v.getTypedArrayFromDType(s.dtype,0),s;let o=[],l=t.map(m=>{if(m.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let A=this.texData.get(m.dataId);if(A.texture==null){if(!e.packedInputs&&v.sizeFromShape(m.shape)<=J().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:A.values};e.packedInputs&&(A.isPacked=!0,A.shape=m.shape)}else if(!!A.isPacked!=!!e.packedInputs)m=A.isPacked?this.unpackTensor(m):this.packTensor(m),o.push(m),A=this.texData.get(m.dataId);else if(A.isPacked&&!lc(A.shape,m.shape)){let y=m,g=m.shape;m.shape=A.shape,m=this.packedReshape(m,g),o.push(m),A=this.texData.get(m.dataId),y.shape=g}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:A,isUniform:!1}});this.uploadToGPU(s.dataId);let c={shape:s.shape,texData:i,isUniform:!1},u=Hz(e,l,c),h=this.getAndSaveBinary(u,()=>Uz(this.gpgpu,e,l,c)),d=this.activeTimers!=null,p;d&&(p=this.startTimer()),jz(this.gpgpu,h,l,c,r),o.forEach(m=>this.disposeIntermediateTensorInfo(m)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=J().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=v.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!J().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let m=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),m}return s}compileAndRun(e,t,n,r,a=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(J().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),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=z(()=>{if(!J().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=J().getBool("DEBUG");J().set("DEBUG",!1);let t=this.abs(ge(1e-8)).dataSync()[0];if(J().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?LP:WP}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:r,values:a,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,c;l&&(c=v.now());let u=t.texShape;if(u==null&&(u=nb(n,o),t.texShape=u),a!=null){let h=op(n),d,p=u[1],f=u[0],m=a instanceof Uint8Array;o?([p,f]=Il(u[0],u[1]),d=new sz(h,[f,p],m)):d=new az(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=Xn.PIXELS:this.texData.get(A.dataId).usage=Xn.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),w=this.texData.get(g.dataId);t.texture=w.texture,t.texShape=w.texShape,t.isPacked=w.isPacked,t.usage=w.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(g.dataId),t.values=null,l&&(this.uploadWaitMs+=v.now()-c)}else{let h=this.acquireTexture(u,i,r,o);t.texture=h}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),t!=null&&(n.values=HP(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}};Rl.nextDataId=0;function HP(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 r=0;r<n.length;++r)n[r]=Math.round(e[r]);return n}else throw new Error(`Unknown dtype ${t}`)}var Wb="3.3.0";function Bb(){J().set("WEBGL_FORCE_F16_TEXTURES",!0)}zu.isBrowser()&&il("webgl",()=>new Rl,2);var GP={forceHalfFloat:Bb},Vb=`
+    `}},gW=Pr.whereImpl,xW=1e-7,bW=1e-4,hA={};function wW(e){return e in hA||(hA[e]={}),hA[e]}var _W=128,vW=600;function kW(){return J().global.screen==null?1024:J().global.screen.height*J().global.screen.width*window.devicePixelRatio*vW/1024/1024}var Rl=class extends uu{constructor(e){super();if(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.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!J().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Wr(J().getNumber("WEBGL_VERSION"));this.binaryCache=wW(J().getNumber("WEBGL_VERSION")),this.gpgpu=new dp(t),this.canvas=t.canvas,this.gpgpuCreatedLocally=!0}else this.gpgpu=e,this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=e.gl.canvas;this.textureManager=new sW(this.gpgpu),this.numMBBeforeWarning=kW(),this.texData=new _h(this,Mr())}nextDataId(){return Rl.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((J().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||J().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 r={id:this.nextDataId()};return this.texData.set(r,{shape:t,dtype:n,values:e,usage:Xn.UPLOAD,refCount:1}),r}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,r,a){if(J().getBool("DEBUG")&&this.checkNumericalProblems(t),r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:r,values:t,usage:Xn.UPLOAD,refCount:a})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:a,slice:s,shape:i,isPacked:o}=t;if(s!=null){let h;o?h=new Cl(i,pp):h=new La(i,pp);let d=this.runWebGLProgram(h,[{dataId:e,shape:i,dtype:r}],r),p=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(r==="string")return n;let l=this.activeTimers!=null,c;l&&(c=v.now());let u;if(r==="complex64"){let h=this.readSync(a.real.dataId),d=this.readSync(a.imag.dataId);u=R.mergeRealAndImagArrays(h,d)}else u=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-c),this.convertAndCacheOnCPU(e,u)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(f=>p.push(f))}let t=this.texData.get(e),{values:n,shape:r,slice:a,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(a!=null){let p;o?p=new Cl(r,pp):p=new La(r,pp);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&J().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,c;if(s!=="complex64"&&J().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let p=this.texData.get(c.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...hc(r))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let u;if(s==="complex64"){let p=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=p[0],m=p[1];u=R.mergeRealAndImagArrays(f,m)}else if(l==null)u=this.getValuesFromTexture(e);else{let p=v.sizeFromShape(r);u=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}c!=null&&this.disposeIntermediateTensorInfo(c);let h=this.convertAndCacheOnCPU(e,u),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(p=>p(h)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&Mr().removeDataId(e,this),this.pendingDeletes--),h}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return Be(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!b_(n))throw J().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 ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),a=v.sizeFromShape(t);if(J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),d=this.texData.get(h.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(d.texture,...hc(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),p}let s=J().getBool("WEBGL_PACK")&&r===!0,i=s?op(t):t,o=s?new zP(i):new OP(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),c=this.texData.get(l.dataId),u=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture,c.texShape[0],c.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),u}timerAvailable(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,c)=>({name:s[c],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(J().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:r,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,s)));let c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return J().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Mr().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=_W){let n=this.getCPUBackend();return!J().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),n!=null&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){R.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return gW(e.shape,t)}packedUnaryOp(e,t,n){let r=new Cl(e.shape,t),a=this.compileAndRun(r,[e],n);return Mr().makeTensorFromDataId(a.dataId,a.shape,a.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let r=p3(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,r)}if(J().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,x3,e.dtype);let t=new La(e.shape,x3),n=this.compileAndRun(t,[e]);return Mr().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let a=n.map(s=>v.encodeString(s));r=this.write(a,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:r}=this.makeTensorInfo(e,t,n);return Mr().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new yW(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new nW(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[gi(e.shape),...xi(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[gi(t),...xi(t)],s=new m3(a,n),i=!0,o=this.runWebGLProgram(s,[r],e.dtype,null,i);return{dataId:o.dataId,shape:t,dtype:o.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:r,dtype:a}=t,s=op(r),i;n?i=new $P(s):i=new DP(s);let o=!0,l=this.runWebGLProgram(i,[{shape:s,dtype:a,dataId:e}],a,null,o);return{dtype:a,shape:r,dataId:l.dataId}}runWebGLProgram(e,t,n,r,a=!1){let s=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(s.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===uc.DENSE){let m=hc(e.outputShape);i.texShape=m.map(A=>A*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(s.shape)===0)return i.values=v.getTypedArrayFromDType(s.dtype,0),s;let o=[],l=t.map(m=>{if(m.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let A=this.texData.get(m.dataId);if(A.texture==null){if(!e.packedInputs&&v.sizeFromShape(m.shape)<=J().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:A.values};e.packedInputs&&(A.isPacked=!0,A.shape=m.shape)}else if(!!A.isPacked!=!!e.packedInputs)m=A.isPacked?this.unpackTensor(m):this.packTensor(m),o.push(m),A=this.texData.get(m.dataId);else if(A.isPacked&&!lc(A.shape,m.shape)){let y=m,g=m.shape;m.shape=A.shape,m=this.packedReshape(m,g),o.push(m),A=this.texData.get(m.dataId),y.shape=g}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:A,isUniform:!1}});this.uploadToGPU(s.dataId);let c={shape:s.shape,texData:i,isUniform:!1},u=IL(e,l,c),h=this.getAndSaveBinary(u,()=>vL(this.gpgpu,e,l,c)),d=this.activeTimers!=null,p;d&&(p=this.startTimer()),kL(this.gpgpu,h,l,c,r),o.forEach(m=>this.disposeIntermediateTensorInfo(m)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=J().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=v.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!J().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let m=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),m}return s}compileAndRun(e,t,n,r,a=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(J().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),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=z(()=>{if(!J().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=J().getBool("DEBUG");J().set("DEBUG",!1);let t=this.abs(ge(1e-8)).dataSync()[0];if(J().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?xW:bW}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:r,values:a,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,c;l&&(c=v.now());let u=t.texShape;if(u==null&&(u=O_(n,o),t.texShape=u),a!=null){let h=op(n),d,p=u[1],f=u[0],m=a instanceof Uint8Array;o?([p,f]=Il(u[0],u[1]),d=new LP(h,[f,p],m)):d=new PP(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=Xn.PIXELS:this.texData.get(A.dataId).usage=Xn.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),b=this.texData.get(g.dataId);t.texture=b.texture,t.texShape=b.texShape,t.isPacked=b.isPacked,t.usage=b.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(g.dataId),t.values=null,l&&(this.uploadWaitMs+=v.now()-c)}else{let h=this.acquireTexture(u,i,r,o);t.texture=h}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),t!=null&&(n.values=IW(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}};Rl.nextDataId=0;function IW(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 r=0;r<n.length;++r)n[r]=Math.round(e[r]);return n}else throw new Error(`Unknown dtype ${t}`)}var b3="3.3.0";function w3(){J().set("WEBGL_FORCE_F16_TEXTURES",!0)}zu.isBrowser()&&il("webgl",()=>new Rl,2);var NW={forceHalfFloat:w3},_3=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
 `,Ml=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
@@ -989,21 +989,21 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function On(e){let{inputs:t,backend:n}=e,{x:r}=t;return n.incRef(r.dataId),{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}var qP={kernelName:vs,backendName:"webgl",kernelFunc:On};function Wa(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.makeTensorInfo(r.shape,"complex64"),i=n.texData.get(s.dataId),o=On({inputs:{x:r},backend:n}),l=On({inputs:{x:a},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var XP={kernelName:Rh,backendName:"webgl",kernelFunc:Wa},Ub="return (a < 0.) ? b * a : a;",jb=`
+    `}};function On(e){let{inputs:t,backend:n}=e,{x:r}=t;return n.incRef(r.dataId),{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}var SW={kernelName:vs,backendName:"webgl",kernelFunc:On};function Wa(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.makeTensorInfo(r.shape,"complex64"),i=n.texData.get(s.dataId),o=On({inputs:{x:r},backend:n}),l=On({inputs:{x:a},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var TW={kernelName:Rh,backendName:"webgl",kernelFunc:Wa},v3="return (a < 0.) ? b * a : a;",k3=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function KP(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new pc(jb,a.shape,i.shape):new Ml(Ub,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var ZP={kernelName:ks,backendName:"webgl",kernelFunc:KP},Hb="return (a < 0.) ? b * a : a;",Gb=`
+`;function EW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new pc(k3,a.shape,i.shape):new Ml(v3,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var CW={kernelName:ks,backendName:"webgl",kernelFunc:EW},I3="return (a < 0.) ? b * a : a;",N3=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function YP(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new pc(Gb,r.shape,a.shape):new Ml(Hb,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var JP={kernelName:Os,backendName:"webgl",kernelFunc:YP},qb="if (isnan(x)) return x;",QP=`
+`;function RW(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new pc(N3,r.shape,a.shape):new Ml(I3,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var MW={kernelName:Os,backendName:"webgl",kernelFunc:RW},S3="if (isnan(x)) return x;",FW=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
-`,eL=`
+`,DW=`
   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;
-`;function Xe({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=r||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let h=o.texData.get(i.dataId),d=n(h.values,l);return o.makeTensorInfo(i.shape,l,d)}let c=J().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,u;return c?u=new Cl(i.shape,t):u=new La(i.shape,e),o.runWebGLProgram(u,[i],l)}}function tn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:c}=i,u=o;if(r&&l.dtype==="complex64"){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(w=>{let[b,_]=w,x={dataId:b.dataId,dtype:b.dtype,shape:l.shape},N={dataId:_.dataId,dtype:_.dtype,shape:c.shape},T=new Ml(e,l.shape,c.shape);return u.runWebGLProgram(T,[x,N],tr(b.dtype,_.dtype))}),g=Wa({inputs:{real:A,imag:y},backend:u});return u.disposeIntermediateTensorInfo(A),u.disposeIntermediateTensorInfo(y),g}let h=s||tr(l.dtype,c.dtype);if(u.shouldExecuteOnCPU([l,c])&&a!=null){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=a(l.shape,c.shape,f.values,m.values,h),g=u.makeTensorInfo(y,h),w=u.texData.get(g.dataId);return w.values=A,g}let d=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new pc(t,l.shape,c.shape,n):p=new Ml(e,l.shape,c.shape),u.runWebGLProgram(p,[l,c],h)}}function mp(e,t=!1){if(e==="linear")return t?FP:EP;if(e==="relu")return t?DP:RP;if(e==="elu")return t?$P:CP;if(e==="relu6")return t?OP:MP;if(e==="prelu")return t?Gb:Hb;if(e==="leakyrelu")return t?jb:Ub;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var Xb=class{constructor(e,t,n,r=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let c=r?e[1]:e[2],u=Math.ceil(c/2),h=r?"i * 2, rc.y":"rc.y, i * 2",d=a?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",A="";i&&(o?m=`vec4 activation(vec4 a) {
+`;function Xe({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=r||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let h=o.texData.get(i.dataId),d=n(h.values,l);return o.makeTensorInfo(i.shape,l,d)}let c=J().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,u;return c?u=new Cl(i.shape,t):u=new La(i.shape,e),o.runWebGLProgram(u,[i],l)}}function tn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:c}=i,u=o;if(r&&l.dtype==="complex64"){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(b=>{let[w,_]=b,x={dataId:w.dataId,dtype:w.dtype,shape:l.shape},N={dataId:_.dataId,dtype:_.dtype,shape:c.shape},T=new Ml(e,l.shape,c.shape);return u.runWebGLProgram(T,[x,N],tr(w.dtype,_.dtype))}),g=Wa({inputs:{real:A,imag:y},backend:u});return u.disposeIntermediateTensorInfo(A),u.disposeIntermediateTensorInfo(y),g}let h=s||tr(l.dtype,c.dtype);if(u.shouldExecuteOnCPU([l,c])&&a!=null){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=a(l.shape,c.shape,f.values,m.values,h),g=u.makeTensorInfo(y,h),b=u.texData.get(g.dataId);return b.values=A,g}let d=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new pc(t,l.shape,c.shape,n):p=new Ml(e,l.shape,c.shape),u.runWebGLProgram(p,[l,c],h)}}function mp(e,t=!1){if(e==="linear")return t?pW:uW;if(e==="relu")return t?mW:hW;if(e==="elu")return t?fW:cW;if(e==="relu6")return t?AW:dW;if(e==="prelu")return t?N3:I3;if(e==="leakyrelu")return t?k3:v3;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var T3=class{constructor(e,t,n,r=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let c=r?e[1]:e[2],u=Math.ceil(c/2),h=r?"i * 2, rc.y":"rc.y, i * 2",d=a?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",A="";i&&(o?m=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${i}
         }`:l?m=`vec4 activation(vec4 a) {
@@ -1011,7 +1011,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           ${i}
         }`:m=`vec4 activation(vec4 x) {
           ${i}
-        }`,A="result = activation(result);");let y=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let g="rc.x",w="rc.x";e[0]<t[0]?g=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(w=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
+        }`,A="result = activation(result);");let y=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let g="rc.x",b="rc.x";e[0]<t[0]?g=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(b=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
       ${m}
 
       const float sharedDimension = ${u}.0;
@@ -1020,7 +1020,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         vec4 result = vec4(0);
         for (int i = 0; i < ${u}; i++) {
           int batchA = ${g};
-          int batchB = ${w};
+          int batchB = ${b};
           vec4 a = getMatrixA(batchA, ${h});
           vec4 b = getMatrixB(batchB, ${d});
 
@@ -1042,7 +1042,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}},Kb={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},Zb=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
+    `}},E3={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},C3=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
       float binaryOpComplex(
           float areal, float aimag, float breal, float bimag) {
         ${e}
@@ -1055,7 +1055,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float bimag = getBImagAtOutCoords();
         setOutput(binaryOpComplex(areal, aimag, breal, bimag));
       }
-    `}},Yb="return a * b;";function Jb(e){let{inputs:t,backend:n}=e,{a:r,b:a}=t,s=R.upcastType(r.dtype,a.dtype);if(r.dtype==="complex64"){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),c=new Zb(Kb.REAL,r.shape,a.shape),u=new Zb(Kb.IMAG,r.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:r.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Wa({inputs:{real:d,imag:p},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,a])){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),[c,u]=oP(r.shape,a.shape,o.values,l.values,s),h=n.makeTensorInfo(u,s),d=n.texData.get(h.dataId);return d.values=c,h}let i;return J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new pc(Yb,r.shape,a.shape):i=new Ml(Yb,r.shape,a.shape),n.runWebGLProgram(i,[r,a],s)}var tL={kernelName:Ms,backendName:"webgl",kernelFunc:Jb};function nL(e,t,n){let r=[gi(e.shape),...xi(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},s=[gi(t),...xi(t)],i=new Db(s,r),o=!0,l=n.runWebGLProgram(i,[a],e.dtype,null,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function xe(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=n,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),c=v.sizeFromShape(l);v.assert(o===c,()=>`The new shape (${l}) has ${c} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let u=i.texData.get(a.dataId);return u.isPacked&&!lc(a.shape,l)&&!(u.texture!==null&&lc(u.shape,l))?nL(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var rL={kernelName:zo,backendName:"webgl",kernelFunc:xe},Qb=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let u=1/t;l=`sumValue += dot(values * ${v.isInt(u)?u.toPrecision(2):u}, ones);`}let c="";a%n>0&&(c=`
+    `}},R3="return a * b;";function M3(e){let{inputs:t,backend:n}=e,{a:r,b:a}=t,s=R.upcastType(r.dtype,a.dtype);if(r.dtype==="complex64"){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),c=new C3(E3.REAL,r.shape,a.shape),u=new C3(E3.IMAG,r.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:r.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Wa({inputs:{real:d,imag:p},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,a])){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),[c,u]=BL(r.shape,a.shape,o.values,l.values,s),h=n.makeTensorInfo(u,s),d=n.texData.get(h.dataId);return d.values=c,h}let i;return J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new pc(R3,r.shape,a.shape):i=new Ml(R3,r.shape,a.shape),n.runWebGLProgram(i,[r,a],s)}var $W={kernelName:Ms,backendName:"webgl",kernelFunc:M3};function OW(e,t,n){let r=[gi(e.shape),...xi(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},s=[gi(t),...xi(t)],i=new m3(s,r),o=!0,l=n.runWebGLProgram(i,[a],e.dtype,null,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function xe(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=n,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),c=v.sizeFromShape(l);v.assert(o===c,()=>`The new shape (${l}) has ${c} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let u=i.texData.get(a.dataId);return u.isPacked&&!lc(a.shape,l)&&!(u.texture!==null&&lc(u.shape,l))?OW(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var zW={kernelName:zo,backendName:"webgl",kernelFunc:xe},F3=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let u=1/t;l=`sumValue += dot(values * ${v.isInt(u)?u.toPrecision(2):u}, ones);`}let c="";a%n>0&&(c=`
         if (inIdx < 0 || inIdx >= ${a}) {
           return 0.0;
         }
@@ -1108,7 +1108,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(sumValue);
       }
-    `}},aL=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let c=Math.floor(n/4)*4,u=n%4,h=`
+    `}},PW=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let c=Math.floor(n/4)*4,u=n%4,h=`
       if (${t==="sum"}) {
         sumValue += dot(values, ones);
       } else if (${t==="prod"}) {
@@ -1193,12 +1193,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(${l});
       }
-    `}};function sL(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],r=R.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function vi(e,t,n,r){let a=sL(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:c}=a[i],u,h;n==="mean"?u=i===0?new Qb({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},o):new Qb({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c}):u=new aL({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},n),h=s,s=r.runWebGLProgram(u,[s],t),h.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(h)}return s}var oL=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let r=ot(this.rank),a=iL(t);this.userCode=`
+    `}};function LW(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],r=R.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function vi(e,t,n,r){let a=LW(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:c}=a[i],u,h;n==="mean"?u=i===0?new F3({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},o):new F3({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c}):u=new PW({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},n),h=s,s=r.runWebGLProgram(u,[s],t),h.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(h)}return s}var BW=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let r=ot(this.rank),a=WW(t);this.userCode=`
     void main() {
       ${r} resRC = getOutputCoords();
       setOutput(getA(${a}));
     }
-    `}};function iL(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t);for(let a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}var lL=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let c=0;c<n.length;c++)n[c]=e[t[c]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let r=ot(this.rank),a=$b("rc",this.rank),s=new Array(this.rank);for(let c=0;c<t.length;c++)s[t[c]]=a[c];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
+    `}};function WW(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t);for(let a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}var VW=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let c=0;c<n.length;c++)n[c]=e[t[c]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let r=ot(this.rank),a=f3("rc",this.rank),s=new Array(this.rank);for(let c=0;c<t.length;c++)s[t[c]]=a[c];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
     void main() {
       ${r} rc = getOutputCoords();
       vec4 result = vec4(0.);
@@ -1215,14 +1215,14 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       }
       setOutput(result);
     }
-    `}};function Ap(e,t,n){let r=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new lL(e.shape,t):new oL(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function uL(e,t,n,r){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=R.getAxesPermutation(o,s),c=l!=null,u=e;c&&(u=Ap(e,l,r),o=R.getInnerMostAxes(o.length,s)),R.assertAxesAreInnerMostDims("sum",o,s);let[h,d]=R.computeOutAndReduceShapes(u.shape,o),p=h;n&&(p=R.expandShapeToKeepDim(h,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,A=xe({inputs:{x:u},attrs:{shape:[m,f]},backend:r}),y=ld(e.dtype),g=vi(A,y,"sum",r),w=xe({inputs:{x:g},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(g),c&&r.disposeIntermediateTensorInfo(u),w}function oA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;return uL(a,s,i,n)}var cL={kernelName:Gs,backendName:"webgl",kernelFunc:oA};function In(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:s}=r,i=n,o=a.shape.length,l=new Array(o);for(let u=0;u<l.length;u++)l[u]=a.shape[s[u]];let c;if(i.shouldExecuteOnCPU([a])){let u=i.texData.get(a.dataId).values,h=sA(u,a.shape,a.dtype,s,l);c=i.makeTensorInfo(l,a.dtype);let d=i.texData.get(c.dataId);d.values=h}else c=Ap(a,s,i);return c}var hL={kernelName:Ys,backendName:"webgl",kernelFunc:In},e_=1e3;function yp({a:e,b:t,transposeA:n,transposeB:r,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let c=e.shape.length,u=t.shape.length,h=n?e.shape[c-2]:e.shape[c-1],d=r?t.shape[u-1]:t.shape[u-2],p=n?e.shape[c-1]:e.shape[c-2],f=r?t.shape[u-2]:t.shape[u-1],m=e.shape.slice(0,-2),A=t.shape.slice(0,-2),y=v.sizeFromShape(m),g=v.sizeFromShape(A),w=y===g||y===1||g===1;v.assert(c>=2&&u>=2&&w,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${A}).`);let b=(y>g?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);v.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let _=n?[y,h,p]:[y,p,h],x=r?[g,f,d]:[g,d,f],N=xe({inputs:{x:e},backend:a,attrs:{shape:_}}),T=xe({inputs:{x:t},backend:a,attrs:{shape:x}}),E=[N,T],F=Math.max(y,g),D=n?N.shape[1]:N.shape[2],L=s!=null,V=i!=null,U=l==="leakyrelu",j=l!=null?mp(l,!0):null,X=L||V||U||j!=null,G;if((p===1||f===1)&&D>e_&&X===!1){let Y=N,ae=T;n&&(Y=In({inputs:{x:N},backend:a,attrs:{perm:[0,2,1]}}),E.push(Y)),r&&(ae=In({inputs:{x:T},backend:a,attrs:{perm:[0,2,1]}}),E.push(ae));let te=f!==1,oe=f===1,Q=Y;te&&(Q=xe({inputs:{x:Y},backend:a,attrs:{shape:[F,D,1]}}),E.push(Q));let he=f===1?2:1,le=ae;oe&&(le=xe({inputs:{x:ae},backend:a,attrs:{shape:[F,1,D]}}),E.push(le));let fe=Jb({inputs:{a:Q,b:le},backend:a});G=oA({inputs:{x:fe},backend:a,attrs:{axis:he,keepDims:!0}}),E.push(fe)}else{let Y=tr(e.dtype,t.dtype),ae=new Xb(_,x,[F,p,f],n,r,L,j,V,U),te=[N,T];if(s!=null&&te.push(s),V&&te.push(i),U){let oe=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));te.push(oe),E.push(oe)}G=a.runWebGLProgram(ae,te,Y)}let ee=xe({inputs:{x:G},backend:a,attrs:{shape:b}});E.push(G);for(let Y of E)a.disposeIntermediateTensorInfo(Y);return ee}function dL(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:c,activation:u,leakyreluAlpha:h}=r;return yp({a,b:s,transposeA:l,transposeB:c,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:u})}var pL={kernelName:Js,backendName:"webgl",kernelFunc:dL},t_="return abs(x);";function fL(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let s=n.texData.get(r.dataId),i=Fb(s.values);return n.makeTensorInfo(r.shape,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Cl(r.shape,t_):a=new La(r.shape,t_),n.runWebGLProgram(a,[r],r.dtype)}var mL={kernelName:Ji,backendName:"webgl",kernelFunc:fL},AL=gr+`
+    `}};function Ap(e,t,n){let r=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new VW(e.shape,t):new BW(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function jW(e,t,n,r){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=R.getAxesPermutation(o,s),c=l!=null,u=e;c&&(u=Ap(e,l,r),o=R.getInnerMostAxes(o.length,s)),R.assertAxesAreInnerMostDims("sum",o,s);let[h,d]=R.computeOutAndReduceShapes(u.shape,o),p=h;n&&(p=R.expandShapeToKeepDim(h,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,A=xe({inputs:{x:u},attrs:{shape:[m,f]},backend:r}),y=ld(e.dtype),g=vi(A,y,"sum",r),b=xe({inputs:{x:g},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(g),c&&r.disposeIntermediateTensorInfo(u),b}function dA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;return jW(a,s,i,n)}var UW={kernelName:Gs,backendName:"webgl",kernelFunc:dA};function In(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:s}=r,i=n,o=a.shape.length,l=new Array(o);for(let u=0;u<l.length;u++)l[u]=a.shape[s[u]];let c;if(i.shouldExecuteOnCPU([a])){let u=i.texData.get(a.dataId).values,h=cA(u,a.shape,a.dtype,s,l);c=i.makeTensorInfo(l,a.dtype);let d=i.texData.get(c.dataId);d.values=h}else c=Ap(a,s,i);return c}var HW={kernelName:Ys,backendName:"webgl",kernelFunc:In},D3=1e3;function yp({a:e,b:t,transposeA:n,transposeB:r,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let c=e.shape.length,u=t.shape.length,h=n?e.shape[c-2]:e.shape[c-1],d=r?t.shape[u-1]:t.shape[u-2],p=n?e.shape[c-1]:e.shape[c-2],f=r?t.shape[u-2]:t.shape[u-1],m=e.shape.slice(0,-2),A=t.shape.slice(0,-2),y=v.sizeFromShape(m),g=v.sizeFromShape(A),b=y===g||y===1||g===1;v.assert(c>=2&&u>=2&&b,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${A}).`);let w=(y>g?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);v.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let _=n?[y,h,p]:[y,p,h],x=r?[g,f,d]:[g,d,f],N=xe({inputs:{x:e},backend:a,attrs:{shape:_}}),T=xe({inputs:{x:t},backend:a,attrs:{shape:x}}),E=[N,T],F=Math.max(y,g),$=n?N.shape[1]:N.shape[2],L=s!=null,V=i!=null,j=l==="leakyrelu",U=l!=null?mp(l,!0):null,X=L||V||j||U!=null,G;if((p===1||f===1)&&$>D3&&X===!1){let Y=N,ae=T;n&&(Y=In({inputs:{x:N},backend:a,attrs:{perm:[0,2,1]}}),E.push(Y)),r&&(ae=In({inputs:{x:T},backend:a,attrs:{perm:[0,2,1]}}),E.push(ae));let te=f!==1,oe=f===1,Q=Y;te&&(Q=xe({inputs:{x:Y},backend:a,attrs:{shape:[F,$,1]}}),E.push(Q));let he=f===1?2:1,le=ae;oe&&(le=xe({inputs:{x:ae},backend:a,attrs:{shape:[F,1,$]}}),E.push(le));let fe=M3({inputs:{a:Q,b:le},backend:a});G=dA({inputs:{x:fe},backend:a,attrs:{axis:he,keepDims:!0}}),E.push(fe)}else{let Y=tr(e.dtype,t.dtype),ae=new T3(_,x,[F,p,f],n,r,L,U,V,j),te=[N,T];if(s!=null&&te.push(s),V&&te.push(i),j){let oe=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));te.push(oe),E.push(oe)}G=a.runWebGLProgram(ae,te,Y)}let ee=xe({inputs:{x:G},backend:a,attrs:{shape:w}});E.push(G);for(let Y of E)a.disposeIntermediateTensorInfo(Y);return ee}function GW(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:c,activation:u,leakyreluAlpha:h}=r;return yp({a,b:s,transposeA:l,transposeB:c,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:u})}var qW={kernelName:Js,backendName:"webgl",kernelFunc:GW},$3="return abs(x);";function XW(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let s=n.texData.get(r.dataId),i=p3(s.values);return n.makeTensorInfo(r.shape,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Cl(r.shape,$3):a=new La(r.shape,$3),n.runWebGLProgram(a,[r],r.dtype)}var KW={kernelName:Ji,backendName:"webgl",kernelFunc:XW},ZW=gr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return acos(x);
-`,yL=Xe({opSnippet:AL}),gL={kernelName:Qi,backendName:"webgl",kernelFunc:yL},xL=gr+`
+`,YW=Xe({opSnippet:ZW}),JW={kernelName:Qi,backendName:"webgl",kernelFunc:YW},QW=gr+`
   if (x < 1.0) return NAN;
-return log(x + sqrt(x * x - 1.0));`,wL=Xe({opSnippet:xL}),bL={kernelName:eo,backendName:"webgl",kernelFunc:wL},n_="return a + b;",_L=tn({opSnippet:n_,packedOpSnippet:n_,supportsComplex:!0,cpuKernelImpl:Gz}),vL={kernelName:va,backendName:"webgl",kernelFunc:_L},kL=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`float v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
+return log(x + sqrt(x * x - 1.0));`,eB=Xe({opSnippet:QW}),tB={kernelName:eo,backendName:"webgl",kernelFunc:eB},O3="return a + b;",nB=tn({opSnippet:O3,packedOpSnippet:O3,supportsComplex:!0,cpuKernelImpl:NL}),rB={kernelName:va,backendName:"webgl",kernelFunc:nB},aB=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`float v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
       void main() {
         ${n.join(`
         `)}
@@ -1230,7 +1230,7 @@ return log(x + sqrt(x * x - 1.0));`,wL=Xe({opSnippet:xL}),bL={kernelName:eo,back
         float result = ${r};
         setOutput(result);
       }
-    `}},IL=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`vec4 v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
+    `}},sB=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`vec4 v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
       void main() {
         ${n.join(`
         `)}
@@ -1238,7 +1238,7 @@ return log(x + sqrt(x * x - 1.0));`,wL=Xe({opSnippet:xL}),bL={kernelName:eo,back
         vec4 result = ${r};
         setOutput(result);
       }
-    `}};function gp(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return On({inputs:{x:r[0]},backend:n});if(r.length>J().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(r.length/2),l=gp({inputs:r.slice(0,o),backend:n}),c=gp({inputs:r.slice(o),backend:n});return gp({inputs:[l,c],backend:n})}let a=r.map(o=>o.dtype).reduce((o,l)=>tr(o,l)),s=r.map(o=>o.shape),i=J().getBool("WEBGL_PACK")?new IL(r[0].shape,s):new kL(r[0].shape,s);return n.runWebGLProgram(i,r,a)}var NL={kernelName:is,backendName:"webgl",kernelFunc:gp};function SL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("all",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"all",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var TL={kernelName:Nh,backendName:"webgl",kernelFunc:SL};function EL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("any",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"any",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var CL={kernelName:Sh,backendName:"webgl",kernelFunc:EL},RL=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:r,batchSize:a,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
+    `}};function gp(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return On({inputs:{x:r[0]},backend:n});if(r.length>J().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(r.length/2),l=gp({inputs:r.slice(0,o),backend:n}),c=gp({inputs:r.slice(o),backend:n});return gp({inputs:[l,c],backend:n})}let a=r.map(o=>o.dtype).reduce((o,l)=>tr(o,l)),s=r.map(o=>o.shape),i=J().getBool("WEBGL_PACK")?new sB(r[0].shape,s):new aB(r[0].shape,s);return n.runWebGLProgram(i,r,a)}var iB={kernelName:is,backendName:"webgl",kernelFunc:gp};function oB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("all",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"all",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var lB={kernelName:Nh,backendName:"webgl",kernelFunc:oB};function uB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("any",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"any",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var cB={kernelName:Sh,backendName:"webgl",kernelFunc:uB},hB=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:r,batchSize:a,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
@@ -1258,7 +1258,7 @@ return log(x + sqrt(x * x - 1.0));`,wL=Xe({opSnippet:xL}),bL={kernelName:eo,back
         }
         setOutput(float(bestIndex));
       }
-    `}},ML=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=ot(o),c=dn("coords",o),u,h;if(s===1){h=o+1;let N=ot(h);u=`
+    `}},dB=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=ot(o),c=dn("coords",o),u,h;if(s===1){h=o+1;let N=ot(h);u=`
         ${N} sourceLocR = ${N}(${c.join()}, 0);
         ++${c[o-1]};
         ${N} sourceLocG = ${N}(${c.join()}, 0);
@@ -1274,7 +1274,7 @@ return log(x + sqrt(x * x - 1.0));`,wL=Xe({opSnippet:xL}),bL={kernelName:eo,back
         ${l} sourceLocA = coords;
         --${c[o-1]};
         ${l} sourceLocB = coords;
-        --${c[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(N=>"int "+N),m=dn("sourceLocR",h-1).concat("inIdx.r"),A=dn("sourceLocG",h-1).concat("inIdx.g"),y=dn("sourceLocB",h-1).concat("inIdx.b"),g=dn("sourceLocA",h-1).concat("inIdx.a"),w=n==="max"?"greaterThan":"lessThan",b=r?"":`
+        --${c[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(N=>"int "+N),m=dn("sourceLocR",h-1).concat("inIdx.r"),A=dn("sourceLocG",h-1).concat("inIdx.g"),y=dn("sourceLocB",h-1).concat("inIdx.b"),g=dn("sourceLocA",h-1).concat("inIdx.a"),b=n==="max"?"greaterThan":"lessThan",w=r?"":`
           inIdx = round(vec4(getBestIndicesAChannel(${m.join()}),
                              getBestIndicesAChannel(${A.join()}),
                              getBestIndicesAChannel(${y.join()}),
@@ -1305,11 +1305,11 @@ return log(x + sqrt(x * x - 1.0));`,wL=Xe({opSnippet:xL}),bL={kernelName:eo,back
 
         for (int i = 0; i < ${t}; i++) {
           inIdx = srcIdx;
-          ${b}
+          ${w}
           vec4 candidate = ${_};
           bvec4 nan = isnan(candidate);
           bvec4 replace = bvec4(
-            vec4(${w}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));
+            vec4(${b}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));
 
           bestValue = vec4(replace.x  ? candidate.x : bestValue.x,
                            replace.y  ? candidate.y : bestValue.y,
@@ -1320,23 +1320,23 @@ return log(x + sqrt(x * x - 1.0));`,wL=Xe({opSnippet:xL}),bL={kernelName:eo,back
         }
         setOutput(bestIndex);
       }
-    `}};function r_(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=R.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new RL(o,n,r==null),c=[t];r!=null&&c.push(r);let u=e.runWebGLProgram(l,c,"int32");if(u.shape[1]===1)return u;let h=r_(e,t,n,u);return e.disposeIntermediateTensorInfo(u),h}function a_(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=R.computeOptimalWindowSize(s),o=new ML(a,i,n,r==null),l=r==null?[t]:[t,r],c=e.runWebGLProgram(o,l,"int32");if(c.shape.length===t.shape.length){let u=a_(e,t,n,c);return e.disposeIntermediateTensorInfo(c),u}return c}function s_(e,t,n,r){let a=[n];if(R.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!J().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=R.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),c=xe({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(c);let u=r_(e,c,r);s.push(u);let h=xe({inputs:{x:u},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return a_(e,t,r)}function FL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=In({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let u=s_(n,l,i[0],"max");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var $L={kernelName:os,backendName:"webgl",kernelFunc:FL};function DL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=In({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let u=s_(n,l,i[0],"min");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var OL={kernelName:du,backendName:"webgl",kernelFunc:DL},zL=gr+`
+    `}};function z3(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=R.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new hB(o,n,r==null),c=[t];r!=null&&c.push(r);let u=e.runWebGLProgram(l,c,"int32");if(u.shape[1]===1)return u;let h=z3(e,t,n,u);return e.disposeIntermediateTensorInfo(u),h}function P3(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=R.computeOptimalWindowSize(s),o=new dB(a,i,n,r==null),l=r==null?[t]:[t,r],c=e.runWebGLProgram(o,l,"int32");if(c.shape.length===t.shape.length){let u=P3(e,t,n,c);return e.disposeIntermediateTensorInfo(c),u}return c}function L3(e,t,n,r){let a=[n];if(R.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!J().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=R.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),c=xe({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(c);let u=z3(e,c,r);s.push(u);let h=xe({inputs:{x:u},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return P3(e,t,r)}function pB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=In({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let u=L3(n,l,i[0],"max");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var fB={kernelName:os,backendName:"webgl",kernelFunc:pB};function mB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=In({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let u=L3(n,l,i[0],"min");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var AB={kernelName:du,backendName:"webgl",kernelFunc:mB},yB=gr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return asin(x);
-`,PL=Xe({opSnippet:zL}),LL={kernelName:to,backendName:"webgl",kernelFunc:PL},WL=gr+"return log(x + sqrt(x * x + 1.0));",BL=Xe({opSnippet:WL}),VL={kernelName:no,backendName:"webgl",kernelFunc:BL},UL=gr+`
+`,gB=Xe({opSnippet:yB}),xB={kernelName:to,backendName:"webgl",kernelFunc:gB},bB=gr+"return log(x + sqrt(x * x + 1.0));",wB=Xe({opSnippet:bB}),_B={kernelName:no,backendName:"webgl",kernelFunc:wB},vB=gr+`
   return atan(x);
-`,jL=Xe({opSnippet:UL}),HL={kernelName:ro,backendName:"webgl",kernelFunc:jL},GL=QP+`
+`,kB=Xe({opSnippet:vB}),IB={kernelName:ro,backendName:"webgl",kernelFunc:kB},NB=FW+`
   return atan(a, b);
-`,qL=`
+`,SB=`
   vec4 result = atan(a, b);
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+eL+`
+  `+DW+`
   return result;
-`,XL=tn({opSnippet:GL,packedOpSnippet:qL}),KL={kernelName:so,backendName:"webgl",kernelFunc:XL},ZL=gr+`
+`,TB=tn({opSnippet:NB,packedOpSnippet:SB}),EB={kernelName:so,backendName:"webgl",kernelFunc:TB},CB=gr+`
   if ((x < -1.0) || (x > 1.0)) return NAN;
-return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelName:ao,backendName:"webgl",kernelFunc:YL},fc=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let N=">=";this.userCode=`
+return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,RB=Xe({opSnippet:CB}),MB={kernelName:ao,backendName:"webgl",kernelFunc:RB},fc=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let N=">=";this.userCode=`
         const ivec2 strides = ivec2(${i}, ${o});
         const ivec2 pads = ivec2(${d}, ${p});
 
@@ -1387,7 +1387,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
           }
           setOutput(float(minMaxPosition));
         }
-      `;return}let g="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / count");let b=Math.floor(s/4)*4,_=s%4,x=`
+      `;return}let g="max",b=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(b="avgValue / count");let w=Math.floor(s/4)*4,_=s%4,x=`
       if (${f}) {
         avgValue += dot(values, ones);
       } else {
@@ -1432,7 +1432,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
             continue;
           }
 
-          for (int wC = 0; wC < ${b}; wC += 4) {
+          for (int wC = 0; wC < ${w}; wC += 4) {
             int xC = xCCorner + wC * ${c};
 
             vec4 values = vec4(
@@ -1445,7 +1445,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
             ${x}
           }
 
-          int xC = xCCorner + ${b};
+          int xC = xCCorner + ${w};
           if (${_===1}) {
             vec4 values = vec4(
               getValue(batch, xR, xC, d),
@@ -1475,9 +1475,9 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
             ${x}
           }
         }
-        setOutput(${w});
+        setOutput(${b});
       }
-    `}},lA=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,c=e.dilationDepth,u=e.dilationHeight,h=e.dilationWidth,d=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,A=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let g=t==="avg",w="0.0";if(g||(w="-1.0 / 1e-20"),n){let E=">=";this.userCode=`
+    `}},pA=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,c=e.dilationDepth,u=e.dilationHeight,h=e.dilationWidth,d=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,A=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let g=t==="avg",b="0.0";if(g||(b="-1.0 / 1e-20"),n){let E=">=";this.userCode=`
         const ivec3 strides =
             ivec3(${i}, ${o}, ${l});
         const ivec3 pads = ivec3(${m}, ${A}, ${y});
@@ -1539,17 +1539,17 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
           }
           setOutput(float(minMaxPosition));
         }
-      `;return}let b="max",_=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(_="avgValue / count");let x=Math.floor(s/4)*4,N=s%4,T=`
+      `;return}let w="max",_=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(_="avgValue / count");let x=Math.floor(s/4)*4,N=s%4,T=`
       if (${g}) {
         avgValue += dot(values, ones);
       } else {
-        minMaxValue = ${b}(values, minMaxValue);
+        minMaxValue = ${w}(values, minMaxValue);
       }
     `;this.userCode=`
       const ivec3 strides =
         ivec3(${i}, ${o}, ${l});
       const ivec3 pads = ivec3(${m}, ${A}, ${y});
-      const float initializationValue = ${w};
+      const float initializationValue = ${b};
       const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
 
       float count = 0.0;
@@ -1574,7 +1574,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
 
         // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
         // ? = to be determined
-        vec4 minMaxValue = vec4(${w});
+        vec4 minMaxValue = vec4(${b});
         float avgValue = 0.0;
         count = 0.0;
 
@@ -1640,7 +1640,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
           setOutput(${_});
         }
       }
-    `}};function QL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return On({inputs:{x:a},backend:n});let h=new fc(u,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var eW={kernelName:ls,backendName:"webgl",kernelFunc:QL};function tW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,l,c),d=new lA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var nW={kernelName:pu,backendName:"webgl",kernelFunc:tW},rW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,c=o-1-e.padInfo.top,u=l-1-e.padInfo.left,h=1/(t*n);this.userCode=`
+    `}};function FB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return On({inputs:{x:a},backend:n});let h=new fc(u,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var DB={kernelName:ls,backendName:"webgl",kernelFunc:FB};function $B(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,l,c),d=new pA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var OB={kernelName:pu,backendName:"webgl",kernelFunc:$B},zB=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,c=o-1-e.padInfo.top,u=l-1-e.padInfo.left,h=1/(t*n);this.userCode=`
       const ivec2 pads = ivec2(${c}, ${u});
       const float avgMultiplier = float(${h});
 
@@ -1682,7 +1682,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},aW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=u-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=`
+    `}},PB=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=u-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=`
       const ivec3 pads = ivec3(${p}, ${f}, ${m});
       const float avgMultiplier = float(${A});
 
@@ -1738,7 +1738,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function sW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new aW(d);return n.runWebGLProgram(p,[a],i.dtype)}var iW={kernelName:Eh,backendName:"webgl",kernelFunc:sW};function oW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;kl([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:c}=r,u=R.computePool2DInfo(i.shape,o,l,1,c),h=new rW(u);return n.runWebGLProgram(h,[a],i.dtype)}var lW={kernelName:Th,backendName:"webgl",kernelFunc:oW};function uW(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return yp({a,b:s,transposeA:i,transposeB:o,backend:n})}var cW={kernelName:us,backendName:"webgl",kernelFunc:uW},hW=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}};function LB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new PB(d);return n.runWebGLProgram(p,[a],i.dtype)}var WB={kernelName:Eh,backendName:"webgl",kernelFunc:LB};function BB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;kl([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:c}=r,u=R.computePool2DInfo(i.shape,o,l,1,c),h=new zB(u);return n.runWebGLProgram(h,[a],i.dtype)}var VB={kernelName:Th,backendName:"webgl",kernelFunc:BB};function jB(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return yp({a,b:s,transposeA:i,transposeB:o,backend:n})}var UB={kernelName:us,backendName:"webgl",kernelFunc:jB},HB=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         float x = getXAtOutCoords();
         float mean = getMeanAtOutCoords();
@@ -1748,7 +1748,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         float inv = scale * inversesqrt(variance + float(${s}));
         setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
       }
-    `}},dW=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}},GB=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         vec4 offset = ${i};
         vec4 scale = ${o};
@@ -1761,7 +1761,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
 
         setOutput((x - mean) * inv + offset);
       }
-    `}},pW=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let c=[r,a,s],u=null;i!=null&&(u=i.shape,c.push(i));let h=null;o!=null&&(h=o.shape,c.push(o));let d=J().getBool("WEBGL_PACK_NORMALIZATION")?new dW(r.shape,a.shape,s.shape,u,h,l):new hW(r.shape,a.shape,s.shape,u,h,l);return t.runWebGLProgram(d,c,c[0].dtype)},fW={kernelName:bs,backendName:"webgl",kernelFunc:pW},AW=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ot(this.rank),n=`uniform int start[${this.rank}];`,r=mW(this.rank),a,s=e.map((i,o)=>`sourceLoc.${uA[o]} = start[${o}] + coords.${uA[o]};`);a=`
+    `}},qB=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let c=[r,a,s],u=null;i!=null&&(u=i.shape,c.push(i));let h=null;o!=null&&(h=o.shape,c.push(o));let d=J().getBool("WEBGL_PACK_NORMALIZATION")?new GB(r.shape,a.shape,s.shape,u,h,l):new HB(r.shape,a.shape,s.shape,u,h,l);return t.runWebGLProgram(d,c,c[0].dtype)},XB={kernelName:ws,backendName:"webgl",kernelFunc:qB},ZB=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ot(this.rank),n=`uniform int start[${this.rank}];`,r=KB(this.rank),a,s=e.map((i,o)=>`sourceLoc.${fA[o]} = start[${o}] + coords.${fA[o]};`);a=`
         ${t} sourceLoc;
         ${t} coords = getOutputCoords();
         ${s.join(`
@@ -1772,7 +1772,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         ${a}
         setOutput(getSource(${r}));
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}},uA=["x","y","z","w","u","v"];function mW(e){if(e===1)return"sourceLoc";if(e<=6)return uA.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var yW=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=ot(this.rank),n=dn("coords",this.rank),r=dn("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${r.slice(-2).join()})`,s=`getChannel(getSource(${r.join()}), ${a})`,i=`
+    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}},fA=["x","y","z","w","u","v"];function KB(e){if(e===1)return"sourceLoc";if(e<=6)return fA.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var YB=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=ot(this.rank),n=dn("coords",this.rank),r=dn("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${r.slice(-2).join()})`,s=`getChannel(getSource(${r.join()}), ${a})`,i=`
       result.x = ${s};
       if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
         ++${r[this.rank-1]};
@@ -1802,7 +1802,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         ${o}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function gW(e,t,n,r){let a=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=ln.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,l+1),s}function mc(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=ln.parseSliceParams(a,s,i);if(ln.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,a.dtype,[]);if(n.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=n.texData.get(a.dataId),d=dP(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:c}=n.texData.get(a.dataId),u=ln.isSliceContinous(a.shape,o,l);if(c||!u){let h=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new yW(l):new AW(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),gW(a,o,l,n)}var xW={kernelName:Bo,backendName:"webgl",kernelFunc:mc},wW=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((g,w)=>g*w),l=R.getReshaped(a.shape,s,o),c=R.getPermuted(l.length,s.length),u=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(u,i,s.length),p=[],f=xe({inputs:{x:a},backend:n,attrs:{shape:l}}),m=In({inputs:{x:f},backend:n,attrs:{perm:c}}),A=xe({inputs:{x:m},backend:n,attrs:{shape:u}}),y=mc({inputs:{x:A},backend:n,attrs:{begin:h,size:d}});return p.push(f),p.push(m),p.push(A),p.forEach(g=>n.disposeIntermediateTensorInfo(g)),y},bW={kernelName:fu,backendName:"webgl",kernelFunc:wW};function _W(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.readSync(a.dataId),l=n.readSync(s.dataId),c=Mb(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var vW={kernelName:Ch,backendName:"webgl",kernelFunc:_W},kW="return float(a != b);",i_=tn({opSnippet:kW,dtype:"bool"}),IW={kernelName:Eo,backendName:"webgl",kernelFunc:i_};function Ac(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return On({inputs:{x:a.complexTensorInfos.real},backend:n})}var NW={kernelName:Yh,backendName:"webgl",kernelFunc:Ac},SW="return float(int(x));";function TW(e,t){let n=new La(e.shape,SW),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function cA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return On({inputs:{x:a},backend:n});let i=Et(a.shape),o=cA({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Wa({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=Ac({inputs:{input:a},backend:n}),o=cA({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=On({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return TW(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=i_({inputs:{a,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var EW={kernelName:cs,backendName:"webgl",kernelFunc:cA},o_="return ceil(x);",CW=Xe({opSnippet:o_,packedOpSnippet:o_,cpuKernelImpl:Xz}),RW={kernelName:hs,backendName:"webgl",kernelFunc:CW},MW=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function JB(e,t,n,r){let a=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=ln.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,l+1),s}function mc(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=ln.parseSliceParams(a,s,i);if(ln.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,a.dtype,[]);if(n.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=n.texData.get(a.dataId),d=GL(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:c}=n.texData.get(a.dataId),u=ln.isSliceContinous(a.shape,o,l);if(c||!u){let h=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new YB(l):new ZB(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),JB(a,o,l,n)}var QB={kernelName:Bo,backendName:"webgl",kernelFunc:mc},eV=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((g,b)=>g*b),l=R.getReshaped(a.shape,s,o),c=R.getPermuted(l.length,s.length),u=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(u,i,s.length),p=[],f=xe({inputs:{x:a},backend:n,attrs:{shape:l}}),m=In({inputs:{x:f},backend:n,attrs:{perm:c}}),A=xe({inputs:{x:m},backend:n,attrs:{shape:u}}),y=mc({inputs:{x:A},backend:n,attrs:{begin:h,size:d}});return p.push(f),p.push(m),p.push(A),p.forEach(g=>n.disposeIntermediateTensorInfo(g)),y},tV={kernelName:fu,backendName:"webgl",kernelFunc:eV};function nV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.readSync(a.dataId),l=n.readSync(s.dataId),c=d3(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var rV={kernelName:Ch,backendName:"webgl",kernelFunc:nV},aV="return float(a != b);",W3=tn({opSnippet:aV,dtype:"bool"}),sV={kernelName:Eo,backendName:"webgl",kernelFunc:W3};function Ac(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return On({inputs:{x:a.complexTensorInfos.real},backend:n})}var iV={kernelName:Yh,backendName:"webgl",kernelFunc:Ac},oV="return float(int(x));";function lV(e,t){let n=new La(e.shape,oV),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function mA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return On({inputs:{x:a},backend:n});let i=Et(a.shape),o=mA({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Wa({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=Ac({inputs:{input:a},backend:n}),o=mA({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=On({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return lV(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=W3({inputs:{a,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var uV={kernelName:cs,backendName:"webgl",kernelFunc:mA},B3="return ceil(x);",cV=Xe({opSnippet:B3,packedOpSnippet:B3,cpuKernelImpl:TL}),hV={kernelName:hs,backendName:"webgl",kernelFunc:cV},dV=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1815,7 +1815,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
 
         setOutput(clamp(value, minVal, maxVal));
       }
-    `}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}},FW=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}},pV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1829,7 +1829,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
 
         setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
       }
-    `}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}};function $W(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o;J().getBool("WEBGL_PACK_CLIP")?o=new FW(a.shape):o=new MW(a.shape);let l=o.getCustomSetupFunc(s,i);return n.runWebGLProgram(o,[a],a.dtype,l)}var DW={kernelName:ka,backendName:"webgl",kernelFunc:$W},OW=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}};function fV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o;J().getBool("WEBGL_PACK_CLIP")?o=new pV(a.shape):o=new dV(a.shape);let l=o.getCustomSetupFunc(s,i);return n.runWebGLProgram(o,[a],a.dtype,l)}var mV={kernelName:ka,backendName:"webgl",kernelFunc:fV},AV=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
       void main() {
         float re = abs(getRealAtOutCoords());
         float im = abs(getImagAtOutCoords());
@@ -1842,7 +1842,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
           mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
         );
       }
-    `}};function l_(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function zW(e){let{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),s=new OW(r.shape),i=[l_(r,a.complexTensorInfos.real),l_(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var PW={kernelName:mu,backendName:"webgl",kernelFunc:zW},LW=class{constructor(e){this.outputShape=[],this.outputShape=R.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let r=t.length,a=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${a}));`),this.userCode=`
+    `}};function V3(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function yV(e){let{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),s=new AV(r.shape),i=[V3(r,a.complexTensorInfos.real),V3(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var gV={kernelName:mu,backendName:"webgl",kernelFunc:yV},xV=class{constructor(e){this.outputShape=[],this.outputShape=R.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let r=t.length,a=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${a}));`),this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int yR = coords.x;
@@ -1851,7 +1851,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         ${n.join(`
         `)}
       }
-    `}},WW=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=R.computeOutShape(e,t);let n=this.outputShape,r=n.length,a=ot(r),s=dn("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],c=i.slice(-2),u=i.join(),h=`if (${l} < ${o[0]}) {
+    `}},bV=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=R.computeOutShape(e,t);let n=this.outputShape,r=n.length,a=ot(r),s=dn("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],c=i.slice(-2),u=i.join(),h=`if (${l} < ${o[0]}) {
         return getChannel(
             getT0(${u}), vec2(${c.join()}));
         }`;for(let f=1;f<o.length;f++){let m=o[f-1];h+=`
@@ -1888,18 +1888,18 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         }
         setOutput(result);
       }
-    `}};function xp(e,t,n){let r=e.indexOf(t);return e.map((a,s)=>s===r?`${a} - ${n}`:a).join()}function wp(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return On({inputs:{x:a.complexTensorInfos.imag},backend:n})}var BW={kernelName:jh,backendName:"webgl",kernelFunc:wp};function Fl(e,t,n){let r=e[0].dtype;if(r==="complex64"){let c=e.map(f=>Ac({inputs:{input:f},backend:n})),u=e.map(f=>wp({inputs:{input:f},backend:n})),h=Fl(c,t,n),d=Fl(u,t,n),p=Wa({inputs:{real:h,imag:d},backend:n});return c.forEach(f=>n.disposeIntermediateTensorInfo(f)),u.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),p}if(r==="string"){let{tensors2D:c,outShape:u}=u_(e,t,n),h=c.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),d=c[0].shape[0]===1,p=Kz(h,u,r,d),f=R.computeOutShape(e.map(A=>A.shape),t),m=n.makeTensorInfo(f,r,p);return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),m}if(e.length>J().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let c=Math.floor(e.length/2),u=Fl(e.slice(0,c),t,n),h=Fl(e.slice(c),t,n),d=Fl([u,h],t,n);return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),d}if(J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let c=new WW(e.map(u=>u.shape),t);return n.runWebGLProgram(c,e,r)}let{tensors2D:a,outShape:s}=u_(e,t,n),i=new LW(a.map(c=>c.shape)),o=n.runWebGLProgram(i,a,r);a.forEach(c=>n.disposeIntermediateTensorInfo(c));let l=xe({inputs:{x:o},attrs:{shape:s},backend:n});return n.disposeIntermediateTensorInfo(o),l}function u_(e,t,n){let r=R.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>xe({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function c_(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(c=>c.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(c=>v.sizeFromShape(c.shape)>0);if(o.length===1)return On({inputs:{x:o[0]},backend:n});let l=o.map(c=>c.shape);return R.assertParamsConsistent(l,s),Fl(o,s,n)}var VW={kernelName:io,backendName:"webgl",kernelFunc:c_},h_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,c=e.dilationHeight,u=e.dilationWidth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",A=m?1:2,y=m?2:3,g=m?3:1,w="",b="";n&&(r?w=`float activation(float a) {
+    `}};function xp(e,t,n){let r=e.indexOf(t);return e.map((a,s)=>s===r?`${a} - ${n}`:a).join()}function bp(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return On({inputs:{x:a.complexTensorInfos.imag},backend:n})}var wV={kernelName:Uh,backendName:"webgl",kernelFunc:bp};function Fl(e,t,n){let r=e[0].dtype;if(r==="complex64"){let c=e.map(f=>Ac({inputs:{input:f},backend:n})),u=e.map(f=>bp({inputs:{input:f},backend:n})),h=Fl(c,t,n),d=Fl(u,t,n),p=Wa({inputs:{real:h,imag:d},backend:n});return c.forEach(f=>n.disposeIntermediateTensorInfo(f)),u.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),p}if(r==="string"){let{tensors2D:c,outShape:u}=j3(e,t,n),h=c.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),d=c[0].shape[0]===1,p=EL(h,u,r,d),f=R.computeOutShape(e.map(A=>A.shape),t),m=n.makeTensorInfo(f,r,p);return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),m}if(e.length>J().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let c=Math.floor(e.length/2),u=Fl(e.slice(0,c),t,n),h=Fl(e.slice(c),t,n),d=Fl([u,h],t,n);return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),d}if(J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let c=new bV(e.map(u=>u.shape),t);return n.runWebGLProgram(c,e,r)}let{tensors2D:a,outShape:s}=j3(e,t,n),i=new xV(a.map(c=>c.shape)),o=n.runWebGLProgram(i,a,r);a.forEach(c=>n.disposeIntermediateTensorInfo(c));let l=xe({inputs:{x:o},attrs:{shape:s},backend:n});return n.disposeIntermediateTensorInfo(o),l}function j3(e,t,n){let r=R.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>xe({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function U3(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(c=>c.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(c=>v.sizeFromShape(c.shape)>0);if(o.length===1)return On({inputs:{x:o[0]},backend:n});let l=o.map(c=>c.shape);return R.assertParamsConsistent(l,s),Fl(o,s,n)}var _V={kernelName:io,backendName:"webgl",kernelFunc:U3},H3=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,c=e.dilationHeight,u=e.dilationWidth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",A=m?1:2,y=m?2:3,g=m?3:1,b="",w="";n&&(r?b=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${n}
-        }`:a?w=`float activation(float a) {
+        }`:a?b=`float activation(float a) {
           float b = getLeakyreluAlphaAtOutCoords();
           ${n}
-        }`:w=`
+        }`:b=`
           float activation(float x) {
             ${n}
           }
-        `,b="result = activation(result);");let _=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
-      ${w}
+        `,w="result = activation(result);");let _=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
+      ${b}
 
       const ivec2 strides = ivec2(${o}, ${l});
       const ivec2 pads = ivec2(${s}, ${i});
@@ -2019,10 +2019,10 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
 
         float result = dotProd;
         ${_}
-        ${b}
+        ${w}
         setOutput(result);
       }
-    `}},UW=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
+    `}},vV=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
       const ivec3 strides = ivec3(${a}, ${s}, ${i});
       const ivec3 pads = ivec3(${t}, ${n}, ${r});
 
@@ -2110,9 +2110,9 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},jW=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:a,strideWidth:s,strideHeight:i,padInfo:o,outWidth:l,dilationWidth:c,dilationHeight:u,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=hn(),A=h==="channelsLast",y=A?0:1,g=A?1:2,w="";for(let b=0;b<=1;b++)for(let _=0;_<=1;_++)w+=`
+    `}},kV=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:a,strideWidth:s,strideHeight:i,padInfo:o,outWidth:l,dilationWidth:c,dilationHeight:u,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=hn(),A=h==="channelsLast",y=A?0:1,g=A?1:2,b="";for(let w=0;w<=1;w++)for(let _=0;_<=1;_++)b+=`
           blockIndex = rc.y + ${_};
-          pos = rc.x + ${b};
+          pos = rc.x + ${w};
 
           if(blockIndex < ${e[1]} && pos < ${e[0]}) {
             offsetY = int(blockIndex / (${l})) * ${i} - ${p};
@@ -2129,12 +2129,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
 
                 if (${A}) {
                   innerDims = vec2(d1, ch);
-                  result[${b*2+_}] = getChannel(
+                  result[${w*2+_}] = getChannel(
                     getA(d0, int(innerDims.x),
                     int(innerDims.y)), innerDims);
                 } else {
                   innerDims = vec2(d0, d1);
-                  result[${b*2+_}] = getChannel(
+                  result[${w*2+_}] = getChannel(
                     getA(ch, int(innerDims.x),
                     int(innerDims.y)), innerDims);
                 }
@@ -2150,11 +2150,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
         vec2 innerDims;
 
-        ${w}
+        ${b}
 
         ${m.output} = result;
       }
-    `}};function d_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,c=r.texData.get(e.dataId),u=n.inChannels,h=l[0]*l[1]*l[2],d=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,A,y=[],g=(h===1||d===1)&&u>e_,w=l[2]%2!=0&&!!c.isPacked;if(g||!J().getBool("WEBGL_LAZILY_UNPACK")||!J().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let b=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=xe({inputs:{x:e},backend:r,attrs:{shape:[1,b,n.inChannels]}}),x=xe({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),N=yp({a:_,b:x,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=xe({inputs:{x:N},backend:r,attrs:{shape:n.outShape}}),y.push(_),y.push(x),y.push(N)}else{let b=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},x=c.shape;c.shape=c.shape.slice(),c.shape[c.shape.length-2]++,v.assert(lc(c.shape,_.shape),()=>`packed reshape ${c.shape} to ${_.shape} isn't free`);let N=xe({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(N);let T=yp({a:_,b:N,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),E=r.texData.get(T.dataId);v.assert(E.isPacked,()=>"batchMatMul result is expected to be packed"),c.shape=x,E.shape=n.outShape,A=On({inputs:{x:T},backend:r}),A.shape=n.outShape,y.push(T)}for(let b of y)r.disposeIntermediateTensorInfo(b);return A}function p_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:c,inChannels:u,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*c*u,A=d*h,y=[m,A],g=!0,w=!1,b=[],_=xe({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),x=xe({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(_),b.push(x);let N=new jW(y,_.shape,n),T=r.runWebGLProgram(N,[_],"float32"),E=xe({inputs:{x:T},backend:r,attrs:{shape:[1,y[0],y[1]]}});b.push(T),b.push(E);let F=a!=null,D=s!=null,L=o==="leakyrelu",V=o?mp(o,!0):null,U=new Xb(E.shape,x.shape,[1,A,n.outChannels],g,w,F,V,D,L),j=[E,x];if(a&&j.push(a),D&&j.push(s),L){let Y=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));j.push(Y),b.push(Y)}let X=r.runWebGLProgram(U,j,"float32"),G=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=xe({inputs:{x:X},backend:r,attrs:{shape:G}});b.push(X);for(let Y of b)r.disposeIntermediateTensorInfo(Y);return ee}function HW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!1,h),p;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"))p=d_({x:a,filter:s,convInfo:d,backend:n});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=p_({x:a,filter:s,convInfo:d,backend:n});else{let m=new h_(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=xe({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var GW={kernelName:ds,backendName:"webgl",kernelFunc:HW},qW=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
+    `}};function G3({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,c=r.texData.get(e.dataId),u=n.inChannels,h=l[0]*l[1]*l[2],d=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,A,y=[],g=(h===1||d===1)&&u>D3,b=l[2]%2!=0&&!!c.isPacked;if(g||!J().getBool("WEBGL_LAZILY_UNPACK")||!J().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!b){let w=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=xe({inputs:{x:e},backend:r,attrs:{shape:[1,w,n.inChannels]}}),x=xe({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),N=yp({a:_,b:x,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=xe({inputs:{x:N},backend:r,attrs:{shape:n.outShape}}),y.push(_),y.push(x),y.push(N)}else{let w=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:e.dataId,shape:[1,w,n.inChannels],dtype:e.dtype},x=c.shape;c.shape=c.shape.slice(),c.shape[c.shape.length-2]++,v.assert(lc(c.shape,_.shape),()=>`packed reshape ${c.shape} to ${_.shape} isn't free`);let N=xe({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(N);let T=yp({a:_,b:N,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),E=r.texData.get(T.dataId);v.assert(E.isPacked,()=>"batchMatMul result is expected to be packed"),c.shape=x,E.shape=n.outShape,A=On({inputs:{x:T},backend:r}),A.shape=n.outShape,y.push(T)}for(let w of y)r.disposeIntermediateTensorInfo(w);return A}function q3({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:c,inChannels:u,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*c*u,A=d*h,y=[m,A],g=!0,b=!1,w=[],_=xe({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),x=xe({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});w.push(_),w.push(x);let N=new kV(y,_.shape,n),T=r.runWebGLProgram(N,[_],"float32"),E=xe({inputs:{x:T},backend:r,attrs:{shape:[1,y[0],y[1]]}});w.push(T),w.push(E);let F=a!=null,$=s!=null,L=o==="leakyrelu",V=o?mp(o,!0):null,j=new T3(E.shape,x.shape,[1,A,n.outChannels],g,b,F,V,$,L),U=[E,x];if(a&&U.push(a),$&&U.push(s),L){let Y=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));U.push(Y),w.push(Y)}let X=r.runWebGLProgram(j,U,"float32"),G=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=xe({inputs:{x:X},backend:r,attrs:{shape:G}});w.push(X);for(let Y of w)r.disposeIntermediateTensorInfo(Y);return ee}function IV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!1,h),p;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"))p=G3({x:a,filter:s,convInfo:d,backend:n});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=q3({x:a,filter:s,convInfo:d,backend:n});else{let m=new H3(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=xe({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var NV={kernelName:ds,backendName:"webgl",kernelFunc:IV},SV=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2196,7 +2196,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},XW=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,c=s?2:3,u=s?3:1;this.userCode=`
+    `}},TV=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,c=s?2:3,u=s?3:1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${o});
 
       void main() {
@@ -2249,7 +2249,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},KW=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
+    `}},EV=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
       void main() {
         ivec5 coords = getOutputCoords();
         int wF = coords.x;
@@ -2291,7 +2291,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},ZW=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,c=r-1-e.padInfo.left;this.userCode=`
+    `}},CV=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,c=r-1-e.padInfo.left;this.userCode=`
       const ivec3 pads = ivec3(${o}, ${l}, ${c});
 
       void main() {
@@ -2348,12 +2348,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function YW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:c,filterShape:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,u,i,1,o,c,!1,h),p=new qW(d);return n.runWebGLProgram(p,[a,s],"float32")}var JW={kernelName:Mh,backendName:"webgl",kernelFunc:YW};function QW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(c),d=R.computeConv2DInfo(i,s.shape,o,1,l,u,!1,h),p=new XW(d);return n.runWebGLProgram(p,[a,s],"float32")}var eB={kernelName:ps,backendName:"webgl",kernelFunc:QW};function tB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeConv3DInfo(a.shape,s.shape,i,l,o),u=new UW(c);return n.runWebGLProgram(u,[a,s],"float32")}var nB={kernelName:Au,backendName:"webgl",kernelFunc:tB};function rB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,c=R.computeConv3DInfo(a.shape,l,i,1,o),u=new KW(c);return n.runWebGLProgram(u,[a,s],"float32")}var aB={kernelName:Fh,backendName:"webgl",kernelFunc:rB};function sB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,c=R.computeConv3DInfo(l,s.shape,o,1,i),u=new ZW(c);return n.runWebGLProgram(u,[a,s],"float32")}var iB={kernelName:$h,backendName:"webgl",kernelFunc:sB},oB=qb+`
+    `}};function RV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:c,filterShape:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,u,i,1,o,c,!1,h),p=new SV(d);return n.runWebGLProgram(p,[a,s],"float32")}var MV={kernelName:Mh,backendName:"webgl",kernelFunc:RV};function FV(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(c),d=R.computeConv2DInfo(i,s.shape,o,1,l,u,!1,h),p=new TV(d);return n.runWebGLProgram(p,[a,s],"float32")}var DV={kernelName:ps,backendName:"webgl",kernelFunc:FV};function $V(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeConv3DInfo(a.shape,s.shape,i,l,o),u=new vV(c);return n.runWebGLProgram(u,[a,s],"float32")}var OV={kernelName:Au,backendName:"webgl",kernelFunc:$V};function zV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,c=R.computeConv3DInfo(a.shape,l,i,1,o),u=new EV(c);return n.runWebGLProgram(u,[a,s],"float32")}var PV={kernelName:Fh,backendName:"webgl",kernelFunc:zV};function LV(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,c=R.computeConv3DInfo(l,s.shape,o,1,i),u=new CV(c);return n.runWebGLProgram(u,[a,s],"float32")}var WV={kernelName:Dh,backendName:"webgl",kernelFunc:LV},BV=S3+`
   return cos(x);
-`,lB=Xe({opSnippet:oB}),uB={kernelName:fs,backendName:"webgl",kernelFunc:lB},cB=`
+`,VV=Xe({opSnippet:BV}),jV={kernelName:fs,backendName:"webgl",kernelFunc:VV},UV=`
   float e2x = exp(-x);
   return (e2x + 1.0 / e2x) / 2.0;
-`,hB=Xe({opSnippet:cB}),dB={kernelName:oo,backendName:"webgl",kernelFunc:hB},pB=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[c]=t,[u,h]=n;this.outputShape=[c,u,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=u>1?[`${(i-1)/(u-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,w,b]=h>1?[`${(o-1)/(h-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
+`,HV=Xe({opSnippet:UV}),GV={kernelName:oo,backendName:"webgl",kernelFunc:HV},qV=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[c]=t,[u,h]=n;this.outputShape=[c,u,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=u>1?[`${(i-1)/(u-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,b,w]=h>1?[`${(o-1)/(h-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(${g});
       void main() {
@@ -2376,14 +2376,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         }
 
         float height_scale = ${A};
-        float width_scale = ${w};
+        float width_scale = ${b};
 
         float in_y = ${y};
         if( in_y < 0.0 || in_y > ${p} ) {
           setOutput(float(${a}));
           return;
         }
-        float in_x = ${b};
+        float in_x = ${w};
         if( in_x < 0.0 || in_x > ${f} ) {
           setOutput(float(${a}));
           return;
@@ -2414,21 +2414,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
           setOutput(newValue);
         }
       }
-    `}},fB=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:c}=r,u=new pB(a.shape,s.shape,o,l,c);return n.runWebGLProgram(u,[a,s,i],"float32")},mB={kernelName:lo,backendName:"webgl",kernelFunc:fB},A_=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${f_(r,"coords")})`,s=e[e.length-1],i="",o="";t?(i=n?`end != ${s-1}`:"end != 0",o=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${s}`:"end >= pow2",o=n?"end + pow2":"end - pow2"),this.userCode=`
+    `}},XV=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:c}=r,u=new qV(a.shape,s.shape,o,l,c);return n.runWebGLProgram(u,[a,s,i],"float32")},KV={kernelName:lo,backendName:"webgl",kernelFunc:XV},Z3=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${X3(r,"coords")})`,s=e[e.length-1],i="",o="";t?(i=n?`end != ${s-1}`:"end != 0",o=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${s}`:"end >= pow2",o=n?"end + pow2":"end - pow2"),this.userCode=`
       uniform float index;
       void main() {
         ${ot(r)} coords = getOutputCoords();
-        int end = ${m_(r,"coords")};
+        int end = ${K3(r,"coords")};
         float val = ${a};
         int pow2 = int(pow(2.0, index));
         if (${i}) {
           int idx = ${o};
-          ${m_(r,"coords")} = idx;
-          val += getX(${f_(r,"coords")});
+          ${K3(r,"coords")} = idx;
+          val += getX(${X3(r,"coords")});
         }
         setOutput(val);
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.index==null&&(this.index=t.getUniformLocation(n,"index")),t.gl.uniform1f(this.index,e)}}};function f_(e,t){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 sum for rank ${e} is not yet supported`)}function m_(e,t){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative sum for rank ${e} is not yet supported`)}function AB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,c=R.getAxesPermutation([s],l),u=a;c!=null&&(u=In({inputs:{x:a},backend:n,attrs:{perm:c}}));let h=R.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=u.shape[h],p=On({inputs:{x:u},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new A_(u.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new A_(u.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(c!=null){let f=R.getUndoAxesPermutation(c),m=In({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(u),m}return p}var yB={kernelName:ms,backendName:"webgl",kernelFunc:AB};function gB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),c=n.readSync(s.dataId),u=Mb(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=qz(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var xB={kernelName:Dh,backendName:"webgl",kernelFunc:gB},wB=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=n,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.index==null&&(this.index=t.getUniformLocation(n,"index")),t.gl.uniform1f(this.index,e)}}};function X3(e,t){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 sum for rank ${e} is not yet supported`)}function K3(e,t){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative sum for rank ${e} is not yet supported`)}function ZV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,c=R.getAxesPermutation([s],l),u=a;c!=null&&(u=In({inputs:{x:a},backend:n,attrs:{perm:c}}));let h=R.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=u.shape[h],p=On({inputs:{x:u},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new Z3(u.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new Z3(u.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(c!=null){let f=R.getUndoAxesPermutation(c),m=In({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(u),m}return p}var YV={kernelName:ms,backendName:"webgl",kernelFunc:ZV};function JV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),c=n.readSync(s.dataId),u=d3(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=SL(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var QV={kernelName:$h,backendName:"webgl",kernelFunc:JV},ej=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];
@@ -2447,7 +2447,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
       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 bB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],c=i==="NHWC"?a.shape[2]:a.shape[3],u=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=c*s,p=u/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new wB(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var _B={kernelName:uo,backendName:"webgl",kernelFunc:bB},y_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,A="",y="";n&&(r?A=`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 tj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],c=i==="NHWC"?a.shape[2]:a.shape[3],u=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=c*s,p=u/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new ej(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var nj={kernelName:uo,backendName:"webgl",kernelFunc:tj},Y3=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,A="",y="";n&&(r?A=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:a?A=`float activation(float a) {
@@ -2503,24 +2503,24 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         ${y}
         setOutput(result);
       }
-    `}},g_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let b=0;b<p;b++)for(let _=0;_<f;_++)A+=`
-          vec4 xTexelR${b}C${_*2} = vec4(0.);
-          vec4 wR${b}C${_} = vec4(0.);
-          vec4 xR${b}C${_} = vec4(0.);`;for(let b=0;b<p;b++)for(let _=0;_<m;_++){let x=_*2;if(A+=`
-          xR = xRCorner + ${b*h};
+    `}},J3=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let w=0;w<p;w++)for(let _=0;_<f;_++)A+=`
+          vec4 xTexelR${w}C${_*2} = vec4(0.);
+          vec4 wR${w}C${_} = vec4(0.);
+          vec4 xR${w}C${_} = vec4(0.);`;for(let w=0;w<p;w++)for(let _=0;_<m;_++){let x=_*2;if(A+=`
+          xR = xRCorner + ${w*h};
           xC = xCCorner + ${x*d};
         `,u===1){if(x<f&&(l%2==1?A+=`
                 xCOffset = xC + 1;
                 if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) {
-                  xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1);
+                  xTexelR${w}C${x} = getX(batch, xR, xCOffset, d1);
 
                   // Need to manually clear unused channels in case
                   // we're reading from recycled texture.
                   if(xCOffset + 1 >= ${i}) {
-                    xTexelR${b}C${x}.zw = vec2(0.);
+                    xTexelR${w}C${x}.zw = vec2(0.);
                   }
                 } else {
-                  xTexelR${b}C${x} = vec4(0.);
+                  xTexelR${w}C${x} = vec4(0.);
                 }
 
                 xCOffset = xC + 1 - 2;
@@ -2533,96 +2533,96 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
                     previous.zw = vec2(0.);
                   }
 
-                  xR${b}C${x} = vec4(previous.zw, xTexelR${b}C${x}.xy);
+                  xR${w}C${x} = vec4(previous.zw, xTexelR${w}C${x}.xy);
                 } else {
-                  xR${b}C${x} = vec4(0, 0, xTexelR${b}C${x}.xy);
+                  xR${w}C${x} = vec4(0, 0, xTexelR${w}C${x}.xy);
                 }
               `:A+=`
                 if(xR >= 0 && xR < ${s} && xC >= 0 && xC < ${i}) {
-                  xTexelR${b}C${x} = getX(batch, xR, xC, d1);
+                  xTexelR${w}C${x} = getX(batch, xR, xC, d1);
                 } else {
-                  xTexelR${b}C${x} = vec4(0.);
+                  xTexelR${w}C${x} = vec4(0.);
                 }
 
-                xR${b}C${x} = xTexelR${b}C${x};
+                xR${w}C${x} = xTexelR${w}C${x};
               `,x+1<f)){let N=l%2==0?v.nearestLargerEven(d):d;d%2==0&&l%2==1||d%2!=0&&l%2!=1?(A+=`
                   xCOffset = xC + ${l%2} + ${N};
 
                   if(xR >= 0 && xR < ${s} &&
                     xCOffset >= 0 && xCOffset < ${i}) {
-                    xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1);
+                    xTexelR${w}C${x+2} = getX(batch, xR, xCOffset, d1);
                   }
                 `,d>1&&(A+=`
                     xCOffset -= 2;
                     if(xR >= 0 && xR < ${s} &&
                       xCOffset >= 0 && xCOffset < ${i}) {
-                      xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1);
+                      xTexelR${w}C${x} = getX(batch, xR, xCOffset, d1);
                     } else {
-                      xTexelR${b}C${x} = vec4(0.);
+                      xTexelR${w}C${x} = vec4(0.);
                     }
                   `),A+=`
-                  xR${b}C${x+1} = vec4(
-                    xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.xy);
+                  xR${w}C${x+1} = vec4(
+                    xTexelR${w}C${x}.zw, xTexelR${w}C${x+2}.xy);
                 `):A+=`
                   xCOffset = xC + ${N};
 
                   if(xR >= 0 && xR < ${s} &&
                     xCOffset >= 0 && xCOffset < ${i}) {
-                    xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1);
+                    xTexelR${w}C${x+2} = getX(batch, xR, xCOffset, d1);
                   }
 
-                  xR${b}C${x+1} = xTexelR${b}C${x+2};
+                  xR${w}C${x+1} = xTexelR${w}C${x+2};
                 `}}else x<f&&(A+=`
               if(xR >= 0 && xR < ${s}) {
             `,l%2==1?(A+=`
                 xCOffset = xC + 1 - ${u};
                 if(xCOffset >= 0 && xCOffset < ${i}) {
-                  xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1);
+                  xTexelR${w}C${x} = getX(batch, xR, xCOffset, d1);
                 } else {
-                  xTexelR${b}C${x} = vec4(0.);
+                  xTexelR${w}C${x} = vec4(0.);
                 }
 
                 if(xC + 1 >= 0 && xC + 1 < ${i}) {
-                  xTexelR${b}C${x+2} = getX(batch, xR, xC + 1, d1);
+                  xTexelR${w}C${x+2} = getX(batch, xR, xC + 1, d1);
                 } else {
-                  xTexelR${b}C${x+2} = vec4(0.);
+                  xTexelR${w}C${x+2} = vec4(0.);
                 }
 
-                xR${b}C${x} = vec4(
-                  xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.zw);
+                xR${w}C${x} = vec4(
+                  xTexelR${w}C${x}.zw, xTexelR${w}C${x+2}.zw);
               `,x+1<f&&(A+=`
                   vec4 final = vec4(0.);
                   xCOffset = xC + 1 + ${u};
                   if(xCOffset >= 0 && xCOffset < ${i}) {
                     final = getX(batch, xR, xCOffset, d1);
                   }
-                  xR${b}C${x+1} = vec4(xTexelR${b}C${x+2}.xy, final.xy);
+                  xR${w}C${x+1} = vec4(xTexelR${w}C${x+2}.xy, final.xy);
                 `)):(A+=`
                 if(xC >= 0 && xC < ${i}) {
-                  xTexelR${b}C${x} = getX(batch, xR, xC, d1);
+                  xTexelR${w}C${x} = getX(batch, xR, xC, d1);
                 } else {
-                  xTexelR${b}C${x} = vec4(0.);
+                  xTexelR${w}C${x} = vec4(0.);
                 }
 
                 xCOffset = xC + ${u};
                 if(xCOffset >= 0 && xCOffset < ${i}) {
-                  xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1);
+                  xTexelR${w}C${x+2} = getX(batch, xR, xCOffset, d1);
                 } else {
-                  xTexelR${b}C${x+2} = vec4(0.);
+                  xTexelR${w}C${x+2} = vec4(0.);
                 }
 
-                xR${b}C${x} = vec4(
-                  xTexelR${b}C${x}.xy, xTexelR${b}C${x+2}.xy);
+                xR${w}C${x} = vec4(
+                  xTexelR${w}C${x}.xy, xTexelR${w}C${x+2}.xy);
               `,x+1<f&&(A+=`
-                  xR${b}C${x+1} = vec4(
-                    xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.zw);
+                  xR${w}C${x+1} = vec4(
+                    xTexelR${w}C${x}.zw, xTexelR${w}C${x+2}.zw);
                 `)),A+="}");x<f&&(A+=`
-            vec4 wTexelR${b}C${x} = getW(${b}, ${x}, d1, q);
-            wR${b}C${x} = vec4(wTexelR${b}C${x}.xz, wTexelR${b}C${x}.xz);
+            vec4 wTexelR${w}C${x} = getW(${w}, ${x}, d1, q);
+            wR${w}C${x} = vec4(wTexelR${w}C${x}.xz, wTexelR${w}C${x}.xz);
           `,x+1<f&&(A+=`
-              vec4 wTexelR${b}C${x+1} = getW(${b}, ${x+1}, d1, q);
-              wR${b}C${x+1} =
-                vec4(wTexelR${b}C${x+1}.xz, wTexelR${b}C${x+1}.xz);`))}for(let b=0;b<p;b++)for(let _=0;_<f;_++)A+=`dotProd += xR${b}C${_} * wR${b}C${_};`;let y="",g="";n&&(r?y=`vec4 activation(vec4 a) {
+              vec4 wTexelR${w}C${x+1} = getW(${w}, ${x+1}, d1, q);
+              wR${w}C${x+1} =
+                vec4(wTexelR${w}C${x+1}.xz, wTexelR${w}C${x+1}.xz);`))}for(let w=0;w<p;w++)for(let _=0;_<f;_++)A+=`dotProd += xR${w}C${_} * wR${w}C${_};`;let y="",g="";n&&(r?y=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:a?y=`vec4 activation(vec4 a) {
@@ -2630,7 +2630,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
           ${n}
         }`:y=`vec4 activation(vec4 x) {
           ${n}
-        }`,g="result = activation(result);");let w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
+        }`,g="result = activation(result);");let b=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
       ${y}
 
       const ivec2 strides = ivec2(${c}, ${u});
@@ -2652,11 +2652,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         ${A}
 
         vec4 result = dotProd;
-        ${w}
+        ${b}
         ${g}
         setOutput(result);
       }
-    `}};function vB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:c}=r,u=l;u==null&&(u=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let h=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!0),d;return J().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new g_(h):d=new y_(h),n.runWebGLProgram(d,[a,s],"float32")}var kB={kernelName:As,backendName:"webgl",kernelFunc:vB},IB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
+    `}};function rj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:c}=r,u=l;u==null&&(u=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let h=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!0),d;return J().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new J3(h):d=new Y3(h),n.runWebGLProgram(d,[a,s],"float32")}var aj={kernelName:As,backendName:"webgl",kernelFunc:rj},sj=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2691,7 +2691,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},NB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
+    `}},ij=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
       const ivec2 pads = ivec2(${s}, ${i});
 
       void main() {
@@ -2736,13 +2736,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function SB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,filterShape:u}=r,h=R.computeConv2DInfo(a.shape,u,i,o,l,c,!0),d=new IB(h);return n.runWebGLProgram(d,[a,s],"float32")}var TB={kernelName:Oh,backendName:"webgl",kernelFunc:SB};function EB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r,h=R.computeConv2DInfo(u,s.shape,i,o,l,c,!0),d=new NB(h);return n.runWebGLProgram(d,[a,s],"float32")}var CB={kernelName:zh,backendName:"webgl",kernelFunc:EB},RB=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
+    `}};function oj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,filterShape:u}=r,h=R.computeConv2DInfo(a.shape,u,i,o,l,c,!0),d=new sj(h);return n.runWebGLProgram(d,[a,s],"float32")}var lj={kernelName:Oh,backendName:"webgl",kernelFunc:oj};function uj(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r,h=R.computeConv2DInfo(u,s.shape,i,o,l,c,!0),d=new ij(h);return n.runWebGLProgram(d,[a,s],"float32")}var cj={kernelName:zh,backendName:"webgl",kernelFunc:uj},hj=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 MB(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=xe({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new RB(s),l=n.runWebGLProgram(o,[i],i.dtype),c=xe({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),c}var FB={kernelName:Ph,backendName:"webgl",kernelFunc:MB},$B=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:c}=e,{top:u,left:h}=r;this.userCode=`
+    `}};function dj(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=xe({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new hj(s),l=n.runWebGLProgram(o,[i],i.dtype),c=xe({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),c}var pj={kernelName:Ph,backendName:"webgl",kernelFunc:dj},fj=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:c}=e,{top:u,left:h}=r;this.userCode=`
       const ivec2 strides = ivec2(${a}, ${s});
       const ivec2 pads = ivec2(${u}, ${h});
       const float neg_infinity = -3.4e38;
@@ -2780,7 +2780,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         float result = curVal;
         setOutput(result);
       }
-    `}};function DB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),u,h=new $B(c);u=n.runWebGLProgram(h,[a,s],"float32");let d=xe({inputs:{x:u},backend:n,attrs:{shape:c.outShape}});return n.disposeIntermediateTensorInfo(u),d}var OB={kernelName:yu,backendName:"webgl",kernelFunc:DB},zB="return (x >= 0.0) ? x : (exp(x) - 1.0);",PB=`
+    `}};function mj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),u,h=new fj(c);u=n.runWebGLProgram(h,[a,s],"float32");let d=xe({inputs:{x:u},backend:n,attrs:{shape:c.outShape}});return n.disposeIntermediateTensorInfo(u),d}var Aj={kernelName:yu,backendName:"webgl",kernelFunc:mj},yj="return (x >= 0.0) ? x : (exp(x) - 1.0);",gj=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -2789,12 +2789,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,LB=Xe({opSnippet:zB,packedOpSnippet:PB}),WB={kernelName:co,backendName:"webgl",kernelFunc:LB},BB="return (b >= 1.0) ? a : a * (b + 1.0);",VB=`
+`,xj=Xe({opSnippet:yj,packedOpSnippet:gj}),bj={kernelName:co,backendName:"webgl",kernelFunc:xj},wj="return (b >= 1.0) ? a : a * (b + 1.0);",_j=`
   vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
   return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
-`,UB=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new pc(VB,r.shape,a.shape):new Ml(BB,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},jB={kernelName:Bh,backendName:"webgl",kernelFunc:UB},HB=`
+`,vj=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new pc(_j,r.shape,a.shape):new Ml(wj,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},kj={kernelName:Bh,backendName:"webgl",kernelFunc:vj},Ij=`
   return vec4(equal(a, b));
-`,GB="return float(a == b);",qB=tn({opSnippet:GB,packedOpSnippet:HB,dtype:"bool"}),XB={kernelName:po,backendName:"webgl",kernelFunc:qB},KB=`
+`,Nj="return float(a == b);",Sj=tn({opSnippet:Nj,packedOpSnippet:Ij,dtype:"bool"}),Tj={kernelName:po,backendName:"webgl",kernelFunc:Sj},Ej=`
   // Error function is calculated approximately with elementary function.
   // See "Handbook of Mathematical Functions with Formulas,
   // Graphs, and Mathematical Tables", Abramowitz and Stegun.
@@ -2809,7 +2809,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
   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));
-`,ZB=Xe({opSnippet:KB}),YB={kernelName:ho,backendName:"webgl",kernelFunc:ZB},x_="return exp(x);",w_=Xe({opSnippet:x_,packedOpSnippet:x_,cpuKernelImpl:Zz}),JB={kernelName:gs,backendName:"webgl",kernelFunc:w_};function hA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),xe({inputs:{x:s},backend:r,attrs:{shape:o}})}var QB={kernelName:fo,backendName:"webgl",kernelFunc:hA},b_="return exp(x) - 1.0;",eV=Xe({opSnippet:b_,packedOpSnippet:b_,cpuKernelImpl:Yz}),tV={kernelName:mo,backendName:"webgl",kernelFunc:eV},__=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${r}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
+`,Cj=Xe({opSnippet:Ej}),Rj={kernelName:ho,backendName:"webgl",kernelFunc:Cj},Q3="return exp(x);",e7=Xe({opSnippet:Q3,packedOpSnippet:Q3,cpuKernelImpl:CL}),Mj={kernelName:gs,backendName:"webgl",kernelFunc:e7};function AA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),xe({inputs:{x:s},backend:r,attrs:{shape:o}})}var Fj={kernelName:fo,backendName:"webgl",kernelFunc:AA},t7="return exp(x) - 1.0;",Dj=Xe({opSnippet:t7,packedOpSnippet:t7,cpuKernelImpl:RL}),$j={kernelName:mo,backendName:"webgl",kernelFunc:Dj},n7=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${r}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
       const float exponentMultiplier = ${a};
 
       float unaryOpComplex(float real, float expR, float imag, float expI) {
@@ -2842,13 +2842,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         ivec2 coords = getOutputCoords();
         setOutput(mulMatDFT(coords[0], coords[1]));
       }
-    `}};function v_(e,t,n){let r=n.texData.get(e.dataId),a=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=xe({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,c=new __("real",l,t),u=new __("imag",l,t),h=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:l},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Wa({inputs:{real:d,imag:p},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p);let m=xe({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),m}function nV(e){let{inputs:t,backend:n}=e,{input:r}=t;return v_(r,!1,n)}var rV={kernelName:Vh,backendName:"webgl",kernelFunc:nV},aV=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.outputShape=e,this.userCode=`
+    `}};function r7(e,t,n){let r=n.texData.get(e.dataId),a=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=xe({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,c=new n7("real",l,t),u=new n7("imag",l,t),h=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:l},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Wa({inputs:{real:d,imag:p},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p);let m=xe({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),m}function Oj(e){let{inputs:t,backend:n}=e,{input:r}=t;return r7(r,!1,n)}var zj={kernelName:Vh,backendName:"webgl",kernelFunc:Oj},Pj=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.outputShape=e,this.userCode=`
       uniform float value;
       void main() {
         // Input can be obtained from uniform value.
         setOutput(value);
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function dA(e){let{backend:t,attrs:n}=e,{shape:r,value:a}=n,{dtype:s}=n;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(r));return i.fill(a),t.makeTensorInfo(r,s,i)}else{let i=new aV(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var sV={kernelName:gu,backendName:"webgl",kernelFunc:dA},iV=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function yA(e){let{backend:t,attrs:n}=e,{shape:r,value:a}=n,{dtype:s}=n;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(r));return i.fill(a),t.makeTensorInfo(r,s,i)}else{let i=new Pj(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var Lj={kernelName:gu,backendName:"webgl",kernelFunc:yA},Wj=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];
@@ -2862,7 +2862,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
           }
           setOutput(outputValue);
         }
-    `}},oV={kernelName:Ao,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new iV(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},k_="return floor(x);",lV=Xe({opSnippet:k_,packedOpSnippet:k_,cpuKernelImpl:Jz}),uV={kernelName:xs,backendName:"webgl",kernelFunc:lV},cV=`
+    `}},Bj={kernelName:Ao,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new Wj(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},a7="return floor(x);",Vj=Xe({opSnippet:a7,packedOpSnippet:a7,cpuKernelImpl:ML}),jj={kernelName:xs,backendName:"webgl",kernelFunc:Vj},Uj=`
   float s = sign(a) * sign(b);
   int ia = round(a);
   int ib = round(b);
@@ -2872,7 +2872,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
   } else {
     return NAN;
   }
-`,hV=`
+`,Hj=`
   ivec4 ia = round(a);
   ivec4 ib = round(b);
   bvec4 cond = notEqual(ib, ivec4(0));
@@ -2893,7 +2893,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
     result[3] = idiv(ia[3], ib[3], s[3]);
   }
   return vec4(result);
-`,dV=tn({opSnippet:cV,packedOpSnippet:hV,dtype:"int32"}),pV={kernelName:ws,backendName:"webgl",kernelFunc:dV},fV=class{constructor(e){this.variableNames=["A"];let t=hn(),[n,r]=e;this.outputShape=e,this.userCode=`
+`,Gj=tn({opSnippet:Uj,packedOpSnippet:Hj,dtype:"int32"}),qj={kernelName:bs,backendName:"webgl",kernelFunc:Gj},Xj=class{constructor(e){this.variableNames=["A"];let t=hn(),[n,r]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -2915,7 +2915,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
 
         setOutput(floor(value * 255.0 + 0.5));
       }
-    `}},mV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=hn(),[n,r]=e;this.outputShape=e,this.userCode=`
+    `}},Kj=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=hn(),[n,r]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -2949,7 +2949,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
 
         ${t.output} = result;
       }
-    `}},yV={kernelName:rd,backendName:"webgl",kernelFunc:AV},$l;function AV(e){let{inputs:t,backend:n,attrs:r}=e,{pixels:a}=t,{numChannels:s}=r,i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,[l,c]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],u=[c,l],h=[c,l,s];(o||i)&&($l==null&&($l=document.createElement("canvas").getContext("2d")),$l.canvas.width=l,$l.canvas.height=c,$l.drawImage(a,0,0,l,c),a=$l.canvas);let d=n.makeTensorInfo(u,"int32");n.texData.get(d.dataId).usage=Xn.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),a);let p=J().getBool("WEBGL_PACK")?new mV(h):new fV(h),f=n.runWebGLProgram(p,[d],"int32");return n.disposeData(d.dataId),f}function gV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=R.convertConv2DDataFormat(u),A=R.computeConv2DInfo(a.shape,s.shape,l,h,c,d,!1,m),y,g=[];if(A.filterHeight===1&&A.filterWidth===1&&A.dilationHeight===1&&A.dilationWidth===1&&A.strideHeight===1&&A.strideWidth===1&&(A.padInfo.type==="SAME"||A.padInfo.type==="VALID"))y=d_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=p_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let b=i!=null,_=o!=null,x=p==="leakyrelu",N=p?mp(p,!1):null,T=new h_(A,b,N,_,x),E=[a,s];if(i&&E.push(i),o&&E.push(o),x){let F=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));E.push(F),g.push(F)}y=n.runWebGLProgram(T,E,"float32")}let w=xe({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(b=>n.disposeIntermediateTensorInfo(b)),w}var xV={kernelName:Qs,backendName:"webgl",kernelFunc:gV};function wV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dilations:u,dimRoundingMode:h,activation:d,leakyreluAlpha:p}=r,f=[],m=u;m==null&&(m=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let A=R.computeConv2DInfo(a.shape,s.shape,l,m,c,h,!0),y=J().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,g=d?mp(d,y):null,w=[a,s],b=i!=null,_=o!=null,x=d==="leakyrelu";if(b&&w.push(i),_&&w.push(o),x){let E=n.makeTensorInfo([],"float32",v.createScalarValue(p,"float32"));w.push(E),f.push(E)}let N;y?N=new g_(A,b,g,_,x):N=new y_(A,b,g,_,x);let T=n.runWebGLProgram(N,w,"float32");return f.forEach(E=>n.disposeIntermediateTensorInfo(E)),T}var bV={kernelName:ei,backendName:"webgl",kernelFunc:wV},_V=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=ot(t.length),a=ot(n.length),s=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
+    `}},Yj={kernelName:rd,backendName:"webgl",kernelFunc:Zj},Dl;function Zj(e){let{inputs:t,backend:n,attrs:r}=e,{pixels:a}=t,{numChannels:s}=r,i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,[l,c]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],u=[c,l],h=[c,l,s];(o||i)&&(Dl==null&&(Dl=document.createElement("canvas").getContext("2d")),Dl.canvas.width=l,Dl.canvas.height=c,Dl.drawImage(a,0,0,l,c),a=Dl.canvas);let d=n.makeTensorInfo(u,"int32");n.texData.get(d.dataId).usage=Xn.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),a);let p=J().getBool("WEBGL_PACK")?new Kj(h):new Xj(h),f=n.runWebGLProgram(p,[d],"int32");return n.disposeData(d.dataId),f}function Jj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=R.convertConv2DDataFormat(u),A=R.computeConv2DInfo(a.shape,s.shape,l,h,c,d,!1,m),y,g=[];if(A.filterHeight===1&&A.filterWidth===1&&A.dilationHeight===1&&A.dilationWidth===1&&A.strideHeight===1&&A.strideWidth===1&&(A.padInfo.type==="SAME"||A.padInfo.type==="VALID"))y=G3({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=q3({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let w=i!=null,_=o!=null,x=p==="leakyrelu",N=p?mp(p,!1):null,T=new H3(A,w,N,_,x),E=[a,s];if(i&&E.push(i),o&&E.push(o),x){let F=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));E.push(F),g.push(F)}y=n.runWebGLProgram(T,E,"float32")}let b=xe({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(w=>n.disposeIntermediateTensorInfo(w)),b}var Qj={kernelName:Qs,backendName:"webgl",kernelFunc:Jj};function eU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dilations:u,dimRoundingMode:h,activation:d,leakyreluAlpha:p}=r,f=[],m=u;m==null&&(m=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let A=R.computeConv2DInfo(a.shape,s.shape,l,m,c,h,!0),y=J().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,g=d?mp(d,y):null,b=[a,s],w=i!=null,_=o!=null,x=d==="leakyrelu";if(w&&b.push(i),_&&b.push(o),x){let E=n.makeTensorInfo([],"float32",v.createScalarValue(p,"float32"));b.push(E),f.push(E)}let N;y?N=new J3(A,w,g,_,x):N=new Y3(A,w,g,_,x);let T=n.runWebGLProgram(N,b,"float32");return f.forEach(E=>n.disposeIntermediateTensorInfo(E)),T}var tU={kernelName:ei,backendName:"webgl",kernelFunc:eU},nU=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=ot(t.length),a=ot(n.length),s=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
         ${r} strides = ${r}(${this.strides});
          void main() {
           ${a} coords = getOutputCoords();
@@ -2960,21 +2960,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
           }
           setOutput(getX(flattenIndex, coords[1]));
         }
-      `}};function vV(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=a.shape,i=s[s.length-1],[o,l,c,u]=R.prepareAndValidate(r,a),h=xe({inputs:{x:a},backend:n,attrs:{shape:[l,i]}}),d=xe({inputs:{x:r},backend:n,attrs:{shape:[v.sizeFromShape(r.shape)/c,c]}}),p=new _V(i,u,[l,c]),f=n.runWebGLProgram(p,[d,h],d.dtype),m=xe({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}var kV={kernelName:go,backendName:"webgl",kernelFunc:vV},NV=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=ot(this.rank),r=IV(e,2);this.userCode=`
+      `}};function rU(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=a.shape,i=s[s.length-1],[o,l,c,u]=R.prepareAndValidate(r,a),h=xe({inputs:{x:a},backend:n,attrs:{shape:[l,i]}}),d=xe({inputs:{x:r},backend:n,attrs:{shape:[v.sizeFromShape(r.shape)/c,c]}}),p=new nU(i,u,[l,c]),f=n.runWebGLProgram(p,[d,h],d.dtype),m=xe({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}var aU={kernelName:go,backendName:"webgl",kernelFunc:rU},iU=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=ot(this.rank),r=sU(e,2);this.userCode=`
       void main() {
         ${n} resRC = getOutputCoords();
         setOutput(getA(${r}));
       }
-    `}};function IV(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let a=0;a<e.length;a++)a===2?r.push("int(getIndices(resRC.x, resRC.z))"):r.push(`${n[a]}`);return r.join()}function SV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],c=R.segment_util.collectGatherOpShapeInfo(a,s,l,o),u=v.sizeFromShape(s.shape),h=[],d=xe({inputs:{x:a},backend:n,attrs:{shape:[c.batchSize,c.outerSize,c.dimSize,c.sliceSize]}}),p=xe({inputs:{x:s},backend:n,attrs:{shape:[c.batchSize,u/c.batchSize]}});h.push(d),h.push(p);let f=[c.batchSize,c.outerSize,u/c.batchSize,c.sliceSize];if(n.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let g=n.bufferSync(p),w=n.bufferSync(d),b=Qz(w,g,f);return h.forEach(_=>n.disposeIntermediateTensorInfo(_)),n.makeTensorInfo(c.outputShape,b.dtype,b.values)}let m=new NV(d.shape,f),A=n.runWebGLProgram(m,[d,p],d.dtype);h.push(A);let y=xe({inputs:{x:A},backend:n,attrs:{shape:c.outputShape}});return h.forEach(g=>n.disposeIntermediateTensorInfo(g)),y}var TV={kernelName:yo,backendName:"webgl",kernelFunc:SV},EV="return float(a > b);",CV=`
+    `}};function sU(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let a=0;a<e.length;a++)a===2?r.push("int(getIndices(resRC.x, resRC.z))"):r.push(`${n[a]}`);return r.join()}function oU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],c=R.segment_util.collectGatherOpShapeInfo(a,s,l,o),u=v.sizeFromShape(s.shape),h=[],d=xe({inputs:{x:a},backend:n,attrs:{shape:[c.batchSize,c.outerSize,c.dimSize,c.sliceSize]}}),p=xe({inputs:{x:s},backend:n,attrs:{shape:[c.batchSize,u/c.batchSize]}});h.push(d),h.push(p);let f=[c.batchSize,c.outerSize,u/c.batchSize,c.sliceSize];if(n.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let g=n.bufferSync(p),b=n.bufferSync(d),w=FL(b,g,f);return h.forEach(_=>n.disposeIntermediateTensorInfo(_)),n.makeTensorInfo(c.outputShape,w.dtype,w.values)}let m=new iU(d.shape,f),A=n.runWebGLProgram(m,[d,p],d.dtype);h.push(A);let y=xe({inputs:{x:A},backend:n,attrs:{shape:c.outputShape}});return h.forEach(g=>n.disposeIntermediateTensorInfo(g)),y}var lU={kernelName:yo,backendName:"webgl",kernelFunc:oU},uU="return float(a > b);",cU=`
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+`,hU=tn({opSnippet:uU,packedOpSnippet:cU,cpuKernelImpl:DL,dtype:"bool"}),dU={kernelName:xo,backendName:"webgl",kernelFunc:hU},pU="return float(a >= b);",fU=`
   return vec4(greaterThanEqual(a, b));
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+`,mU=tn({opSnippet:pU,packedOpSnippet:fU,dtype:"bool"}),AU={kernelName:_s,backendName:"webgl",kernelFunc:mU};function yU(e){let{inputs:t,backend:n}=e,{input:r}=t;return r7(r,!0,n)}var gU={kernelName:jh,backendName:"webgl",kernelFunc:yU},xU="return float(!isnan(x) && !isinf(x));",bU=Xe({opSnippet:xU,dtype:"bool"}),wU={kernelName:bo,backendName:"webgl",kernelFunc:bU},_U="return float(isinf(x));",vU=Xe({opSnippet:_U,dtype:"bool"}),kU={kernelName:wo,backendName:"webgl",kernelFunc:vU},IU="return float(isnan(x));",NU=Xe({opSnippet:IU,dtype:"bool"}),SU={kernelName:_o,backendName:"webgl",kernelFunc:NU},TU="return float(a < b);",EU=`
   return vec4(lessThan(a, b));
-`,ZV=tn({opSnippet:XV,packedOpSnippet:KV,cpuKernelImpl:tP,dtype:"bool"}),YV={kernelName:vo,backendName:"webgl",kernelFunc:ZV},JV="return float(a <= b);",QV=`
+`,CU=tn({opSnippet:TU,packedOpSnippet:EU,cpuKernelImpl:$L,dtype:"bool"}),RU={kernelName:vo,backendName:"webgl",kernelFunc:CU},MU="return float(a <= b);",FU=`
   return vec4(lessThanEqual(a, b));
-`,eU=tn({opSnippet:JV,packedOpSnippet:QV,dtype:"bool"}),tU={kernelName:ko,backendName:"webgl",kernelFunc:eU};function nU(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=nP(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var rU={kernelName:Hh,backendName:"webgl",kernelFunc:nU},aU=`if (x < 0.0) return NAN;
-  return log(x);`,sU=`
+`,DU=tn({opSnippet:MU,packedOpSnippet:FU,dtype:"bool"}),$U={kernelName:ko,backendName:"webgl",kernelFunc:DU};function OU(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=OL(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var zU={kernelName:Hh,backendName:"webgl",kernelFunc:OU},PU=`if (x < 0.0) return NAN;
+  return log(x);`,LU=`
   vec4 result = log(x);
   vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
   result.r = isNaN.r == 1.0 ? NAN : result.r;
@@ -2983,16 +2983,16 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
   result.a = isNaN.a == 1.0 ? NAN : result.a;
 
   return result;
-`,iU=Xe({opSnippet:aU,packedOpSnippet:sU,cpuKernelImpl:rP}),oU={kernelName:Is,backendName:"webgl",kernelFunc:iU},lU="return log(1.0 + x);",uU=Xe({opSnippet:lU}),cU={kernelName:Io,backendName:"webgl",kernelFunc:uU},hU="return float(a >= 1.0 && b >= 1.0);",dU=`
+`,WU=Xe({opSnippet:PU,packedOpSnippet:LU,cpuKernelImpl:zL}),BU={kernelName:Is,backendName:"webgl",kernelFunc:WU},VU="return log(1.0 + x);",jU=Xe({opSnippet:VU}),UU={kernelName:Io,backendName:"webgl",kernelFunc:jU},HU="return float(a >= 1.0 && b >= 1.0);",GU=`
   return vec4(
     vec4(greaterThanEqual(a, vec4(1.0))) *
     vec4(greaterThanEqual(b, vec4(1.0))));
-`,pU=tn({opSnippet:hU,packedOpSnippet:dU,dtype:"bool"}),fU={kernelName:No,backendName:"webgl",kernelFunc:pU},mU="return float(!(x >= 1.0));",AU=Xe({opSnippet:mU}),yU={kernelName:xu,backendName:"webgl",kernelFunc:AU},gU="return float(a >= 1.0 || b >= 1.0);",xU=`
+`,qU=tn({opSnippet:HU,packedOpSnippet:GU,dtype:"bool"}),XU={kernelName:No,backendName:"webgl",kernelFunc:qU},KU="return float(!(x >= 1.0));",ZU=Xe({opSnippet:KU}),YU={kernelName:xu,backendName:"webgl",kernelFunc:ZU},JU="return float(a >= 1.0 || b >= 1.0);",QU=`
   return min(
     vec4(greaterThanEqual(a, vec4(1.0))) +
     vec4(greaterThanEqual(b, vec4(1.0))),
     vec4(1.0));
-`,wU=tn({opSnippet:gU,packedOpSnippet:xU,dtype:"bool"}),bU={kernelName:wu,backendName:"webgl",kernelFunc:wU},_U=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
+`,eH=tn({opSnippet:JU,packedOpSnippet:QU,dtype:"bool"}),tH={kernelName:bu,backendName:"webgl",kernelFunc:eH},nH=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3011,7 +3011,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         float val = x * ${o};
         setOutput(val);
       }
-    `}},vU=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
+    `}},rH=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords.x;
@@ -3073,7 +3073,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         vec4 result = xAtOutputCoords * ${o};
         setOutput(result);
       }
-    `}},kU=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,c=J().getBool("WEBGL_PACK_NORMALIZATION")?new vU(a.shape,s,i,o,l):new _U(a.shape,s,i,o,l);return n.runWebGLProgram(c,[a],a.dtype)},IU={kernelName:bu,backendName:"webgl",kernelFunc:kU},NU=class{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode=`
+    `}},aH=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,c=J().getBool("WEBGL_PACK_NORMALIZATION")?new rH(a.shape,s,i,o,l):new nH(a.shape,s,i,o,l);return n.runWebGLProgram(c,[a],a.dtype)},sH={kernelName:wu,backendName:"webgl",kernelFunc:aH},iH=class{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3128,14 +3128,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
       }
       setOutput(result);
       }
-    `}},SU=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:c,beta:u}=r,h=new NU(a.shape,o,l,c,u);return n.runWebGLProgram(h,[a,s,i],a.dtype)},TU={kernelName:Gh,backendName:"webgl",kernelFunc:SU};function EU(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=xe({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,e.dtype,"max",r),l=xe({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function I_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,w=new Array(o);for(let x=0;x<w.length;x++)w[x]=a.shape[u[x]];let b=sA(g,a.shape,a.dtype,u,w);p=n.makeTensorInfo(w,a.dtype);let _=n.texData.get(p.dataId);_.values=b}else p=Ap(a,u,n);c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("max",c,o);let[f,m]=R.computeOutAndReduceShapes(p.shape,c),A=f;i&&(A=R.expandShapeToKeepDim(f,l));let y;if(d){let g=n.texData.get(p.dataId).values,w=aP(g,v.sizeFromShape(m),A,a.dtype);y=n.makeTensorInfo(A,a.dtype);let b=n.texData.get(y.dataId);b.values=w}else y=EU(p,m,A,n);return h&&n.disposeIntermediateTensorInfo(p),y}var CU={kernelName:Ns,backendName:"webgl",kernelFunc:I_},RU=Vb+`
+    `}},oH=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:c,beta:u}=r,h=new iH(a.shape,o,l,c,u);return n.runWebGLProgram(h,[a,s,i],a.dtype)},lH={kernelName:Gh,backendName:"webgl",kernelFunc:oH};function uH(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=xe({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,e.dtype,"max",r),l=xe({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function s7(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,b=new Array(o);for(let x=0;x<b.length;x++)b[x]=a.shape[u[x]];let w=cA(g,a.shape,a.dtype,u,b);p=n.makeTensorInfo(b,a.dtype);let _=n.texData.get(p.dataId);_.values=w}else p=Ap(a,u,n);c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("max",c,o);let[f,m]=R.computeOutAndReduceShapes(p.shape,c),A=f;i&&(A=R.expandShapeToKeepDim(f,l));let y;if(d){let g=n.texData.get(p.dataId).values,b=PL(g,v.sizeFromShape(m),A,a.dtype);y=n.makeTensorInfo(A,a.dtype);let w=n.texData.get(y.dataId);w.values=b}else y=uH(p,m,A,n);return h&&n.disposeIntermediateTensorInfo(p),y}var cH={kernelName:Ns,backendName:"webgl",kernelFunc:s7},hH=_3+`
   return max(a, b);
-`,MU=`
+`,dH=`
   vec4 result = vec4(max(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
   `+fp+`
   return result;
-`,FU=tn({opSnippet:RU,packedOpSnippet:MU,cpuKernelImpl:sP}),$U={kernelName:Ss,backendName:"webgl",kernelFunc:FU};function DU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return On({inputs:{x:a},backend:n});let h=new fc(u,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var OU={kernelName:Ts,backendName:"webgl",kernelFunc:DU};function zU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,c,l),d=new lA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var PU={kernelName:_u,backendName:"webgl",kernelFunc:zU},LU=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
+`,pH=tn({opSnippet:hH,packedOpSnippet:dH,cpuKernelImpl:LL}),fH={kernelName:Ss,backendName:"webgl",kernelFunc:pH};function mH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return On({inputs:{x:a},backend:n});let h=new fc(u,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var AH={kernelName:Ts,backendName:"webgl",kernelFunc:mH};function yH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,c,l),d=new pA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var gH={kernelName:_u,backendName:"webgl",kernelFunc:yH},xH=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${o});
 
       void main() {
@@ -3181,7 +3181,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},WU=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,c=e.effectiveFilterWidth,u=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=c-1-e.padInfo.left,p=o*l*c-1;this.userCode=`
+    `}},bH=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,c=e.effectiveFilterWidth,u=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=c-1-e.padInfo.left,p=o*l*c-1;this.userCode=`
       const ivec3 pads = ivec3(${u}, ${h}, ${d});
 
       void main() {
@@ -3245,14 +3245,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function BU(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new lA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new WU(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var VU={kernelName:Xh,backendName:"webgl",kernelFunc:BU};function UU(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;kl([s,i],"maxPoolGrad");let{filterSize:l,strides:c,pad:u,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,c,1,u,h),p=!0,f=new fc(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new LU(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var jU={kernelName:qh,backendName:"webgl",kernelFunc:UU};function HU(e,t,n,r){let a=new fc(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new fc(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var GU={kernelName:Kh,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let c=[1,1];v.assert(R.eitherStridesOrDilationsAreOne(s,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${c}'`);let u=R.computePool2DInfo(r.shape,a,s,c,i),[h,d]=HU(r,o,u,l);return[h,d]}};function qU(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=xe({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,"float32","mean",r),l=xe({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var XU={kernelName:Es,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:a,axis:s}=t,i=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let w=i.texData.get(f.dataId).values,b=new Array(o);for(let N=0;N<b.length;N++)b[N]=r.shape[u[N]];let _=sA(w,r.shape,r.dtype,u,b);f=i.makeTensorInfo(b,r.dtype);let x=i.texData.get(f.dataId);x.values=_}else f=Ap(r,u,i);p.push(f),c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("sum",c,o);let[m,A]=R.computeOutAndReduceShapes(f.shape,c),y=m;a&&(y=R.expandShapeToKeepDim(m,l));let g=qU(f,A,y,i);for(let w of p)i.disposeIntermediateTensorInfo(w);return g}};function KU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,a.shape.length)),R.assertAxesAreInnerMostDims("min",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"min",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var ZU={kernelName:Cs,backendName:"webgl",kernelFunc:KU},YU=Vb+`
+    `}};function wH(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new pA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new bH(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var _H={kernelName:Xh,backendName:"webgl",kernelFunc:wH};function vH(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;kl([s,i],"maxPoolGrad");let{filterSize:l,strides:c,pad:u,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,c,1,u,h),p=!0,f=new fc(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new xH(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var kH={kernelName:qh,backendName:"webgl",kernelFunc:vH};function IH(e,t,n,r){let a=new fc(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new fc(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var NH={kernelName:Kh,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let c=[1,1];v.assert(R.eitherStridesOrDilationsAreOne(s,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${c}'`);let u=R.computePool2DInfo(r.shape,a,s,c,i),[h,d]=IH(r,o,u,l);return[h,d]}};function SH(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=xe({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,"float32","mean",r),l=xe({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var TH={kernelName:Es,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:a,axis:s}=t,i=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let b=i.texData.get(f.dataId).values,w=new Array(o);for(let N=0;N<w.length;N++)w[N]=r.shape[u[N]];let _=cA(b,r.shape,r.dtype,u,w);f=i.makeTensorInfo(w,r.dtype);let x=i.texData.get(f.dataId);x.values=_}else f=Ap(r,u,i);p.push(f),c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("sum",c,o);let[m,A]=R.computeOutAndReduceShapes(f.shape,c),y=m;a&&(y=R.expandShapeToKeepDim(m,l));let g=SH(f,A,y,i);for(let b of p)i.disposeIntermediateTensorInfo(b);return g}};function EH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,a.shape.length)),R.assertAxesAreInnerMostDims("min",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"min",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var CH={kernelName:Cs,backendName:"webgl",kernelFunc:EH},RH=_3+`
   return min(a, b);
-`,JU=`
+`,MH=`
   vec4 result = vec4(min(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
   `+fp+`
   return result;
-`,QU=tn({opSnippet:YU,packedOpSnippet:JU,cpuKernelImpl:iP}),ej={kernelName:Rs,backendName:"webgl",kernelFunc:QU},tj=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((c,u)=>c[0]+e[u]+c[1]);let r=e.length,a=ot(r),s=t.map(c=>c[0]).join(","),i=t.map((c,u)=>c[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),l=n==="reflect"?0:1;if(r===1){this.userCode=`
+`,FH=tn({opSnippet:RH,packedOpSnippet:MH,cpuKernelImpl:WL}),DH={kernelName:Rs,backendName:"webgl",kernelFunc:FH},$H=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((c,u)=>c[0]+e[u]+c[1]);let r=e.length,a=ot(r),s=t.map(c=>c[0]).join(","),i=t.map((c,u)=>c[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),l=n==="reflect"?0:1;if(r===1){this.userCode=`
         int start = ${s};
         int end = ${i};
 
@@ -3281,7 +3281,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         ${a} coords = outC - start;
         setOutput(getX(${o}));
       }
-    `}},nj=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,f)=>p[0]+e[f]+p[1]);let r=e.length,a=ot(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=dn("rc",r),l=dn("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=n==="reflect"?0:1,d="";if(r===1){let p=`
+    `}},OH=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,f)=>p[0]+e[f]+p[1]);let r=e.length,a=ot(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=dn("rc",r),l=dn("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=n==="reflect"?0:1,d="";if(r===1){let p=`
         ${a} source = rc;
         if (source < start) {
           source = start * 2 - source - ${h};
@@ -3337,13 +3337,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         ${d}
         setOutput(result);
       }
-    `}},rj=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new nj(r.shape,a,s):new tj(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},aj={kernelName:vu,backendName:"webgl",kernelFunc:rj},sj=`if (b == 0.0) return NAN;
-  return mod(a, b);`,ij=`
+    `}},zH=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new OH(r.shape,a,s):new $H(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},PH={kernelName:vu,backendName:"webgl",kernelFunc:zH},LH=`if (b == 0.0) return NAN;
+  return mod(a, b);`,WH=`
   vec4 result = mod(a, b);
   vec4 isNaN = vec4(equal(b, vec4(0.0)));
   `+fp+`
   return result;
-`,oj=tn({opSnippet:sj,packedOpSnippet:ij}),lj={kernelName:So,backendName:"webgl",kernelFunc:oj},uj=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=`
+`,BH=tn({opSnippet:LH,packedOpSnippet:WH}),VH={kernelName:So,backendName:"webgl",kernelFunc:BH},jH=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=`
       uniform float seed;
 
       void main() {
@@ -3365,11 +3365,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,YL=Xe({opSnippet:ZL}),JL={kernelNam
         // If no other event happened, last event happened.
         setOutput(float(${t-1}));
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(n,"seed")),t.gl.uniform1f(this.seedLoc,e)}}},cj=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(n,"seed")),t.gl.uniform1f(this.seedLoc,e)}}},UH=`
 if (a == b) {
   return 1.0;
 };
-return a / b;`,hj=`
+return a / b;`,HH=`
   // vec4 one = vec4(equal(a, b));
   // return one + (vec4(1.0) - one) * a / b;
   vec4 result = a / b;
@@ -3387,14 +3387,14 @@ return a / b;`,hj=`
   }
 
   return result;
-`,N_=tn({opSnippet:cj,packedOpSnippet:hj,checkOutOfBounds:!0}),dj={kernelName:ys,backendName:"webgl",kernelFunc:N_},S_="return a - b;",T_=tn({opSnippet:S_,packedOpSnippet:S_,supportsComplex:!0,cpuKernelImpl:fP}),pj={kernelName:Ks,backendName:"webgl",kernelFunc:T_};function E_(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=I_({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=R.expandShapeToKeepDim(o.shape,i),c=xe({inputs:{x:o},backend:n,attrs:{shape:l}}),u=T_({inputs:{a,b:c},backend:n}),h=w_({inputs:{x:u},backend:n}),d=oA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=xe({inputs:{x:d},backend:n,attrs:{shape:l}}),f=N_({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var fj={kernelName:qs,backendName:"webgl",kernelFunc:E_};function mj(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:E_({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),c=l.shape[0],u=l.shape[1],h=new uj(c,u,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var Aj={kernelName:Zh,backendName:"webgl",kernelFunc:mj},C_="return -x;";function yj(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=lP(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Cl(r.shape,C_):a=new La(r.shape,C_),n.runWebGLProgram(a,[r],r.dtype)}var gj={kernelName:To,backendName:"webgl",kernelFunc:yj},xj=Pr.nonMaxSuppressionV3Impl;function wj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,c=n.readSync(a.dataId),u=n.readSync(s.dataId),{selectedIndices:h}=xj(c,u,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var bj={kernelName:Co,backendName:"webgl",kernelFunc:wj},_j=Pr.nonMaxSuppressionV4Impl;function vj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=_j(u,h,i,o,l,c);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var kj={kernelName:Ro,backendName:"webgl",kernelFunc:vj},Ij=Pr.nonMaxSuppressionV5Impl;function Nj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=c,{selectedIndices:A,selectedScores:y}=Ij(u,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var Sj={kernelName:Mo,backendName:"webgl",kernelFunc:Nj},Tj=class{constructor(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
+`,i7=tn({opSnippet:UH,packedOpSnippet:HH,checkOutOfBounds:!0}),GH={kernelName:ys,backendName:"webgl",kernelFunc:i7},o7="return a - b;",l7=tn({opSnippet:o7,packedOpSnippet:o7,supportsComplex:!0,cpuKernelImpl:XL}),qH={kernelName:Ks,backendName:"webgl",kernelFunc:l7};function u7(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=s7({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=R.expandShapeToKeepDim(o.shape,i),c=xe({inputs:{x:o},backend:n,attrs:{shape:l}}),u=l7({inputs:{a,b:c},backend:n}),h=e7({inputs:{x:u},backend:n}),d=dA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=xe({inputs:{x:d},backend:n,attrs:{shape:l}}),f=i7({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var XH={kernelName:qs,backendName:"webgl",kernelFunc:u7};function KH(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:u7({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),c=l.shape[0],u=l.shape[1],h=new jH(c,u,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var ZH={kernelName:Zh,backendName:"webgl",kernelFunc:KH},c7="return -x;";function YH(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=VL(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Cl(r.shape,c7):a=new La(r.shape,c7),n.runWebGLProgram(a,[r],r.dtype)}var JH={kernelName:To,backendName:"webgl",kernelFunc:YH},QH=Pr.nonMaxSuppressionV3Impl;function eG(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,c=n.readSync(a.dataId),u=n.readSync(s.dataId),{selectedIndices:h}=QH(c,u,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var tG={kernelName:Co,backendName:"webgl",kernelFunc:eG},nG=Pr.nonMaxSuppressionV4Impl;function rG(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=nG(u,h,i,o,l,c);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var aG={kernelName:Ro,backendName:"webgl",kernelFunc:rG},sG=Pr.nonMaxSuppressionV5Impl;function iG(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=c,{selectedIndices:A,selectedScores:y}=sG(u,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var oG={kernelName:Mo,backendName:"webgl",kernelFunc:iG},lG=class{constructor(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int index = round(getIndices(coords.x));
         setOutput(mix(float(${r}), float(${n}),
                       float(index == coords.y)));
       }
-    `}},Ej=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),c=new Tj(l,s,i,o),u=xe({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(c,[u],a.dtype);n.disposeIntermediateTensorInfo(u);let d=[...a.shape,s],p=xe({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},Cj={kernelName:Fs,backendName:"webgl",kernelFunc:Ej};function bp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=Ac({inputs:{input:r},backend:n}),s=bp({inputs:{x:a},backend:n}),i=wp({inputs:{input:r},backend:n}),o=bp({inputs:{x:i},backend:n}),l=Wa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return dA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var Rj={kernelName:Zo,backendName:"webgl",kernelFunc:bp};function R_(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let a=Ac({inputs:{input:r},backend:n}),s=R_({inputs:{x:a},backend:n}),i=wp({inputs:{input:r},backend:n}),o=bp({inputs:{x:i},backend:n}),l=Wa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return dA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var Mj={kernelName:Fo,backendName:"webgl",kernelFunc:R_};function Fj(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return hA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(u=>{v.assertShapesMatch(s,u.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===u.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(u=>{let h=hA({inputs:{input:u},backend:n,attrs:{dim:a}});return o.push(h),h}),c=c_({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(u=>n.disposeIntermediateTensorInfo(u)),c}var $j={kernelName:$o,backendName:"webgl",kernelFunc:Fj},Dj=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,c)=>l[0]+e[c]+l[1]);let r=e.length,a=ot(r),s=t.map(l=>l[0]).join(","),i=t.map((l,c)=>l[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);if(r===1){this.userCode=`
+    `}},uG=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),c=new lG(l,s,i,o),u=xe({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(c,[u],a.dtype);n.disposeIntermediateTensorInfo(u);let d=[...a.shape,s],p=xe({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},cG={kernelName:Fs,backendName:"webgl",kernelFunc:uG};function wp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=Ac({inputs:{input:r},backend:n}),s=wp({inputs:{x:a},backend:n}),i=bp({inputs:{input:r},backend:n}),o=wp({inputs:{x:i},backend:n}),l=Wa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return yA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var hG={kernelName:Zo,backendName:"webgl",kernelFunc:wp};function h7(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let a=Ac({inputs:{input:r},backend:n}),s=h7({inputs:{x:a},backend:n}),i=bp({inputs:{input:r},backend:n}),o=wp({inputs:{x:i},backend:n}),l=Wa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return yA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var dG={kernelName:Fo,backendName:"webgl",kernelFunc:h7};function pG(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return AA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(u=>{v.assertShapesMatch(s,u.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===u.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(u=>{let h=AA({inputs:{input:u},backend:n,attrs:{dim:a}});return o.push(h),h}),c=U3({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(u=>n.disposeIntermediateTensorInfo(u)),c}var fG={kernelName:Do,backendName:"webgl",kernelFunc:pG},mG=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,c)=>l[0]+e[c]+l[1]);let r=e.length,a=ot(r),s=t.map(l=>l[0]).join(","),i=t.map((l,c)=>l[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);if(r===1){this.userCode=`
         int start = ${s};
         int end = ${i};
         uniform float value;
@@ -3421,7 +3421,7 @@ return a / b;`,hj=`
           setOutput(getX(${o}));
         }
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},Oj=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,a=ot(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=dn("rc",r),l=dn("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1;
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},AG=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,a=ot(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=dn("rc",r),l=dn("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1;
        if(${c}) {
       `,r===1?"":`}
        rc = outputLoc;
@@ -3446,7 +3446,7 @@ return a / b;`,hj=`
         ${p}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},M_=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Oj(a.shape,s,i):new Dj(a.shape,s,i),l=o.getCustomSetupFunc(i);return n.runWebGLProgram(o,[a],a.dtype,l)},zj={kernelName:$s,backendName:"webgl",kernelFunc:M_},Pj=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},d7=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new AG(a.shape,s,i):new mG(a.shape,s,i),l=o.getCustomSetupFunc(i);return n.runWebGLProgram(o,[a],a.dtype,l)},yG={kernelName:Ds,backendName:"webgl",kernelFunc:d7},gG=`
   if(a < 0.0 && floor(b) < b){
     return NAN;
   }
@@ -3455,7 +3455,7 @@ return a / b;`,hj=`
   }
   return (round(mod(b, 2.0)) != 1) ?
       pow(abs(a), b) : sign(a) * pow(abs(a), b);
-`,Lj=`
+`,xG=`
   // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
   vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
   vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
@@ -3471,9 +3471,9 @@ return a / b;`,hj=`
   vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
   `+fp+`
   return result;
-`,Wj=tn({opSnippet:Pj,packedOpSnippet:Lj}),Bj={kernelName:Ds,backendName:"webgl",kernelFunc:Wj};function Vj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],c=v.parseAxisParam(s,a.shape),u=c,h=R.getAxesPermutation(u,o),d=a;h!=null&&(d=In({inputs:{x:a},backend:n,attrs:{perm:h}}),u=R.getInnerMostAxes(u.length,o),l.push(d)),R.assertAxesAreInnerMostDims("prod",u,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=uP(d.shape,d.dtype,f,u);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=R.computeOutAndReduceShapes(d.shape,u),A=v.sizeFromShape(m),y=xe({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=ld(a.dtype),w=vi(y,g,"prod",n);p=xe({inputs:{x:w},backend:n,attrs:{shape:f}}),l.push(y),l.push(w)}if(i){l.push(p);let f=R.expandShapeToKeepDim(p.shape,c);p=xe({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var Uj={kernelName:Do,backendName:"webgl",kernelFunc:Vj},F_=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=cP(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},jj={kernelName:ku,backendName:"webgl",kernelFunc:F_},Hj="return 1.0 / x;",Gj=Xe({opSnippet:Hj}),qj={kernelName:Oo,backendName:"webgl",kernelFunc:Gj},Xj=gr+`
+`,bG=tn({opSnippet:gG,packedOpSnippet:xG}),wG={kernelName:$s,backendName:"webgl",kernelFunc:bG};function _G(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],c=v.parseAxisParam(s,a.shape),u=c,h=R.getAxesPermutation(u,o),d=a;h!=null&&(d=In({inputs:{x:a},backend:n,attrs:{perm:h}}),u=R.getInnerMostAxes(u.length,o),l.push(d)),R.assertAxesAreInnerMostDims("prod",u,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=jL(d.shape,d.dtype,f,u);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=R.computeOutAndReduceShapes(d.shape,u),A=v.sizeFromShape(m),y=xe({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=ld(a.dtype),b=vi(y,g,"prod",n);p=xe({inputs:{x:b},backend:n,attrs:{shape:f}}),l.push(y),l.push(b)}if(i){l.push(p);let f=R.expandShapeToKeepDim(p.shape,c);p=xe({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var vG={kernelName:$o,backendName:"webgl",kernelFunc:_G},p7=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=UL(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},kG={kernelName:ku,backendName:"webgl",kernelFunc:p7},IG="return 1.0 / x;",NG=Xe({opSnippet:IG}),SG={kernelName:Oo,backendName:"webgl",kernelFunc:NG},TG=gr+`
   return (x < 0.0) ? 0.0 : x;
-`,Kj=`
+`,EG=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3483,9 +3483,9 @@ return a / b;`,hj=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,Zj=Xe({opSnippet:Xj,packedOpSnippet:Kj}),Yj={kernelName:zs,backendName:"webgl",kernelFunc:Zj},Jj=gr+`
+`,CG=Xe({opSnippet:TG,packedOpSnippet:EG}),RG={kernelName:zs,backendName:"webgl",kernelFunc:CG},MG=gr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,Qj=`
+`,FG=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3495,7 +3495,7 @@ return a / b;`,hj=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,eH=Xe({opSnippet:Jj,packedOpSnippet:Qj}),tH={kernelName:Ls,backendName:"webgl",kernelFunc:eH},nH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+`,DG=Xe({opSnippet:MG,packedOpSnippet:FG}),$G={kernelName:Ls,backendName:"webgl",kernelFunc:DG},OG=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
           ${c[0]/u[0]},
           ${c[1]/u[1]});
@@ -3528,7 +3528,7 @@ return a / b;`,hj=`
 
         setOutput(newValue);
       }
-    `}},rH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}},zG=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec3 effectiveInputOverOutputRatioRC = vec3(
           ${c[0]/u[0]},
           ${c[1]/u[1]},
@@ -3605,7 +3605,7 @@ return a / b;`,hj=`
 
         setOutput(newValue);
       }
-    `}};function aH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=J().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new rH(a.shape,l,c,s,i):new nH(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],"float32")}var sH={kernelName:Ps,backendName:"webgl",kernelFunc:aH},iH=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
+    `}};function PG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=J().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new zG(a.shape,l,c,s,i):new OG(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],"float32")}var LG={kernelName:Ps,backendName:"webgl",kernelFunc:PG},WG=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3686,7 +3686,7 @@ return a / b;`,hj=`
 
         setOutput(accumulator);
       }
-    `}};function oH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new iH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var lH={kernelName:Qh,backendName:"webgl",kernelFunc:oH},uH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0",d;a?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}};function BG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new WG(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var VG={kernelName:Qh,backendName:"webgl",kernelFunc:BG},jG=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0",d;a?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
           ${c[0]/u[0]},
           ${c[1]/u[1]});
@@ -3708,7 +3708,7 @@ return a / b;`,hj=`
 
         setOutput(newValue);
       }
-    `}};function cH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=new uH(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],a.dtype)}var hH={kernelName:Iu,backendName:"webgl",kernelFunc:cH},dH=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
+    `}};function UG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=new jG(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],a.dtype)}var HG={kernelName:Iu,backendName:"webgl",kernelFunc:UG},GG=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3778,7 +3778,7 @@ return a / b;`,hj=`
 
         setOutput(accumulator);
       }
-    `}};function pH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new dH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var fH={kernelName:Jh,backendName:"webgl",kernelFunc:pH},mH=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
+    `}};function qG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new GG(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var XG={kernelName:Jh,backendName:"webgl",kernelFunc:qG},KG=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${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));
@@ -3788,7 +3788,7 @@ return a / b;`,hj=`
         ${s} coords = getOutputCoords();
         setOutput(getX(${a}));
       }
-    `}},AH=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let r=dn("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=ot(n);n===1?this.userCode=`
+    `}},ZG=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let r=dn("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=ot(n);n===1?this.userCode=`
         void main(){
           int rc = getOutputCoords();
           vec4 result = vec4(0.);
@@ -3816,7 +3816,7 @@ return a / b;`,hj=`
           }
           setOutput(result);
         }
-    `;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function c(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function u(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function yH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return On({inputs:{x:a},backend:n});let l=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new AH(a.shape,o):new mH(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var gH={kernelName:Ws,backendName:"webgl",kernelFunc:yH},xH=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let n=e[1],r=e[2];this.outputShape=e;let a="";typeof t=="number"?a=`float outputValue = ${t.toFixed(2)};`:a=`
+    `;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function c(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function u(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function YG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return On({inputs:{x:a},backend:n});let l=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new ZG(a.shape,o):new KG(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var JG={kernelName:Ws,backendName:"webgl",kernelFunc:YG},QG=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let n=e[1],r=e[2];this.outputShape=e;let a="";typeof t=="number"?a=`float outputValue = ${t.toFixed(2)};`:a=`
         vec3 fill = vec3(${t.join(",")});
         float outputValue = fill[coords[3]];`,this.userCode=`
         uniform vec4 params;
@@ -3836,7 +3836,7 @@ return a / b;`,hj=`
           }
           setOutput(outputValue);
         }
-    `}getCustomSetupFunc(e,t,n,r){return(a,s)=>{this.paramsLoc==null&&(this.paramsLoc=a.getUniformLocationNoThrow(s,"params")),a.gl.uniform4f(this.paramsLoc,e,t,n,r)}}},wH={kernelName:Yo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new xH(r.shape,s),[c,u]=R.getImageCenter(i,r.shape[1],r.shape[2]),h=l.getCustomSetupFunc(c,u,Math.sin(a),Math.cos(a));return o.runWebGLProgram(l,[r],r.dtype,h)}},bH=`
+    `}getCustomSetupFunc(e,t,n,r){return(a,s)=>{this.paramsLoc==null&&(this.paramsLoc=a.getUniformLocationNoThrow(s,"params")),a.gl.uniform4f(this.paramsLoc,e,t,n,r)}}},eq={kernelName:Yo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new QG(r.shape,s),[c,u]=R.getImageCenter(i,r.shape[1],r.shape[2]),h=l.getCustomSetupFunc(c,u,Math.sin(a),Math.cos(a));return o.runWebGLProgram(l,[r],r.dtype,h)}},tq=`
   // OpenGL ES does not support round function.
   // The algorithm is based on banker's rounding.
   float base = floor(x);
@@ -3851,7 +3851,7 @@ return a / b;`,hj=`
       return base + 1.0;
     }
   }
-`,_H=Xe({opSnippet:bH}),vH={kernelName:Bs,backendName:"webgl",kernelFunc:_H},kH="return inversesqrt(x);",IH=Xe({opSnippet:kH,cpuKernelImpl:hP}),NH={kernelName:Vs,backendName:"webgl",kernelFunc:IH},$_=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=ot(a.length),l=ot(s.length),c="";n===1?c="i":n===2&&(c="i, j");let u=`getIndices(${c})`,h="";r===1?h="i":r===2&&(h="i, coords[1]");let d=`getUpdates(${h})`,p=t>1?"strides[j]":"strides";this.userCode=`
+`,nq=Xe({opSnippet:tq}),rq={kernelName:Bs,backendName:"webgl",kernelFunc:nq},aq="return inversesqrt(x);",sq=Xe({opSnippet:aq,cpuKernelImpl:HL}),iq={kernelName:Vs,backendName:"webgl",kernelFunc:sq},f7=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=ot(a.length),l=ot(s.length),c="";n===1?c="i":n===2&&(c="i, j");let u=`getIndices(${c})`,h="";r===1?h="i":r===2&&(h="i, coords[1]");let d=`getUpdates(${h})`,p=t>1?"strides[j]":"strides";this.userCode=`
         ${o} strides = ${o}(${a});
 
         void main() {
@@ -3871,7 +3871,7 @@ return a / b;`,hj=`
           }
           setOutput(mix(getDefaultValue(), sum, float(found)));
         }
-      `}};function SH(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:c,strides:u,outputSize:h}=R.calculateShapes(s,a,i),d=[h/c,c];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=xe({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=xe({inputs:{x:s},backend:n,attrs:{shape:[l,c]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new $_(l,o,p.shape.length,f.shape.length,u,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=xe({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var TH={kernelName:Po,backendName:"webgl",kernelFunc:SH},EH=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let c=0;c<t.length;c++)l.push(`${i[c]}`),c<e&&o.push(`${i[c]}`);r=o.join(),a=l.join()}let s=ot(n);this.userCode=`
+      `}};function oq(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:c,strides:u,outputSize:h}=R.calculateShapes(s,a,i),d=[h/c,c];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=xe({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=xe({inputs:{x:s},backend:n,attrs:{shape:[l,c]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new f7(l,o,p.shape.length,f.shape.length,u,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=xe({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var lq={kernelName:Po,backendName:"webgl",kernelFunc:oq},uq=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let c=0;c<t.length;c++)l.push(`${i[c]}`),c<e&&o.push(`${i[c]}`);r=o.join(),a=l.join()}let s=ot(n);this.userCode=`
       void main() {
         ${s} resRC = getOutputCoords();
         float cVal = getC(${r});
@@ -3881,21 +3881,21 @@ return a / b;`,hj=`
           setOutput(getB(${a}));
         }
       }
-    `}};function CH(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new EH(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],tr(a.dtype,s.dtype))}var RH={kernelName:Lo,backendName:"webgl",kernelFunc:CH},MH=`
+    `}};function cq(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new uq(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],tr(a.dtype,s.dtype))}var hq={kernelName:Lo,backendName:"webgl",kernelFunc:cq},dq=`
   // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
   // see: https://arxiv.org/abs/1706.02515
   float scaleAlpha = ${R.SELU_SCALEALPHA};
   float scale = ${R.SELU_SCALE};
   return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
-`,FH=Xe({opSnippet:MH}),$H={kernelName:Wo,backendName:"webgl",kernelFunc:FH},DH="return 1.0 / (1.0 + exp(-1.0 * x));",OH=Xe({opSnippet:DH}),zH={kernelName:js,backendName:"webgl",kernelFunc:OH},PH=`
+`,pq=Xe({opSnippet:dq}),fq={kernelName:Wo,backendName:"webgl",kernelFunc:pq},mq="return 1.0 / (1.0 + exp(-1.0 * x));",Aq=Xe({opSnippet:mq}),yq={kernelName:Us,backendName:"webgl",kernelFunc:Aq},gq=`
   if (isnan(x)) { return 0.0; }
   return sign(x);
-`,LH=Xe({opSnippet:PH}),WH={kernelName:Uo,backendName:"webgl",kernelFunc:LH},BH=qb+`
+`,xq=Xe({opSnippet:gq}),bq={kernelName:jo,backendName:"webgl",kernelFunc:xq},wq=S3+`
   return sin(x);
-`,VH=Xe({opSnippet:BH}),UH={kernelName:Us,backendName:"webgl",kernelFunc:VH},jH=`
+`,_q=Xe({opSnippet:wq}),vq={kernelName:js,backendName:"webgl",kernelFunc:_q},kq=`
   float e2x = exp(x);
   return (e2x - 1.0 / e2x) / 2.0;
-`,HH=Xe({opSnippet:jH}),GH={kernelName:Vo,backendName:"webgl",kernelFunc:HH},qH=`
+`,Iq=Xe({opSnippet:kq}),Nq={kernelName:Vo,backendName:"webgl",kernelFunc:Iq},Sq=`
   float epsilon = 1.1920928955078125e-7;
   float threshold = log(epsilon) + 2.0;
 
@@ -3915,9 +3915,9 @@ return a / b;`,hj=`
     result = log(exp_x + 1.0);
   }
   return result;
-`,XH=Xe({opSnippet:qH}),KH={kernelName:jo,backendName:"webgl",kernelFunc:XH},ZH=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,paddings:i}=r;v.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,g)=>y*g),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<a.shape.length;++y)l.push([0,0]);let c=[],u=M_({inputs:{x:a},backend:n,attrs:{paddings:l,constantValue:0}}),h=R.getReshaped(u.shape,s,o,!1),d=R.getPermuted(h.length,s.length,!1),p=R.getReshapedPermuted(u.shape,s,o,!1),f=xe({inputs:{x:u},backend:n,attrs:{shape:h}}),m=In({inputs:{x:f},backend:n,attrs:{perm:d}}),A=xe({inputs:{x:m},backend:n,attrs:{shape:p}});return c.push(u),c.push(f),c.push(m),c.forEach(y=>n.disposeIntermediateTensorInfo(y)),A},YH={kernelName:Nu,backendName:"webgl",kernelFunc:ZH};function JH(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:c,strides:u,outputSize:h}=R.calculateShapes(s,a,o),d=!1,p=new $_(c,l,a.shape.length,s.shape.length,u,[h,1],d),f=n.runWebGLProgram(p,[s,a,i],s.dtype),m=xe({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),m}var QH={kernelName:ed,backendName:"webgl",kernelFunc:JH};function eG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=r,o=v.parseAxisParam(i,a.shape)[0],l=R.prepareSplitSize(a,s,o),c=a.shape.length,u=new Array(c).fill(0),h=a.shape.slice();return l.map(d=>{let p=[...h];p[o]=d;let f=mc({inputs:{x:a},backend:n,attrs:{begin:u,size:p}});return u[o]+=d,f})}var tG={kernelName:Ho,backendName:"webgl",kernelFunc:eG},nG="return sqrt(x);",rG=Xe({opSnippet:nG}),aG={kernelName:Hs,backendName:"webgl",kernelFunc:rG},sG="return x * x;",iG=Xe({opSnippet:sG}),oG={kernelName:Su,backendName:"webgl",kernelFunc:iG},D_="return (a - b) * (a - b);",lG=tn({opSnippet:D_,packedOpSnippet:D_}),uG={kernelName:Xs,backendName:"webgl",kernelFunc:lG};function cG({inputs:e,attrs:t,backend:n}){let{x:r}=e,a=gr+`
+`,Tq=Xe({opSnippet:Sq}),Eq={kernelName:Uo,backendName:"webgl",kernelFunc:Tq},Cq=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,paddings:i}=r;v.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,g)=>y*g),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<a.shape.length;++y)l.push([0,0]);let c=[],u=d7({inputs:{x:a},backend:n,attrs:{paddings:l,constantValue:0}}),h=R.getReshaped(u.shape,s,o,!1),d=R.getPermuted(h.length,s.length,!1),p=R.getReshapedPermuted(u.shape,s,o,!1),f=xe({inputs:{x:u},backend:n,attrs:{shape:h}}),m=In({inputs:{x:f},backend:n,attrs:{perm:d}}),A=xe({inputs:{x:m},backend:n,attrs:{shape:p}});return c.push(u),c.push(f),c.push(m),c.forEach(y=>n.disposeIntermediateTensorInfo(y)),A},Rq={kernelName:Nu,backendName:"webgl",kernelFunc:Cq};function Mq(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:c,strides:u,outputSize:h}=R.calculateShapes(s,a,o),d=!1,p=new f7(c,l,a.shape.length,s.shape.length,u,[h,1],d),f=n.runWebGLProgram(p,[s,a,i],s.dtype),m=xe({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),m}var Fq={kernelName:ed,backendName:"webgl",kernelFunc:Mq};function Dq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=r,o=v.parseAxisParam(i,a.shape)[0],l=R.prepareSplitSize(a,s,o),c=a.shape.length,u=new Array(c).fill(0),h=a.shape.slice();return l.map(d=>{let p=[...h];p[o]=d;let f=mc({inputs:{x:a},backend:n,attrs:{begin:u,size:p}});return u[o]+=d,f})}var $q={kernelName:Ho,backendName:"webgl",kernelFunc:Dq},Oq="return sqrt(x);",zq=Xe({opSnippet:Oq}),Pq={kernelName:Hs,backendName:"webgl",kernelFunc:zq},Lq="return x * x;",Wq=Xe({opSnippet:Lq}),Bq={kernelName:Su,backendName:"webgl",kernelFunc:Wq},m7="return (a - b) * (a - b);",Vq=tn({opSnippet:m7,packedOpSnippet:m7}),jq={kernelName:Xs,backendName:"webgl",kernelFunc:Vq};function Uq({inputs:e,attrs:t,backend:n}){let{x:r}=e,a=gr+`
     return x > 0.0 ? 1.0 : float(${t.alpha});
-  `,s=new La(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var hG={kernelName:Na,backendName:"webgl",kernelFunc:cG},dG=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=ot(n.length),s=ot(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,c)=>(o++,n.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${o-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
+  `,s=new La(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var Hq={kernelName:Na,backendName:"webgl",kernelFunc:Uq},Gq=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=ot(n.length),s=ot(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,c)=>(o++,n.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${o-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
       ${a} begin = ${a}(${e});
       ${a} strides = ${a}(${t});
 
@@ -3925,15 +3925,15 @@ return a / b;`,hj=`
         ${s} coords = getOutputCoords();
         setOutput(getX(${i}));
       }
-    `}};function pG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:c,ellipsisMask:u,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=ln.sliceInfo(a.shape,s,i,o,l,c,u,h,d),w=xe({inputs:{x:a},backend:n,attrs:{shape:y}}),b;if(p){let x=mc({inputs:{x:w},backend:n,attrs:{begin:f,size:A}});b=xe({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))b=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([w])){let x=n.texData.get(w.dataId).values,N=Be(w.shape,w.dtype,x),T=pP(g,N,m,f);b=n.makeTensorInfo(g,w.dtype,T.values)}else{let x=new dG(f,m,g);b=n.runWebGLProgram(x,[w],w.dtype)}let _=xe({inputs:{x:b},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(b),_}var fG={kernelName:Go,backendName:"webgl",kernelFunc:pG},mG="return tan(x);",AG=Xe({opSnippet:mG}),yG={kernelName:qo,backendName:"webgl",kernelFunc:AG},gG=`
+    `}};function qq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:c,ellipsisMask:u,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=ln.sliceInfo(a.shape,s,i,o,l,c,u,h,d),b=xe({inputs:{x:a},backend:n,attrs:{shape:y}}),w;if(p){let x=mc({inputs:{x:b},backend:n,attrs:{begin:f,size:A}});w=xe({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))w=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([b])){let x=n.texData.get(b.dataId).values,N=Be(b.shape,b.dtype,x),T=qL(g,N,m,f);w=n.makeTensorInfo(g,b.dtype,T.values)}else{let x=new Gq(f,m,g);w=n.runWebGLProgram(x,[b],b.dtype)}let _=xe({inputs:{x:w},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(w),_}var Xq={kernelName:Go,backendName:"webgl",kernelFunc:qq},Kq="return tan(x);",Zq=Xe({opSnippet:Kq}),Yq={kernelName:qo,backendName:"webgl",kernelFunc:Zq},Jq=`
   float e2x = exp(-2.0 * abs(x));
   return sign(x) * (1.0 - e2x) / (1.0 + e2x);
-`,xG=Xe({opSnippet:gG}),wG={kernelName:Zs,backendName:"webgl",kernelFunc:xG},_G=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.rank=n.length;let r=ot(this.rank),a=bG(e);this.userCode=`
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+    `}};function tX(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[];for(let a=0;a<e.length;a++)r.push(`imod(${n[a]}, ${e[a]})`);return r.join()}function A7(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reps:s}=r;if(a.dtype==="string"){let o=n.readSync(a.dataId).map(u=>v.decodeString(u)),l=Be(a.shape,a.dtype,o),c=KL(l,s);return n.makeTensorInfo(c.shape,c.dtype,c.values)}let i=new nX(a.shape,s);return n.runWebGLProgram(i,[a],a.dtype)}var rX={kernelName:Ia,backendName:"webgl",kernelFunc:A7};function aX(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r,o=n.readSync(a.dataId),[l,c]=ZL(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(c.shape,c.dtype,c.values)]}var sX={kernelName:Xo,backendName:"webgl",kernelFunc:aX},iX=class{constructor(e,t,n,r,a,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=n==="nearest"?1:2,o;switch(r){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
             float mapCoord(float outCoord, float len) {
               float inCoord = outCoord;
               if(${o} == 2) {
@@ -4045,7 +4045,7 @@ return a / b;`,hj=`
               }
               setOutput(outputValue);
             }
-        `}};function SG(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:c}=r,[u,h,d,p]=a.shape,[f,m]=c!=null?c:[h,d],A=[u,f,m,p],y=new NG(h,d,i,o,l,A);return n.runWebGLProgram(y,[a,s],"float32")}var TG={kernelName:td,backendName:"webgl",kernelFunc:SG};function EG(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;kl(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=r.readSync(s.dataId),{outputValues:o,outputShape:l,indices:c}=yP(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([c.length],"int32",c)]}var CG={kernelName:nd,backendName:"webgl",kernelFunc:EG};function RG(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],c=new Array(o-1),u=0;for(let m=0;m<o;m++)m!==s&&(c[u++]=i.shape[m]);let h=[],d=new Array(o).fill(0),p=i.shape.slice();p[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let A=mc({inputs:{x:i},backend:n,attrs:{begin:d,size:p}}),y=xe({inputs:{x:A},backend:n,attrs:{shape:c}});f[m]=y,h.push(A)}return h.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var MG={kernelName:Ko,backendName:"webgl",kernelFunc:RG},FG=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,r=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/n);this.outputShape=[r,i];let o="0.0",l="sumValue",c=Math.floor(n/4)*4,u=n%4,h=`
+        `}};function oX(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:c}=r,[u,h,d,p]=a.shape,[f,m]=c!=null?c:[h,d],A=[u,f,m,p],y=new iX(h,d,i,o,l,A);return n.runWebGLProgram(y,[a,s],"float32")}var lX={kernelName:td,backendName:"webgl",kernelFunc:oX};function uX(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;kl(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=r.readSync(s.dataId),{outputValues:o,outputShape:l,indices:c}=YL(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([c.length],"int32",c)]}var cX={kernelName:nd,backendName:"webgl",kernelFunc:uX};function hX(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],c=new Array(o-1),u=0;for(let m=0;m<o;m++)m!==s&&(c[u++]=i.shape[m]);let h=[],d=new Array(o).fill(0),p=i.shape.slice();p[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let A=mc({inputs:{x:i},backend:n,attrs:{begin:d,size:p}}),y=xe({inputs:{x:A},backend:n,attrs:{shape:c}});f[m]=y,h.push(A)}return h.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var dX={kernelName:Ko,backendName:"webgl",kernelFunc:hX},pX=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,r=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/n);this.outputShape=[r,i];let o="0.0",l="sumValue",c=Math.floor(n/4)*4,u=n%4,h=`
         sumValue += dot(values, segFilter);
     `,d="";a%n>0&&(d=`
         if (inIdx < 0 || inIdx >= ${a}) {
@@ -4151,26 +4151,26 @@ return a / b;`,hj=`
         }
         setOutput(${l});
       }
-    `}};function $G(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,segmentIds:s}=t,{numSegments:i}=r,o=a.shape.length,l=[],c=0,u=R.getAxesPermutation([c],o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),l.push(h),c=R.getInnerMostAxes(1,o)[0]);let d=R.segment_util.computeOutShape(h.shape,c,i),p=v.sizeFromShape([h.shape[c]]),f=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,p]}});l.push(f);let m=ld(a.dtype),A=(b,_,x,N,T)=>{let E=b.shape[0],F=b.shape[1],D=R.segment_util.segOpComputeOptimalWindowSize(F,T),L={windowSize:D,inSize:F,batchSize:E,numSegments:T},V=new FG(L,_),U=n.compileAndRun(V,[b,x],N);if(l.push(U),U.shape[1]===T)return U;let j=F_({backend:n,attrs:{start:0,stop:T,step:1,dtype:"float32"}}),X=O_({inputs:{x:j},backend:n,attrs:{reps:[F/D]}});return l.push(j),l.push(X),A(U,_,X,N,T)},y=A(f,"unsortedSegmentSum",s,m,i),g=xe({inputs:{x:y},backend:n,attrs:{shape:d}}),w=g;if(u!=null){l.push(g);let b=R.getUndoAxesPermutation(u);w=In({inputs:{x:w},backend:n,attrs:{perm:b}})}return 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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}}},Mee=0,qe=class extends re.Serializable{constructor(e={}){super();this._callHook=null,this._addedWeightNames=[],this._stateful=!1,this.id=Mee++,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)+"_"+Pp(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 a=null;e.batchSize!=null&&(a=e.batchSize),n=[a].concat(e.inputShape)}this.batchInputShape=n;let 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They will not be included in the serialized model (and thus will be missing at deserialization time).`),p={}}if(h.inboundLayers.length>0){let f=[];for(let m=0;m<h.inboundLayers.length;m++){let A=h.inboundLayers[m],y=h.nodeIndices[m],g=h.tensorIndices[m],w=Hr.nodeKey(A,y),b=t[w];b==null&&(b=0),f.push([A.name,b,g,p])}l.push(f)}}}let c={};c.name=s.name,c.className=i,c.config=o,c.inboundNodes=l,n.push(c)}e.layers=n;let r=[];for(let s=0;s<this.inputLayers.length;s++){let i=this.inputLayers[s],o=this.inputLayersNodeIndices[s],l=Hr.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let c=t[l];c==null&&(c=0);let u=this.inputLayersTensorIndices[s];r.push([i.name,c,u])}e.inputLayers=r;let a=[];for(let s=0;s<this.outputLayers.length;s++){let i=this.outputLayers[s],o=this.outputLayersNodeIndices[s],l=Hr.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let c=t[l];c==null&&(c=0);let u=this.outputLayersTensorIndices[s];a.push([i.name,c,u])}return e.outputLayers=a,e}static fromConfig(e,t,n={},r=!1){let a={},s={};function i(m,A){m.name in s?s[m.name].push(A):s[m.name]=[A]}function o(m,A){let y=[],g;for(let w of A){let b=w[0],_=w[1],x=w[2];if(g=w[3]==null?{}:w[3],!(b in a)){i(m,A);return}let N=a[b];if(N.inboundNodes.length<=_){i(m,A);return}let T=N.inboundNodes[_];y.push(T.outputTensors[x])}y.length>0&&m.apply(Sn(y),g)}function l(m){let A=m.name,y=kr(m,t.customObjects!=null?t.customObjects:{});y.setFastWeightInitDuringBuild(r),a[A]=y,m.inboundNodes.forEach(g=>{if(!(g instanceof Array))throw new B(`Corrupted configuration, expected array for nodeData: ${g}`);i(y,g)})}let c=t.name,u=t.layers;for(let m of u)l(m);for(;!zJ(s);)for(let m of u){let A=a[m.name];if(A.name in s){let y=s[A.name];delete s[A.name];for(let g of y)o(A,g)}}let h=[],d=[],p=t.inputLayers;for(let m of p){let A=m[0],y=m[1],g=m[2];Br(A in a);let w=a[A].inboundNodes[y].outputTensors;h.push(w[g])}let f=t.outputLayers;for(let m of f){let A=m[0],y=m[1],g=m[2];Br(A in a);let w=a[A].inboundNodes[y].outputTensors;d.push(w[g])}return new e({inputs:h,outputs:d,name:c})}get stateful(){if(this._stateful)throw new B("Container instance unexpectedly has _stateful = true. 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Provided ${n} not understood: ${JSON.stringify(e)}`)}function M7(e,t){return dte(e,t,"classWeight")}async function F7(e,t,n,r){if(t!=null||r!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let a=z(()=>{if(e.shape.length===1)return e.clone();if(e.shape.length===2)if(e.shape[1]>1){let o=1;return e.argMax(o)}else{if(e.shape[1]===1)return e.reshape([e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${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.`)}),s=Array.from(await a.data());ve(a);let i=[];return s.forEach(o=>{if(n[o]==null)throw new Error(`classWeight must contain all classes in the training data. 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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(!r||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()`. 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t}makeTrainFunction(){return e=>{let t=[],n=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),a=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+this.outputs.length*2),s=[],i=()=>{let c=[];for(let p=0;p<this.inputs.length;++p)c.push({key:this.inputs[p],value:n[p]});let u=new Ci(c),h=Rc(this.outputs,u,{training:!0}),d;for(let p=0;p<this.lossFunctions.length;++p){let f=this.lossFunctions[p](r[p],h[p]);a[p]!=null&&(f=pte(f,a[p]));let m=vt(f);t.push(m),p===0?d=f:d=se(d,f)}for(let p=0;p<this.metricsTensors.length;++p){let f;if(this.outputs.length>1&&p<this.outputs.length)f=t[p];else{let m=this.metricsTensors[p][0],A=this.metricsTensors[p][1];f=vt(m(r[A],h[A]))}Ut(f),s.push(f)}return d=vt(d),this.calculateLosses().forEach(p=>{d=se(d,p)}),d},o=this.collectedTrainableWeights.map(c=>c.read()),l=!0;return[this.optimizer_.minimize(i,l,o)].concat(s)}}makeTestFunction(){this.testFunction=e=>z(()=>{let t=[],n,r=e.slice(0,this.inputs.length),a=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),s=[];for(let l=0;l<this.inputs.length;++l)s.push({key:this.inputs[l],value:r[l]});let i=new Ci(s),o=Rc(this.outputs,i);for(let l=0;l<this.lossFunctions.length;++l){let c=this.lossFunctions[l],u=vt(c(a[l],o[l]));l===0?n=u:n=se(n,u),t.push(n)}for(let l=0;l<this.metricsTensors.length;++l){let c=this.metricsTensors[l][0],u=this.metricsTensors[l][1],h=vt(c(a[u],o[u]));t.push(h)}return t})}async fit(e,t,n={}){return bte(this,e,t,n)}async fitDataset(e,t){return yte(this,e,t)}async trainOnBatch(e,t){let n=await this.standardizeUserData(e,t),r=n[0],a=n[1],s=this.makeTrainFunction()(r.concat(a)),i=[];for(let o of s){let l=await o.data();i.push(l[0])}return ve(s),Sn(i)}getNamedWeights(e){let t=[],n=e!=null&&e.trainableOnly,r=n?this.trainableWeights:this.weights,a=this.getWeights(n);for(let s=0;s<r.length;++s)n&&!r[s].trainable||t.push({name:r[s].originalName,tensor:a[s]});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=pd().numTensors;this.optimizer_.dispose(),e.numDisposedVariables+=t-pd().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 r of t)if(typeof n[r]=="string")e[r]=ua(n[r]);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(Xp(this.metrics))];if(Array.isArray(this.metrics))return this.metrics.map(e=>ua(Xp(e)));{let e={};for(let t in this.metrics)e[t]=ua(Xp(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=Cc(e.optimizer_config),n=kr(t),r;if(typeof e.loss=="string")r=Ii(e.loss);else if(Array.isArray(e.loss))r=e.loss.map(s=>Ii(s));else if(e.loss!=null){r={};for(let s in e.loss)r[s]=Ii(e.loss[s])}let a;if(Array.isArray(e.metrics))a=e.metrics.map(s=>Ii(s));else if(e.metrics!=null){a={};for(let s in e.metrics)a[s]=Ii(e.metrics[s])}this.compile({loss:r,metrics:a,optimizer:n})}async save(e,t){if(typeof e=="string"){let i=wn.getSaveHandlers(e);if(i.length===0)throw new B(`Cannot find any save handlers for URL '${e}'`);if(i.length>1)throw new B(`Found more than one (${i.length}) save handlers for URL '${e}'`);e=i[0]}if(e.save==null)throw new B("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await wn.encodeWeights(this.getNamedWeights(t)),r=!1,a=null,s={modelTopology:this.toJSON(a,r),format:Nte,generatedBy:`TensorFlow.js tfjs-layers v${YA}`,convertedBy:null};if((t==null?!1:t.includeOptimizer)&&this.optimizer!=null){s.trainingConfig=this.getTrainingConfig();let i="optimizer",{data:o,specs:l}=await wn.encodeWeights(await this.optimizer.getWeights(),i);n.specs.push(...l),n.data=wn.concatenateArrayBuffers([n.data,o])}if(this.userDefinedMetadata!=null){let i=!0;T7(this.userDefinedMetadata,this.name,i),s.userDefinedMetadata=this.userDefinedMetadata}return s.weightData=n.data,s.weightSpecs=n.specs,e.save(s)}setUserDefinedMetadata(e){T7(e,this.name),this.userDefinedMetadata=e}getUserDefinedMetadata(){return this.userDefinedMetadata}};ca.className="Model";re.registerClass(ca);var B7=class extends ca{};B7.className="Functional";re.registerClass(B7);async function Ste(e,t){"modelTopology"in e||(e={modelTopology:e}),e=e;let n=e.modelTopology;n.model_config!=null&&(n=n.model_config);let r=Cc(n),a=kr(r,t);if(e.weightsManifest!=null){let s=await wn.loadWeights(e.weightsManifest,e.pathPrefix,a.weights.map(o=>o.originalName)),i={};for(let o of a.weights)i[o.originalName]=s[o.originalName];a.loadWeights(i),ve(s)}return a}async function Ete(e,t){if(t==null&&(t={}),typeof e=="string"){let n=wn.getLoadHandlers(e,t);if(n.length===0)n.push(wn.browserHTTPRequest(e,t));else if(n.length>1)throw new B(`Found more than one (${n.length}) load handlers for URL '${e}'`);e=n[0]}return Tte(e,void 0,t)}async function Tte(e,t,n){if(n==null&&(n={}),e.load==null)throw new B("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let r=await e.load(),a=r.modelTopology;a.model_config!=null&&(a=a.model_config);let s=n.strict==null?!0:n.strict,i=r.weightData!=null&&r.weightSpecs!=null&&s,o=kr(Cc(a),t,i),l=r.trainingConfig;if(l!=null&&o.loadTrainingConfig(l),r.userDefinedMetadata!=null&&o.setUserDefinedMetadata(r.userDefinedMetadata),r.weightData!=null){if(r.weightSpecs==null)throw new B("LayersModel artifacts contains weight data, but not weight specs. 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e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};cy.className="ThresholdedReLU";re.registerClass(cy);var hy=class extends qe{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new ry().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Pe(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}};hy.className="Softmax";re.registerClass(hy);function Vl(e,t,n){if(typeof e=="number")return ki(e,t);if(e.length!==t)throw new B(`The ${n} argument must be an integer or tuple of ${t} integers. 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Received: ${JSON.stringify(e)} including a non-integer number ${a}`)}return e}function Ir(e,t,n,r,a=1){if(e==null)return e;let s=t+(t-1)*(a-1),i;return n==="same"?i=e:i=e-s+1,Math.floor((i+r-1)/r)}function Zp(e,t,n,r){if(e==null)return null;if(r==="valid")e=e*t+Ua([n-t,0]);else if(r==="same")e=e*t;else throw new B(`Unsupport padding mode: ${r}.`);return e}function dy(e,t){return z(()=>(St(t),t==="channelsFirst"?nt(e,[0,2,3,1]):e))}function rv(e,t){return z(()=>(St(t),t==="channelsFirst"?nt(e,[0,2,3,4,1]):e))}function zte(e,t,n,r=1,a="valid",s,i=1){return z(()=>{if(s==null&&(s=wr()),St(s),e.shape.length!==3)throw new B(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new B(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new B(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(s==="channelsFirst"&&(e=nt(e,[0,2,1])),a==="causal")throw new $e("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=yd(e,t,r,a==="same"?"same":"valid","NWC",i);return n!=null&&(o=Ur(o,n)),o})}function av(e,t,n,r=[1,1],a="valid",s,i,o=null){return z(()=>{if(s==null&&(s=wr()),St(s),e.rank!==3&&e.rank!==4)throw new B(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new B(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=dy(e,s);if(a==="causal")throw new $e("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=za.conv2d({x:l,filter:t,strides:r,pad:a==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=nt(l,[0,3,1,2])),l})}function Pte(e,t,n,r=[1,1,1],a="valid",s,i){return z(()=>{if(s==null&&(s=wr()),St(s),e.rank!==4&&e.rank!==5)throw new B(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new B(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=rv(e,s);if(a==="causal")throw new $e("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=tm(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Ur(o,n)),s==="channelsFirst"&&(o=nt(o,[0,4,1,2,3])),o})}var py=class extends qe{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",py.verifyArgs(t),this.rank=e,Ht(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new $e(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Vl(t.kernelSize,e,"kernelSize"),this.strides=Vl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Kn(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,St(this.dataFormat),this.activation=Ga(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=yt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Wt(t.biasConstraint),this.biasRegularizer=gt(t.biasRegularizer),this.activityRegularizer=gt(t.activityRegularizer),this.dilationRate=Vl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new B(`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 B(`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 B(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Br("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!bA(e.kernelSize,"number",1,3))throw new B(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:Ha(this.activation),useBias:this.useBias,biasInitializer:kt(this.biasInitializer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),biasConstraint:Lt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},$c=class extends py{constructor(e,t){super(e,t);this.kernel=null,$c.verifyArgs(t),this.filters=t.filters,Ht(this.filters,"filters"),this.kernelInitializer=yt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Wt(t.kernelConstraint),this.kernelRegularizer=gt(t.kernelRegularizer)}build(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new B(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],r=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",r,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 z(()=>{e=Pe(e);let n,r=this.bias==null?null:this.bias.read(),a=U3(this.activation.getClassName());if(a!=null&&this.rank===2)n=av(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate,a);else{if(this.rank===1)n=zte(e,this.kernel.read(),r,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=av(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=Pte(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new $e("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=lt(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let a=0;a<n.length;++a){let s=Ir(n[a],this.kernelSize[a],this.padding,this.strides[a],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[a]);t.push(s)}let r=[e[0]];return this.dataFormat==="channelsLast"?(r=r.concat(t),r.push(this.filters)):(r.push(this.filters),r=r.concat(t)),r}getConfig(){let e={filters:this.filters,kernelInitializer:kt(this.kernelInitializer),kernelRegularizer:ut(this.kernelRegularizer),kernelConstraint:Lt(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 B(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Dc=class extends $c{constructor(e){super(2,e);Dc.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!bA(e.kernelSize,"number",1,2))throw new B(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Dc.className="Conv2D";re.registerClass(Dc);var Yp=class extends $c{constructor(e){super(3,e);Yp.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 B(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};Yp.className="Conv3D";re.registerClass(Yp);var fy=class extends Dc{constructor(e){super(e);if(this.inputSpec=[new Gt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new B(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=lt(e),e.length!==4)throw new B("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new B("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Gt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return z(()=>{let n=Pe(e);if(n.shape.length!==4)throw new B(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let r=n.shape,a=r[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=r[s],l=r[i],c=this.kernelSize[0],u=this.kernelSize[1],h=this.strides[0],d=this.strides[1],p=Zp(o,h,c,this.padding),f=Zp(l,d,u,this.padding),m=[a,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=nt(n,[0,2,3,1]));let A=gd(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=nt(A,[0,3,1,2])),this.bias!=null&&(A=Ur(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=lt(e);let t=e.slice(),n,r,a;this.dataFormat==="channelsFirst"?(n=1,r=2,a=3):(n=3,r=1,a=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[r]=Zp(t[r],o,s,this.padding),t[a]=Zp(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};fy.className="Conv2DTranspose";re.registerClass(fy);var sv=class extends $c{constructor(e,t){super(e,t);if(this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new B("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new B("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(t.padding!=null&&t.padding!=="same"&&t.padding!=="valid")throw new B(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=yt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=gt(t.depthwiseRegularizer),this.depthwiseConstraint=Wt(t.depthwiseConstraint),this.pointwiseInitializer=yt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=gt(t.pointwiseRegularizer),this.pointwiseConstraint=Wt(t.pointwiseConstraint)}build(e){if(e=lt(e),e.length<this.rank+2)throw new B(`Inputs to SeparableConv${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 B(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Gt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return z(()=>{e=Pe(e);let n;if(this.rank===1)throw new $e("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=nt(e,[0,2,3,1])),n=xm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Ur(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=nt(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=kt(this.depthwiseInitializer),e.pointwiseInitializer=kt(this.pointwiseInitializer),e.depthwiseRegularizer=ut(this.depthwiseRegularizer),e.pointwiseRegularizer=ut(this.pointwiseRegularizer),e.depthwiseConstraint=Lt(this.depthwiseConstraint),e.pointwiseConstraint=Lt(this.pointwiseConstraint),e}};sv.className="SeparableConv";var my=class extends sv{constructor(e){super(2,e)}};my.className="SeparableConv2D";re.registerClass(my);var Jp=class extends $c{constructor(e){super(1,e);Jp.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"&&!bA(e.kernelSize,"number",1,1))throw new B(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Jp.className="Conv1D";re.registerClass(Jp);var Ay=class extends qe{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 z(()=>{if(e=Pe(e),this.dataFormat==="channelsLast"){let n=Tp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Tp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Tp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Tp(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}};Ay.className="Cropping2D";re.registerClass(Ay);var yy=class extends qe{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,St(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,sQ(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 z(()=>{let n=Pe(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=nt(n,[0,2,3,1]);let a=this.size[0]*r[2],s=this.size[1]*r[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s]);return nt(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};yy.className="UpSampling2D";re.registerClass(yy);function Lte(e,t,n=[1,1],r="valid",a,s){return z(()=>{a==null&&(a=wr()),St(a);let i=dy(e,a);if(e.rank!==4)throw new B(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new B(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=cl(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=nt(i,[0,3,1,2])),i})}var gy=class extends py{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=yt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Wt(e.depthwiseConstraint),this.depthwiseRegularizer=gt(e.depthwiseRegularizer)}build(e){if(e=lt(e),e.length<4)throw new B(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new B(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],r=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",r,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 z(()=>{e=Pe(e);let n=Lte(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Ur(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Ir(t,this.kernelSize[0],this.padding,this.strides[0]),s=Ir(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=kt(this.depthwiseInitializer),e.depthwiseRegularizer=ut(this.depthwiseRegularizer),e.depthwiseConstraint=Lt(this.depthwiseRegularizer),e}};gy.className="DepthwiseConv2D";re.registerClass(gy);function iv(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new B("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),n=a(n),{inputs:e,initialState:t,constants:n}}function ov(e,t,n,r=!1,a,s,i=!1,o=!1){return z(()=>{let l=t.shape.length;if(l<3)throw new B(`Input should be at least 3D, but is ${l}D.`);let c=[1,0].concat(_r(2,l));if(t=nt(t,c),s!=null)throw new $e("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=a.asType("bool").asType("float32"),a.rank===l-1&&(a=Jt(a,-1)),a=nt(a,c)),r&&(t=$n(t,0),a!=null&&(a=$n(a,0)));let u=[],h,d=n,p=t.shape[0],f=ar(t),m;a!=null&&(m=ar(a));for(let y=0;y<p;++y){let g=f[y],w=z(()=>e(g,d));if(a==null)h=w[0],d=w[1];else{let b=z(()=>{let _=m[y],x=Fn(_).sub(_),N=w[0].mul(_).add(d[0].mul(x)),T=d.map((E,F)=>w[1][F].mul(_).add(E.mul(x)));return{output:N,newStates:T}});h=b.output,d=b.newStates}o&&u.push(h)}let A;return o&&(A=un(u,1)),[h,A,d]})}var jr=class extends qe{constructor(e){super(e);let t;if(e.cell==null)throw new B("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Qp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new B("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 Gt({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 _r(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){BA(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return z(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(a=>null);return[n].concat(r)}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){let t=null;if(this.numConstants!=null)throw new $e("Constants support is not implemented in RNN yet.");BA(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Gt({shape:[n,null,...r]});let a=[e[0]].concat(e.slice(2));if(t!=null)throw new $e("Constants support is not implemented in RNN yet.");this.cell.build(a);let s;if(Array.isArray(this.cell.stateSize)?s=this.cell.stateSize:s=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),s))throw new B(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=s.map(i=>new Gt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){z(()=>{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 B("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(r=>Et([n,r])):this.states_=[Et([n,this.cell.stateSize])];else if(e==null)ve(this.states_),this.keptStates!=null&&(ve(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Et([n,r])):this.states_[0]=Et([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`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()):ve(this.states_);for(let r=0;r<this.states_.length;++r){let a=e[r],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[r]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(a.shape,i))throw new B(`State ${r} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${a.shape}`);this.states_[r]=a}}this.states_=this.states_.map(r=>Ut(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=iv(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Gt({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof vr){let o=[e].concat(s),l=this.inputSpec.concat(i),c=this.inputSpec;this.inputSpec=l;let u=super.apply(o,t);return this.inputSpec=c,u}else return super.apply(e,t)}call(e,t){return z(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Pe(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new B(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:r},o=ov((d,p)=>{let f=this.cell.call([d].concat(p),i);return[f[0],f.slice(1)]},e,a,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],c=o[1],u=o[2];this.stateful&&this.resetStates(u,r);let h=this.returnSequences?c:l;return this.returnState?[h].concat(u):h})}getInitialState(e){return z(()=>{let t=Et(e.shape);return t=Ee(t,[1,2]),t=Ic(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?SA(t,[1,n]):t):this.cell.stateSize>1?[SA(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 r=t.cell,a=kr(r,n);return new e(Object.assign(t,{cell:a}))}};jr.className="RNN";re.registerClass(jr);var Tc=class extends qe{},e0=class extends Tc{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,Ht(this.units,"units"),this.activation=Ga(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=zl([1,Ua([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ua([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=lt(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 z(()=>{if(e=e,e.length!==2)throw new B(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let r=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=Vr(P(e,s),this.kernel.read()):a=Vr(e,this.kernel.read()),this.bias!=null&&(a=Ur(a,this.bias.read())),i!=null&&(n=P(n,i));let o=se(a,Vr(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ha(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),recurrentRegularizer:ut(this.recurrentRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),recurrentConstraint:Lt(this.recurrentConstraint),biasConstraint:Lt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};e0.className="SimpleRNNCell";re.registerClass(e0);var xy=class extends jr{constructor(e){e.cell=new e0(e),super(e)}call(e,t){return z(()=>{this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};xy.className="SimpleRNN";re.registerClass(xy);var t0=class extends Tc{constructor(e){super(e);if(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 B("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Ht(this.units,"units"),this.activation=Ga(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ga(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=zl([1,Ua([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ua([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=lt(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 z(()=>{if(e=e,e.length!==2)throw new B(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,r=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=P(e,a[0]));let c=Vr(e,this.kernel.read());this.useBias&&(c=Ur(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,s[0]));let u=this.recurrentKernel.read(),[h,d]=zt(u,[2*this.units,this.units],u.rank-1),p=Vr(r,h),[f,m,A]=zt(c,3,c.rank-1),[y,g]=zt(p,2,p.rank-1);i=this.recurrentActivation.apply(se(f,y)),o=this.recurrentActivation.apply(se(m,g));let w=Vr(P(o,r),d);l=this.activation.apply(se(A,w));let b=se(P(i,r),P(se(1,_t(i)),l));return[b,b]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ha(this.activation),recurrentActivation:Ha(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),recurrentRegularizer:ut(this.recurrentRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),recurrentConstraint:Lt(this.recurrentConstraint),biasConstraint:Lt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};t0.className="GRUCell";re.registerClass(t0);var wy=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 t0(e),super(e)}call(e,t){return z(()=>{this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};wy.className="GRU";re.registerClass(wy);var Oc=class extends Tc{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,Ht(this.units,"units"),this.activation=Ga(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ga(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=zl([1,Ua([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ua([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=lt(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 r;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;r=new(t=class extends or{apply(i,o){let l=a.apply([s]),c=new Cp().apply([s]),u=a.apply([s*2]);return Q3(Q3(l,c),u)}},t.className="CustomInit",t)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return z(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new B(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,c,u;0<this.dropout&&this.dropout<1&&(e=P(e,s[0]));let h=Vr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,i[0])),h=se(h,Vr(r,this.recurrentKernel.read())),this.useBias&&(h=Ur(h,this.bias.read()));let[d,p,f,m]=zt(h,4,h.rank-1);o=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(p),c=se(P(l,a),P(o,this.activation.apply(f))),u=this.recurrentActivation.apply(m);let A=P(u,this.activation.apply(c));return[A,A,c]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ha(this.activation),recurrentActivation:Ha(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:ut(this.kernelRegularizer),recurrentRegularizer:ut(this.recurrentRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),recurrentConstraint:Lt(this.recurrentConstraint),biasConstraint:Lt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Oc.className="LSTMCell";re.registerClass(Oc);var by=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 Oc(e),super(e)}call(e,t){return z(()=>{this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};by.className="LSTM";re.registerClass(by);var Qp=class extends Tc{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 z(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=r[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),a.push(s.slice(1))}n=[];for(let i of a.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){BA(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,r)=>{Si(`RNNCell_${r}`,()=>{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()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,n={}){let r=[];for(let a of t.cells)r.push(kr(a,n));return new e({cells:r})}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 VA(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],a[s]])}UA(t)}};Qp.className="StackedRNNCells";re.registerClass(Qp);function qa(e){let{ones:t,rate:n,training:r=!1,count:a=1}=e,s=()=>t7(t(),n),i=()=>Sc(s,t,r);return!a||a<=1?Ut(i().clone()):Array(a).fill(void 0).map(i).map(o=>Ut(o.clone()))}var Wte=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]]);return n},lv=class extends jr{constructor(e){if(e.unroll)throw new $e("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new $e("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Gt({ndim:5})]}call(e,t){return z(()=>{if(this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new B("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}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 z(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=Et(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){z(()=>{if(!this.stateful)throw new la("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new B("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(()=>Et(a)):this.states_=[Et(a)];else if(e==null)ve(this.states_),this.keptStates!=null&&(ve(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Et(a)):this.states_[0]=Et(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`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()):ve(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!v.arraysEqual(i.shape,o))throw new B(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>Ut(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:r,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],c=e[o?4:3],u=Ir(l,r[0],a,s[0],i[0]),h=Ir(c,r[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[n,u,h]:[u,h,n]]}};lv.className="ConvRNN2D";var n0=class extends Oc{constructor(e){let{filters:t,kernelSize:n,strides:r,padding:a,dataFormat:s,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,Ht(this.filters,"filters"),this.kernelSize=Vl(n,2,"kernelSize"),this.kernelSize.forEach(o=>Ht(o,"kernelSize")),this.strides=Vl(r||1,2,"strides"),this.strides.forEach(o=>Ht(o,"strides")),this.padding=a||"valid",Kn(this.padding),this.dataFormat=s||"channelsLast",St(this.dataFormat),this.dilationRate=Vl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Ht(o,"dilationRate"))}build(e){var t;e=lt(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new B(`The channel dimension of the input should be defined. Found ${e[n]}`);let r=e[n],a=4,s=this.kernelSize.concat([r,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,c=this.filters;o=new(t=class extends or{apply(u,h){let d=l.apply([c]),p=Or([c]),f=l.apply([c*2]);return EA([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return z(()=>{if(e.length!==3)throw new B(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(Y,ae,te)=>!ae||!ae[te]?Y:P(ae[te],Y),c=l(r,o,0),u=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[w,b,_,x]=zt(this.kernel.read(),i,g),[N,T,E,F]=this.useBias?zt(this.bias.read(),i):[null,null,null,null];c=this.inputConv(c,w,N,this.padding),u=this.inputConv(u,b,T,this.padding),h=this.inputConv(h,_,E,this.padding),d=this.inputConv(d,x,F,this.padding);let[D,L,V,U]=zt(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,D),m=this.recurrentConv(m,L),A=this.recurrentConv(A,V),y=this.recurrentConv(y,U);let j=this.recurrentActivation.apply(se(c,f)),X=this.recurrentActivation.apply(se(u,m)),G=se(P(X,s),P(j,this.activation.apply(se(h,A)))),ee=P(this.recurrentActivation.apply(se(d,y)),this.activation.apply(G));return[ee,ee,G]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=Wte(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=na(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Ur(a,n,this.dataFormat):a}recurrentConv(e,t){return na(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};n0.className="ConvLSTM2DCell";re.registerClass(n0);var _y=class extends lv{constructor(e){let t=new n0(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};_y.className="ConvLSTM2D";re.registerClass(_y);var r0=class extends qe{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 r=0;r<this.noiseShape.length;++r)n.push(this.noiseShape[r]==null?t[r]:this.noiseShape[r]);return n}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,a=this.getNoiseShape(n);return Sc(()=>t7(n,this.rate,a,this.seed),()=>n,r)}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()}};r0.className="Dropout";re.registerClass(r0);var vy=class extends r0{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};vy.className="SpatialDropout1D";re.registerClass(vy);var ky=class extends qe{constructor(e){super(e);if(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,Ht(this.units,"units"),this.activation=Ga(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Wt(e.kernelConstraint),this.biasConstraint=Wt(e.biasConstraint),this.kernelRegularizer=gt(e.kernelRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.activityRegularizer=gt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=lt(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=lt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=U3(this.activation.getClassName()),a;return r!=null?a=Vr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=Vr(n,this.kernel.read()),this.bias!=null&&(a=Ur(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:Ha(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),biasConstraint:Lt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};ky.className="Dense";re.registerClass(ky);var Iy=class extends qe{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=lt(e);for(let t of e.slice(1))if(t==null)throw new B(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). 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z(()=>(e=Pe(e),uQ(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};Sy.className="RepeatVector";re.registerClass(Sy);var Ty=class extends qe{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.",r=t.slice(),a=1,s=null;for(let o=0;o<r.length;++o){let l=r[o];if(this.isUnknown(l))if(s===null)s=o;else throw new B("Can only specifiy one unknown dimension.");else a*=l}let i=Va(e);if(s!==null){if(a===0||i%a!=0)throw new B(n);r[s]=i/a}else if(i!==a)throw new B(n);return r}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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=n.shape,a=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};Ty.className="Reshape";re.registerClass(Ty);var Ey=class extends qe{constructor(e){super(e);if(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=_r(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 Gt({ndim:this.dims.length+1})]}computeOutputShape(e){e=lt(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return nt(Pe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Ey.className="Permute";re.registerClass(Ey);var Cy=class extends qe{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=Pe(e),r=-1;return Wu(pi(n,this.maskValue),r)}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=-1,a=!0,s=Wu(pi(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};Cy.className="Masking";re.registerClass(Cy);var Ry=class extends qe{constructor(e){super(e);if(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(pt(e.inputLength))}this.inputDim=e.inputDim,Ht(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Ht(this.outputDim,"outputDim"),this.embeddingsInitializer=yt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=gt(e.embeddingsRegularizer),this.activityRegularizer=gt(e.activityRegularizer),this.embeddingsConstraint=Wt(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 z(()=>this.maskZero?(e=Pe(e),pi(e,je(e))):null)}computeOutputShape(e){if(e=lt(e),this.inputLength==null)return[...e,this.outputDim];let t=pt(this.inputLength);if(t.length!==e.length-1)throw new B(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let r=0;r<t.length;++r){let a=t[r],s=e[r+1];if(a!=null&&s!=null&&a!==s)throw new B(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);a==null&&(t[n]=s),n++}}return[e[0],...t,this.outputDim]}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return n.dtype!=="int32"&&(n=kc(n,"int32")),e7(this.embeddings.read(),n.as1D()).reshape(lt(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:kt(this.embeddingsInitializer),embeddingsRegularizer:ut(this.embeddingsRegularizer),activityRegularizer:ut(this.activityRegularizer),embeddingsConstraint:Lt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Ry.className="Embedding";re.registerClass(Ry);var Mi=class extends qe{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new $e}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 r=0;r<t.length;++r){let a=e[e.length-t.length+r],s=t[r];if(a==null||s==null||a<0||s<0)n.push(null);else if(a===1)n.push(s);else if(s===1)n.push(a);else{if(a!==s)throw new B("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[lt(e)]),e=e,e.length<2)throw new B(`A merge layer should be called on an Array of at least 2 inputs. 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e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};zy.className="Concatenate";re.registerClass(zy);function zc(e,t){for(;e<0;)e+=t;return e}function Bte(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new $e("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 $e("batchDot is not implemented for complex64-type Tensors yet.");let r=e.shape.length,a=t.shape.length;n==null&&(n=[r-1,a-2]);let s=n;return z(()=>{let i;if(r>a){i=r-a;let l=[];for(let c=0;c<i;++c)l.push(1);t=t.reshape(t.shape.concat(l))}else if(a>r){i=a-r;let l=[];for(let c=0;c<i;++c)l.push(1);e=e.reshape(e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=e.mul(t).sum(s[0]):o=e.transpose([1,0]).mul(t).sum(s[1]);else{let l=s[0]!==e.shape.length-1,c=s[1]===t.shape.length-1;o=e.matMul(t,l,c)}if(i>0){let l;r>a?l=r+a-3:l=r-1;let c=[];for(let u=l;u<l+i;++u)c.push(u);o=o.squeeze(c)}return o.shape.length===1&&(o=o.expandDims(1)),o})}var Py=class extends Mi{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 $e("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new B(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new B(`A \`Dot\` layer must be called on exactly 2 inputs, but 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Ly=class extends qe{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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return Sc(()=>Ep(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};Ly.className="GaussianNoise";re.registerClass(Ly);var Wy=class extends qe{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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.rate>0&&this.rate<1?Sc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(Ep(n.shape,1,r))},()=>n,t.training||!1):n})}};Wy.className="GaussianDropout";re.registerClass(Wy);var By=class extends qe{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return 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r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return z(()=>{let n=t.training==null?!1:t.training,r=Pe(e),a=r.shape,s=a.length,i=_r(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=ki(1,s);l[o]=a[o];let c=i.slice();c.sort();let u=!v.arraysEqual(c,_r(0,s).slice(0,s-1)),h=()=>{if(u){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,w=this.scale?this.gamma.read().reshape(l):null;return Pc(r,A,y,g,w,this.epsilon)}else return 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extends qe{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=yt(e.betaInitializer||"zeros"),this.gammaInitializer=yt(e.gammaInitializer||"ones"),this.betaRegularizer=gt(e.betaRegularizer),this.gammaRegularizer=gt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=lt(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a<this.axis.length;++a)this.axis[a]<0&&(this.axis[a]+=t);for(let a of this.axis)if(a<0||a>=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==Ba(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(a=>e[a]),r=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,r):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,r):this.beta=null,this.built=!0}call(e,t){let n=Pe(e),r=n.shape,a=r.length;return z(()=>{let s=!0,{mean:i,variance:o}=Sd(n,this.axis,s),l=ki(1,a);for(let f of this.axis)l[f]=r[f];let c=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,u=c(this.gamma.read()),h=c(this.beta.read()),d=[],p=[];for(let f=0;f<a;++f)this.axis.indexOf(f)!==-1?(d.push(r[f]),p.push(1)):(d.push(1),p.push(r[f]));return i=i.tile(d),o=o.tile(d),u=u.tile(p),h=h.tile(p),Pc(n,i,o,h,u,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:kt(this.betaInitializer),gammaInitializer:kt(this.gammaInitializer),betaRegularizer:ut(this.betaRegularizer),gammaRegularizer:ut(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};Uy.className="LayerNormalization";re.registerClass(Uy);function Hte(e,t,n){return z(()=>{if(e.rank!==4)throw new B(`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 B("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=wr()),n!=="channelsLast"&&n!=="channelsFirst")throw new B(`Unknown data format: ${n}. 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length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new Gt({ndim:4})]}computeOutputShape(e){e=lt(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 z(()=>Hte(Pe(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};jy.className="ZeroPadding2D";re.registerClass(jy);function a0(e,t,n,r,a,s){return z(()=>{St(a),q3(s),Kn(r),n==null&&(n=[1,1]),r==null&&(r="valid"),a==null&&(a=wr()),s==null&&(s="max"),e=dy(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=Ku(e,t,n,o):i=Vu(e,t,n,o),a==="channelsFirst"&&(i=nt(i,[0,3,1,2])),i})}function uv(e,t,n,r,a,s){return z(()=>{St(a),q3(s),Kn(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=wr()),s==null&&(s="max"),e=rv(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=dm(e,t,n,o):i=Jf(e,t,n,o),a==="channelsFirst"&&(i=nt(i,[0,4,1,2,3])),i})}var cv=class extends qe{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 B(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Ht(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 B(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Ht(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,Kn(this.padding),this.inputSpec=[new Gt({ndim:3})]}computeOutputShape(e){e=lt(e);let t=Ir(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return z(()=>{this.invokeCallHook(e,t),e=Ic(Pe(e),2);let n=this.poolingFunction(Pe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return Oa(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},Hy=class extends cv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"max")}};Hy.className="MaxPooling1D";re.registerClass(Hy);var Gy=class extends cv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"avg")}};Gy.className="AveragePooling1D";re.registerClass(Gy);var hv=class extends qe{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 B(`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];Ht(this.poolSize,"poolSize"),Ht(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,St(this.dataFormat),Kn(this.padding),this.inputSpec=[new Gt({ndim:4})]}computeOutputShape(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Ir(t,this.poolSize[0],this.padding,this.strides[0]),n=Ir(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 z(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(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}},qy=class extends hv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"max")}};qy.className="MaxPooling2D";re.registerClass(qy);var Xy=class extends hv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"avg")}};Xy.className="AveragePooling2D";re.registerClass(Xy);var dv=class extends qe{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 B(`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];Ht(this.poolSize,"poolSize"),Ht(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,St(this.dataFormat),Kn(this.padding),this.inputSpec=[new Gt({ndim:5})]}computeOutputShape(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Ir(t,this.poolSize[0],this.padding,this.strides[0]),n=Ir(n,this.poolSize[1],this.padding,this.strides[1]),r=Ir(r,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}call(e,t){return z(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(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}},Ky=class extends dv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),uv(e,t,n,r,a,"max")}};Ky.className="MaxPooling3D";re.registerClass(Ky);var Zy=class extends dv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),uv(e,t,n,r,a,"avg")}};Zy.className="AveragePooling3D";re.registerClass(Zy);var pv=class extends qe{constructor(e){super(e);this.inputSpec=[new Gt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new $e}},Yy=class extends pv{constructor(e){super(e||{})}call(e,t){return z(()=>{let n=Pe(e);return vt(n,1)})}};Yy.className="GlobalAveragePooling1D";re.registerClass(Yy);var Jy=class extends pv{constructor(e){super(e||{})}call(e,t){return z(()=>{let n=Pe(e);return vn(n,1)})}};Jy.className="GlobalMaxPooling1D";re.registerClass(Jy);var fv=class extends qe{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,St(this.dataFormat),this.inputSpec=[new Gt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new $e}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Qy=class extends fv{call(e,t){return z(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?vt(n,[1,2]):vt(n,[2,3])})}};Qy.className="GlobalAveragePooling2D";re.registerClass(Qy);var e2=class extends fv{call(e,t){return z(()=>{let n=Pe(e);return 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e(s)}},t2=class extends mv{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=lt(e),e.length<3)throw new B(`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=lt(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))}call(e,t){return z(()=>(e=Pe(e),ov((n,r)=>[Pe(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};t2.className="TimeDistributed";re.registerClass(t2);function Gte(e){Ni(aQ,"BidirectionalMergeMode",e)}var qte="concat",n2=class extends mv{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=kr(n),t.goBackwards=t.goBackwards!==!0;let r={};if(r.className=e.layer.getClassName(),r.config=t,this.backwardLayer=kr(r),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?qte:e.mergeMode,Gte(this.mergeMode),e.weights)throw new $e("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,r,a;return this.returnState&&(a=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,r=[n]):this.mergeMode==null?r=[n,n.slice()]:r=[n],this.returnState?this.mergeMode==null?r.concat(a).concat(a.slice()):[n].concat(a).concat(a.slice()):Sn(r)}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=iv(e,n,r,this.numConstants);if(e=a.inputs,n=a.initialState,r=a.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&r==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new B("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let c=n.map(u=>new 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i;return this.mergeMode==="concat"?i=EA([r,a]):this.mergeMode==="sum"?i=se(r,a):this.mergeMode==="ave"?i=P(.5,se(r,a)):this.mergeMode==="mul"?i=P(r,a):this.mergeMode==null&&(i=[r,a]),this.returnState?this.mergeMode==null?i.concat(s):[i].concat(s):i})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){Si(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),Si(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 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vne=[{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:"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"}]}],Rv={};Oe(Rv,{json:()=>kne});var 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t.atob(e);if(typeof Buffer!="undefined")return new Buffer(e,"base64").toString();throw new Error("Unable to decode base64 in this environment. 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r=e[t];return r&&r.shape?jv(r.shape):n}function h2(e,t,n){let r=e[t];return r?((r.list.f&&r.list.f.length?r.list.f:r.list.i)||[]).map(a=>typeof a=="number"?a:parseInt(a,10)):n}function d2(e,t,n,r=!1){let a=e[t];return a&&a.list&&a.list.s?a.list.s.map(s=>Uv(s,r)):n}function p2(e,t,n){let r=e[t];return r&&r.list&&r.list.shape?r.list.shape.map(a=>jv(a)):n}function f2(e,t,n){let r=e[t];return r&&r.list&&r.list.b?r.list.b:n}var Dne=class{constructor(e,t,n){this.node=e,this.tensorMap=t,this.context=n,this.inputs=[],this.attrs={},this.inputs=e.inputNames.map(r=>this.getInput(r)),e.rawAttrs!=null&&(this.attrs=Object.keys(e.rawAttrs).reduce((r,a)=>(r[a]=this.getAttr(a),r),{}))}getInput(e){return En(e,this.tensorMap,this.context)}getAttr(e,t){let n=this.node.rawAttrs[e];if(n.tensor!=null)return En(e,this.tensorMap,this.context);if(n.i!=null||n.f!=null)return i2(this.node.rawAttrs,e,t);if(n.s!=null)return a2(this.node.rawAttrs,e,t);if(n.b!=null)return 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t}},One=(e,t,n)=>{switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[se(k("a",e,t,n),k("b",e,t,n))];case"AddN":return[Ra(k("tensors",e,t,n))];case"FloorMod":case"Mod":return[fm(k("a",e,t,n),k("b",e,t,n))];case"Mul":return[P(k("a",e,t,n),k("b",e,t,n))];case"RealDiv":case"Div":return[me(k("a",e,t,n),k("b",e,t,n))];case"DivNoNan":return[am(k("a",e,t,n),k("b",e,t,n))];case"FloorDiv":return[fd(k("a",e,t,n),k("b",e,t,n))];case"Sub":return[Ae(k("a",e,t,n),k("b",e,t,n))];case"Minimum":return[ml(k("a",e,t,n),k("b",e,t,n))];case"Maximum":return[Dr(k("a",e,t,n),k("b",e,t,n))];case"Pow":return[aa(k("a",e,t,n),k("b",e,t,n))];case"SquaredDifference":return[Pd(k("a",e,t,n),k("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not 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TypeError(`Node type ${e.op} is not implemented`)}};function ur(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 r=0;r<e.length;r++){let a=e[r],s=t[r];v.assert(a<0||s<0||a===s,()=>n+` Shapes ${e} and ${t} must match`)}}}function Hv(e){return!(typeof e=="number"||e.some(t=>t<0))}function Lc(e,t,n){let r=m2(e,n),a=!Hv(r);if(a&&t.length===0)throw new Error(`Tried to calculate elements of an empty list with non-fully-defined elementShape: ${r}`);if(a&&t.forEach(s=>{r=m2(s.shape,r)}),!Hv(r))throw new Error(`Non-fully-defined elementShape: ${r}`);return r}function m2(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 r=0;r<e.length;++r){let a=e[r],s=t[r];if(a>=0&&s>=0&&a!==s)throw new Error(`Incompatible shape during merge: ${e} vs. ${t}`);n[r]=a>=0?a:s}return n}var 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a=h6(e[0],t);n=a.sorted,r=a.recipientMap}else{let a=new Set;for(let s of e){let{sorted:i,recipientMap:o}=h6(s,t);for(let l of i)a.has(l.name)||(n.push(l),a.add(l.name));for(let l in o)r[l]==null&&(r[l]=new Set),o[l].forEach(c=>r[l].add(c))}}return{sorted:n,recipientCounts:Hne(r)}}function Hne(e){let t={};for(let n in e)t[n]=e[n].size;return t}function h6(e,t){let n=new Set,r=[],a={};for(let o of t.names())n.add(o);let s=[],i=[];for(s.push(e);s.length>0;){let o=s[s.length-1];if(n.has(o.name)){s.pop();continue}let l=i[i.length-1]===s.length-1;if(o.inputs.length===0||l)s.pop(),r.push(o),n.add(o.name),l&&i.pop();else{i.push(s.length-1);for(let c of o.inputs)a[c.name]==null&&(a[c.name]=new Set),a[c.name].add(o.name),!n.has(c.name)&&s.push(c)}}return{sorted:r,recipientMap:a}}function Une(e){let t;if(e.sourceLayer.inboundNodes.length===1)t=e.sourceLayer.output;else{let n=null;for(let r=0;r<e.sourceLayer.inboundNodes.length;++r)for(let a of 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gt(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in $6?$6[e]:e,config:{}};return O6(t)}else return e instanceof D6?e:O6(e)}var hy=class extends qe{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=Pe(e);let n=zr(e);return this.maxValue!=null&&(n=wn(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};hy.className="ReLU";re.registerClass(hy);var dy=class extends qe{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=Pe(e);return qu(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};dy.className="LeakyReLU";re.registerClass(dy);var py=class extends qe{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=yt(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=gt(e.alphaRegularizer),this.alphaConstraint=Wt(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 B(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=lt(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let r of this.sharedAxes)t[r-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let r=1;r<e.length;++r)n[r]=e[r];this.inputSpec=[new Gt({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=Pe(e),Yu(e,this.alpha.read())}getConfig(){let e={alphaInitializer:kt(this.alphaInitializer),alphaRegularizer:ut(this.alphaRegularizer),alphaConstraint:Lt(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};py.className="PReLU";re.registerClass(py);var fy=class extends qe{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new $e(`Non-default alpha value (${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=Pe(e);return hl(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};fy.className="ELU";re.registerClass(fy);var my=class extends qe{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=Pe(e);return n.mul(kc(n.greater(this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};my.className="ThresholdedReLU";re.registerClass(my);var Ay=class extends qe{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new ly().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Pe(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}};Ay.className="Softmax";re.registerClass(Ay);function Vl(e,t,n){if(typeof e=="number")return ki(e,t);if(e.length!==t)throw new B(`The ${n} argument must be an integer or tuple of ${t} integers. 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B(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new B(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=z6(e,s);if(a==="causal")throw new $e("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=im(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=jr(o,n)),s==="channelsFirst"&&(o=nt(o,[0,4,1,2,3])),o})}var gy=class extends qe{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",gy.verifyArgs(t),this.rank=e,Ht(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new $e(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Vl(t.kernelSize,e,"kernelSize"),this.strides=Vl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Kn(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,St(this.dataFormat),this.activation=Ga(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=yt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Wt(t.biasConstraint),this.biasRegularizer=gt(t.biasRegularizer),this.activityRegularizer=gt(t.activityRegularizer),this.dilationRate=Vl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new B(`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 B(`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 B(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Br("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!NA(e.kernelSize,"number",1,3))throw new B(`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:Ha(this.activation),useBias:this.useBias,biasInitializer:kt(this.biasInitializer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),biasConstraint:Lt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Dc=class extends gy{constructor(e,t){super(e,t);this.kernel=null,Dc.verifyArgs(t),this.filters=t.filters,Ht(this.filters,"filters"),this.kernelInitializer=yt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Wt(t.kernelConstraint),this.kernelRegularizer=gt(t.kernelRegularizer)}build(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new B(`The channel dimension of the input should be defined. 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t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null||e[t]<0)throw new B(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Gt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return z(()=>{e=Pe(e);let n;if(this.rank===1)throw new $e("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=nt(e,[0,2,3,1])),n=km(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=jr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=nt(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=kt(this.depthwiseInitializer),e.pointwiseInitializer=kt(this.pointwiseInitializer),e.depthwiseRegularizer=ut(this.depthwiseRegularizer),e.pointwiseRegularizer=ut(this.pointwiseRegularizer),e.depthwiseConstraint=Lt(this.depthwiseConstraint),e.pointwiseConstraint=Lt(this.pointwiseConstraint),e}};L6.className="SeparableConv";var by=class extends L6{constructor(e){super(2,e)}};by.className="SeparableConv2D";re.registerClass(by);var Jp=class extends Dc{constructor(e){super(1,e);Jp.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"&&!NA(e.kernelSize,"number",1,1))throw new B(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Jp.className="Conv1D";re.registerClass(Jp);var wy=class extends qe{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 z(()=>{if(e=Pe(e),this.dataFormat==="channelsLast"){let n=Tp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Tp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Tp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Tp(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}};wy.className="Cropping2D";re.registerClass(wy);var _y=class extends qe{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,St(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,Lee(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 z(()=>{let n=Pe(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=nt(n,[0,2,3,1]);let a=this.size[0]*r[2],s=this.size[1]*r[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s]);return nt(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};_y.className="UpSampling2D";re.registerClass(_y);function xre(e,t,n=[1,1],r="valid",a,s){return z(()=>{a==null&&(a=br()),St(a);let i=yy(e,a);if(e.rank!==4)throw new B(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new B(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=cl(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=nt(i,[0,3,1,2])),i})}var vy=class extends gy{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=yt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Wt(e.depthwiseConstraint),this.depthwiseRegularizer=gt(e.depthwiseRegularizer)}build(e){if(e=lt(e),e.length<4)throw new B(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new B(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],r=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",r,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 z(()=>{e=Pe(e);let n=xre(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=jr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Ir(t,this.kernelSize[0],this.padding,this.strides[0]),s=Ir(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=kt(this.depthwiseInitializer),e.depthwiseRegularizer=ut(this.depthwiseRegularizer),e.depthwiseConstraint=Lt(this.depthwiseRegularizer),e}};vy.className="DepthwiseConv2D";re.registerClass(vy);function W6(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new B("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),n=a(n),{inputs:e,initialState:t,constants:n}}function B6(e,t,n,r=!1,a,s,i=!1,o=!1){return z(()=>{let l=t.shape.length;if(l<3)throw new B(`Input should be at least 3D, but is ${l}D.`);let c=[1,0].concat(_r(2,l));if(t=nt(t,c),s!=null)throw new $e("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=a.asType("bool").asType("float32"),a.rank===l-1&&(a=Jt(a,-1)),a=nt(a,c)),r&&(t=Dn(t,0),a!=null&&(a=Dn(a,0)));let u=[],h,d=n,p=t.shape[0],f=ar(t),m;a!=null&&(m=ar(a));for(let y=0;y<p;++y){let g=f[y],b=z(()=>e(g,d));if(a==null)h=b[0],d=b[1];else{let w=z(()=>{let _=m[y],x=Fn(_).sub(_),N=b[0].mul(_).add(d[0].mul(x)),T=d.map((E,F)=>b[1][F].mul(_).add(E.mul(x)));return{output:N,newStates:T}});h=w.output,d=w.newStates}o&&u.push(h)}let A;return o&&(A=un(u,1)),[h,A,d]})}var Ur=class extends qe{constructor(e){super(e);let t;if(e.cell==null)throw new B("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Qp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new B("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 Gt({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 _r(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){GA(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return z(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(a=>null);return[n].concat(r)}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){let t=null;if(this.numConstants!=null)throw new $e("Constants support is not implemented in RNN yet.");GA(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Gt({shape:[n,null,...r]});let a=[e[0]].concat(e.slice(2));if(t!=null)throw new $e("Constants support is not implemented in RNN yet.");this.cell.build(a);let s;if(Array.isArray(this.cell.stateSize)?s=this.cell.stateSize:s=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),s))throw new B(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=s.map(i=>new Gt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){z(()=>{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 B("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(r=>Et([n,r])):this.states_=[Et([n,this.cell.stateSize])];else if(e==null)ve(this.states_),this.keptStates!=null&&(ve(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Et([n,r])):this.states_[0]=Et([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`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()):ve(this.states_);for(let r=0;r<this.states_.length;++r){let a=e[r],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[r]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(a.shape,i))throw new B(`State ${r} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${a.shape}`);this.states_[r]=a}}this.states_=this.states_.map(r=>jt(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=W6(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Gt({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof vr){let o=[e].concat(s),l=this.inputSpec.concat(i),c=this.inputSpec;this.inputSpec=l;let u=super.apply(o,t);return this.inputSpec=c,u}else return super.apply(e,t)}call(e,t){return z(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Pe(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new B(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:r},o=B6((d,p)=>{let f=this.cell.call([d].concat(p),i);return[f[0],f.slice(1)]},e,a,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],c=o[1],u=o[2];this.stateful&&this.resetStates(u,r);let h=this.returnSequences?c:l;return this.returnState?[h].concat(u):h})}getInitialState(e){return z(()=>{let t=Et(e.shape);return t=Ee(t,[1,2]),t=Ic(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?MA(t,[1,n]):t):this.cell.stateSize>1?[MA(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()===Ur.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let r=t.cell,a=kr(r,n);return new e(Object.assign(t,{cell:a}))}};Ur.className="RNN";re.registerClass(Ur);var Tc=class extends qe{},e0=class extends Tc{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,Ht(this.units,"units"),this.activation=Ga(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=zl([1,ja([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,ja([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=lt(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 z(()=>{if(e=e,e.length!==2)throw new B(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let r=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=Vr(P(e,s),this.kernel.read()):a=Vr(e,this.kernel.read()),this.bias!=null&&(a=jr(a,this.bias.read())),i!=null&&(n=P(n,i));let o=se(a,Vr(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ha(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),recurrentRegularizer:ut(this.recurrentRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),recurrentConstraint:Lt(this.recurrentConstraint),biasConstraint:Lt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};e0.className="SimpleRNNCell";re.registerClass(e0);var ky=class extends Ur{constructor(e){e.cell=new e0(e),super(e)}call(e,t){return z(()=>{this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};ky.className="SimpleRNN";re.registerClass(ky);var t0=class extends Tc{constructor(e){super(e);if(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 B("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Ht(this.units,"units"),this.activation=Ga(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ga(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=zl([1,ja([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,ja([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=lt(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 z(()=>{if(e=e,e.length!==2)throw new B(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,r=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=P(e,a[0]));let c=Vr(e,this.kernel.read());this.useBias&&(c=jr(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,s[0]));let u=this.recurrentKernel.read(),[h,d]=zt(u,[2*this.units,this.units],u.rank-1),p=Vr(r,h),[f,m,A]=zt(c,3,c.rank-1),[y,g]=zt(p,2,p.rank-1);i=this.recurrentActivation.apply(se(f,y)),o=this.recurrentActivation.apply(se(m,g));let b=Vr(P(o,r),d);l=this.activation.apply(se(A,b));let w=se(P(i,r),P(se(1,_t(i)),l));return[w,w]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ha(this.activation),recurrentActivation:Ha(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),recurrentRegularizer:ut(this.recurrentRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),recurrentConstraint:Lt(this.recurrentConstraint),biasConstraint:Lt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};t0.className="GRUCell";re.registerClass(t0);var Iy=class extends Ur{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 t0(e),super(e)}call(e,t){return z(()=>{this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Iy.className="GRU";re.registerClass(Iy);var Oc=class extends Tc{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,Ht(this.units,"units"),this.activation=Ga(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ga(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=zl([1,ja([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,ja([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=lt(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 r;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;r=new(t=class extends or{apply(i,o){let l=a.apply([s]),c=new Cp().apply([s]),u=a.apply([s*2]);return Fv(Fv(l,c),u)}},t.className="CustomInit",t)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return z(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new B(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,c,u;0<this.dropout&&this.dropout<1&&(e=P(e,s[0]));let h=Vr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,i[0])),h=se(h,Vr(r,this.recurrentKernel.read())),this.useBias&&(h=jr(h,this.bias.read()));let[d,p,f,m]=zt(h,4,h.rank-1);o=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(p),c=se(P(l,a),P(o,this.activation.apply(f))),u=this.recurrentActivation.apply(m);let A=P(u,this.activation.apply(c));return[A,A,c]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ha(this.activation),recurrentActivation:Ha(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:ut(this.kernelRegularizer),recurrentRegularizer:ut(this.recurrentRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),recurrentConstraint:Lt(this.recurrentConstraint),biasConstraint:Lt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Oc.className="LSTMCell";re.registerClass(Oc);var Ny=class extends Ur{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 Oc(e),super(e)}call(e,t){return z(()=>{this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Ny.className="LSTM";re.registerClass(Ny);var Qp=class extends Tc{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 z(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=r[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),a.push(s.slice(1))}n=[];for(let i of a.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){GA(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,r)=>{Si(`RNNCell_${r}`,()=>{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()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,n={}){let r=[];for(let a of t.cells)r.push(kr(a,n));return new e({cells:r})}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 qA(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],a[s]])}XA(t)}};Qp.className="StackedRNNCells";re.registerClass(Qp);function qa(e){let{ones:t,rate:n,training:r=!1,count:a=1}=e,s=()=>$v(t(),n),i=()=>Sc(s,t,r);return!a||a<=1?jt(i().clone()):Array(a).fill(void 0).map(i).map(o=>jt(o.clone()))}var bre=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]]);return n},V6=class extends Ur{constructor(e){if(e.unroll)throw new $e("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new $e("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Gt({ndim:5})]}call(e,t){return z(()=>{if(this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new B("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}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 z(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=Et(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){z(()=>{if(!this.stateful)throw new la("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new B("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(()=>Et(a)):this.states_=[Et(a)];else if(e==null)ve(this.states_),this.keptStates!=null&&(ve(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Et(a)):this.states_[0]=Et(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`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()):ve(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!v.arraysEqual(i.shape,o))throw new B(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>jt(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:r,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],c=e[o?4:3],u=Ir(l,r[0],a,s[0],i[0]),h=Ir(c,r[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[n,u,h]:[u,h,n]]}};V6.className="ConvRNN2D";var n0=class extends Oc{constructor(e){let{filters:t,kernelSize:n,strides:r,padding:a,dataFormat:s,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,Ht(this.filters,"filters"),this.kernelSize=Vl(n,2,"kernelSize"),this.kernelSize.forEach(o=>Ht(o,"kernelSize")),this.strides=Vl(r||1,2,"strides"),this.strides.forEach(o=>Ht(o,"strides")),this.padding=a||"valid",Kn(this.padding),this.dataFormat=s||"channelsLast",St(this.dataFormat),this.dilationRate=Vl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Ht(o,"dilationRate"))}build(e){var t;e=lt(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new B(`The channel dimension of the input should be defined. Found ${e[n]}`);let r=e[n],a=4,s=this.kernelSize.concat([r,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,c=this.filters;o=new(t=class extends or{apply(u,h){let d=l.apply([c]),p=Or([c]),f=l.apply([c*2]);return DA([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return z(()=>{if(e.length!==3)throw new B(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(Y,ae,te)=>!ae||!ae[te]?Y:P(ae[te],Y),c=l(r,o,0),u=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[b,w,_,x]=zt(this.kernel.read(),i,g),[N,T,E,F]=this.useBias?zt(this.bias.read(),i):[null,null,null,null];c=this.inputConv(c,b,N,this.padding),u=this.inputConv(u,w,T,this.padding),h=this.inputConv(h,_,E,this.padding),d=this.inputConv(d,x,F,this.padding);let[$,L,V,j]=zt(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,$),m=this.recurrentConv(m,L),A=this.recurrentConv(A,V),y=this.recurrentConv(y,j);let U=this.recurrentActivation.apply(se(c,f)),X=this.recurrentActivation.apply(se(u,m)),G=se(P(X,s),P(U,this.activation.apply(se(h,A)))),ee=P(this.recurrentActivation.apply(se(d,y)),this.activation.apply(G));return[ee,ee,G]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=bre(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=na(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?jr(a,n,this.dataFormat):a}recurrentConv(e,t){return na(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};n0.className="ConvLSTM2DCell";re.registerClass(n0);var Sy=class extends V6{constructor(e){let t=new n0(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};Sy.className="ConvLSTM2D";re.registerClass(Sy);var r0=class extends qe{constructor(e){super(e);this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,n=[];for(let r=0;r<this.noiseShape.length;++r)n.push(this.noiseShape[r]==null?t[r]:this.noiseShape[r]);return n}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,a=this.getNoiseShape(n);return Sc(()=>$v(n,this.rate,a,this.seed),()=>n,r)}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()}};r0.className="Dropout";re.registerClass(r0);var Ty=class extends r0{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};Ty.className="SpatialDropout1D";re.registerClass(Ty);var Ey=class extends qe{constructor(e){super(e);if(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,Ht(this.units,"units"),this.activation=Ga(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Wt(e.kernelConstraint),this.biasConstraint=Wt(e.biasConstraint),this.kernelRegularizer=gt(e.kernelRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.activityRegularizer=gt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=lt(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=lt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=vv(this.activation.getClassName()),a;return r!=null?a=Vr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=Vr(n,this.kernel.read()),this.bias!=null&&(a=jr(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:Ha(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),biasConstraint:Lt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Ey.className="Dense";re.registerClass(Ey);var Cy=class extends qe{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=lt(e);for(let t of e.slice(1))if(t==null)throw new B(`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],Va(e,1)]}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let r=[0];for(let a=2;a<n.rank;++a)r.push(a);r.push(1),n=n.transpose(r)}return Hee(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};Cy.className="Flatten";re.registerClass(Cy);var Ry=class extends qe{constructor(e){super(e);this.supportsMasking=!0,this.activation=Ga(e.activation)}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.activation.apply(n)})}getConfig(){let e={activation:Ha(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};Ry.className="Activation";re.registerClass(Ry);var My=class extends qe{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 z(()=>(e=Pe(e),jee(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};My.className="RepeatVector";re.registerClass(My);var Fy=class extends qe{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.",r=t.slice(),a=1,s=null;for(let o=0;o<r.length;++o){let l=r[o];if(this.isUnknown(l))if(s===null)s=o;else throw new B("Can only specifiy one unknown dimension.");else a*=l}let i=Va(e);if(s!==null){if(a===0||i%a!=0)throw new B(n);r[s]=i/a}else if(i!==a)throw new B(n);return r}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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=n.shape,a=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};Fy.className="Reshape";re.registerClass(Fy);var Dy=class extends qe{constructor(e){super(e);if(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=_r(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 Gt({ndim:this.dims.length+1})]}computeOutputShape(e){e=lt(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return nt(Pe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Dy.className="Permute";re.registerClass(Dy);var $y=class extends qe{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Pe(e),r=-1;return Wu(pi(n,this.maskValue),r)}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=-1,a=!0,s=Wu(pi(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};$y.className="Masking";re.registerClass($y);var Oy=class extends qe{constructor(e){super(e);if(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(pt(e.inputLength))}this.inputDim=e.inputDim,Ht(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Ht(this.outputDim,"outputDim"),this.embeddingsInitializer=yt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=gt(e.embeddingsRegularizer),this.activityRegularizer=gt(e.activityRegularizer),this.embeddingsConstraint=Wt(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 z(()=>this.maskZero?(e=Pe(e),pi(e,Ue(e))):null)}computeOutputShape(e){if(e=lt(e),this.inputLength==null)return[...e,this.outputDim];let 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extends qe{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new $e}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 r=0;r<t.length;++r){let a=e[e.length-t.length+r],s=t[r];if(a==null||s==null||a<0||s<0)n.push(null);else if(a===1)n.push(s);else if(s===1)n.push(a);else{if(a!==s)throw new B("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[lt(e)]),e=e,e.length<2)throw new B(`A merge layer should be called on an Array of at least 2 inputs. 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e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Vy.className="Concatenate";re.registerClass(Vy);function zc(e,t){for(;e<0;)e+=t;return e}function wre(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new $e("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 $e("batchDot is not implemented for complex64-type Tensors yet.");let r=e.shape.length,a=t.shape.length;n==null&&(n=[r-1,a-2]);let s=n;return z(()=>{let i;if(r>a){i=r-a;let l=[];for(let c=0;c<i;++c)l.push(1);t=t.reshape(t.shape.concat(l))}else if(a>r){i=a-r;let l=[];for(let c=0;c<i;++c)l.push(1);e=e.reshape(e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=e.mul(t).sum(s[0]):o=e.transpose([1,0]).mul(t).sum(s[1]);else{let l=s[0]!==e.shape.length-1,c=s[1]===t.shape.length-1;o=e.matMul(t,l,c)}if(i>0){let l;r>a?l=r+a-3:l=r-1;let c=[];for(let u=l;u<l+i;++u)c.push(u);o=o.squeeze(c)}return o.shape.length===1&&(o=o.expandDims(1)),o})}var jy=class extends Mi{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 $e("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new B(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new B(`A \`Dot\` layer must be called on exactly 2 inputs, but 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Uy=class extends qe{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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return Sc(()=>Ep(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};Uy.className="GaussianNoise";re.registerClass(Uy);var Hy=class extends qe{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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.rate>0&&this.rate<1?Sc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(Ep(n.shape,1,r))},()=>n,t.training||!1):n})}};Hy.className="GaussianDropout";re.registerClass(Hy);var Gy=class extends qe{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return 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r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return z(()=>{let n=t.training==null?!1:t.training,r=Pe(e),a=r.shape,s=a.length,i=_r(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=ki(1,s);l[o]=a[o];let c=i.slice();c.sort();let u=!v.arraysEqual(c,_r(0,s).slice(0,s-1)),h=()=>{if(u){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,b=this.scale?this.gamma.read().reshape(l):null;return Pc(r,A,y,g,b,this.epsilon)}else return 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extends qe{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=yt(e.betaInitializer||"zeros"),this.gammaInitializer=yt(e.gammaInitializer||"ones"),this.betaRegularizer=gt(e.betaRegularizer),this.gammaRegularizer=gt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=lt(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a<this.axis.length;++a)this.axis[a]<0&&(this.axis[a]+=t);for(let a of this.axis)if(a<0||a>=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==Ba(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(a=>e[a]),r=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,r):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,r):this.beta=null,this.built=!0}call(e,t){let n=Pe(e),r=n.shape,a=r.length;return z(()=>{let s=!0,{mean:i,variance:o}=Sd(n,this.axis,s),l=ki(1,a);for(let f of this.axis)l[f]=r[f];let c=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,u=c(this.gamma.read()),h=c(this.beta.read()),d=[],p=[];for(let f=0;f<a;++f)this.axis.indexOf(f)!==-1?(d.push(r[f]),p.push(1)):(d.push(1),p.push(r[f]));return i=i.tile(d),o=o.tile(d),u=u.tile(p),h=h.tile(p),Pc(n,i,o,h,u,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:kt(this.betaInitializer),gammaInitializer:kt(this.gammaInitializer),betaRegularizer:ut(this.betaRegularizer),gammaRegularizer:ut(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};Xy.className="LayerNormalization";re.registerClass(Xy);function Ire(e,t,n){return z(()=>{if(e.rank!==4)throw new B(`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 B("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=br()),n!=="channelsLast"&&n!=="channelsFirst")throw new B(`Unknown data format: ${n}. 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s==="max"?i=Ku(e,t,n,o):i=Vu(e,t,n,o),a==="channelsFirst"&&(i=nt(i,[0,3,1,2])),i})}function j6(e,t,n,r,a,s){return z(()=>{St(a),Sv(s),Kn(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=br()),s==null&&(s="max"),e=z6(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=ym(e,t,n,o):i=rm(e,t,n,o),a==="channelsFirst"&&(i=nt(i,[0,4,1,2,3])),i})}var U6=class extends qe{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 B(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Ht(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 B(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Ht(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,Kn(this.padding),this.inputSpec=[new Gt({ndim:3})]}computeOutputShape(e){e=lt(e);let t=Ir(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return z(()=>{this.invokeCallHook(e,t),e=Ic(Pe(e),2);let n=this.poolingFunction(Pe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return Oa(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},Zy=class extends U6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"max")}};Zy.className="MaxPooling1D";re.registerClass(Zy);var Yy=class extends U6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return 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t=Ir(t,this.poolSize[0],this.padding,this.strides[0]),n=Ir(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 z(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(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}},Jy=class extends H6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"max")}};Jy.className="MaxPooling2D";re.registerClass(Jy);var Qy=class extends H6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"avg")}};Qy.className="AveragePooling2D";re.registerClass(Qy);var G6=class extends qe{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 B(`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];Ht(this.poolSize,"poolSize"),Ht(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,St(this.dataFormat),Kn(this.padding),this.inputSpec=[new Gt({ndim:5})]}computeOutputShape(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Ir(t,this.poolSize[0],this.padding,this.strides[0]),n=Ir(n,this.poolSize[1],this.padding,this.strides[1]),r=Ir(r,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}call(e,t){return z(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(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}},e2=class extends G6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),j6(e,t,n,r,a,"max")}};e2.className="MaxPooling3D";re.registerClass(e2);var t2=class extends G6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),j6(e,t,n,r,a,"avg")}};t2.className="AveragePooling3D";re.registerClass(t2);var q6=class extends qe{constructor(e){super(e);this.inputSpec=[new Gt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new $e}},n2=class extends q6{constructor(e){super(e||{})}call(e,t){return z(()=>{let n=Pe(e);return vt(n,1)})}};n2.className="GlobalAveragePooling1D";re.registerClass(n2);var r2=class extends q6{constructor(e){super(e||{})}call(e,t){return z(()=>{let n=Pe(e);return vn(n,1)})}};r2.className="GlobalMaxPooling1D";re.registerClass(r2);var X6=class extends qe{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,St(this.dataFormat),this.inputSpec=[new Gt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new $e}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},a2=class extends X6{call(e,t){return z(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?vt(n,[1,2]):vt(n,[2,3])})}};a2.className="GlobalAveragePooling2D";re.registerClass(a2);var s2=class extends X6{call(e,t){return z(()=>{let n=Pe(e);return 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e(s)}},i2=class extends K6{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=lt(e),e.length<3)throw new B(`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=lt(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))}call(e,t){return z(()=>(e=Pe(e),B6((n,r)=>[Pe(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};i2.className="TimeDistributed";re.registerClass(i2);function Nre(e){Ni(Pee,"BidirectionalMergeMode",e)}var Sre="concat",o2=class extends K6{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=kr(n),t.goBackwards=t.goBackwards!==!0;let r={};if(r.className=e.layer.getClassName(),r.config=t,this.backwardLayer=kr(r),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?Sre:e.mergeMode,Nre(this.mergeMode),e.weights)throw new $e("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,r,a;return this.returnState&&(a=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,r=[n]):this.mergeMode==null?r=[n,n.slice()]:r=[n],this.returnState?this.mergeMode==null?r.concat(a).concat(a.slice()):[n].concat(a).concat(a.slice()):Sn(r)}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=W6(e,n,r,this.numConstants);if(e=a.inputs,n=a.initialState,r=a.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&r==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new B("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let c=n.map(u=>new 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+        ${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 a=n===0?0:t.size/n,s=[];z(()=>{t=H(t,[1,n,a]);for(let o=0;o<e.length;++o){let l=o===0?0:r[o-1],c=[0,l,0],u=[1,e[o],a];s[o]=H(Ce(t,c,u),this.elementShape)}return s});let i=[];for(let o=0;o<e.length;o++)i[o]=o;this.writeMany(i,s)}},Wc=class{constructor(e,t,n,r=-1){this.tensors=e,this.elementShape=t,this.elementDtype=n,e!=null&&e.forEach(a=>{if(n!==a.dtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${a.dtype}`);ur(t,a.shape,"TensorList shape mismatch: "),jt(a)}),this.idTensor=ge(0),this.maxNumElements=r,jt(this.idTensor)}get id(){return this.idTensor.id}copy(){return new Wc([...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.`);ur(e,this.elementShape,"TensorList shape mismatch: ");let r=Lc(this.elementShape,this.tensors,e);return z(()=>{let a=this.tensors.map(s=>H(s,r));return un(a,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=Lc(this.elementShape,this.tensors,e),r=this.tensors.pop();return ur(r.shape,e,"TensorList shape mismatch: "),H(r,n)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(ur(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");jt(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}.`);this.tensors.length=e}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.`);ur(this.tensors[e].shape,t,"TensorList shape mismatch: ");let r=Lc(this.elementShape,this.tensors,t);return H(this.tensors[e],r)}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.`);ur(this.elementShape,t.shape,"TensorList shape mismatch: "),jt(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}`);ur(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size());let r=Lc(this.elementShape,this.tensors,n);return e.length===0?yr([],[0].concat(r)):z(()=>{let a=e.map(s=>H(this.tensors[s],r));return un(a,0)})}concat(e,t){if(!!e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);ur(this.elementShape,t,"TensorList shape mismatch: ");let n=Lc(this.elementShape,this.tensors,t);return this.size()===0?yr([],[0].concat(n)):z(()=>{let r=this.tensors.map(a=>H(a,n));return rt(r,0)})}};function xae(e,t,n){let r=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 a=e.shape.slice(1);ur(a,t,"TensorList shape mismatch: ");let s=ar(e);return new Wc(s,t,r)}function bae(e,t,n){return new Wc([],e,t,n)}function wae(e,t,n,r){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);let a=Math.max(...t);if(r!=null&&r!==-1&&a>=r)throw new Error(`Max index must be < array size (${a}  vs. ${r})`);let s=new Wc([],n,e.dtype,r),i=ar(e,0);return t.forEach((o,l)=>{s.setItem(o,i[l])}),s}function _ae(e,t,n){let r=0,a=t.map(u=>(r+=u,r));if(r!==e.shape[0])throw new Error(`Expected sum of lengths to be equal to
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r=k("size",e,t,n),a=k("dtype",e,t,n),s=k("elementShape",e,t,n),i=k("dynamicSize",e,t,n),o=k("clearAfterRead",e,t,n),l=k("identicalElementShapes",e,t,n),c=k("name",e,t,n),u=new Pne(c,a,r,s,l,i,o);return n.addTensorArray(u),[u.idTensor,ge(1)]}case"TensorArrayWriteV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.write(a,s),[i.idTensor]}case"TensorArrayReadV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n);return[n.getTensorArray(r.id).read(a)]}case"TensorArrayGatherV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("dtype",e,t,n);return[n.getTensorArray(r.id).gather(a,s)]}case"TensorArrayScatterV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.scatter(a,s),[i.idTensor]}case"TensorArrayConcatV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id),s=k("dtype",e,t,n);return[a.concat(s)]}case"TensorArraySplitV3":{let r=k("tensorArrayId",e,t,n),a=k("tensor",e,t,n),s=k("lengths",e,t,n),i=n.getTensorArray(r.id);return i.split(s,a),[i.idTensor]}case"TensorArraySizeV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return[ge(a.size(),"int32")]}case"TensorArrayCloseV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return a.clearAndClose(),[a.idTensor]}case"TensorListSetItem":{let r=k("tensorListId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorList(r.id);return i.setItem(a,s),[i.idTensor]}case"TensorListGetItem":{let r=k("tensorListId",e,t,n),a=k("index",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).getItem(a,s,i)]}case"TensorListScatterV2":case"TensorListScatter":{let r=k("indices",e,t,n),a=k("tensor",e,t,n),s=k("elementShape",e,t,n),i=k("numElements",e,t,n),o=Bne(a,r,s,i);return n.addTensorList(o),[o.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let r=k("elementShape",e,t,n),a=k("elementDType",e,t,n),s;e.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=k(s,e,t,n),o=Wne(r,a,i);return n.addTensorList(o),[o.idTensor]}case"TensorListGather":{let r=k("tensorListId",e,t,n),a=k("indices",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).gather(a,i,s)]}case"TensorListStack":{let r=k("tensorListId",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=k("numElements",e,t,n);return[n.getTensorList(r.id).stack(a,s,i)]}case"TensorListFromTensor":{let r=k("tensor",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=Lne(r,a,s);return n.addTensorList(i),[i.idTensor]}case"TensorListConcat":{let r=k("tensorListId",e,t,n),a=n.getTensorList(r.id),s=k("dtype",e,t,n),i=k("elementShape",e,t,n);return[a.concat(s,i)]}case"TensorListPushBack":{let r=k("tensorListId",e,t,n),a=k("tensor",e,t,n),s=n.getTensorList(r.id);return s.pushBack(a),[s.idTensor]}case"TensorListPopBack":{let 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c}processChildNodes(e,t,n,r,a,s){e.children.forEach(i=>{let[o]=ha(i.name,n);a[o]||!s.has(i.name)||(i.op==="Merge"?i.inputNames.some(l=>!!En(l,r,n))&&(a[o]=!0,t.push({contexts:n.currentContext,node:i})):i.inputNames.every(l=>!!En(l,r,n))&&(a[o]=!0,t.push({contexts:n.currentContext,node:i})))})}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],[r]=Ln(t),a=this.graph.nodes[r];if(a.attrParams.shape&&a.attrParams.shape.value){let s=a.attrParams.shape.value,i=s.length===n.shape.length&&n.shape.every((o,l)=>s[l]===-1||s[l]===o);v.assert(i,()=>`The shape of dict['${a.name}'] provided in model.execute(dict) must be [${s}], but was [${n.shape}]`)}a.attrParams.dtype&&a.attrParams.dtype.value&&v.assert(n.dtype===a.attrParams.dtype.value,()=>`The dtype of dict['${a.name}'] provided in model.execute(dict) must be ${a.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let r=this._signature.inputs[n];t[r.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[r]=Ln(n);return this.graph.nodes[r]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${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]=Ln(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},hre=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},dre="?tfjs-format=file",pre="model.json",Yv=class{constructor(e,t={}){this.modelUrl=e,this.loadOptions=t,this.version="n/a",t==null&&(this.loadOptions={}),this.resourceManager=new hre}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=wn.browserHTTPRequest(e,this.loadOptions);else{let t=wn.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(wn.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}async load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=await this.handler.load();return this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,n;this.artifacts.userDefinedMetadata!=null&&this.artifacts.userDefinedMetadata.signature!=null?n=this.artifacts.userDefinedMetadata.signature:n=this.artifacts.signature,this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let r=wn.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new y2(Vv.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let a=Vv.Instance.transformGraph(e.modelInitializer);this.initializer=new y2(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=wn.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${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){return this.execute(e,this.outputNodes)}normalizeInputs(e){if(!(e instanceof We)&&!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 ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,r)=>(t[n]=e[r],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function ct(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. 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uae=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],cae=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],hae=[33,133,362,263,1,78,308],the=uae.map(e=>Uc[e]),nhe=cae.map(e=>Uc[e]),rhe=hae.map(e=>Uc[e]);var V2=Xr.leftEyeLower0,U2=Xr.rightEyeLower0,ql={leftBounds:[V2[0],V2[V2.length-1]],rightBounds:[U2[0],U2[U2.length-1]]},N0={count:468,mouth:13,symmetryLine:[13,Xr.midwayBetweenEyes[0]]},C6={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Xl={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function S0(e,t,n,r){for(let a=0;a<B2.length;a++){let{key:s,indices:i}=B2[a],o=Xr[`${n}${s}`];if(!r||r.includes(s))for(let l=0;l<i.length;l++){let c=i[l];e[o[l]]=[t[c][0],t[c][1],(t[c][2]+e[o[l]][2])/2]}}}var j2=class{constructor(t,n,r){var a,s;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=r,this.boxSize=((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((s=t==null?void 0:t.model)==null?void 0:s.inputs[0].shape[2]),this.irisSize=(r==null?void 0:r.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(t,n,r,a){let s=Vc({startPoint:n.startPoint,endPoint:n.endPoint}),i=t.map(h=>[s[0]/this.meshSize*(h[0]-this.meshSize/2),s[1]/this.meshSize*(h[1]-this.meshSize/2),h[2]]),o=r!==0?I0(r,[0,0]):k0,l=r!==0?i.map(h=>[...E6(h,o),h[2]]):i,c=r!==0?T6(a):k0,u=[...Hl({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(h=>[h[0]+Ya(u,c[0]),h[1]+Ya(u,c[1]),h[2]])}getLeftToRightEyeDepthDifference(t){let n=t[ql.leftBounds[0]][2],r=t[ql.rightBounds[0]][2];return n-r}getEyeBox(t,n,r,a,s=!1){let i=v0(_0(this.calculateLandmarksBoundingBox([t[r],t[a]]),this.irisEnlarge)),o=Vc(i),l=ze.cropAndResize(n,[[i.startPoint[1]/this.meshSize,i.startPoint[0]/this.meshSize,i.endPoint[1]/this.meshSize,i.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return s&&fr.flags.IS_BROWSER&&(l=ze.flipLeftRight(l)),{box:i,boxSize:o,crop:l}}getEyeCoords(t,n,r,a=!1){let s=[];for(let i=0;i<Xl.numCoordinates;i++){let o=t[i*3],l=t[i*3+1],c=t[i*3+2];s.push([(a?1-o/this.irisSize:o/this.irisSize)*r[0]+n.startPoint[0],l/this.irisSize*r[1]+n.startPoint[1],c])}return{rawCoords:s,iris:s.slice(Xl.index)}}getAdjustedIrisCoords(t,n,r){let a=t[Xr[`${r}EyeUpper0`][Xl.upperCenter]][2],s=t[Xr[`${r}EyeLower0`][Xl.lowerCenter]][2],i=(a+s)/2;return n.map((o,l)=>{let c=i;return l===2?c=a:l===4&&(c=s),[o[0],o[1],c]})}async predict(t,n){let r=!1,a;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(a=await this.boundingBoxDetector.getBoundingBoxes(t),this.skipped=0),n.videoOptimized&&this.skipped++,!n.videoOptimized||a&&a.boxes&&(!n.face.mesh.enabled||a.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let i of a.boxes)this.storedBoxes.push({startPoint:i.box.startPoint.dataSync(),endPoint:i.box.endPoint.dataSync(),landmarks:i.landmarks,confidence:i.confidence});this.storedBoxes.length>0&&(r=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),r){if(!a||!a.boxes||a.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let i=0;i<this.storedBoxes.length;i++){let o=I6({startPoint:this.storedBoxes[i].startPoint,endPoint:this.storedBoxes[i].endPoint},a.scaleFactor),l=_0(o),c=v0(l),u=this.storedBoxes[i].landmarks.arraySync(),h=this.storedBoxes[i].confidence;this.storedBoxes[i]={...c,confidence:h,landmarks:u}}}a&&a.boxes&&a.boxes.forEach(i=>{i.box.startPoint.dispose(),i.box.endPoint.dispose(),i.landmarks.dispose()});let s=z(()=>this.storedBoxes.map((i,o)=>{let l=i.confidence,c,u=0,h;if(n.face.detector.rotation&&n.face.mesh.enabled&&fr.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=N0.count?N0.symmetryLine:C6.symmetryLine;u=W2(i.landmarks[_],i.landmarks[x]);let N=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],E=ze.rotateWithOffset(t,u,0,T);h=I0(-u,N),n.face.mesh.enabled?c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.meshSize,this.meshSize]).div(255):c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.boxSize,this.boxSize]).div(255)}else{h=k0;let _=t.clone();n.face.mesh.enabled?c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.meshSize,this.meshSize]).div(255):c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:i,faceConfidence:null,boxConfidence:l,confidence:i.confidence,image:c};let[,d,p]=this.meshDetector.predict(c),f=d.dataSync()[0];if(f<n.face.detector.minConfidence)return null;let A=H(p,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:_,boxSize:x,crop:N}=this.getEyeBox(A,c,ql.leftBounds[0],ql.leftBounds[1],!0),{box:T,boxSize:E,crop:F}=this.getEyeBox(A,c,ql.rightBounds[0],ql.rightBounds[1]),L=this.irisModel.predict(rt([N,F])).dataSync(),V=L.slice(0,Xl.numCoordinates*3),{rawCoords:U,iris:j}=this.getEyeCoords(V,_,x,!0),X=L.slice(Xl.numCoordinates*3),{rawCoords:G,iris:ee}=this.getEyeCoords(X,T,E),Y=this.getLeftToRightEyeDepthDifference(A);Math.abs(Y)<30?(S0(A,U,"left",null),S0(A,G,"right",null)):Y<1?S0(A,U,"left",["EyeUpper0","EyeLower0"]):S0(A,G,"right",["EyeUpper0","EyeLower0"]);let ae=this.getAdjustedIrisCoords(A,j,"left"),te=this.getAdjustedIrisCoords(A,ee,"right");A=A.concat(ae).concat(te)}let y=this.transformRawCoords(A,i,u,h);i=_0(this.calculateLandmarksBoundingBox(y),1.5);let g=kn(y);if(n.face.detector.rotation&&n.face.mesh.enabled&&(n.face.description.enabled||n.face.embedding.enabled)&&fr.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=N0.count?N0.symmetryLine:C6.symmetryLine;u=W2(i.landmarks[_],i.landmarks[x]);let N=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],E=ze.rotateWithOffset(t,u,0,T);h=I0(-u,N),c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.meshSize,this.meshSize]).div(255)}let w={coords:g,box:i,faceConfidence:f,boxConfidence:l,image:c,rawCoords:A},b=v0(i);return this.storedBoxes[o]={...b,landmarks:y,confidence:i.confidence,faceConfidence:f},w}));return s=s.filter(i=>i!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(i=>i.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s,landmarks:t}}};var G2=class{constructor(t,n,r,a){this.facePipeline=new j2(t,n,r),this.config=a}async estimateFaces(t,n){let r=await this.facePipeline.predict(t,n),a=[];for(let s of r||[]){if(s.isDisposedInternal)continue;let i=s.coords?s.coords.arraySync():[],o=i.map(h=>[h[0]/t.shape[2],h[1]/t.shape[1],h[2]/this.facePipeline.meshSize]),l={};if(i&&i.length>0)for(let h of Object.keys(Xr))l[h]=Xr[h].map(d=>i[d]);let c=s.box?[Math.max(0,s.box.startPoint[0]),Math.max(0,s.box.startPoint[1]),Math.min(t.shape[2],s.box.endPoint[0])-Math.max(0,s.box.startPoint[0]),Math.min(t.shape[1],s.box.endPoint[1])-Math.max(0,s.box.startPoint[1])]:0,u=s.box?[s.box.startPoint[0]/t.shape[2],s.box.startPoint[1]/t.shape[1],(s.box.endPoint[0]-s.box.startPoint[0])/t.shape[2],(s.box.endPoint[1]-s.box.startPoint[1])/t.shape[1]]:[];a.push({confidence:Math.round(100*s.faceConfidence||100*s.boxConfidence||0)/100,boxConfidence:Math.round(100*s.boxConfidence)/100,faceConfidence:Math.round(100*s.faceConfidence)/100,box:c,boxRaw:u,mesh:i,meshRaw:o,annotations:l,image:s.image?s.image.clone():null}),s.coords&&s.coords.dispose(),s.image&&s.image.dispose()}return a}},$i=[null,null,null];async function q2(e){$i=await Promise.all([!$i[0]&&e.face.enabled?k6(e):null,!$i[1]&&e.face.mesh.enabled?ct(e.face.mesh.modelPath,{fromTFHub:e.face.mesh.modelPath.includes("tfhub.dev")}):null,!$i[2]&&e.face.iris.enabled?ct(e.face.iris.modelPath,{fromTFHub:e.face.iris.modelPath.includes("tfhub.dev")}):null]);let t=new G2($i[0],$i[1],$i[2],e);return e.face.mesh.enabled&&e.debug&&Ne(`load model: ${e.face.mesh.modelPath.match(/\/(.*)\./)[1]}`),e.face.iris.enabled&&e.debug&&Ne(`load model: ${e.face.iris.modelPath.match(/\/(.*)\./)[1]}`),t}var R6=Fi,M6=Uc;var rg={};pr(rg,{PoseNet:()=>ag,load:()=>sg});function dae(e){let[t,n,r,a]=e;return{offsets:t,heatmap:n,displacementFwd:r,displacementBwd:a}}var X2=class{constructor(t){this.model=t}predict(t){return z(()=>{let r=t.toFloat().div(127.5).sub(1).expandDims(0),s=this.model.predict(r).map(o=>o.squeeze([0])),i=dae(s);return{heatmapScores:i.heatmap.sigmoid(),offsets:i.offsets,displacementFwd:i.displacementFwd,displacementBwd:i.displacementBwd}})}dispose(){this.model.dispose()}};function K2(e){return Math.floor(e/2)}var Z2=class{constructor(t,n){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(K2(t),t);)this.exchange(t,K2(t)),t=K2(t)}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 r=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[n],this.priorityQueue[n]=r}};function pae(e,t,n,r,a,s){let[i,o]=s.shape,l=!0,c=Math.max(n-a,0),u=Math.min(n+a+1,i);for(let h=c;h<u;++h){let d=Math.max(r-a,0),p=Math.min(r+a+1,o);for(let f=d;f<p;++f)if(s.get(h,f,e)>t){l=!1;break}if(!l)break}return l}function F6(e,t,n){let[r,a,s]=n.shape,i=new Z2(r*a*s,({score:o})=>o);for(let o=0;o<r;++o)for(let l=0;l<a;++l)for(let c=0;c<s;++c){let u=n.get(o,l,c);u<e||pae(c,u,o,l,t,n)&&i.enqueue({score:u,part:{heatmapY:o,heatmapX:l,id:c}})}return i}var Kl=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],Zl=Kl.length,jc=Kl.reduce((e,t,n)=>(e[t]=n,e),{}),fae=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],whe=fae.map(([e,t])=>[jc[e],jc[t]]),$6=[["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 Y2(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+Zl)}}function T0(e,t,n){let{heatmapY:r,heatmapX:a,id:s}=e,{y:i,x:o}=Y2(r,a,s,n);return{x:e.heatmapX*t+o,y:e.heatmapY*t+i}}function J2(e,t,n){return e<t?t:e>n?n:e}function D6(e,t,n,r){let a=n-e,s=r-t;return a*a+s*s}function Q2(e,t){return{x:e.x+t.x,y:e.y+t.y}}function O6(e,t){let n=t.shape[0],r=new Float32Array(n);for(let a=0;a<n;a++){let s=t.get(a,0),i=t.get(a,1);r[a]=e.get(s,i,a)}return r}function mae(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+Zl)}}function Aae(e,t){let n=[];for(let r=0;r<Zl;r++){let a=e.get(r,0).valueOf(),s=e.get(r,1).valueOf(),{x:i,y:o}=mae(a,s,r,t);n.push(o),n.push(i)}return kn(n,[Zl,2])}function z6(e,t,n){return z(()=>e.toTensor().mul(ge(t,"int32")).toFloat().add(Aae(e,n)))}function yae(e,t){return z(()=>{let n=e.div(ge(t,"int32"));return e.sub(n.mul(ge(t,"int32")))})}function P6(e){let[t,n,r]=e.shape;return z(()=>{let s=e.reshape([t*n,r]).argMax(0),i=s.div(ge(n,"int32")).expandDims(1),o=yae(s,n).expandDims(1);return rt([i,o],1)})}var L6=$6.map(([e,t])=>[jc[e],jc[t]]),eg=L6.map(([,e])=>e),W6=L6.map(([e])=>e),gae=16;function xae(e,t,n){let r=n.shape[2]/2;return{y:n.get(t.y,t.x,e),x:n.get(t.y,t.x,r+e)}}function tg(e,t,n,r){return{y:J2(Math.round(e.y/t),0,n-1),x:J2(Math.round(e.x/t),0,r-1)}}function B6(e,t,n,r,a,s,i,o=2){let[l,c]=r.shape,u=tg(t.position,s,l,c),h=xae(e,u,i),p=Q2(t.position,h);for(let A=0;A<o;A++){let y=tg(p,s,l,c),g=Y2(y.y,y.x,n,a);p=Q2({x:y.x*s,y:y.y*s},{x:g.x,y:g.y})}let f=tg(p,s,l,c),m=r.get(f.y,f.x,n);return{position:p,part:Kl[n],score:m}}function V6(e,t,n,r,a,s){let i=t.shape[2],o=eg.length,l=new Array(i),{part:c,score:u}=e,h=T0(c,r,n);l[c.id]={score:u,part:Kl[c.id],position:h};for(let d=o-1;d>=0;--d){let p=eg[d],f=W6[d];l[p]&&!l[f]&&(l[f]=B6(d,l[p],f,t,n,r,s))}for(let d=0;d<o;++d){let p=W6[d],f=eg[d];l[p]&&!l[f]&&(l[f]=B6(d,l[p],f,t,n,r,a))}return l}async function U6(e,t,n){let r=0,a=P6(e),s=await Promise.all([e.buffer(),t.buffer(),a.buffer()]),i=s[0],o=s[1],l=s[2],c=z6(l,gae,o),u=await c.buffer(),d=Array.from(O6(i,l)).map((f,m)=>(r+=f,{position:{y:u.get(m,0),x:u.get(m,1)},part:Kl[m],score:f})),p=d.filter(f=>f.score>n);return a.dispose(),c.dispose(),{keypoints:p,score:r/d.length}}var wae=1,j6=16;function H6(e,t,{x:n,y:r},a){return e.some(({keypoints:s})=>{let i=s[a].position;return D6(r,n,i.y,i.x)<=t})}function bae(e,t,n){return n.reduce((a,{position:s,score:i},o)=>(H6(e,t,s,o)||(a+=i),a),0)/n.length}function G6(e,t,n,r,a,s,i){let o=[],l=F6(i,wae,e),c=a^2;for(;o.length<s&&!l.empty();){let u=l.dequeue(),h=T0(u.part,j6,t);if(H6(o,c,h,u.part.id))continue;let d=V6(u,e,t,j6,n,r),p=bae(o,c,d);p>i&&o.push({keypoints:d,score:Math.round(100*p)/100})}return o}async function q6(e){return Promise.all(e.map(t=>t.buffer()))}function 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r=X6(t,[this.inputSize,this.inputSize]),a=this.baseModel.predict(r,n),s=n.body.maxDetections<2?await kae(t,a,n,this.inputSize):await vae(t,a,n,this.inputSize);return a.heatmapScores.dispose(),a.offsets.dispose(),a.displacementFwd.dispose(),a.displacementBwd.dispose(),r.dispose(),s}dispose(){this.baseModel.dispose()}};async function sg(e){let t=await ct(e.body.modelPath),n=new X2(t);return e.debug&&Ne(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`),new ag(n)}var cg={};pr(cg,{HandPose:()=>dg,load:()=>pg});function E0(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function Hc(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function K6(e,t,n){let r=t.shape[1],a=t.shape[2],s=[[e.startPoint[1]/r,e.startPoint[0]/a,e.endPoint[1]/r,e.endPoint[0]/a]];return ze.cropAndResize(t,s,[0],n)}function Z6(e,t){let 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g=A.dataSync()[0];if(A.dispose(),g>=n.hand.minConfidence){let w=H(y,[-1,3]),b=w.arraySync();y.dispose(),w.dispose();let _=this.transformRawCoords(b,p,l,d),x=this.getBoxForHandLandmarks(_);this.storedBoxes[i]=x;let N={landmarks:_,confidence:g,box:{topLeft:x.startPoint,bottomRight:x.endPoint}};s.push(N)}else this.storedBoxes[i]=null;y.dispose()}else{let l=C0(R0(o),t4),c={confidence:o.confidence,box:{topLeft:l.startPoint,bottomRight:l.endPoint}};s.push(c)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s}}};var 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a4=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],s4=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var cr;async function mg(e){return cr||(cr=await ct(e.body.modelPath),cr.width=parseInt(cr.signature.inputs["input_1:0"].tensorShape.dim[2].size),cr.height=parseInt(cr.signature.inputs["input_1:0"].tensorShape.dim[1].size),e.debug&&Ne(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`)),cr}async function Ag(e,t){if(!cr||!t.body.enabled)return null;let n={width:e.shape[2],height:e.shape[1]},r=ze.resizeBilinear(e,[cr.width,cr.height],!1),a=me(r,[255]);r.dispose();let s;if(t.profile){let u=await an(()=>cr.predict(a));s=u.result.find(h=>h.size===195||h.size===155).dataSync(),u.result.forEach(h=>h.dispose()),fn("blazepose",u)}else{let u=await cr.predict(a);s=u.find(h=>h.size===195||h.size===155).dataSync(),u.forEach(h=>h.dispose())}a.dispose();let i=[],o=s.length===195?a4:s4,l=5;for(let 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c}processChildNodes(e,t,n,r,a,s){e.children.forEach(i=>{let[o]=ha(i.name,n);a[o]||!s.has(i.name)||(i.op==="Merge"?i.inputNames.some(l=>!!En(l,r,n))&&(a[o]=!0,t.push({contexts:n.currentContext,node:i})):i.inputNames.every(l=>!!En(l,r,n))&&(a[o]=!0,t.push({contexts:n.currentContext,node:i})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[r]=Ln(t),a=this.graph.nodes[r];if(a.attrParams.shape&&a.attrParams.shape.value){let s=a.attrParams.shape.value,i=s.length===n.shape.length&&n.shape.every((o,l)=>s[l]===-1||s[l]===o);v.assert(i,()=>`The shape of dict['${a.name}'] provided in model.execute(dict) must be [${s}], but was [${n.shape}]`)}a.attrParams.dtype&&a.attrParams.dtype.value&&v.assert(n.dtype===a.attrParams.dtype.value,()=>`The dtype of dict['${a.name}'] provided in model.execute(dict) must be ${a.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let r=this._signature.inputs[n];t[r.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[r]=Ln(n);return this.graph.nodes[r]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${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]=Ln(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},Hae=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},Gae="?tfjs-format=file",qae="model.json",R4=class{constructor(e,t={}){this.modelUrl=e,this.loadOptions=t,this.version="n/a",t==null&&(this.loadOptions={}),this.resourceManager=new Hae}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=bn.browserHTTPRequest(e,this.loadOptions);else{let t=bn.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(bn.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}async load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=await this.handler.load();return this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,n;this.artifacts.userDefinedMetadata!=null&&this.artifacts.userDefinedMetadata.signature!=null?n=this.artifacts.userDefinedMetadata.signature:n=this.artifacts.signature,this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let r=bn.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new _2(_4.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let a=_4.Instance.transformGraph(e.modelInitializer);this.initializer=new _2(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=bn.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${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){return this.execute(e,this.outputNodes)}normalizeInputs(e){if(!(e instanceof We)&&!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 ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,r)=>(t[n]=e[r],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function ct(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&e.load==null&&(e.endsWith("/")||(e=e+"/"),e=`${e}${qae}${Gae}`);let n=new R4(e,t);return await n.load(),n}var Xae="3.3.0",M4={};Me(M4,{CSVDataset:()=>D4,Dataset:()=>jl,FileDataSource:()=>$4,TextLineDataset:()=>F4,URLDataSource:()=>O4,array:()=>Kae,csv:()=>Yae,func:()=>Jae,generator:()=>Qae,microphone:()=>tse,version_data:()=>nse,webcam:()=>ese,zip:()=>Zae});var rse=Ki(qg()),ase=Ki(qg());function sse(e,t){return l0(e,t)}function l0(e,t,n=new Map,r=new Set){if(e==null)return null;if(r.has(e))throw new Error("Circular references are not supported.");if(n.has(e))return n.get(e);let a=t(e);if(a.recurse&&a.value!==null)throw new Error("A deep map function may not return both a value and recurse=true.");if(a.recurse)if(Ul(e)){let s=Array.isArray(e)?[]:{};r.add(e);for(let i in e){let o=e[i],l=l0(o,t,n,r);s[i]=l}return r.delete(e),s}else throw new Error(`Can't recurse into non-iterable type: ${e}`);else return n.set(e,a.value),a.value}function ise(e,t=P4){return z4(e,t)}function z4(e,t,n=new Set){let r=e[0];if(n.has(r))throw new Error("Circular references are not supported.");let a=t(e);if(a.recurse&&a.value!==null)throw new Error("A deep zip function may not return both a value and recurse=true.");if(a.recurse)if(Ul(r)){let s=Array.isArray(r)?[]:{};n.add(r);for(let i in r){let o=e.map(c=>c[i]),l=z4(o,t,n);s[i]=l}return n.delete(r),s}else throw new Error(`Can't recurse into non-iterable type: ${r}`);else return a.value}function P4(e){return e===null?null:Ul(e[0])?{value:null,recurse:!0}:{value:e,recurse:!1}}async function L4(e,t){let n=new Map;l0(e,t,n);for(let r of Array.from(n.keys())){let a=n.get(r);if(v.isPromise(a)){let s=await a;n.set(r,s)}}return l0(e,t,n)}function Ul(e){return e!=null&&!ArrayBuffer.isView(e)&&(Array.isArray(e)||typeof e=="object"&&!(e instanceof We))}function lse(e){return e==null||ose(e)||Array.isArray(e)||typeof e=="object"&&e instanceof We||v.isTypedArray(e)}function ose(e){return e===null||typeof e!="object"&&typeof e!="function"}function cse(e){return sse(e,use)}function use(e){return e instanceof We?{value:e.clone(),recurse:!1}:Ul(e)?{value:null,recurse:!0}:{value:e,recurse:!1}}var W4=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 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Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},q4=class extends qt{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(J().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new q4(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 r=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(r,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let r=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(r,[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(r=>{let a=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&r({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(a),r({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((r,a)=>n.set(r,a*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),yr(n,t)}},X4=class extends qt{constructor(e,t){super();if(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=sn([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,r=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,a=(1-n)/2,s=(1-r)/2,i=a+n,o=r+s;this.cropBox=kn([s,a,o,i],[1,4])}else this.cropBox=kn([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(J().get("IS_NODE"))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 X4(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=si.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return z(()=>{let t=Jt(ye(e,"float32"),0),n;n=ze.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let r=n.shape;return H(n,r.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},K4=class{},Z4=class extends qt{split(e){return new Sse(this,e)}},Sse=class extends Z4{constructor(e,t){super();this.upstream=e,this.impl=new Tse(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Tse=class extends I2{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},Cse=class extends qt{decodeUTF8(){return new Ese(this)}},Ese=class extends Z4{constructor(e){super();this.upstream=e,this.impl=new Rse(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Rse=class extends I2{constructor(e){super();if(this.upstream=e,J().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=A9();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return J().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},Y4=class extends Cse{constructor(e,t={}){super();this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(J().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((e,t)=>{let n=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,n)));else{let r=new FileReader;r.onload=s=>{let i=r.result;if(i instanceof ArrayBuffer&&(i=new Uint8Array(i)),!(i instanceof Uint8Array))return t(new TypeError("FileReader returned unknown type."));e(i)},r.onabort=s=>t(new Error("Aborted")),r.onerror=s=>t(new Error(s.type));let a=this.file.slice(this.offset,n);r.readAsArrayBuffer(a)}this.offset=n}),done:!1}}};async function Fse(e,t={}){let n,r;typeof e=="string"?n=e:(n=e.url,r=Mse(e));let a=await v.fetch(n,r);if(a.ok){let s=new Uint8Array(await a.arrayBuffer());return new Y4(s,t)}else throw new Error(a.statusText)}var Mse=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 J4(e){return typeof e=="string"&&e.substr(0,7)==="file://"}var $4=class extends K4{constructor(e,t={}){super();this.input=e,this.options=t}async iterator(){if(J4(this.input)&&J().get("IS_NODE")){let e=require("fs");this.input=e.readFileSync(this.input.substr(7))}return new Y4(this.input,this.options)}},O4=class extends K4{constructor(e,t={}){super();this.url=e,this.fileOptions=t}async iterator(){return J4(this.url)?new $4(this.url,this.fileOptions).iterator():Fse(this.url,this.fileOptions)}};function Yae(e,t={}){return new D4(new O4(e),t)}function Jae(e){let t=k2(e);return Wn(async()=>t)}function Qae(e){return Wn(async()=>{let t=await e();return k2(()=>t.next())})}async function ese(e,t){return X4.create(e,t)}async function tse(e){return q4.create(e)}var nse="3.3.0",Dse={tfjs:(sf==null?void 0:sf.version)||void 0,"tfjs-core":(of==null?void 0:of.version)||void 0,"tfjs-data":(lf==null?void 0:lf.version)||void 0,"tfjs-layers":(uf==null?void 0:uf.version)||void 0,"tfjs-converter":(cf==null?void 0:cf.version)||void 0,"tfjs-backend-cpu":Jw||void 0,"tfjs-backend-webgl":b3||void 0,"tfjs-backend-wasm":cv||void 0};var 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jse=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],Use=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],Hse=[33,133,362,263,1,78,308],$de=jse.map(e=>jc[e]),Ode=Use.map(e=>jc[e]),zde=Hse.map(e=>jc[e]);var q2=Xr.leftEyeLower0,X2=Xr.rightEyeLower0,ql={leftBounds:[q2[0],q2[q2.length-1]],rightBounds:[X2[0],X2[X2.length-1]]},N0={count:468,mouth:13,symmetryLine:[13,Xr.midwayBetweenEyes[0]]},c8={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Xl={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function S0(e,t,n,r){for(let a=0;a<G2.length;a++){let{key:s,indices:i}=G2[a],o=Xr[`${n}${s}`];if(!r||r.includes(s))for(let l=0;l<i.length;l++){let c=i[l];e[o[l]]=[t[c][0],t[c][1],(t[c][2]+e[o[l]][2])/2]}}}var K2=class{constructor(t,n,r){var a,s;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=r,this.boxSize=((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((s=t==null?void 0:t.model)==null?void 0:s.inputs[0].shape[2]),this.irisSize=(r==null?void 0:r.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(t,n,r,a){let s=Vc({startPoint:n.startPoint,endPoint:n.endPoint}),i=t.map(h=>[s[0]/this.meshSize*(h[0]-this.meshSize/2),s[1]/this.meshSize*(h[1]-this.meshSize/2),h[2]]),o=r!==0?I0(r,[0,0]):k0,l=r!==0?i.map(h=>[...u8(h,o),h[2]]):i,c=r!==0?l8(a):k0,u=[...Hl({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(h=>[h[0]+Ya(u,c[0]),h[1]+Ya(u,c[1]),h[2]])}getLeftToRightEyeDepthDifference(t){let n=t[ql.leftBounds[0]][2],r=t[ql.rightBounds[0]][2];return n-r}getEyeBox(t,n,r,a,s=!1){let i=v0(_0(this.calculateLandmarksBoundingBox([t[r],t[a]]),this.irisEnlarge)),o=Vc(i),l=ze.cropAndResize(n,[[i.startPoint[1]/this.meshSize,i.startPoint[0]/this.meshSize,i.endPoint[1]/this.meshSize,i.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return s&&fr.flags.IS_BROWSER&&(l=ze.flipLeftRight(l)),{box:i,boxSize:o,crop:l}}getEyeCoords(t,n,r,a=!1){let s=[];for(let i=0;i<Xl.numCoordinates;i++){let o=t[i*3],l=t[i*3+1],c=t[i*3+2];s.push([(a?1-o/this.irisSize:o/this.irisSize)*r[0]+n.startPoint[0],l/this.irisSize*r[1]+n.startPoint[1],c])}return{rawCoords:s,iris:s.slice(Xl.index)}}getAdjustedIrisCoords(t,n,r){let a=t[Xr[`${r}EyeUpper0`][Xl.upperCenter]][2],s=t[Xr[`${r}EyeLower0`][Xl.lowerCenter]][2],i=(a+s)/2;return n.map((o,l)=>{let c=i;return l===2?c=a:l===4&&(c=s),[o[0],o[1],c]})}async predict(t,n){let r=!1,a;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(a=await this.boundingBoxDetector.getBoundingBoxes(t),this.skipped=0),n.videoOptimized&&this.skipped++,!n.videoOptimized||a&&a.boxes&&(!n.face.mesh.enabled||a.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let i of a.boxes)this.storedBoxes.push({startPoint:i.box.startPoint.dataSync(),endPoint:i.box.endPoint.dataSync(),landmarks:i.landmarks,confidence:i.confidence});this.storedBoxes.length>0&&(r=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),r){if(!a||!a.boxes||a.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let i=0;i<this.storedBoxes.length;i++){let o=s8({startPoint:this.storedBoxes[i].startPoint,endPoint:this.storedBoxes[i].endPoint},a.scaleFactor),l=_0(o),c=v0(l),u=this.storedBoxes[i].landmarks.arraySync(),h=this.storedBoxes[i].confidence;this.storedBoxes[i]={...c,confidence:h,landmarks:u}}}a&&a.boxes&&a.boxes.forEach(i=>{i.box.startPoint.dispose(),i.box.endPoint.dispose(),i.landmarks.dispose()});let s=z(()=>this.storedBoxes.map((i,o)=>{let l=i.confidence,c,u=0,h;if(n.face.detector.rotation&&n.face.mesh.enabled&&fr.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=N0.count?N0.symmetryLine:c8.symmetryLine;u=H2(i.landmarks[_],i.landmarks[x]);let N=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],E=ze.rotateWithOffset(t,u,0,T);h=I0(-u,N),n.face.mesh.enabled?c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.meshSize,this.meshSize]).div(255):c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.boxSize,this.boxSize]).div(255)}else{h=k0;let _=t.clone();n.face.mesh.enabled?c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.meshSize,this.meshSize]).div(255):c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:i,faceConfidence:null,boxConfidence:l,confidence:i.confidence,image:c};let[,d,p]=this.meshDetector.predict(c),f=d.dataSync()[0];if(f<n.face.detector.minConfidence)return null;let A=H(p,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:_,boxSize:x,crop:N}=this.getEyeBox(A,c,ql.leftBounds[0],ql.leftBounds[1],!0),{box:T,boxSize:E,crop:F}=this.getEyeBox(A,c,ql.rightBounds[0],ql.rightBounds[1]),L=this.irisModel.predict(rt([N,F])).dataSync(),V=L.slice(0,Xl.numCoordinates*3),{rawCoords:j,iris:U}=this.getEyeCoords(V,_,x,!0),X=L.slice(Xl.numCoordinates*3),{rawCoords:G,iris:ee}=this.getEyeCoords(X,T,E),Y=this.getLeftToRightEyeDepthDifference(A);Math.abs(Y)<30?(S0(A,j,"left",null),S0(A,G,"right",null)):Y<1?S0(A,j,"left",["EyeUpper0","EyeLower0"]):S0(A,G,"right",["EyeUpper0","EyeLower0"]);let ae=this.getAdjustedIrisCoords(A,U,"left"),te=this.getAdjustedIrisCoords(A,ee,"right");A=A.concat(ae).concat(te)}let y=this.transformRawCoords(A,i,u,h);i=_0(this.calculateLandmarksBoundingBox(y),1.5);let g=kn(y);if(n.face.detector.rotation&&n.face.mesh.enabled&&(n.face.description.enabled||n.face.embedding.enabled)&&fr.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=N0.count?N0.symmetryLine:c8.symmetryLine;u=H2(i.landmarks[_],i.landmarks[x]);let N=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],E=ze.rotateWithOffset(t,u,0,T);h=I0(-u,N),c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.meshSize,this.meshSize]).div(255)}let b={coords:g,box:i,faceConfidence:f,boxConfidence:l,image:c,rawCoords:A},w=v0(i);return this.storedBoxes[o]={...w,landmarks:y,confidence:i.confidence,faceConfidence:f},b}));return s=s.filter(i=>i!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(i=>i.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s,landmarks:t}}};var Y2=class{constructor(t,n,r,a){this.facePipeline=new K2(t,n,r),this.config=a}async estimateFaces(t,n){let r=await this.facePipeline.predict(t,n),a=[];for(let s of r||[]){if(s.isDisposedInternal)continue;let i=s.coords?s.coords.arraySync():[],o=i.map(h=>[h[0]/t.shape[2],h[1]/t.shape[1],h[2]/this.facePipeline.meshSize]),l={};if(i&&i.length>0)for(let h of Object.keys(Xr))l[h]=Xr[h].map(d=>i[d]);let c=s.box?[Math.max(0,s.box.startPoint[0]),Math.max(0,s.box.startPoint[1]),Math.min(t.shape[2],s.box.endPoint[0])-Math.max(0,s.box.startPoint[0]),Math.min(t.shape[1],s.box.endPoint[1])-Math.max(0,s.box.startPoint[1])]:0,u=s.box?[s.box.startPoint[0]/t.shape[2],s.box.startPoint[1]/t.shape[1],(s.box.endPoint[0]-s.box.startPoint[0])/t.shape[2],(s.box.endPoint[1]-s.box.startPoint[1])/t.shape[1]]:[];a.push({confidence:Math.round(100*s.faceConfidence||100*s.boxConfidence||0)/100,boxConfidence:Math.round(100*s.boxConfidence)/100,faceConfidence:Math.round(100*s.faceConfidence)/100,box:c,boxRaw:u,mesh:i,meshRaw:o,annotations:l,image:s.image?s.image.clone():null}),s.coords&&s.coords.dispose(),s.image&&s.image.dispose()}return a}},Di=[null,null,null];async function J2(e){Di=await Promise.all([!Di[0]&&e.face.enabled?a8(e):null,!Di[1]&&e.face.mesh.enabled?ct(e.face.mesh.modelPath,{fromTFHub:e.face.mesh.modelPath.includes("tfhub.dev")}):null,!Di[2]&&e.face.iris.enabled?ct(e.face.iris.modelPath,{fromTFHub:e.face.iris.modelPath.includes("tfhub.dev")}):null]);let t=new Y2(Di[0],Di[1],Di[2],e);return e.face.mesh.enabled&&e.debug&&Ne(`load model: ${e.face.mesh.modelPath.match(/\/(.*)\./)[1]}`),e.face.iris.enabled&&e.debug&&Ne(`load model: ${e.face.iris.modelPath.match(/\/(.*)\./)[1]}`),t}var h8=Fi,d8=jc;var lg={};pr(lg,{PoseNet:()=>ug,load:()=>cg});function Gse(e){let[t,n,r,a]=e;return{offsets:t,heatmap:n,displacementFwd:r,displacementBwd:a}}var Q2=class{constructor(t){this.model=t}predict(t){return z(()=>{let r=t.toFloat().div(127.5).sub(1).expandDims(0),s=this.model.predict(r).map(o=>o.squeeze([0])),i=Gse(s);return{heatmapScores:i.heatmap.sigmoid(),offsets:i.offsets,displacementFwd:i.displacementFwd,displacementBwd:i.displacementBwd}})}dispose(){this.model.dispose()}};function eg(e){return Math.floor(e/2)}var tg=class{constructor(t,n){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(eg(t),t);)this.exchange(t,eg(t)),t=eg(t)}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 r=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[n],this.priorityQueue[n]=r}};function qse(e,t,n,r,a,s){let[i,o]=s.shape,l=!0,c=Math.max(n-a,0),u=Math.min(n+a+1,i);for(let h=c;h<u;++h){let d=Math.max(r-a,0),p=Math.min(r+a+1,o);for(let f=d;f<p;++f)if(s.get(h,f,e)>t){l=!1;break}if(!l)break}return l}function p8(e,t,n){let[r,a,s]=n.shape,i=new tg(r*a*s,({score:o})=>o);for(let o=0;o<r;++o)for(let l=0;l<a;++l)for(let c=0;c<s;++c){let u=n.get(o,l,c);u<e||qse(c,u,o,l,t,n)&&i.enqueue({score:u,part:{heatmapY:o,heatmapX:l,id:c}})}return i}var Kl=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],Zl=Kl.length,Uc=Kl.reduce((e,t,n)=>(e[t]=n,e),{}),Xse=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],epe=Xse.map(([e,t])=>[Uc[e],Uc[t]]),f8=[["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 ng(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+Zl)}}function T0(e,t,n){let{heatmapY:r,heatmapX:a,id:s}=e,{y:i,x:o}=ng(r,a,s,n);return{x:e.heatmapX*t+o,y:e.heatmapY*t+i}}function rg(e,t,n){return e<t?t:e>n?n:e}function m8(e,t,n,r){let a=n-e,s=r-t;return a*a+s*s}function ag(e,t){return{x:e.x+t.x,y:e.y+t.y}}function A8(e,t){let n=t.shape[0],r=new Float32Array(n);for(let a=0;a<n;a++){let s=t.get(a,0),i=t.get(a,1);r[a]=e.get(s,i,a)}return r}function Kse(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+Zl)}}function Zse(e,t){let n=[];for(let r=0;r<Zl;r++){let a=e.get(r,0).valueOf(),s=e.get(r,1).valueOf(),{x:i,y:o}=Kse(a,s,r,t);n.push(o),n.push(i)}return kn(n,[Zl,2])}function y8(e,t,n){return z(()=>e.toTensor().mul(ge(t,"int32")).toFloat().add(Zse(e,n)))}function Yse(e,t){return z(()=>{let n=e.div(ge(t,"int32"));return e.sub(n.mul(ge(t,"int32")))})}function g8(e){let[t,n,r]=e.shape;return z(()=>{let s=e.reshape([t*n,r]).argMax(0),i=s.div(ge(n,"int32")).expandDims(1),o=Yse(s,n).expandDims(1);return rt([i,o],1)})}var x8=f8.map(([e,t])=>[Uc[e],Uc[t]]),sg=x8.map(([,e])=>e),b8=x8.map(([e])=>e),Jse=16;function Qse(e,t,n){let r=n.shape[2]/2;return{y:n.get(t.y,t.x,e),x:n.get(t.y,t.x,r+e)}}function ig(e,t,n,r){return{y:rg(Math.round(e.y/t),0,n-1),x:rg(Math.round(e.x/t),0,r-1)}}function w8(e,t,n,r,a,s,i,o=2){let[l,c]=r.shape,u=ig(t.position,s,l,c),h=Qse(e,u,i),p=ag(t.position,h);for(let A=0;A<o;A++){let y=ig(p,s,l,c),g=ng(y.y,y.x,n,a);p=ag({x:y.x*s,y:y.y*s},{x:g.x,y:g.y})}let f=ig(p,s,l,c),m=r.get(f.y,f.x,n);return{position:p,part:Kl[n],score:m}}function _8(e,t,n,r,a,s){let i=t.shape[2],o=sg.length,l=new Array(i),{part:c,score:u}=e,h=T0(c,r,n);l[c.id]={score:u,part:Kl[c.id],position:h};for(let d=o-1;d>=0;--d){let p=sg[d],f=b8[d];l[p]&&!l[f]&&(l[f]=w8(d,l[p],f,t,n,r,s))}for(let d=0;d<o;++d){let p=b8[d],f=sg[d];l[p]&&!l[f]&&(l[f]=w8(d,l[p],f,t,n,r,a))}return l}async function v8(e,t,n){let r=0,a=g8(e),s=await Promise.all([e.buffer(),t.buffer(),a.buffer()]),i=s[0],o=s[1],l=s[2],c=y8(l,Jse,o),u=await c.buffer(),d=Array.from(A8(i,l)).map((f,m)=>(r+=f,{position:{y:u.get(m,0),x:u.get(m,1)},part:Kl[m],score:f})),p=d.filter(f=>f.score>n);return a.dispose(),c.dispose(),{keypoints:p,score:r/d.length}}var eie=1,k8=16;function I8(e,t,{x:n,y:r},a){return e.some(({keypoints:s})=>{let i=s[a].position;return m8(r,n,i.y,i.x)<=t})}function tie(e,t,n){return n.reduce((a,{position:s,score:i},o)=>(I8(e,t,s,o)||(a+=i),a),0)/n.length}function N8(e,t,n,r,a,s,i){let o=[],l=p8(i,eie,e),c=a^2;for(;o.length<s&&!l.empty();){let u=l.dequeue(),h=T0(u.part,k8,t);if(I8(o,c,h,u.part.id))continue;let d=_8(u,e,t,k8,n,r),p=tie(o,c,d);p>i&&o.push({keypoints:d,score:Math.round(100*p)/100})}return o}async function S8(e){return Promise.all(e.map(t=>t.buffer()))}function nie(e,t,n){return{score:e.score,keypoints:e.keypoints.map(({score:r,part:a,position:s})=>({score:r,part:a,position:{x:Math.trunc(s.x*n),y:Math.trunc(s.y*t)}}))}}function T8(e,[t,n]){let r=e.squeeze(0),a=r.resizeBilinear([t,n]);return r.dispose(),a}function og(e,[t,n],[r,a]){return e.map(i=>nie(i,t/r,n/a))}async function rie(e,t,n,r){return new Promise(async a=>{let s=await S8([t.heatmapScores,t.offsets,t.displacementFwd,t.displacementBwd]),i=s[0],o=s[1],l=s[2],c=s[3],u=await N8(i,o,l,c,n.body.nmsRadius,n.body.maxDetections,n.body.scoreThreshold),h=og(u,[e.shape[1],e.shape[2]],[r,r]);a(h)})}async function aie(e,t,n,r){return new Promise(async a=>{let s=await v8(t.heatmapScores,t.offsets,n.body.scoreThreshold),i=og([s],[e.shape[1],e.shape[2]],[r,r]);a(i)})}var ug=class{constructor(t){this.baseModel=t,this.inputSize=t.model.inputs[0].shape[1],this.inputSize<128&&(this.inputSize=257)}async estimatePoses(t,n){let r=T8(t,[this.inputSize,this.inputSize]),a=this.baseModel.predict(r,n),s=n.body.maxDetections<2?await aie(t,a,n,this.inputSize):await rie(t,a,n,this.inputSize);return a.heatmapScores.dispose(),a.offsets.dispose(),a.displacementFwd.dispose(),a.displacementBwd.dispose(),r.dispose(),s}dispose(){this.baseModel.dispose()}};async function cg(e){let t=await ct(e.body.modelPath),n=new Q2(t);return e.debug&&Ne(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`),new ug(n)}var mg={};pr(mg,{HandPose:()=>yg,load:()=>gg});function E0(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function Hc(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function E8(e,t,n){let r=t.shape[1],a=t.shape[2],s=[[e.startPoint[1]/r,e.startPoint[0]/a,e.endPoint[1]/r,e.endPoint[0]/a]];return ze.cropAndResize(t,s,[0],n)}function C8(e,t){let 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g=A.dataSync()[0];if(A.dispose(),g>=n.hand.minConfidence){let b=H(y,[-1,3]),w=b.arraySync();y.dispose(),b.dispose();let _=this.transformRawCoords(w,p,l,d),x=this.getBoxForHandLandmarks(_);this.storedBoxes[i]=x;let N={landmarks:_,confidence:g,box:{topLeft:x.startPoint,bottomRight:x.endPoint}};s.push(N)}else this.storedBoxes[i]=null;y.dispose()}else{let l=C0(R0(o),$8),c={confidence:o.confidence,box:{topLeft:l.startPoint,bottomRight:l.endPoint}};s.push(c)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s}}};var 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P8=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],L8=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var cr;async function bg(e){return cr||(cr=await ct(e.body.modelPath),cr.width=parseInt(cr.signature.inputs["input_1:0"].tensorShape.dim[2].size),cr.height=parseInt(cr.signature.inputs["input_1:0"].tensorShape.dim[1].size),e.debug&&Ne(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`)),cr}async function wg(e,t){if(!cr||!t.body.enabled)return null;let n={width:e.shape[2],height:e.shape[1]},r=ze.resizeBilinear(e,[cr.width,cr.height],!1),a=me(r,[255]);r.dispose();let s;if(t.profile){let u=await an(()=>cr.predict(a));s=u.result.find(h=>h.size===195||h.size===155).dataSync(),u.result.forEach(h=>h.dispose()),fn("blazepose",u)}else{let u=await cr.predict(a);s=u.find(h=>h.size===195||h.size===155).dataSync(),u.forEach(h=>h.dispose())}a.dispose();let i=[],o=s.length===195?P8:L8,l=5;for(let 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r=0;r<t.length;r++){if(!Qa[r]&&ie.bufferedOutput&&(Qa[r]={...t[r]}),n.strokeStyle=ie.color,n.lineWidth=ie.lineWidth,ie.drawPoints)for(let a=0;a<t[r].keypoints.length;a++)n.fillStyle=ie.useDepth&&t[r].keypoints[a].position.z?`rgba(${127.5+2*t[r].keypoints[a].position.z}, ${127.5-2*t[r].keypoints[a].position.z}, 255, 0.5)`:ie.color,ie.bufferedOutput?(Qa[r].keypoints[a][0]=(Qa[r].keypoints[a][0]+t[r].keypoints[a].position.x)/2,Qa[r].keypoints[a][1]=(Qa[r].keypoints[a][1]+t[r].keypoints[a].position.y)/2,z0(n,Qa[r].keypoints[a][0],Qa[r].keypoints[a][1])):z0(n,t[r].keypoints[a].position.x,t[r].keypoints[a].position.y);if(ie.drawLabels&&(n.font=ie.font,t[r].keypoints))for(let a of t[r].keypoints)n.fillStyle=ie.useDepth&&a.position.z?`rgba(${127.5+2*a.position.z}, ${127.5-2*a.position.z}, 255, 0.5)`:ie.color,n.fillText(`${a.part}`,a.position.x+4,a.position.y+4);if(ie.drawPolygons&&t[r].keypoints){let a,s=[];s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),qc(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),s.length===4&&Ig(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftKnee"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftAnkle"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHeel"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftFoot"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),qc(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightKnee"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightAnkle"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHeel"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightFoot"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),qc(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftElbow"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftWrist"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftPalm"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),qc(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightElbow"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightWrist"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightPalm"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),qc(n,s)}}}}async function f4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=ie.font;for(let r of t){if(ie.drawBoxes&&(n.strokeStyle=ie.color,n.fillStyle=ie.color,ie.useRawBoxes?Yl(n,e.width*r.boxRaw[0],e.height*r.boxRaw[1],e.width*r.boxRaw[2],e.height*r.boxRaw[3]):Yl(n,r.box[0],r.box[1],r.box[2],r.box[3]),ie.drawLabels&&(ie.shadowColor&&ie.shadowColor!==""&&(n.fillStyle=ie.shadowColor,n.fillText("hand",r.box[0]+3,1+r.box[1]+ie.lineHeight,r.box[2])),n.fillStyle=ie.labelColor,n.fillText("hand",r.box[0]+2,0+r.box[1]+ie.lineHeight,r.box[2])),n.stroke()),ie.drawPoints&&r.landmarks&&r.landmarks.length>0)for(let a of r.landmarks)n.fillStyle=ie.useDepth?`rgba(${127.5+2*a[2]}, ${127.5-2*a[2]}, 255, 0.5)`:ie.color,z0(n,a[0],a[1]);if(ie.drawPolygons){let a=s=>{if(!!s)for(let i=0;i<s.length;i++)n.lineWidth=ie.lineWidth,n.beginPath(),n.strokeStyle=ie.useDepth?`rgba(${127.5+2*s[i][2]}, ${127.5-2*s[i][2]}, 255, 0.5)`:ie.color,n.moveTo(s[i>0?i-1:0][0],s[i>0?i-1:0][1]),n.lineTo(s[i][0],s[i][1]),n.stroke()};a(r.annotations.indexFinger),a(r.annotations.middleFinger),a(r.annotations.ringFinger),a(r.annotations.pinky),a(r.annotations.thumb)}}}}async function m4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=ie.font;for(let r of t)if(ie.drawBoxes){if(n.strokeStyle=ie.color,n.fillStyle=ie.color,ie.useRawBoxes?Yl(n,e.width*r.boxRaw[0],e.height*r.boxRaw[1],e.width*r.boxRaw[2],e.height*r.boxRaw[3]):Yl(n,r.box[0],r.box[1],r.box[2],r.box[3]),ie.drawLabels){let a=`${Math.round(100*r.score)}% ${r.label}`;ie.shadowColor&&ie.shadowColor!==""&&(n.fillStyle=ie.shadowColor,n.fillText(a,r.box[0]+3,1+r.box[1]+ie.lineHeight,r.box[2])),n.fillStyle=ie.labelColor,n.fillText(a,r.box[0]+2,0+r.box[1]+ie.lineHeight,r.box[2])}n.stroke()}}}async function $ae(e,t){if(!e||!t||!(e instanceof HTMLCanvasElement)||!(t instanceof HTMLCanvasElement))return;let n=e.getContext("2d");n==null||n.drawImage(e,0,0)}async function Dae(e,t){!t||!e||e instanceof HTMLCanvasElement&&(d4(e,t.face),p4(e,t.body),f4(e,t.hand),h4(e,t.gesture),m4(e,t.object))}var P0=`
+`),h.brightness=function(_){let x=(_||0)+1;h.colorMatrix([x,0,0,0,0,0,x,0,0,0,0,0,x,0,0,0,0,0,1,0])},h.saturation=function(_){let x=(_||0)*2/3+1,N=(x-1)*-.5;h.colorMatrix([x,N,N,0,0,N,x,N,0,0,N,N,x,0,0,0,0,0,1,0])},h.desaturate=function(){h.saturation(-1)},h.contrast=function(_){let x=(_||0)+1,N=-128*(x-1);h.colorMatrix([x,0,0,0,N,0,x,0,0,N,0,0,x,0,N,0,0,0,1,0])},h.negative=function(){h.contrast(-2)},h.hue=function(_){_=(_||0)/180*Math.PI;let x=Math.cos(_),N=Math.sin(_),T=.213,E=.715,F=.072;h.colorMatrix([T+x*(1-T)+N*-T,E+x*-E+N*-E,F+x*-F+N*(1-F),0,0,T+x*-T+N*.143,E+x*(1-E)+N*.14,F+x*-F+N*-.283,0,0,T+x*-T+N*-(1-T),E+x*-E+N*E,F+x*(1-F)+N*F,0,0,0,0,0,1,0])},h.desaturateLuminance=function(){h.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},h.sepia=function(){h.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},h.brownie=function(){h.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},h.vintagePinhole=function(){h.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},h.kodachrome=function(){h.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])},h.technicolor=function(){h.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])},h.polaroid=function(){h.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},h.shiftToBGR=function(){h.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},h.convolution=function(_){let x=new Float32Array(_),N=1/o,T=1/l,E=w(h.convolution.SHADER);m.uniform1fv(E.uniform.m,x),m.uniform2f(E.uniform.px,N,T),b()},h.convolution.SHADER=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","uniform vec2 px;","uniform float m[9];","void main(void) {","vec4 c11 = texture2D(texture, vUv - px);","vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));","vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));","vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );","vec4 c22 = texture2D(texture, vUv);","vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );","vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );","vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );","vec4 c33 = texture2D(texture, vUv + px );","gl_FragColor = ","c11 * m[0] + c12 * m[1] + c22 * m[2] +","c21 * m[3] + c22 * m[4] + c23 * m[5] +","c31 * m[6] + c32 * m[7] + c33 * m[8];","gl_FragColor.a = c22.a;","}"].join(`
+`),h.detectEdges=function(){h.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},h.sobelX=function(){h.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},h.sobelY=function(){h.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},h.sharpen=function(_){let x=_||1;h.convolution.call(this,[0,-1*x,0,-1*x,1+4*x,-1*x,0,-1*x,0])},h.emboss=function(_){let x=_||1;h.convolution.call(this,[-2*x,-1*x,0,-1*x,1,1*x,0,1*x,2*x])},h.blur=function(_){let x=_/7/o,N=_/7/l,T=w(h.blur.SHADER);m.uniform2f(T.uniform.px,0,N),b(f.INTERMEDIATE),m.uniform2f(T.uniform.px,x,0),b()},h.blur.SHADER=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","uniform vec2 px;","void main(void) {","gl_FragColor = vec4(0.0);","gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;","gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;","gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;","gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;","gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;","gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;","gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;","gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;","gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;","gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;","gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;","gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;","gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;","gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;","gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;","}"].join(`
+`),h.pixelate=function(_){let x=_/o,N=_/l,T=w(h.pixelate.SHADER);m.uniform2f(T.uniform.size,x,N),b()},h.pixelate.SHADER=["precision highp float;","varying vec2 vUv;","uniform vec2 size;","uniform sampler2D texture;","vec2 pixelate(vec2 coord, vec2 size) {","return floor( coord / size ) * size;","}","void main(void) {","gl_FragColor = vec4(0.0);","vec2 coord = pixelate(vUv, size);","gl_FragColor += texture2D(texture, coord);","}"].join(`
+`)}var O0=2048,Tt=null,Xt=null,Rt=null;function Tg(e,t){let n;if(!e)throw new Error("Human: Input is missing");if(!(e instanceof We)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(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("Human: Input type is not recognized");if(e instanceof We)n=Rr(e);else{let a=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,s=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0,i=a,o=s;if(i>O0&&(i=O0,o=i*s/a),o>O0&&(o=O0,i=o*a/s),t.filter.width>0?i=t.filter.width:t.filter.height>0&&(i=a*(t.filter.height/s)),t.filter.height>0?o=t.filter.height:t.filter.width>0&&(o=s*(t.filter.width/a)),!i||!o)throw new Error("Human: Input cannot determine dimension");(!Tt||Tt.width!==i||Tt.height!==o)&&(Tt=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(i,o):document.createElement("canvas"),Tt.width!==i&&(Tt.width=i),Tt.height!==o&&(Tt.height=o));let l=Tt.getContext("2d");if(e instanceof ImageData?l.putImageData(e,0,0):l.drawImage(e,0,0,a,s,0,0,Tt.width,Tt.height),t.filter.enabled){if((!Rt||!Xt||Tt.width!==Xt.width||Tt.height!==Xt.height)&&(Xt=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(Tt.width,Tt.height):document.createElement("canvas"),Xt.width!==Tt.width&&(Xt.width=Tt.width),Xt.height!==Tt.height&&(Xt.height=Tt.height),Rt=fr.flags.IS_BROWSER?new U8({canvas:Xt}):null),!Rt)return{tensor:null,canvas:Tt};Rt.reset(),Rt.addFilter("brightness",t.filter.brightness),t.filter.contrast!==0&&Rt.addFilter("contrast",t.filter.contrast),t.filter.sharpness!==0&&Rt.addFilter("sharpen",t.filter.sharpness),t.filter.blur!==0&&Rt.addFilter("blur",t.filter.blur),t.filter.saturation!==0&&Rt.addFilter("saturation",t.filter.saturation),t.filter.hue!==0&&Rt.addFilter("hue",t.filter.hue),t.filter.negative&&Rt.addFilter("negative"),t.filter.sepia&&Rt.addFilter("sepia"),t.filter.vintage&&Rt.addFilter("brownie"),t.filter.sepia&&Rt.addFilter("sepia"),t.filter.kodachrome&&Rt.addFilter("kodachrome"),t.filter.technicolor&&Rt.addFilter("technicolor"),t.filter.polaroid&&Rt.addFilter("polaroid"),t.filter.pixelate!==0&&Rt.addFilter("pixelate",t.filter.pixelate),Rt.apply(Tt)}else Xt=Tt,Rt&&(Rt=null);let c;if(Xt.data){let h=[Xt.height,Xt.width,3];c=hd(Xt.data,h,"int32")}else if(Xt instanceof ImageData)c=si.fromPixels(Xt);else if(t.backend==="webgl"||t.backend==="humangl"){let h=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(i,o):document.createElement("canvas");h.width=i,h.height=o;let d=h.getContext("2d");d==null||d.drawImage(Xt,0,0),c=si.fromPixels(h)}else{let h=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(i,o):document.createElement("canvas");h.width=i,h.height=o;let d=h.getContext("2d");d==null||d.drawImage(Xt,0,0);let p=d==null?void 0:d.getImageData(0,0,i,o);c=si.fromPixels(p)}let u=c.toFloat();n=u.expandDims(0),c.dispose(),u.dispose()}let r=t.filter.return?Xt:null;return{tensor:n,canvas:r}}var Eg={};pr(Eg,{all:()=>mie,body:()=>q8,canvas:()=>fie,drawOptions:()=>ie,face:()=>G8,gesture:()=>H8,hand:()=>X8,object:()=>K8});var ht={backend:"webgl",wasmPath:"../assets/",debug:!0,async:!0,profile:!1,deallocate:!1,scoped:!1,videoOptimized:!0,warmup:"face",filter:{enabled:!0,width:0,height:0,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:"../models/blazeface-back.json",rotation:!1,maxFaces:10,skipFrames:21,skipInitial:!1,minConfidence:.2,iouThreshold:.1,scoreThreshold:.2,return:!1},mesh:{enabled:!0,modelPath:"../models/facemesh.json"},iris:{enabled:!0,modelPath:"../models/iris.json"},description:{enabled:!0,modelPath:"../models/faceres.json",skipFrames:31},emotion:{enabled:!0,minConfidence:.1,skipFrames:32,modelPath:"../models/emotion.json"},age:{enabled:!1,modelPath:"../models/age.json",skipFrames:33},gender:{enabled:!1,minConfidence:.1,modelPath:"../models/gender.json",skipFrames:34},embedding:{enabled:!1,modelPath:"../models/mobileface.json"}},body:{enabled:!0,modelPath:"../models/posenet.json",maxDetections:10,scoreThreshold:.3,nmsRadius:20},hand:{enabled:!0,rotation:!1,skipFrames:12,skipInitial:!1,minConfidence:.1,iouThreshold:.1,scoreThreshold:.5,maxHands:1,landmarks:!0,detector:{modelPath:"../models/handdetect.json"},skeleton:{modelPath:"../models/handskeleton.json"}},object:{enabled:!1,modelPath:"../models/nanodet.json",minConfidence:.2,iouThreshold:.4,maxResults:10,skipFrames:41}};var 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backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&Ne("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let r=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&Ne(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),r||Ne("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&x6();try{await this.tf.setBackend(this.config.backend)}catch(r){Ne("error: cannot set backend:",this.config.backend,r)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"||this.tf.getBackend()==="humangl"){this.tf.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),this.tf.ENV.set("WEBGL_PACK_DEPTHWISECONV",!0),this.config.deallocate&&(Ne("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let r=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&Ne(`gl version:${r.getParameter(r.VERSION)} renderer:${r.getParameter(r.RENDERER)}`)}await this.tf.ready(),this.perf.backend=Math.trunc(Ye()-n)}});B0.set(this,async()=>{let t=(a,s="application/octet-stream")=>fetch(`data:${s};base64,${a}`).then(i=>i.blob()),n,r;switch(this.config.warmup){case"face":n=await t(P0);break;case"full":n=await t(L0);break;default:n=null}if(n){let a=await createImageBitmap(n);r=await this.detect(a,this.config),a.close()}return r});V0.set(this,async()=>new Promise(t=>{let n,r=0;switch(this.config.warmup){case"face":r=256,n="data:image/jpeg;base64,"+P0;break;case"full":case"body":r=1200,n="data:image/jpeg;base64,"+L0;break;default:n=null}let a=new Image;a.onload=async()=>{let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(r,r):document.createElement("canvas");s.width=a.naturalWidth,s.height=a.naturalHeight;let i=s.getContext("2d");i==null||i.drawImage(a,0,0);let o=await this.detect(s,this.config);t(o)},n?a.src=n:t(null)}));U0.set(this,async()=>{let t=i=>Buffer.from(i,"base64"),n=this.config.warmup==="face"?t(P0):t(L0),r=(void 0).decodeJpeg(n),a=r.expandDims(0);this.tf.dispose(r);let s=await this.detect(a,this.config);return this.tf.dispose(a),s});this.tf=wh,this.draw=kg,this.version=A4,this.config=Xi(ht,t),this.state="idle",rs(this,Jl,0),rs(this,Xc,!1),rs(this,Kc,!1),rs(this,Di,!0),this.perf={},this.models={face:null,posenet:null,blazepose:null,efficientpose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null,faceres:null},this.image=n=>vg(n,this.config),this.classes={facemesh:H2,age:_2,gender:k2,emotion:E2,faceres:D2,body:this.config.body.modelPath.includes("posenet")?rg:fg,hand:cg,nanodet:xg},this.faceTriangulation=R6,this.faceUVMap=M6,this.sysinfo=Lg()}profileData(){return this.config.profile?h0:{}}similarity(t,n){return this.config.face.description.enabled?z2(t,n):this.config.face.embedding.enabled?w6(t,n):0}enhance(t){return P2(t)}match(t,n,r=0){return b6(t,n,r)}async load(t={}){this.state="load";let n=Ye();t&&(this.config=Xi(this.config,t)),Jn(this,Di)&&(this.config.debug&&Ne(`version: ${this.version}`),this.config.debug&&Ne(`tfjs version: ${this.tf.version_core}`),this.config.debug&&Ne("platform:",this.sysinfo.platform),this.config.debug&&Ne("agent:",this.sysinfo.agent),await Jn(this,Zc).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&Ne("configuration:",this.config),this.config.debug&&Ne("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.efficientpose,this.models.nanodet,this.models.faceres]=await Promise.all([this.models.face||(this.config.face.enabled?q2(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?v2(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?T2(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?M2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?F2(this.config):null),this.models.handpose||(this.config.hand.enabled?pg(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?sg(this.config):null),this.models.blazepose||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?mg(this.config):null),this.models.efficientpose||(this.config.body.enabled&&this.config.body.modelPath.includes("efficientpose")?yg(this.config):null),this.models.nanodet||(this.config.object.enabled?bg(this.config):null),this.models.faceres||(this.config.face.enabled&&this.config.face.description.enabled?O2(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await q2(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await v2(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await T2(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await M2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await F2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await pg(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await sg(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await mg(this.config)),this.config.body.enabled&&!this.models.efficientpose&&this.config.body.modelPath.includes("efficientpose")&&(this.models.efficientpose=await yg(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await bg(this.config)),this.config.face.enabled&&this.config.face.description.enabled&&!this.models.faceres&&(this.models.faceres=await O2(this.config))),Jn(this,Di)&&(this.config.debug&&Ne("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),rs(this,Di,!1));let r=Math.trunc(Ye()-n);r>(this.perf.load||0)&&(this.perf.load=r)}async detect(t,n={}){return new Promise(async r=>{var m,A,y,g;this.state="config";let a;this.config=Xi(this.config,n),this.state="check";let s=Jn(this,W0).call(this,t);s&&(Ne(s,t),r({error:s}));let i=Ye();await Jn(this,Zc).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),this.analyze("Start Scope:"),a=Ye();let o=vg(t,this.config);if(!o||!o.tensor){Ne("could not convert input to tensor"),r({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(Ye()-a),this.analyze("Get Image:");let l,c,u,h,d;this.config.async?(u=this.config.face.enabled?L2(this,o.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",a=Ye(),u=this.config.face.enabled?await L2(this,o.tensor):[],d=Math.trunc(Ye()-a),d>0&&(this.perf.face=d)),this.analyze("Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?(m=this.models.posenet)==null?void 0:m.estimatePoses(o.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?l=this.config.body.enabled?Ag(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(l=this.config.body.enabled?gg(o.tensor,this.config):[]),this.perf.body&&delete this.perf.body):(this.state="run:body",a=Ye(),this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?await((A=this.models.posenet)==null?void 0:A.estimatePoses(o.tensor,this.config)):[]:this.config.body.modelPath.includes("blazepose")?l=this.config.body.enabled?await Ag(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(l=this.config.body.enabled?await gg(o.tensor,this.config):[]),d=Math.trunc(Ye()-a),d>0&&(this.perf.body=d)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(c=this.config.hand.enabled?(y=this.models.handpose)==null?void 0:y.estimateHands(o.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",a=Ye(),c=this.config.hand.enabled?await((g=this.models.handpose)==null?void 0:g.estimateHands(o.tensor,this.config)):[],d=Math.trunc(Ye()-a),d>0&&(this.perf.hand=d)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.config.async?(h=this.config.object.enabled?_g(o.tensor,this.config):[],this.perf.object&&delete this.perf.object):(this.state="run:object",a=Ye(),h=this.config.object.enabled?await _g(o.tensor,this.config):[],d=Math.trunc(Ye()-a),d>0&&(this.perf.object=d)),this.analyze("End Object:"),this.config.async&&([u,l,c,h]=await Promise.all([u,l,c,h])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),this.analyze("End Scope:");let p=[];this.config.gesture.enabled&&(a=Ye(),p=[...o4(u),...i4(l),...u4(c),...l4(u)],this.config.async?this.perf.gesture&&delete this.perf.gesture:this.perf.gesture=Math.trunc(Ye()-a)),this.perf.total=Math.trunc(Ye()-i),this.state="idle";let f={face:u,body:l,hand:c,gesture:p,object:h,performance:this.perf,canvas:o.canvas};r(f)})}async warmup(t={}){let n=Ye();t&&(this.config=Xi(this.config,t));let r=this.config.videoOptimized;this.config.videoOptimized=!1;let a;typeof createImageBitmap=="function"?a=await Jn(this,B0).call(this):typeof Image!="undefined"?a=await Jn(this,V0).call(this):a=await Jn(this,U0).call(this),this.config.videoOptimized=r;let s=Ye();return this.config.debug&&Ne("Warmup",this.config.warmup,Math.round(s-n),"ms",a),a}};Jl=new WeakMap,Xc=new WeakMap,Kc=new WeakMap,Di=new WeakMap,W0=new WeakMap,Zc=new WeakMap,B0=new WeakMap,V0=new WeakMap,U0=new WeakMap;export{Oae as Human,Oae as default};
+2Q==`;var Z8="1.3.5";var Jl,Xc,Kc,$i,W0,Zc,B0,V0,j0,Aie=class{constructor(t={}){Jl.set(this,void 0);Xc.set(this,void 0);Kc.set(this,void 0);$i.set(this,void 0);this.analyze=(...t)=>{if(!Jn(this,Xc))return;let n=this.tf.engine().state.numTensors,r=Jn(this,Jl);rs(this,Jl,n);let a=n-r;a!==0&&Ne(...t,a)};W0.set(this,t=>{if(!Jn(this,Kc))return null;if(!t)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(t instanceof We))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});Zc.set(this,async(t=!1)=>{if(this.config.backend&&this.config.backend!==""&&t||this.tf.getBackend()!==this.config.backend){let n=Ye();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.tf.ENV.flags.IS_BROWSER&&this.config.backend==="tensorflow"&&(this.config.backend="webgl"),this.tf.ENV.flags.IS_NODE&&(this.config.backend==="webgl"||this.config.backend==="wasm")&&(this.config.backend="tensorflow"),this.config.debug&&Ne("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&Ne("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let r=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&Ne(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),r||Ne("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&Q4();try{await this.tf.setBackend(this.config.backend)}catch(r){Ne("error: cannot set backend:",this.config.backend,r)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"||this.tf.getBackend()==="humangl"){this.tf.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),this.tf.ENV.set("WEBGL_PACK_DEPTHWISECONV",!0),this.config.deallocate&&(Ne("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let r=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&Ne(`gl version:${r.getParameter(r.VERSION)} renderer:${r.getParameter(r.RENDERER)}`)}await this.tf.ready(),this.perf.backend=Math.trunc(Ye()-n)}});B0.set(this,async()=>{let t=(a,s="application/octet-stream")=>fetch(`data:${s};base64,${a}`).then(i=>i.blob()),n,r;switch(this.config.warmup){case"face":n=await t(P0);break;case"full":n=await t(L0);break;default:n=null}if(n){let a=await createImageBitmap(n);r=await this.detect(a,this.config),a.close()}return r});V0.set(this,async()=>new Promise(t=>{let n,r=0;switch(this.config.warmup){case"face":r=256,n="data:image/jpeg;base64,"+P0;break;case"full":case"body":r=1200,n="data:image/jpeg;base64,"+L0;break;default:n=null}let a=new Image;a.onload=async()=>{let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(r,r):document.createElement("canvas");s.width=a.naturalWidth,s.height=a.naturalHeight;let i=s.getContext("2d");i==null||i.drawImage(a,0,0);let o=await this.detect(s,this.config);t(o)},n?a.src=n:t(null)}));j0.set(this,async()=>{let t=i=>Buffer.from(i,"base64"),n=this.config.warmup==="face"?t(P0):t(L0),r=(void 0).decodeJpeg(n),a=r.expandDims(0);this.tf.dispose(r);let s=await this.detect(a,this.config);return this.tf.dispose(a),s});this.tf=bh,this.draw=Eg,this.version=Z8,this.config=Xi(ht,t),this.state="idle",rs(this,Jl,0),rs(this,Xc,!1),rs(this,Kc,!1),rs(this,$i,!0),this.perf={},this.models={face:null,posenet:null,blazepose:null,efficientpose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null,faceres:null},this.image=n=>Tg(n,this.config),this.classes={facemesh:Z2,age:S2,gender:E2,emotion:D2,faceres:W2,body:this.config.body.modelPath.includes("posenet")?lg:xg,hand:mg,nanodet:kg},this.faceTriangulation=h8,this.faceUVMap=d8,this.sysinfo=Ug()}profileData(){return this.config.profile?h0:{}}similarity(t,n){return this.config.face.description.enabled?V2(t,n):this.config.face.embedding.enabled?e8(t,n):0}enhance(t){return j2(t)}match(t,n,r=0){return t8(t,n,r)}async load(t={}){this.state="load";let n=Ye();t&&(this.config=Xi(this.config,t)),Jn(this,$i)&&(this.config.debug&&Ne(`version: ${this.version}`),this.config.debug&&Ne(`tfjs version: ${this.tf.version_core}`),this.config.debug&&Ne("platform:",this.sysinfo.platform),this.config.debug&&Ne("agent:",this.sysinfo.agent),await Jn(this,Zc).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&Ne("configuration:",this.config),this.config.debug&&Ne("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.efficientpose,this.models.nanodet,this.models.faceres]=await Promise.all([this.models.face||(this.config.face.enabled?J2(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?T2(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?F2(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?z2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?P2(this.config):null),this.models.handpose||(this.config.hand.enabled?gg(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?cg(this.config):null),this.models.blazepose||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?bg(this.config):null),this.models.efficientpose||(this.config.body.enabled&&this.config.body.modelPath.includes("efficientpose")?_g(this.config):null),this.models.nanodet||(this.config.object.enabled?Ng(this.config):null),this.models.faceres||(this.config.face.enabled&&this.config.face.description.enabled?B2(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await J2(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await T2(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await F2(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await z2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await P2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await gg(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await cg(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await bg(this.config)),this.config.body.enabled&&!this.models.efficientpose&&this.config.body.modelPath.includes("efficientpose")&&(this.models.efficientpose=await _g(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await Ng(this.config)),this.config.face.enabled&&this.config.face.description.enabled&&!this.models.faceres&&(this.models.faceres=await B2(this.config))),Jn(this,$i)&&(this.config.debug&&Ne("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),rs(this,$i,!1));let r=Math.trunc(Ye()-n);r>(this.perf.load||0)&&(this.perf.load=r)}async detect(t,n={}){return new Promise(async r=>{var m,A,y,g;this.state="config";let a;this.config=Xi(this.config,n),this.state="check";let s=Jn(this,W0).call(this,t);s&&(Ne(s,t),r({error:s}));let i=Ye();await Jn(this,Zc).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),this.analyze("Start Scope:"),a=Ye();let o=Tg(t,this.config);if(!o||!o.tensor){Ne("could not convert input to tensor"),r({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(Ye()-a),this.analyze("Get Image:");let l,c,u,h,d;this.config.async?(u=this.config.face.enabled?U2(this,o.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",a=Ye(),u=this.config.face.enabled?await U2(this,o.tensor):[],d=Math.trunc(Ye()-a),d>0&&(this.perf.face=d)),this.analyze("Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?(m=this.models.posenet)==null?void 0:m.estimatePoses(o.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?l=this.config.body.enabled?wg(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(l=this.config.body.enabled?vg(o.tensor,this.config):[]),this.perf.body&&delete this.perf.body):(this.state="run:body",a=Ye(),this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?await((A=this.models.posenet)==null?void 0:A.estimatePoses(o.tensor,this.config)):[]:this.config.body.modelPath.includes("blazepose")?l=this.config.body.enabled?await wg(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(l=this.config.body.enabled?await vg(o.tensor,this.config):[]),d=Math.trunc(Ye()-a),d>0&&(this.perf.body=d)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(c=this.config.hand.enabled?(y=this.models.handpose)==null?void 0:y.estimateHands(o.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",a=Ye(),c=this.config.hand.enabled?await((g=this.models.handpose)==null?void 0:g.estimateHands(o.tensor,this.config)):[],d=Math.trunc(Ye()-a),d>0&&(this.perf.hand=d)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.config.async?(h=this.config.object.enabled?Sg(o.tensor,this.config):[],this.perf.object&&delete this.perf.object):(this.state="run:object",a=Ye(),h=this.config.object.enabled?await Sg(o.tensor,this.config):[],d=Math.trunc(Ye()-a),d>0&&(this.perf.object=d)),this.analyze("End Object:"),this.config.async&&([u,l,c,h]=await Promise.all([u,l,c,h])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),this.analyze("End Scope:");let p=[];this.config.gesture.enabled&&(a=Ye(),p=[...B8(u),...W8(l),...j8(c),...V8(u)],this.config.async?this.perf.gesture&&delete this.perf.gesture:this.perf.gesture=Math.trunc(Ye()-a)),this.perf.total=Math.trunc(Ye()-i),this.state="idle";let f={face:u,body:l,hand:c,gesture:p,object:h,performance:this.perf,canvas:o.canvas};r(f)})}async warmup(t={}){let n=Ye();t&&(this.config=Xi(this.config,t));let r=this.config.videoOptimized;this.config.videoOptimized=!1;let a;typeof createImageBitmap=="function"?a=await Jn(this,B0).call(this):typeof Image!="undefined"?a=await Jn(this,V0).call(this):a=await Jn(this,j0).call(this),this.config.videoOptimized=r;let s=Ye();return this.config.debug&&Ne("Warmup",this.config.warmup,Math.round(s-n),"ms",a),a}};Jl=new WeakMap,Xc=new WeakMap,Kc=new WeakMap,$i=new WeakMap,W0=new WeakMap,Zc=new WeakMap,B0=new WeakMap,V0=new WeakMap,j0=new WeakMap;export{Aie as Human,Aie as default};
 /**
  * @license
  * Copyright 2017 Google LLC. All Rights Reserved.
diff --git a/dist/human.esm.js.map b/dist/human.esm.js.map
index e888c34c..23834767 100644
--- a/dist/human.esm.js.map
+++ b/dist/human.esm.js.map
@@ -1,7 +1,7 @@
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-  "sourcesContent": ["// helper function: wrapper around console output\nexport function log(...msg) {\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: 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: perform deep merge of multiple objects so it allows full inheriance 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", "export function info(): { platform: string, agent: string } {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\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) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = 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) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\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\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) 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 + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\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\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModuleThreadedSimd) {\n  WasmBackendModuleThreadedSimd = WasmBackendModuleThreadedSimd || {};\n\nfunction GROWABLE_HEAP_I8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP8}function GROWABLE_HEAP_U8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU8}function GROWABLE_HEAP_I32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP32}function GROWABLE_HEAP_U32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU32}function GROWABLE_HEAP_F64(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPF64}var Module=typeof WasmBackendModuleThreadedSimd!==\"undefined\"?WasmBackendModuleThreadedSimd:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var ENVIRONMENT_IS_PTHREAD=Module[\"ENVIRONMENT_IS_PTHREAD\"]||false;if(ENVIRONMENT_IS_PTHREAD){buffer=Module[\"buffer\"]}var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process[\"on\"](\"unhandledRejection\",abort);quit_=function(status){process[\"exit\"](status)};Module[\"inspect\"]=function(){return\"[Emscripten Module object]\"};var nodeWorkerThreads;try{nodeWorkerThreads=require(\"worker_threads\")}catch(e){console.error('The \"worker_threads\" module is not supported in this node.js build - perhaps a newer version is needed?');throw e}global.Worker=nodeWorkerThreads.Worker}else if(ENVIRONMENT_IS_SHELL){if(typeof read!=\"undefined\"){read_=function shell_read(f){return read(f)}}readBinary=function readBinary(f){var data;if(typeof readbuffer===\"function\"){return new Uint8Array(readbuffer(f))}data=read(f,\"binary\");assert(typeof data===\"object\");return data};if(typeof scriptArgs!=\"undefined\"){arguments_=scriptArgs}else if(typeof arguments!=\"undefined\"){arguments_=arguments}if(typeof quit===\"function\"){quit_=function(status){quit(status)}}if(typeof print!==\"undefined\"){if(typeof console===\"undefined\")console={};console.log=print;console.warn=console.error=typeof printErr!==\"undefined\"?printErr:print}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href}else if(typeof document!==\"undefined\"&&document.currentScript){scriptDirectory=document.currentScript.src}if(typeof _scriptDir !== \"undefined\" && _scriptDir){scriptDirectory=_scriptDir}if(scriptDirectory.indexOf(\"blob:\")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf(\"/\")+1)}else{scriptDirectory=\"\"}if(ENVIRONMENT_IS_NODE){read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret}}else{read_=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}if(ENVIRONMENT_IS_NODE){if(typeof performance===\"undefined\"){global.performance=require(\"perf_hooks\").performance}}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var Atomics_load=Atomics.load;var Atomics_store=Atomics.store;var Atomics_compareExchange=Atomics.compareExchange;var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var wasmModule;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module[\"wasmMemory\"];buffer=Module[\"buffer\"]}else{if(Module[\"wasmMemory\"]){wasmMemory=Module[\"wasmMemory\"]}else{wasmMemory=new WebAssembly.Memory({\"initial\":INITIAL_MEMORY/65536,\"maximum\":2147483648/65536,\"shared\":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){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\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];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)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={\"e\":___assert_fail,\"r\":___call_main,\"x\":__emscripten_notify_thread_queue,\"b\":_abort,\"y\":_emscripten_asm_const_int,\"j\":_emscripten_conditional_set_current_thread_status,\"c\":_emscripten_futex_wait,\"d\":_emscripten_futex_wake,\"f\":_emscripten_get_now,\"p\":_emscripten_memcpy_big,\"z\":_emscripten_num_logical_cores,\"u\":_emscripten_receive_on_main_thread_js,\"q\":_emscripten_resize_heap,\"v\":_emscripten_set_canvas_element_size,\"i\":_emscripten_set_current_thread_status,\"t\":_emscripten_set_thread_name,\"w\":_emscripten_webgl_create_context,\"m\":_fd_close,\"n\":_fd_seek,\"g\":_fd_write,\"o\":initPthreadsJS,\"a\":wasmMemory||Module[\"wasmMemory\"],\"k\":_pthread_cleanup_pop,\"l\":_pthread_cleanup_push,\"h\":_pthread_create,\"s\":_sysconf};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var 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_ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"X\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"Y\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"Z\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"_\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"$\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"aa\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"ba\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"ca\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"da\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"ea\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"fa\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"ga\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"ha\"]).apply(null,arguments)};var _Log=Module[\"_Log\"]=function(){return(_Log=Module[\"_Log\"]=Module[\"asm\"][\"ia\"]).apply(null,arguments)};var _LogicalAnd=Module[\"_LogicalAnd\"]=function(){return(_LogicalAnd=Module[\"_LogicalAnd\"]=Module[\"asm\"][\"ja\"]).apply(null,arguments)};var _Max=Module[\"_Max\"]=function(){return(_Max=Module[\"_Max\"]=Module[\"asm\"][\"ka\"]).apply(null,arguments)};var _MaxPool=Module[\"_MaxPool\"]=function(){return(_MaxPool=Module[\"_MaxPool\"]=Module[\"asm\"][\"la\"]).apply(null,arguments)};var _Maximum=Module[\"_Maximum\"]=function(){return(_Maximum=Module[\"_Maximum\"]=Module[\"asm\"][\"ma\"]).apply(null,arguments)};var _Mean=Module[\"_Mean\"]=function(){return(_Mean=Module[\"_Mean\"]=Module[\"asm\"][\"na\"]).apply(null,arguments)};var _Min=Module[\"_Min\"]=function(){return(_Min=Module[\"_Min\"]=Module[\"asm\"][\"oa\"]).apply(null,arguments)};var _Minimum=Module[\"_Minimum\"]=function(){return(_Minimum=Module[\"_Minimum\"]=Module[\"asm\"][\"pa\"]).apply(null,arguments)};var 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_OneHot=Module[\"_OneHot\"]=function(){return(_OneHot=Module[\"_OneHot\"]=Module[\"asm\"][\"wa\"]).apply(null,arguments)};var _PadV2=Module[\"_PadV2\"]=function(){return(_PadV2=Module[\"_PadV2\"]=Module[\"asm\"][\"xa\"]).apply(null,arguments)};var _Pow=Module[\"_Pow\"]=function(){return(_Pow=Module[\"_Pow\"]=Module[\"asm\"][\"ya\"]).apply(null,arguments)};var _Prelu=Module[\"_Prelu\"]=function(){return(_Prelu=Module[\"_Prelu\"]=Module[\"asm\"][\"za\"]).apply(null,arguments)};var _Prod=Module[\"_Prod\"]=function(){return(_Prod=Module[\"_Prod\"]=Module[\"asm\"][\"Aa\"]).apply(null,arguments)};var _RealDiv=Module[\"_RealDiv\"]=function(){return(_RealDiv=Module[\"_RealDiv\"]=Module[\"asm\"][\"Ba\"]).apply(null,arguments)};var _Relu=Module[\"_Relu\"]=function(){return(_Relu=Module[\"_Relu\"]=Module[\"asm\"][\"Ca\"]).apply(null,arguments)};var _Relu6=Module[\"_Relu6\"]=function(){return(_Relu6=Module[\"_Relu6\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var 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___pthread_tsd_run_dtors=Module[\"___pthread_tsd_run_dtors\"]=function(){return(___pthread_tsd_run_dtors=Module[\"___pthread_tsd_run_dtors\"]=Module[\"asm\"][\"db\"]).apply(null,arguments)};var _emscripten_main_thread_process_queued_calls=Module[\"_emscripten_main_thread_process_queued_calls\"]=function(){return(_emscripten_main_thread_process_queued_calls=Module[\"_emscripten_main_thread_process_queued_calls\"]=Module[\"asm\"][\"eb\"]).apply(null,arguments)};var _emscripten_current_thread_process_queued_calls=Module[\"_emscripten_current_thread_process_queued_calls\"]=function(){return(_emscripten_current_thread_process_queued_calls=Module[\"_emscripten_current_thread_process_queued_calls\"]=Module[\"asm\"][\"fb\"]).apply(null,arguments)};var _emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=function(){return(_emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=Module[\"asm\"][\"gb\"]).apply(null,arguments)};var __emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=function(){return(__emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=Module[\"asm\"][\"hb\"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=function(){return(_emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=Module[\"asm\"][\"ib\"]).apply(null,arguments)};var _emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=function(){return(_emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=Module[\"asm\"][\"jb\"]).apply(null,arguments)};var __emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=function(){return(__emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=Module[\"asm\"][\"kb\"]).apply(null,arguments)};var _emscripten_tls_init=Module[\"_emscripten_tls_init\"]=function(){return(_emscripten_tls_init=Module[\"_emscripten_tls_init\"]=Module[\"asm\"][\"lb\"]).apply(null,arguments)};var __emscripten_thread_init=Module[\"__emscripten_thread_init\"]=function(){return(__emscripten_thread_init=Module[\"__emscripten_thread_init\"]=Module[\"asm\"][\"mb\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"nb\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"ob\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"pb\"]).apply(null,arguments)};var _emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=function(){return(_emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=Module[\"asm\"][\"qb\"]).apply(null,arguments)};var _memalign=Module[\"_memalign\"]=function(){return(_memalign=Module[\"_memalign\"]=Module[\"asm\"][\"rb\"]).apply(null,arguments)};var __emscripten_allow_main_runtime_queued_calls=Module[\"__emscripten_allow_main_runtime_queued_calls\"]=9880;var __emscripten_main_thread_futex=Module[\"__emscripten_main_thread_futex\"]=11368;Module[\"cwrap\"]=cwrap;Module[\"PThread\"]=PThread;Module[\"PThread\"]=PThread;Module[\"wasmMemory\"]=wasmMemory;Module[\"ExitStatus\"]=ExitStatus;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}if(ENVIRONMENT_IS_PTHREAD){readyPromiseResolve(Module);postMessage({\"cmd\":\"loaded\"});return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;function exit(status,implicit){if(implicit&&noExitRuntime&&status===0){return}if(!implicit){if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exitProcess\",\"returnCode\":status});throw new ExitStatus(status)}else{}}if(noExitRuntime){}else{PThread.terminateAllThreads();EXITSTATUS=status;exitRuntime();if(Module[\"onExit\"])Module[\"onExit\"](status);ABORT=true}quit_(status,new ExitStatus(status))}if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}if(ENVIRONMENT_IS_PTHREAD){noExitRuntime=false;PThread.initWorker()}run();\n\n\n  return WasmBackendModuleThreadedSimd.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModuleThreadedSimd;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModuleThreadedSimd; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModuleThreadedSimd\"] = WasmBackendModuleThreadedSimd;\n", "\nvar WasmBackendModule = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModule) {\n  WasmBackendModule = WasmBackendModule || {};\n\nvar Module=typeof WasmBackendModule!==\"undefined\"?WasmBackendModule:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process[\"on\"](\"unhandledRejection\",abort);quit_=function(status){process[\"exit\"](status)};Module[\"inspect\"]=function(){return\"[Emscripten Module object]\"}}else if(ENVIRONMENT_IS_SHELL){if(typeof read!=\"undefined\"){read_=function shell_read(f){return read(f)}}readBinary=function readBinary(f){var data;if(typeof readbuffer===\"function\"){return new Uint8Array(readbuffer(f))}data=read(f,\"binary\");assert(typeof data===\"object\");return data};if(typeof scriptArgs!=\"undefined\"){arguments_=scriptArgs}else if(typeof arguments!=\"undefined\"){arguments_=arguments}if(typeof quit===\"function\"){quit_=function(status){quit(status)}}if(typeof print!==\"undefined\"){if(typeof console===\"undefined\")console={};console.log=print;console.warn=console.error=typeof printErr!==\"undefined\"?printErr:print}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href}else if(typeof document!==\"undefined\"&&document.currentScript){scriptDirectory=document.currentScript.src}if(_scriptDir){scriptDirectory=_scriptDir}if(scriptDirectory.indexOf(\"blob:\")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf(\"/\")+1)}else{scriptDirectory=\"\"}{read_=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return 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Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). 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fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmMemory=Module[\"asm\"][\"g\"];updateGlobalBufferAndViews(wasmMemory.buffer);wasmTable=Module[\"asm\"][\"m\"];removeRunDependency(\"wasm-instantiate\")}addRunDependency(\"wasm-instantiate\");function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"])}function instantiateArrayBuffer(receiver){return 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false}}instantiateAsync().catch(readyPromiseReject);return{}}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _abort(){abort()}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num)}function _emscripten_get_heap_size(){return HEAPU8.length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var 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_Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\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) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = 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) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\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\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) 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 + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\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\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");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;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(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;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}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);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}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);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var nodeFS=require(\"fs\");var nodeRead=function(filename){return nodeFS.readFileSync(filename,\"utf8\")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance===\"undefined\"){performance={now:function(){return Date.now()}}}}';", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }\n\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export versions\nexport const version = {\n  tfjs: packageBundle.version,\n  'tfjs-core': packageCore.version,\n  'tfjs-data': packageData.version,\n  'tfjs-layers': packageLayers.version,\n  'tfjs-converter': packageConverter.version,\n  'tfjs-backend-cpu': version_cpu,\n  'tfjs-backend-webgl': version_webgl,\n  'tfjs-backend-wasm': version_wasm,\n};\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\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\nexport function register(): void {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 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    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './helpers';\n\nexport const data = {};\n\nexport function run(modelName: string, profileData: any): void {\n  if (!profileData || !profileData.kernels) return;\n  const maxResults = 5;\n  const time = profileData.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = profileData.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = profileData.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  data[modelName] = {\n    model: modelName,\n    newBytes: profileData.newBytes,\n    newTensors: profileData.newTensors,\n    peakBytes: profileData.peakBytes,\n    numKernelOps: profileData.kernels.length,\n    timeKernelOps: time,\n    slowestKernelOps: slowest,\n    largestKernelOps: largest,\n  };\n  log('profiler', modelName, data[modelName]);\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(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 = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      if (!Array.isArray(genderT)) {\n        const data = genderT.dataSync();\n        if (alternative) {\n          // returns two values 0..1, bigger one is prediction\n          if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n            obj.gender = data[0] > data[1] ? 'female' : 'male';\n            obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n          }\n        } else {\n          // returns one value 0..1, .5 is prediction threshold\n          const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n          if (confidence > config.face.gender.minConfidence) {\n            obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n            obj.confidence = Math.min(0.99, confidence);\n          }\n        }\n        genderT.dispose();\n      } else {\n        const gender = genderT[0].dataSync();\n        const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n        /*\n        let age = genderT[1].argMax(1).dataSync()[0];\n        const all = genderT[1].dataSync();\n        age = Math.round(all[age - 1] > all[age + 1] ? 10 * age - 100 * all[age - 1] : 10 * age + 100 * all[age + 1]) / 10;\n        const descriptor = genderT[1].dataSync();\n        */\n        genderT.forEach((t) => tf.dispose(t));\n      }\n    }\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\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\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\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    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = typeof tf.Tensor;\ntype DB = Array<{ name: string, source: string, embedding: number[] }>;\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function similarity(embedding1, embedding2, order = 2): number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<number>, db: DB, threshold = 0) {\n  let best = { similarity: 0, name: '', source: '', embedding: [] as number[] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = similarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.similarity) best = { ...f, similarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = 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    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\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    // 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    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\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\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([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: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\ntype Tensor = typeof tf.Tensor;\ntype DB = Array<{ name: string, source: string, embedding: number[] }>;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.description.modelPath);\n    if (config.debug) log(`load model: ${config.face.description.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function similarity(embedding1, embedding2, order = 2): number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = 4.0 * embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(0, 100 - distance) / 100.0;\n  return res;\n}\n\nexport function match(embedding: Array<number>, db: DB, threshold = 0) {\n  let best = { similarity: 0, name: '', source: '', embedding: [] as number[] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = similarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.similarity) best = { ...f, similarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    const tensor = input.image || input.tensor || input;\n    if (!(tensor instanceof tf.Tensor)) return null;\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    // const crop = tf.image.resizeBilinear(tensor, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\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    /*\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\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n    /*\n    // normalize brightness from 0..1\n    const darken = crop.sub(crop.min());\n    const lighten = darken.div(darken.max());\n    */\n    const norm = crop.mul(255);\n\n    return norm;\n  });\n  return image;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.description.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    // const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    // const enhanced = tf.mul(resize, [255.0]);\n    // tf.dispose(resize);\n    const enhanced = enhance(image);\n\n    let resT;\n    const obj = {\n      age: <number>0,\n      gender: <string>'unknown',\n      genderConfidence: <number>0,\n      descriptor: <number[]>[] };\n\n    if (!config.profile) {\n      if (config.face.description.enabled) resT = await model.predict(enhanced);\n    } else {\n      const profileDesc = config.face.description.enabled ? await tf.profile(() => model.predict(enhanced)) : {};\n      resT = profileDesc.result;\n      profile.run('faceres', profileDesc);\n    }\n    tf.dispose(enhanced);\n\n    if (resT) {\n      tf.tidy(() => {\n        const gender = resT.find((t) => t.shape[1] === 1).dataSync();\n        const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n          obj.genderConfidence = Math.min(0.99, confidence);\n        }\n        const age = resT.find((t) => t.shape[1] === 100).argMax(1).dataSync()[0];\n        const all = resT.find((t) => t.shape[1] === 100).dataSync();\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]);\n        // const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n        obj.descriptor = [...desc.dataSync()];\n      });\n      resT.forEach((t) => tf.dispose(t));\n    }\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log, now } from './helpers';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as faceres from './faceres/faceres';\n\ntype Tensor = typeof tf.Tensor;\n\nconst calculateFaceAngle = (face, image_size): { angle: { pitch: number, yaw: number, roll: number }, matrix: [number, number, number, number, number, number, number, number, number] } => {\n  // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n  const degrees = (theta) => (theta * 180) / Math.PI;\n  // const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n  const normalize = (v) => { // 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, b) => { // 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, b) => { // 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) => {\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; let thetaY; let thetaZ;\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    return { pitch: 2 * -thetaX, yaw: 2 * -thetaY, roll: 2 * -thetaZ };\n  };\n  // simple Euler angle calculation based existing 3D mesh\n  // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n  const meshToEulerAngle = (mesh) => {\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // pitch is face move up/down\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\n      // yaw is face turn left/right\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\n      // roll is face lean 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\n    };\n    return angle;\n  };\n\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] };\n\n  const size = Math.max(face.boxRaw[2] * image_size[0], face.boxRaw[3] * image_size[1]) / 1.5;\n  // top, bottom, left, right\n  const pts = [mesh[10], mesh[152], mesh[234], mesh[454]].map((pt) => [\n    // make the xyz coordinates proportional, independent of the image/box size\n    pt[0] * image_size[0] / size,\n    pt[1] * image_size[1] / size,\n    pt[2],\n  ]);\n\n  const y_axis = normalize(subVectors(pts[1], pts[0]));\n  let x_axis = normalize(subVectors(pts[3], pts[2]));\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  return { angle, matrix };\n};\n\nexport const detectFace = async (parent, input): Promise<any> => {\n  // run facemesh, includes blazeface and iris\n  // eslint-disable-next-line no-async-promise-executor\n  let timeStamp;\n  let ageRes;\n  let genderRes;\n  let emotionRes;\n  let embeddingRes;\n  let descRes;\n  const faceRes: Array<{\n      confidence: number,\n      boxConfidence: number,\n      faceConfidence: number,\n      box: [number, number, number, number],\n      mesh: Array<[number, number, number]>\n      meshRaw: Array<[number, number, number]>\n      boxRaw: [number, number, number, number],\n      annotations: Array<{ part: string, points: Array<[number, number, number]>[] }>,\n      age: number,\n      gender: string,\n      genderConfidence: number,\n      emotion: string,\n      embedding: number[],\n      iris: number,\n      rotation: {\n        angle: { pitch: number, yaw: number, roll: number },\n        matrix: [number, number, number, number, number, number, number, number, number]\n      },\n      tensor: Tensor,\n    }> = [];\n  parent.state = 'run:face';\n  timeStamp = now();\n  const faces = await parent.models.face?.estimateFaces(input, parent.config);\n  parent.perf.face = Math.trunc(now() - timeStamp);\n  if (!faces) return [];\n  for (const face of faces) {\n    parent.analyze('Get Face');\n\n    // is something went wrong, skip the face\n    if (!face.image || face.image.isDisposedInternal) {\n      log('Face object is disposed:', face.image);\n      continue;\n    }\n\n    const rotation = calculateFaceAngle(face, [input.shape[2], input.shape[1]]);\n\n    // run age, inherits face from blazeface\n    parent.analyze('Start Age:');\n    if (parent.config.async) {\n      ageRes = parent.config.face.age.enabled ? age.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:age';\n      timeStamp = now();\n      ageRes = parent.config.face.age.enabled ? await age.predict(face.image, parent.config) : {};\n      parent.perf.age = Math.trunc(now() - timeStamp);\n    }\n\n    // run gender, inherits face from blazeface\n    parent.analyze('Start Gender:');\n    if (parent.config.async) {\n      genderRes = parent.config.face.gender.enabled ? gender.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:gender';\n      timeStamp = now();\n      genderRes = parent.config.face.gender.enabled ? await gender.predict(face.image, parent.config) : {};\n      parent.perf.gender = Math.trunc(now() - timeStamp);\n    }\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Emotion:');\n    if (parent.config.async) {\n      emotionRes = parent.config.face.emotion.enabled ? emotion.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:emotion';\n      timeStamp = now();\n      emotionRes = parent.config.face.emotion.enabled ? await emotion.predict(face.image, parent.config) : {};\n      parent.perf.emotion = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Emotion:');\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Embedding:');\n    if (parent.config.async) {\n      embeddingRes = parent.config.face.embedding.enabled ? embedding.predict(face, parent.config) : [];\n    } else {\n      parent.state = 'run:embedding';\n      timeStamp = now();\n      embeddingRes = parent.config.face.embedding.enabled ? await embedding.predict(face, parent.config) : [];\n      parent.perf.embedding = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Embedding:');\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Description:');\n    if (parent.config.async) {\n      descRes = parent.config.face.description.enabled ? faceres.predict(face, parent.config) : [];\n    } else {\n      parent.state = 'run:description';\n      timeStamp = now();\n      descRes = parent.config.face.description.enabled ? await faceres.predict(face.image, parent.config) : [];\n      parent.perf.embedding = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Description:');\n\n    // if async wait for results\n    if (parent.config.async) {\n      [ageRes, genderRes, emotionRes, embeddingRes, descRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes, descRes]);\n    }\n\n    parent.analyze('Finish Face:');\n\n    // calculate iris distance\n    // iris: array[ center, left, top, right, bottom]\n    if (!parent.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n      delete face.annotations.leftEyeIris;\n      delete face.annotations.rightEyeIris;\n    }\n    const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n    /* average human iris size is 11.7mm */\n      ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n      : 0;\n\n    // combine results\n    faceRes.push({\n      ...face,\n      age: descRes.age || ageRes.age,\n      gender: descRes.gender || genderRes.gender,\n      genderConfidence: descRes.genderConfidence || genderRes.confidence,\n      embedding: descRes.descriptor || embeddingRes,\n      emotion: emotionRes,\n      iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n      rotation,\n      tensor: parent.config.face.detector.return ? face.image?.squeeze() : null,\n    });\n    // dispose original face tensor\n    face.image?.dispose();\n\n    parent.analyze('End Face');\n  }\n  parent.analyze('End FaceMesh:');\n  if (parent.config.async) {\n    if (parent.perf.face) delete parent.perf.face;\n    if (parent.perf.age) delete parent.perf.age;\n    if (parent.perf.gender) delete parent.perf.gender;\n    if (parent.perf.emotion) delete parent.perf.emotion;\n  }\n  return faceRes;\n};\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[2], prediction.box.endPoint[0]) - Math.max(0, prediction.box.startPoint[0]),\n        Math.min(input.shape[1], prediction.box.endPoint[1]) - Math.max(0, prediction.box.startPoint[1]),\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        prediction.box.startPoint[0] / input.shape[2],\n        prediction.box.startPoint[1] / input.shape[1],\n        (prediction.box.endPoint[0] - prediction.box.startPoint[0]) / input.shape[2],\n        (prediction.box.endPoint[1] - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: Math.round(100 * prediction.faceConfidence || 100 * prediction.boxConfidence || 0) / 100,\n        boxConfidence: Math.round(100 * prediction.boxConfidence) / 100,\n        faceConfidence: Math.round(100 * prediction.faceConfidence) / 100,\n        box,\n        boxRaw,\n        mesh,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config): Promise<MediaPipeFaceMesh> {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexport const triangulation = coords.TRI468;\nexport const uvmap = coords.UV468;\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\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++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\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 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]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\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];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\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 function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\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\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\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],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\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 MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\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 = [\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 = [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 = [\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 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\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 = [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 = [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", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\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], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  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.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\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.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\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 / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * 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.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${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\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (!config.videoOptimized || (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces)))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(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\n          // 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          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && (config.face.description.enabled || config.face.embedding.enabled) && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\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, landmarks };\n  }\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\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() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\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    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", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, 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(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.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 < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "export 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 NUM_KEYPOINTS = 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 const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\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", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\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 sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, 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 sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !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    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score: Math.round(100 * score) / 100 });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.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\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return 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: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, boxRaw: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - Math.max(0, prediction.box.topLeft[0]),\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - Math.max(0, prediction.box.topLeft[1]),\n      ] : [];\n      const boxRaw = [\n        (prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.topLeft[1]) / input.shape[1],\n        (prediction.box.bottomRight[0] - prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.bottomRight[1] - prediction.box.topLeft[1]) / input.shape[1],\n      ];\n      hands.push({ confidence: Math.round(100 * prediction.confidence) / 100, box, boxRaw, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config): Promise<HandPose> {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\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]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\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]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\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];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\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]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "export 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", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\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 box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.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 = [...box.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      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) 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.maxHands) || !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<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\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[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? 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 = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\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", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.984375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.984375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    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   x_center: 0.5625,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  const score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n  return [{ score, keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet keypoints: Array<any> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst bodyParts = ['head', 'neck', 'rightShoulder', 'rightElbow', 'rightWrist', 'chest', 'leftShoulder', 'leftElbow', 'leftWrist', 'pelvis', 'rightHip', 'rightKnee', 'rightAnkle', 'leftHip', 'leftKnee', 'leftAnkle'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\n// performs argmax and max functions on a 2d tensor\nfunction max2d(inputs, minScore) {\n  const [width, height] = inputs.shape;\n  return tf.tidy(() => {\n    // modulus op implemented in tf\n    const mod = (a, b) => tf.sub(a, tf.mul(tf.div(a, tf.scalar(b, 'int32')), tf.scalar(b, 'int32')));\n    // combine all data\n    const reshaped = tf.reshape(inputs, [height * width]);\n    // get highest score\n    const score = tf.max(reshaped, 0).dataSync()[0];\n    if (score > minScore) {\n      // skip coordinate calculation is score is too low\n      const coords = tf.argMax(reshaped, 0);\n      const x = mod(coords, width).dataSync()[0];\n      const y = tf.div(coords, tf.scalar(width, 'int32')).dataSync()[0];\n      return [x, y, score];\n    }\n    return [0, 0, score];\n  });\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.body.skipFrames) && config.videoOptimized && Object.keys(keypoints).length > 0) {\n    skipped++;\n    return keypoints;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const tensor = tf.tidy(() => {\n      const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n      const enhance = tf.mul(resize, 2);\n      const norm = enhance.sub(1);\n      return norm;\n    });\n\n    let resT;\n\n    if (!config.profile) {\n      if (config.body.enabled) resT = await model.predict(tensor);\n    } else {\n      const profileT = config.body.enabled ? await tf.profile(() => model.predict(tensor)) : {};\n      resT = profileT.result.clone();\n      profileT.result.dispose();\n      profile.run('body', profileT);\n    }\n    tensor.dispose();\n\n    if (resT) {\n      const parts: Array<{ id, score, part, position: { x, y }, positionRaw: { xRaw, yRaw} }> = [];\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, score] = max2d(stack[id], config.body.scoreThreshold);\n        if (score > config.body.scoreThreshold) {\n          parts.push({\n            id,\n            score: Math.round(100 * score) / 100,\n            part: bodyParts[id],\n            positionRaw: {\n              xRaw: x / model.inputs[0].shape[2], // x normalized to 0..1\n              yRaw: y / model.inputs[0].shape[1], // y normalized to 0..1\n            },\n            position: {\n              x: Math.round(image.shape[2] * x / model.inputs[0].shape[2]), // x normalized to input image size\n              y: Math.round(image.shape[1] * y / model.inputs[0].shape[1]), // y normalized to input image size\n            },\n          });\n        }\n      }\n      stack.forEach((s) => tf.dispose(s));\n      keypoints = parts;\n    }\n    const score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n    resolve([{ score, keypoints }]);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport { labels } from './labels';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let id = 0;\n  let results: Array<{ score: number, strideSize: number, class: number, label: string, center: number[], centerRaw: number[], box: number[], boxRaw: number[] }> = [];\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(() => { // 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 = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === labels.length))?.squeeze();\n      const featuresT = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] < labels.length))?.squeeze();\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 = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      const scores = scoresT.arraySync(); // 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 && 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) => 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 = [x, y, w, h]; // results normalized to range 0..1\n            boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // 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,\n              center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n              centerRaw: [cx, cy],\n              box: box.map((a) => Math.trunc(a)),\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);\n  const nmsScores = results.map((a) => a.score);\n  let nmsIdx: any[] = [];\n  if (nmsBoxes && nmsBoxes.length > 0) {\n    const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n    nmsIdx = nms.dataSync();\n    tf.dispose(nms);\n  }\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n    resize.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result;\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export 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", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\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.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) 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) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\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];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (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\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), 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, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\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  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\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  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\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    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\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    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\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;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\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)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\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  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\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  ].join('\\n');\n\n  _filter.brightness = function (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  _filter.saturation = function (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  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\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  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (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\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  _filter.desaturateLuminance = function () {\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  _filter.sepia = function () {\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  _filter.brownie = function () {\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  _filter.vintagePinhole = function () {\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  _filter.kodachrome = function () {\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  _filter.technicolor = function () {\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  _filter.polaroid = function () {\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  _filter.shiftToBGR = function () {\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  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\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  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\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  _filter.emboss = function (size) {\n    const s = size || 1;\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  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\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  _filter.blur.SHADER = [\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  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\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  ].join('\\n');\n}\n", "// @ts-nocheck\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\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 function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (!input) throw new Error('Human: Input is missing');\n  if (\n    !(input instanceof tf.Tensor)\n    && !(typeof Image !== 'undefined' && input instanceof Image)\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('Human: Input type is not recognized');\n  }\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\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    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) throw new Error('Human: Input cannot determine dimension');\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) { // if we have data, just convert to tensor\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if (outCanvas instanceof ImageData) { // if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else if (config.backend === 'webgl' || config.backend === 'humangl') { // tf kernel-optimized method to get imagedata\n      // we can use canvas as-is as it already has a context, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      pixels = tf.browser.fromPixels(tempCanvas);\n    } else { // cpu and wasm kernel does not implement efficient fromPixels method\n      // we can use canvas as-is as it already has a context, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "import { defaults } from '../config';\nimport { TRI468 as triangulation } from '../blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n  useRawBoxes: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n      else rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.rotation && f.rotation.angle && f.rotation.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.rotation.angle.roll) / 100} yaw:${Math.trunc(100 * f.rotation.angle.yaw) / 100} pitch:${Math.trunc(100 * f.rotation.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.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 (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.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 (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      if (result[i].keypoints) {\n        for (const pt of result[i].keypoints) {\n          ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n          ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons && result[i].keypoints) {\n      let part;\n      const points: any[] = [];\n      // shoulder line\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // torso main\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 4) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas: HTMLCanvasElement, outCanvas: HTMLCanvasElement) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas: HTMLCanvasElement, result:any) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\n/**\n * Configuration interface definition for **Human** library\n *\n * Contains all configurable parameters\n */\nexport interface Config {\n  backend: string,\n  wasmPath: string,\n  debug: boolean,\n  async: boolean,\n  profile: boolean,\n  deallocate: boolean,\n  scoped: boolean,\n  videoOptimized: boolean,\n  warmup: string,\n  filter: {\n    enabled: boolean,\n    width: number,\n    height: number,\n    return: boolean,\n    brightness: number,\n    contrast: number,\n    sharpness: number,\n    blur: number\n    saturation: number,\n    hue: number,\n    negative: boolean,\n    sepia: boolean,\n    vintage: boolean,\n    kodachrome: boolean,\n    technicolor: boolean,\n    polaroid: boolean,\n    pixelate: number,\n  },\n  gesture: {\n    enabled: boolean,\n  },\n  face: {\n    enabled: boolean,\n    detector: {\n      modelPath: string,\n      rotation: boolean,\n      maxFaces: number,\n      skipFrames: number,\n      skipInitial: boolean,\n      minConfidence: number,\n      iouThreshold: number,\n      scoreThreshold: number,\n      return: boolean,\n    },\n    mesh: {\n      enabled: boolean,\n      modelPath: string,\n    },\n    iris: {\n      enabled: boolean,\n      modelPath: string,\n    },\n    description: {\n      enabled: boolean,\n      modelPath: string,\n      skipFrames: number,\n    },\n    age: {\n      enabled: boolean,\n      modelPath: string,\n      skipFrames: number,\n    },\n    gender: {\n      enabled: boolean,\n      minConfidence: number,\n      modelPath: string,\n      skipFrames: number,\n    },\n    emotion: {\n      enabled: boolean,\n      minConfidence: number,\n      skipFrames: number,\n      modelPath: string,\n    },\n    embedding: {\n      enabled: boolean,\n      modelPath: string,\n    },\n  },\n  body: {\n    enabled: boolean,\n    modelPath: string,\n    maxDetections: number,\n    scoreThreshold: number,\n    nmsRadius: number,\n  },\n  hand: {\n    enabled: boolean,\n    rotation: boolean,\n    skipFrames: number,\n    skipInitial: boolean,\n    minConfidence: number,\n    iouThreshold: number,\n    scoreThreshold: number,\n    maxHands: number,\n    landmarks: boolean,\n    detector: {\n      modelPath: string,\n    },\n    skeleton: {\n      modelPath: string,\n    },\n  },\n  object: {\n    enabled: boolean,\n    modelPath: string,\n    minConfidence: number,\n    iouThreshold: number,\n    maxResults: number,\n    skipFrames: number,\n  },\n}\n\nconst config: Config = {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // 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    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    description: {\n      enabled: true,         // to improve accuracy of face description extraction it is\n                             // recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/faceres.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 32,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    age: {\n      enabled: false,        // obsolete, replaced by description module\n      modelPath: '../models/age.json',\n      skipFrames: 33,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: false,        // obsolete, replaced by description module\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 34,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    embedding: {\n      enabled: false,        // obsolete, replaced by description module\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet', 'blazepose' or 'efficientpose'\n                             // 'blazepose' and 'efficientpose' are experimental\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n                             // 'nanodet' is experimental\n    minConfidence: 0.20,     // threshold for discarding a prediction\n    iouThreshold: 0.40,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 41,          // how many frames to go without re-running the detector\n  },\n};\nexport { config as defaults };\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import { log, now, mergeDeep } from './helpers';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as faceall from './faceall';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as faceres from './faceres/faceres';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as efficientpose from './efficientpose/efficientpose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image/image';\nimport * as draw from './draw/draw';\nimport * as profile from './profile';\nimport { Config, defaults } from './config';\nimport { Result } from './result';\nimport * as sample from './sample';\nimport * as app from '../package.json';\n\n/** Generic Tensor object type */\nexport type Tensor = typeof tf.Tensor;\nexport type { Config } from './config';\nexport type { Result } from './result';\n/** Defines all possible input types for **Human** detection */\nexport type Input = Tensor | typeof Image | ImageData | ImageBitmap | HTMLImageElement | HTMLMediaElement | HTMLVideoElement | HTMLCanvasElement | OffscreenCanvas;\n\n/** Error message */\nexport type Error = { error: string };\n/** Instance of TensorFlow/JS */\nexport type TensorFlow = typeof tf;\n/** Generic Model object type, holds instance of individual models */\ntype Model = Object;\n\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 */\nexport class Human {\n  version: string;\n  config: Config;\n  state: string;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: TensorFlow;\n  draw: {\n    drawOptions?: typeof draw.drawOptions,\n    gesture: typeof draw.gesture,\n    face: typeof draw.face,\n    body: typeof draw.body,\n    hand: typeof draw.hand,\n    canvas: typeof draw.canvas,\n    all: typeof draw.all,\n  };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | Model | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    efficientpose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n    faceres: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n    faceres: typeof faceres;\n  };\n  faceTriangulation: typeof facemesh.triangulation;\n  faceUVMap: typeof facemesh.uvmap;\n  sysinfo: { platform: string, agent: string };\n  perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: boolean;\n  #checkSanity: boolean;\n  #firstRun: boolean;\n  // definition end\n\n  constructor(userConfig: Config | Object = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.version = app.version;\n    this.config = mergeDeep(defaults, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      efficientpose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n      faceres: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Input) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      faceres,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    this.faceTriangulation = facemesh.triangulation;\n    this.faceUVMap = facemesh.uvmap;\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | string => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_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  similarity(embedding1: Array<number>, embedding2: Array<number>): number {\n    if (this.config.face.description.enabled) return faceres.similarity(embedding1, embedding2);\n    if (this.config.face.embedding.enabled) return embedding.similarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return faceres.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<number>, db: Array<{ name: string, source: string, embedding: number[] }>, threshold = 0): { name: string, source: string, similarity: number, embedding: number[] } {\n    return faceres.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Config | Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        // @ts-ignore\n        this.models.handpose,\n        // @ts-ignore false warning with latest @typescript-eslint\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.efficientpose,\n        this.models.nanodet,\n        this.models.faceres,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? <Promise<handpose.HandPose>>handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.blazepose || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.efficientpose || (this.config.body.enabled && this.config.body.modelPath.includes('efficientpose') ? efficientpose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n        this.models.faceres || ((this.config.face.enabled && this.config.face.description.enabled) ? faceres.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.body.enabled && !this.models.efficientpose && this.config.body.modelPath.includes('efficientpose')) this.models.efficientpose = await efficientpose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n      if (this.config.face.enabled && this.config.face.description.enabled && !this.models.faceres) this.models.faceres = await faceres.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.perf.load || 0)) this.perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        // force browser vs node backend\n        if (this.tf.ENV.flags.IS_BROWSER && this.config.backend === 'tensorflow') this.config.backend = 'webgl';\n        if (this.tf.ENV.flags.IS_NODE && (this.config.backend === 'webgl' || this.config.backend === 'wasm')) this.config.backend = 'tensorflow';\n\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      // this.tf.enableDebugMode();\n      if (this.tf.getBackend() === 'webgl' || this.tf.getBackend() === 'humangl') {\n        this.tf.ENV.set('CHECK_COMPUTATION_FOR_ERRORS', false);\n        this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  // main detect function\n  async detect(input: Input, userConfig: Config | Object = {}): Promise<Result | Error> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.perf.image = Math.trunc(now() - timeStamp);\n      this.analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n      let current;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? faceall.detectFace(this, process.tensor) : [];\n        if (this.perf.face) delete this.perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await faceall.detectFace(this, process.tensor) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.face = current;\n      }\n\n      // run body: can be posenet or blazepose\n      this.analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('blazepose')) bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('efficientpose')) bodyRes = this.config.body.enabled ? efficientpose.predict(process.tensor, this.config) : [];\n        if (this.perf.body) delete this.perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('blazepose')) bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('efficientpose')) bodyRes = this.config.body.enabled ? await efficientpose.predict(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.body = current;\n      }\n      this.analyze('End Body:');\n\n      // run handpose\n      this.analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.perf.hand) delete this.perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.hand = current;\n      }\n      this.analyze('End Hand:');\n\n      // run nanodet\n      this.analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.perf.object) delete this.perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.object = current;\n      }\n      this.analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.perf.gesture) delete this.perf.gesture;\n      }\n\n      this.perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      const result = {\n        face: faceRes,\n        body: bodyRes,\n        hand: handRes,\n        gesture: gestureRes,\n        object: objectRes,\n        performance: this.perf,\n        canvas: process.canvas,\n      };\n      // log('Result:', result);\n      resolve(result);\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\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 this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.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    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Config | Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\n/**\n * Class Human is also available as default export\n */\nexport { Human as default };\n"],
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+  "sourcesContent": ["// helper function: wrapper around console output\nexport function log(...msg) {\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')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n\n// helper function: gets elapsed time on both browser and nodejs\nexport const now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nexport function mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n", "export function info(): { platform: string, agent: string } {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\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) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = 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) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\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\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) 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 + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\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\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModuleThreadedSimd) {\n  WasmBackendModuleThreadedSimd = WasmBackendModuleThreadedSimd || {};\n\nfunction GROWABLE_HEAP_I8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP8}function GROWABLE_HEAP_U8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU8}function GROWABLE_HEAP_I32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP32}function GROWABLE_HEAP_U32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU32}function GROWABLE_HEAP_F64(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPF64}var Module=typeof WasmBackendModuleThreadedSimd!==\"undefined\"?WasmBackendModuleThreadedSimd:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var ENVIRONMENT_IS_PTHREAD=Module[\"ENVIRONMENT_IS_PTHREAD\"]||false;if(ENVIRONMENT_IS_PTHREAD){buffer=Module[\"buffer\"]}var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process[\"on\"](\"unhandledRejection\",abort);quit_=function(status){process[\"exit\"](status)};Module[\"inspect\"]=function(){return\"[Emscripten Module object]\"};var nodeWorkerThreads;try{nodeWorkerThreads=require(\"worker_threads\")}catch(e){console.error('The \"worker_threads\" module is not supported in this node.js build - perhaps a newer version is needed?');throw e}global.Worker=nodeWorkerThreads.Worker}else if(ENVIRONMENT_IS_SHELL){if(typeof read!=\"undefined\"){read_=function shell_read(f){return read(f)}}readBinary=function readBinary(f){var data;if(typeof readbuffer===\"function\"){return new Uint8Array(readbuffer(f))}data=read(f,\"binary\");assert(typeof data===\"object\");return data};if(typeof scriptArgs!=\"undefined\"){arguments_=scriptArgs}else if(typeof arguments!=\"undefined\"){arguments_=arguments}if(typeof quit===\"function\"){quit_=function(status){quit(status)}}if(typeof print!==\"undefined\"){if(typeof console===\"undefined\")console={};console.log=print;console.warn=console.error=typeof printErr!==\"undefined\"?printErr:print}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href}else if(typeof document!==\"undefined\"&&document.currentScript){scriptDirectory=document.currentScript.src}if(typeof _scriptDir !== \"undefined\" && _scriptDir){scriptDirectory=_scriptDir}if(scriptDirectory.indexOf(\"blob:\")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf(\"/\")+1)}else{scriptDirectory=\"\"}if(ENVIRONMENT_IS_NODE){read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret}}else{read_=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}if(ENVIRONMENT_IS_NODE){if(typeof performance===\"undefined\"){global.performance=require(\"perf_hooks\").performance}}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var Atomics_load=Atomics.load;var Atomics_store=Atomics.store;var Atomics_compareExchange=Atomics.compareExchange;var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var wasmModule;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module[\"wasmMemory\"];buffer=Module[\"buffer\"]}else{if(Module[\"wasmMemory\"]){wasmMemory=Module[\"wasmMemory\"]}else{wasmMemory=new WebAssembly.Memory({\"initial\":INITIAL_MEMORY/65536,\"maximum\":2147483648/65536,\"shared\":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){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\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];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)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={\"e\":___assert_fail,\"r\":___call_main,\"x\":__emscripten_notify_thread_queue,\"b\":_abort,\"y\":_emscripten_asm_const_int,\"j\":_emscripten_conditional_set_current_thread_status,\"c\":_emscripten_futex_wait,\"d\":_emscripten_futex_wake,\"f\":_emscripten_get_now,\"p\":_emscripten_memcpy_big,\"z\":_emscripten_num_logical_cores,\"u\":_emscripten_receive_on_main_thread_js,\"q\":_emscripten_resize_heap,\"v\":_emscripten_set_canvas_element_size,\"i\":_emscripten_set_current_thread_status,\"t\":_emscripten_set_thread_name,\"w\":_emscripten_webgl_create_context,\"m\":_fd_close,\"n\":_fd_seek,\"g\":_fd_write,\"o\":initPthreadsJS,\"a\":wasmMemory||Module[\"wasmMemory\"],\"k\":_pthread_cleanup_pop,\"l\":_pthread_cleanup_push,\"h\":_pthread_create,\"s\":_sysconf};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var _ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"X\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"Y\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"Z\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"_\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"$\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"aa\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"ba\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"ca\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"da\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"ea\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"fa\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"ga\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"ha\"]).apply(null,arguments)};var 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_emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=function(){return(_emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=Module[\"asm\"][\"gb\"]).apply(null,arguments)};var __emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=function(){return(__emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=Module[\"asm\"][\"hb\"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=function(){return(_emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=Module[\"asm\"][\"ib\"]).apply(null,arguments)};var _emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=function(){return(_emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=Module[\"asm\"][\"jb\"]).apply(null,arguments)};var __emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=function(){return(__emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=Module[\"asm\"][\"kb\"]).apply(null,arguments)};var _emscripten_tls_init=Module[\"_emscripten_tls_init\"]=function(){return(_emscripten_tls_init=Module[\"_emscripten_tls_init\"]=Module[\"asm\"][\"lb\"]).apply(null,arguments)};var __emscripten_thread_init=Module[\"__emscripten_thread_init\"]=function(){return(__emscripten_thread_init=Module[\"__emscripten_thread_init\"]=Module[\"asm\"][\"mb\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"nb\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"ob\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"pb\"]).apply(null,arguments)};var _emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=function(){return(_emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=Module[\"asm\"][\"qb\"]).apply(null,arguments)};var _memalign=Module[\"_memalign\"]=function(){return(_memalign=Module[\"_memalign\"]=Module[\"asm\"][\"rb\"]).apply(null,arguments)};var __emscripten_allow_main_runtime_queued_calls=Module[\"__emscripten_allow_main_runtime_queued_calls\"]=9880;var __emscripten_main_thread_futex=Module[\"__emscripten_main_thread_futex\"]=11368;Module[\"cwrap\"]=cwrap;Module[\"PThread\"]=PThread;Module[\"PThread\"]=PThread;Module[\"wasmMemory\"]=wasmMemory;Module[\"ExitStatus\"]=ExitStatus;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}if(ENVIRONMENT_IS_PTHREAD){readyPromiseResolve(Module);postMessage({\"cmd\":\"loaded\"});return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;function exit(status,implicit){if(implicit&&noExitRuntime&&status===0){return}if(!implicit){if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exitProcess\",\"returnCode\":status});throw new ExitStatus(status)}else{}}if(noExitRuntime){}else{PThread.terminateAllThreads();EXITSTATUS=status;exitRuntime();if(Module[\"onExit\"])Module[\"onExit\"](status);ABORT=true}quit_(status,new ExitStatus(status))}if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}if(ENVIRONMENT_IS_PTHREAD){noExitRuntime=false;PThread.initWorker()}run();\n\n\n  return WasmBackendModuleThreadedSimd.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModuleThreadedSimd;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModuleThreadedSimd; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModuleThreadedSimd\"] = WasmBackendModuleThreadedSimd;\n", "\nvar WasmBackendModule = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModule) {\n  WasmBackendModule = WasmBackendModule || {};\n\nvar Module=typeof WasmBackendModule!==\"undefined\"?WasmBackendModule:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var 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XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return 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Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function 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_Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\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) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = 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) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\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\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) 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 + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\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\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");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;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(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;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}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);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}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);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var nodeFS=require(\"fs\");var nodeRead=function(filename){return nodeFS.readFileSync(filename,\"utf8\")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance===\"undefined\"){performance={now:function(){return Date.now()}}}}';", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1250, moduleBytes: 4013323, imports: 7, importBytes: 2255, outputBytes: 2991826, outputFiles: 'dist/tfjs.esm.js' }\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1253, moduleBytes: 4029357, imports: 7, importBytes: 2285, outputBytes: 2998298, outputFiles: 'dist/tfjs.esm.js' }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all - compiled\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all - sources\n/*\nexport * from '@tensorflow/tfjs-core/src/index';\nexport * from '@tensorflow/tfjs-layers/src/index';\nexport * from '@tensorflow/tfjs-converter/src/index';\nexport * as data from '@tensorflow/tfjs-data/src/index';\nexport * from '@tensorflow/tfjs-backend-cpu/src/index';\nexport * from '@tensorflow/tfjs-backend-webgl/src/index';\nexport * from '@tensorflow/tfjs-backend-wasm/src/index';\n*/\n\n// export versions\nexport const version = {\n  tfjs: packageBundle?.version || undefined,\n  'tfjs-core': packageCore?.version || undefined,\n  'tfjs-data': packageData?.version || undefined,\n  'tfjs-layers': packageLayers?.version || undefined,\n  'tfjs-converter': packageConverter?.version || undefined,\n  'tfjs-backend-cpu': version_cpu || undefined,\n  'tfjs-backend-webgl': version_webgl || undefined,\n  'tfjs-backend-wasm': version_wasm || undefined,\n};\n// export const version = {};\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\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\nexport function register(): void {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 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    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './helpers';\n\nexport const data = {};\n\nexport function run(modelName: string, profileData: any): void {\n  if (!profileData || !profileData.kernels) return;\n  const maxResults = 5;\n  const time = profileData.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = profileData.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = profileData.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  data[modelName] = {\n    model: modelName,\n    newBytes: profileData.newBytes,\n    newTensors: profileData.newTensors,\n    peakBytes: profileData.peakBytes,\n    numKernelOps: profileData.kernels.length,\n    timeKernelOps: time,\n    slowestKernelOps: slowest,\n    largestKernelOps: largest,\n  };\n  log('profiler', modelName, data[modelName]);\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(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 = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      if (!Array.isArray(genderT)) {\n        const data = genderT.dataSync();\n        if (alternative) {\n          // returns two values 0..1, bigger one is prediction\n          if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n            obj.gender = data[0] > data[1] ? 'female' : 'male';\n            obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n          }\n        } else {\n          // returns one value 0..1, .5 is prediction threshold\n          const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n          if (confidence > config.face.gender.minConfidence) {\n            obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n            obj.confidence = Math.min(0.99, confidence);\n          }\n        }\n        genderT.dispose();\n      } else {\n        const gender = genderT[0].dataSync();\n        const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n        /*\n        let age = genderT[1].argMax(1).dataSync()[0];\n        const all = genderT[1].dataSync();\n        age = Math.round(all[age - 1] > all[age + 1] ? 10 * age - 100 * all[age - 1] : 10 * age + 100 * all[age + 1]) / 10;\n        const descriptor = genderT[1].dataSync();\n        */\n        genderT.forEach((t) => tf.dispose(t));\n      }\n    }\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\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\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\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    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = typeof tf.Tensor;\ntype DB = Array<{ name: string, source: string, embedding: number[] }>;\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function similarity(embedding1, embedding2, order = 2): number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<number>, db: DB, threshold = 0) {\n  let best = { similarity: 0, name: '', source: '', embedding: [] as number[] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = similarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.similarity) best = { ...f, similarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = 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    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\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    // 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    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\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\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([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: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\ntype Tensor = typeof tf.Tensor;\ntype DB = Array<{ name: string, source: string, embedding: number[] }>;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.description.modelPath);\n    if (config.debug) log(`load model: ${config.face.description.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function similarity(embedding1, embedding2, order = 2): number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = 4.0 * embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(0, 100 - distance) / 100.0;\n  return res;\n}\n\nexport function match(embedding: Array<number>, db: DB, threshold = 0) {\n  let best = { similarity: 0, name: '', source: '', embedding: [] as number[] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = similarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.similarity) best = { ...f, similarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    const tensor = input.image || input.tensor || input;\n    if (!(tensor instanceof tf.Tensor)) return null;\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    // const crop = tf.image.resizeBilinear(tensor, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\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    /*\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\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n    /*\n    // normalize brightness from 0..1\n    const darken = crop.sub(crop.min());\n    const lighten = darken.div(darken.max());\n    */\n    const norm = crop.mul(255);\n\n    return norm;\n  });\n  return image;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.description.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    // const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    // const enhanced = tf.mul(resize, [255.0]);\n    // tf.dispose(resize);\n    const enhanced = enhance(image);\n\n    let resT;\n    const obj = {\n      age: <number>0,\n      gender: <string>'unknown',\n      genderConfidence: <number>0,\n      descriptor: <number[]>[] };\n\n    if (!config.profile) {\n      if (config.face.description.enabled) resT = await model.predict(enhanced);\n    } else {\n      const profileDesc = config.face.description.enabled ? await tf.profile(() => model.predict(enhanced)) : {};\n      resT = profileDesc.result;\n      profile.run('faceres', profileDesc);\n    }\n    tf.dispose(enhanced);\n\n    if (resT) {\n      tf.tidy(() => {\n        const gender = resT.find((t) => t.shape[1] === 1).dataSync();\n        const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n          obj.genderConfidence = Math.min(0.99, confidence);\n        }\n        const age = resT.find((t) => t.shape[1] === 100).argMax(1).dataSync()[0];\n        const all = resT.find((t) => t.shape[1] === 100).dataSync();\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]);\n        // const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n        obj.descriptor = [...desc.dataSync()];\n      });\n      resT.forEach((t) => tf.dispose(t));\n    }\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log, now } from './helpers';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as faceres from './faceres/faceres';\n\ntype Tensor = typeof tf.Tensor;\n\nconst calculateFaceAngle = (face, image_size): { angle: { pitch: number, yaw: number, roll: number }, matrix: [number, number, number, number, number, number, number, number, number] } => {\n  // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n  const degrees = (theta) => (theta * 180) / Math.PI;\n  // const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n  const normalize = (v) => { // 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, b) => { // 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, b) => { // 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) => {\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; let thetaY; let thetaZ;\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    return { pitch: 2 * -thetaX, yaw: 2 * -thetaY, roll: 2 * -thetaZ };\n  };\n  // simple Euler angle calculation based existing 3D mesh\n  // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n  const meshToEulerAngle = (mesh) => {\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // pitch is face move up/down\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\n      // yaw is face turn left/right\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\n      // roll is face lean 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\n    };\n    return angle;\n  };\n\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] };\n\n  const size = Math.max(face.boxRaw[2] * image_size[0], face.boxRaw[3] * image_size[1]) / 1.5;\n  // top, bottom, left, right\n  const pts = [mesh[10], mesh[152], mesh[234], mesh[454]].map((pt) => [\n    // make the xyz coordinates proportional, independent of the image/box size\n    pt[0] * image_size[0] / size,\n    pt[1] * image_size[1] / size,\n    pt[2],\n  ]);\n\n  const y_axis = normalize(subVectors(pts[1], pts[0]));\n  let x_axis = normalize(subVectors(pts[3], pts[2]));\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  return { angle, matrix };\n};\n\nexport const detectFace = async (parent, input): Promise<any> => {\n  // run facemesh, includes blazeface and iris\n  // eslint-disable-next-line no-async-promise-executor\n  let timeStamp;\n  let ageRes;\n  let genderRes;\n  let emotionRes;\n  let embeddingRes;\n  let descRes;\n  const faceRes: Array<{\n      confidence: number,\n      boxConfidence: number,\n      faceConfidence: number,\n      box: [number, number, number, number],\n      mesh: Array<[number, number, number]>\n      meshRaw: Array<[number, number, number]>\n      boxRaw: [number, number, number, number],\n      annotations: Array<{ part: string, points: Array<[number, number, number]>[] }>,\n      age: number,\n      gender: string,\n      genderConfidence: number,\n      emotion: string,\n      embedding: number[],\n      iris: number,\n      rotation: {\n        angle: { pitch: number, yaw: number, roll: number },\n        matrix: [number, number, number, number, number, number, number, number, number]\n      },\n      tensor: Tensor,\n    }> = [];\n  parent.state = 'run:face';\n  timeStamp = now();\n  const faces = await parent.models.face?.estimateFaces(input, parent.config);\n  parent.perf.face = Math.trunc(now() - timeStamp);\n  if (!faces) return [];\n  for (const face of faces) {\n    parent.analyze('Get Face');\n\n    // is something went wrong, skip the face\n    if (!face.image || face.image.isDisposedInternal) {\n      log('Face object is disposed:', face.image);\n      continue;\n    }\n\n    const rotation = calculateFaceAngle(face, [input.shape[2], input.shape[1]]);\n\n    // run age, inherits face from blazeface\n    parent.analyze('Start Age:');\n    if (parent.config.async) {\n      ageRes = parent.config.face.age.enabled ? age.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:age';\n      timeStamp = now();\n      ageRes = parent.config.face.age.enabled ? await age.predict(face.image, parent.config) : {};\n      parent.perf.age = Math.trunc(now() - timeStamp);\n    }\n\n    // run gender, inherits face from blazeface\n    parent.analyze('Start Gender:');\n    if (parent.config.async) {\n      genderRes = parent.config.face.gender.enabled ? gender.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:gender';\n      timeStamp = now();\n      genderRes = parent.config.face.gender.enabled ? await gender.predict(face.image, parent.config) : {};\n      parent.perf.gender = Math.trunc(now() - timeStamp);\n    }\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Emotion:');\n    if (parent.config.async) {\n      emotionRes = parent.config.face.emotion.enabled ? emotion.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:emotion';\n      timeStamp = now();\n      emotionRes = parent.config.face.emotion.enabled ? await emotion.predict(face.image, parent.config) : {};\n      parent.perf.emotion = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Emotion:');\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Embedding:');\n    if (parent.config.async) {\n      embeddingRes = parent.config.face.embedding.enabled ? embedding.predict(face, parent.config) : [];\n    } else {\n      parent.state = 'run:embedding';\n      timeStamp = now();\n      embeddingRes = parent.config.face.embedding.enabled ? await embedding.predict(face, parent.config) : [];\n      parent.perf.embedding = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Embedding:');\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Description:');\n    if (parent.config.async) {\n      descRes = parent.config.face.description.enabled ? faceres.predict(face, parent.config) : [];\n    } else {\n      parent.state = 'run:description';\n      timeStamp = now();\n      descRes = parent.config.face.description.enabled ? await faceres.predict(face.image, parent.config) : [];\n      parent.perf.embedding = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Description:');\n\n    // if async wait for results\n    if (parent.config.async) {\n      [ageRes, genderRes, emotionRes, embeddingRes, descRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes, descRes]);\n    }\n\n    parent.analyze('Finish Face:');\n\n    // calculate iris distance\n    // iris: array[ center, left, top, right, bottom]\n    if (!parent.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n      delete face.annotations.leftEyeIris;\n      delete face.annotations.rightEyeIris;\n    }\n    const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n    /* average human iris size is 11.7mm */\n      ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n      : 0;\n\n    // combine results\n    faceRes.push({\n      ...face,\n      age: descRes.age || ageRes.age,\n      gender: descRes.gender || genderRes.gender,\n      genderConfidence: descRes.genderConfidence || genderRes.confidence,\n      embedding: descRes.descriptor || embeddingRes,\n      emotion: emotionRes,\n      iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n      rotation,\n      tensor: parent.config.face.detector.return ? face.image?.squeeze() : null,\n    });\n    // dispose original face tensor\n    face.image?.dispose();\n\n    parent.analyze('End Face');\n  }\n  parent.analyze('End FaceMesh:');\n  if (parent.config.async) {\n    if (parent.perf.face) delete parent.perf.face;\n    if (parent.perf.age) delete parent.perf.age;\n    if (parent.perf.gender) delete parent.perf.gender;\n    if (parent.perf.emotion) delete parent.perf.emotion;\n  }\n  return faceRes;\n};\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[2], prediction.box.endPoint[0]) - Math.max(0, prediction.box.startPoint[0]),\n        Math.min(input.shape[1], prediction.box.endPoint[1]) - Math.max(0, prediction.box.startPoint[1]),\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        prediction.box.startPoint[0] / input.shape[2],\n        prediction.box.startPoint[1] / input.shape[1],\n        (prediction.box.endPoint[0] - prediction.box.startPoint[0]) / input.shape[2],\n        (prediction.box.endPoint[1] - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: Math.round(100 * prediction.faceConfidence || 100 * prediction.boxConfidence || 0) / 100,\n        boxConfidence: Math.round(100 * prediction.boxConfidence) / 100,\n        faceConfidence: Math.round(100 * prediction.faceConfidence) / 100,\n        box,\n        boxRaw,\n        mesh,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config): Promise<MediaPipeFaceMesh> {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexport const triangulation = coords.TRI468;\nexport const uvmap = coords.UV468;\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\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++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\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 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]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\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];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\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 function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\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\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\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],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\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 MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\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 = [\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 = [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 = [\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 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\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 = [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 = [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", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\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], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  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.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\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.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\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 / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * 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.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${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\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (!config.videoOptimized || (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces)))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(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\n          // 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          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && (config.face.description.enabled || config.face.embedding.enabled) && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\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, landmarks };\n  }\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\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() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\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    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", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, 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(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.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 < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "export 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 NUM_KEYPOINTS = 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 const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\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", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\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 sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, 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 sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !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    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score: Math.round(100 * score) / 100 });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.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\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return 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: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, boxRaw: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - Math.max(0, prediction.box.topLeft[0]),\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - Math.max(0, prediction.box.topLeft[1]),\n      ] : [];\n      const boxRaw = [\n        (prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.topLeft[1]) / input.shape[1],\n        (prediction.box.bottomRight[0] - prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.bottomRight[1] - prediction.box.topLeft[1]) / input.shape[1],\n      ];\n      hands.push({ confidence: Math.round(100 * prediction.confidence) / 100, box, boxRaw, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config): Promise<HandPose> {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\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]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\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]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\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];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\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]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "export 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", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\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 box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.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 = [...box.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      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) 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.maxHands) || !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<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\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[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? 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 = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\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", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.984375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.984375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    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   x_center: 0.5625,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  const score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n  return [{ score, keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet keypoints: Array<any> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst bodyParts = ['head', 'neck', 'rightShoulder', 'rightElbow', 'rightWrist', 'chest', 'leftShoulder', 'leftElbow', 'leftWrist', 'pelvis', 'rightHip', 'rightKnee', 'rightAnkle', 'leftHip', 'leftKnee', 'leftAnkle'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\n// performs argmax and max functions on a 2d tensor\nfunction max2d(inputs, minScore) {\n  const [width, height] = inputs.shape;\n  return tf.tidy(() => {\n    // modulus op implemented in tf\n    const mod = (a, b) => tf.sub(a, tf.mul(tf.div(a, tf.scalar(b, 'int32')), tf.scalar(b, 'int32')));\n    // combine all data\n    const reshaped = tf.reshape(inputs, [height * width]);\n    // get highest score\n    const score = tf.max(reshaped, 0).dataSync()[0];\n    if (score > minScore) {\n      // skip coordinate calculation is score is too low\n      const coords = tf.argMax(reshaped, 0);\n      const x = mod(coords, width).dataSync()[0];\n      const y = tf.div(coords, tf.scalar(width, 'int32')).dataSync()[0];\n      return [x, y, score];\n    }\n    return [0, 0, score];\n  });\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.body.skipFrames) && config.videoOptimized && Object.keys(keypoints).length > 0) {\n    skipped++;\n    return keypoints;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const tensor = tf.tidy(() => {\n      const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n      const enhance = tf.mul(resize, 2);\n      const norm = enhance.sub(1);\n      return norm;\n    });\n\n    let resT;\n\n    if (!config.profile) {\n      if (config.body.enabled) resT = await model.predict(tensor);\n    } else {\n      const profileT = config.body.enabled ? await tf.profile(() => model.predict(tensor)) : {};\n      resT = profileT.result.clone();\n      profileT.result.dispose();\n      profile.run('body', profileT);\n    }\n    tensor.dispose();\n\n    if (resT) {\n      const parts: Array<{ id, score, part, position: { x, y }, positionRaw: { xRaw, yRaw} }> = [];\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, score] = max2d(stack[id], config.body.scoreThreshold);\n        if (score > config.body.scoreThreshold) {\n          parts.push({\n            id,\n            score: Math.round(100 * score) / 100,\n            part: bodyParts[id],\n            positionRaw: {\n              xRaw: x / model.inputs[0].shape[2], // x normalized to 0..1\n              yRaw: y / model.inputs[0].shape[1], // y normalized to 0..1\n            },\n            position: {\n              x: Math.round(image.shape[2] * x / model.inputs[0].shape[2]), // x normalized to input image size\n              y: Math.round(image.shape[1] * y / model.inputs[0].shape[1]), // y normalized to input image size\n            },\n          });\n        }\n      }\n      stack.forEach((s) => tf.dispose(s));\n      keypoints = parts;\n    }\n    const score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n    resolve([{ score, keypoints }]);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport { labels } from './labels';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let id = 0;\n  let results: Array<{ score: number, strideSize: number, class: number, label: string, center: number[], centerRaw: number[], box: number[], boxRaw: number[] }> = [];\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(() => { // 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 = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === labels.length))?.squeeze();\n      const featuresT = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] < labels.length))?.squeeze();\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 = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      const scores = scoresT.arraySync(); // 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 && 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) => 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 = [x, y, w, h]; // results normalized to range 0..1\n            boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // 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,\n              center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n              centerRaw: [cx, cy],\n              box: box.map((a) => Math.trunc(a)),\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);\n  const nmsScores = results.map((a) => a.score);\n  let nmsIdx: any[] = [];\n  if (nmsBoxes && nmsBoxes.length > 0) {\n    const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n    nmsIdx = nms.dataSync();\n    tf.dispose(nms);\n  }\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n    resize.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result;\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export 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", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\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.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) 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) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\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];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (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\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), 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, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\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  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\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  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\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    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\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    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\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;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\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)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\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  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\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  ].join('\\n');\n\n  _filter.brightness = function (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  _filter.saturation = function (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  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\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  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (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\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  _filter.desaturateLuminance = function () {\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  _filter.sepia = function () {\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  _filter.brownie = function () {\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  _filter.vintagePinhole = function () {\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  _filter.kodachrome = function () {\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  _filter.technicolor = function () {\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  _filter.polaroid = function () {\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  _filter.shiftToBGR = function () {\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  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\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  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\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  _filter.emboss = function (size) {\n    const s = size || 1;\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  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\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  _filter.blur.SHADER = [\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  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\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  ].join('\\n');\n}\n", "// @ts-nocheck\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\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 function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (!input) throw new Error('Human: Input is missing');\n  if (\n    !(input instanceof tf.Tensor)\n    && !(typeof Image !== 'undefined' && input instanceof Image)\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('Human: Input type is not recognized');\n  }\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\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    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) throw new Error('Human: Input cannot determine dimension');\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) { // if we have data, just convert to tensor\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if (outCanvas instanceof ImageData) { // if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else if (config.backend === 'webgl' || config.backend === 'humangl') { // tf kernel-optimized method to get imagedata\n      // we can use canvas as-is as it already has a context, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      pixels = tf.browser.fromPixels(tempCanvas);\n    } else { // cpu and wasm kernel does not implement efficient fromPixels method\n      // we can use canvas as-is as it already has a context, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "import { defaults } from '../config';\nimport { TRI468 as triangulation } from '../blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n  useRawBoxes: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n      else rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.rotation && f.rotation.angle && f.rotation.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.rotation.angle.roll) / 100} yaw:${Math.trunc(100 * f.rotation.angle.yaw) / 100} pitch:${Math.trunc(100 * f.rotation.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.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 (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.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 (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      if (result[i].keypoints) {\n        for (const pt of result[i].keypoints) {\n          ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n          ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons && result[i].keypoints) {\n      let part;\n      const points: any[] = [];\n      // shoulder line\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // torso main\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 4) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas: HTMLCanvasElement, outCanvas: HTMLCanvasElement) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas: HTMLCanvasElement, result:any) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\n/**\n * Configuration interface definition for **Human** library\n *\n * Contains all configurable parameters\n */\nexport interface Config {\n  backend: string,\n  wasmPath: string,\n  debug: boolean,\n  async: boolean,\n  profile: boolean,\n  deallocate: boolean,\n  scoped: boolean,\n  videoOptimized: boolean,\n  warmup: string,\n  filter: {\n    enabled: boolean,\n    width: number,\n    height: number,\n    return: boolean,\n    brightness: number,\n    contrast: number,\n    sharpness: number,\n    blur: number\n    saturation: number,\n    hue: number,\n    negative: boolean,\n    sepia: boolean,\n    vintage: boolean,\n    kodachrome: boolean,\n    technicolor: boolean,\n    polaroid: boolean,\n    pixelate: number,\n  },\n  gesture: {\n    enabled: boolean,\n  },\n  face: {\n    enabled: boolean,\n    detector: {\n      modelPath: string,\n      rotation: boolean,\n      maxFaces: number,\n      skipFrames: number,\n      skipInitial: boolean,\n      minConfidence: number,\n      iouThreshold: number,\n      scoreThreshold: number,\n      return: boolean,\n    },\n    mesh: {\n      enabled: boolean,\n      modelPath: string,\n    },\n    iris: {\n      enabled: boolean,\n      modelPath: string,\n    },\n    description: {\n      enabled: boolean,\n      modelPath: string,\n      skipFrames: number,\n    },\n    age: {\n      enabled: boolean,\n      modelPath: string,\n      skipFrames: number,\n    },\n    gender: {\n      enabled: boolean,\n      minConfidence: number,\n      modelPath: string,\n      skipFrames: number,\n    },\n    emotion: {\n      enabled: boolean,\n      minConfidence: number,\n      skipFrames: number,\n      modelPath: string,\n    },\n    embedding: {\n      enabled: boolean,\n      modelPath: string,\n    },\n  },\n  body: {\n    enabled: boolean,\n    modelPath: string,\n    maxDetections: number,\n    scoreThreshold: number,\n    nmsRadius: number,\n  },\n  hand: {\n    enabled: boolean,\n    rotation: boolean,\n    skipFrames: number,\n    skipInitial: boolean,\n    minConfidence: number,\n    iouThreshold: number,\n    scoreThreshold: number,\n    maxHands: number,\n    landmarks: boolean,\n    detector: {\n      modelPath: string,\n    },\n    skeleton: {\n      modelPath: string,\n    },\n  },\n  object: {\n    enabled: boolean,\n    modelPath: string,\n    minConfidence: number,\n    iouThreshold: number,\n    maxResults: number,\n    skipFrames: number,\n  },\n}\n\nconst config: Config = {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // 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    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    description: {\n      enabled: true,         // to improve accuracy of face description extraction it is\n                             // recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/faceres.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 32,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    age: {\n      enabled: false,        // obsolete, replaced by description module\n      modelPath: '../models/age.json',\n      skipFrames: 33,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: false,        // obsolete, replaced by description module\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 34,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    embedding: {\n      enabled: false,        // obsolete, replaced by description module\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet', 'blazepose' or 'efficientpose'\n                             // 'blazepose' and 'efficientpose' are experimental\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n                             // 'nanodet' is experimental\n    minConfidence: 0.20,     // threshold for discarding a prediction\n    iouThreshold: 0.40,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 41,          // how many frames to go without re-running the detector\n  },\n};\nexport { config as defaults };\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import { log, now, mergeDeep } from './helpers';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as faceall from './faceall';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as faceres from './faceres/faceres';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as efficientpose from './efficientpose/efficientpose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image/image';\nimport * as draw from './draw/draw';\nimport * as profile from './profile';\nimport { Config, defaults } from './config';\nimport { Result } from './result';\nimport * as sample from './sample';\nimport * as app from '../package.json';\n\n/** Generic Tensor object type */\nexport type Tensor = typeof tf.Tensor;\nexport type { Config } from './config';\nexport type { Result } from './result';\n/** Defines all possible input types for **Human** detection */\nexport type Input = Tensor | typeof Image | ImageData | ImageBitmap | HTMLImageElement | HTMLMediaElement | HTMLVideoElement | HTMLCanvasElement | OffscreenCanvas;\n\n/** Error message */\nexport type Error = { error: string };\n/** Instance of TensorFlow/JS */\nexport type TensorFlow = typeof tf;\n/** Generic Model object type, holds instance of individual models */\ntype Model = Object;\n\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 */\nexport class Human {\n  version: string;\n  config: Config;\n  state: string;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: TensorFlow;\n  draw: {\n    drawOptions?: typeof draw.drawOptions,\n    gesture: typeof draw.gesture,\n    face: typeof draw.face,\n    body: typeof draw.body,\n    hand: typeof draw.hand,\n    canvas: typeof draw.canvas,\n    all: typeof draw.all,\n  };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | Model | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    efficientpose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n    faceres: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n    faceres: typeof faceres;\n  };\n  faceTriangulation: typeof facemesh.triangulation;\n  faceUVMap: typeof facemesh.uvmap;\n  sysinfo: { platform: string, agent: string };\n  perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: boolean;\n  #checkSanity: boolean;\n  #firstRun: boolean;\n  // definition end\n\n  constructor(userConfig: Config | Object = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.version = app.version;\n    this.config = mergeDeep(defaults, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      efficientpose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n      faceres: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Input) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      faceres,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    this.faceTriangulation = facemesh.triangulation;\n    this.faceUVMap = facemesh.uvmap;\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | string => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_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  similarity(embedding1: Array<number>, embedding2: Array<number>): number {\n    if (this.config.face.description.enabled) return faceres.similarity(embedding1, embedding2);\n    if (this.config.face.embedding.enabled) return embedding.similarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return faceres.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<number>, db: Array<{ name: string, source: string, embedding: number[] }>, threshold = 0): { name: string, source: string, similarity: number, embedding: number[] } {\n    return faceres.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Config | Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        // @ts-ignore\n        this.models.handpose,\n        // @ts-ignore false warning with latest @typescript-eslint\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.efficientpose,\n        this.models.nanodet,\n        this.models.faceres,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? <Promise<handpose.HandPose>>handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.blazepose || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.efficientpose || (this.config.body.enabled && this.config.body.modelPath.includes('efficientpose') ? efficientpose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n        this.models.faceres || ((this.config.face.enabled && this.config.face.description.enabled) ? faceres.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.body.enabled && !this.models.efficientpose && this.config.body.modelPath.includes('efficientpose')) this.models.efficientpose = await efficientpose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n      if (this.config.face.enabled && this.config.face.description.enabled && !this.models.faceres) this.models.faceres = await faceres.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.perf.load || 0)) this.perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        // force browser vs node backend\n        if (this.tf.ENV.flags.IS_BROWSER && this.config.backend === 'tensorflow') this.config.backend = 'webgl';\n        if (this.tf.ENV.flags.IS_NODE && (this.config.backend === 'webgl' || this.config.backend === 'wasm')) this.config.backend = 'tensorflow';\n\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      // this.tf.enableDebugMode();\n      if (this.tf.getBackend() === 'webgl' || this.tf.getBackend() === 'humangl') {\n        this.tf.ENV.set('CHECK_COMPUTATION_FOR_ERRORS', false);\n        this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  // main detect function\n  async detect(input: Input, userConfig: Config | Object = {}): Promise<Result | Error> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.perf.image = Math.trunc(now() - timeStamp);\n      this.analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n      let current;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? faceall.detectFace(this, process.tensor) : [];\n        if (this.perf.face) delete this.perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await faceall.detectFace(this, process.tensor) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.face = current;\n      }\n\n      // run body: can be posenet or blazepose\n      this.analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('blazepose')) bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('efficientpose')) bodyRes = this.config.body.enabled ? efficientpose.predict(process.tensor, this.config) : [];\n        if (this.perf.body) delete this.perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('blazepose')) bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('efficientpose')) bodyRes = this.config.body.enabled ? await efficientpose.predict(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.body = current;\n      }\n      this.analyze('End Body:');\n\n      // run handpose\n      this.analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.perf.hand) delete this.perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.hand = current;\n      }\n      this.analyze('End Hand:');\n\n      // run nanodet\n      this.analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.perf.object) delete this.perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.object = current;\n      }\n      this.analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.perf.gesture) delete this.perf.gesture;\n      }\n\n      this.perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      const result = {\n        face: faceRes,\n        body: bodyRes,\n        hand: handRes,\n        gesture: gestureRes,\n        object: objectRes,\n        performance: this.perf,\n        canvas: process.canvas,\n      };\n      // log('Result:', result);\n      resolve(result);\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\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 this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.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    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Config | Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\n/**\n * Class Human is also available as default export\n */\nexport { Human as default };\n"],
+  "mappings": 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   "names": []
 }
diff --git a/dist/human.js b/dist/human.js
index 47616ba3..7cd7fb6a 100644
--- a/dist/human.js
+++ b/dist/human.js
@@ -5,31 +5,31 @@
   author: <https://github.com/vladmandic>'
   */
 
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r=++this.pendingBackendInitId,a=n.then(s=>r<this.pendingBackendInitId?!1:(this.registry[e]=s,this.pendingBackendInit=null,!0)).catch(s=>(r<this.pendingBackendInitId||(this.pendingBackendInit=null,console.warn(`Initialization of backend ${e} failed`),console.warn(s.stack||s.message)),!1));return this.pendingBackendInit=a,{success:a,asyncInit:!0}}else return this.registry[e]=n,{success:!0,asyncInit:!1}}catch(n){return console.warn(`Initialization of backend ${e} failed`),console.warn(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${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:r,asyncInit:a}=this.initializeBackend(n);if(a||r)return{name:n,asyncInit:a}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let n=this.state.tensorInfo.get(t),r=n.backend,a=this.readSync(t),s=r.refCount(t);r.disposeData(t,!0),n.backend=e,e.move(t,a,n.shape,n.dtype,s),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 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this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let r=this.backend.numDataIds(),a=0;n.forEach(o=>{a+=o.dtype==="complex64"?3:1});let s=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=r-t-a-s;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],r=this.isTapeOn(),a=this.state.numBytes,s=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let o,l=bf(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(bf(e)){let{kernelName:p,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let A=ad(p,this.backendName);M(A!=null,()=>`Cannot find registered kernel '${p}' for backend '${this.backendName}'`),i=()=>{let y=this.backend.numDataIds();o=A.kernelFunc({inputs:f,attrs:m,backend:this.backend});let g=Array.isArray(o)?o:[o];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(p,y,g);let w=g.map(b=>{if(b.rank!=null)return b;let{dataId:_,shape:x,dtype:N}=b;return this.makeTensorFromDataId(_,x,N)});if(r){let b=this.getTensorsForGradient(p,f,w);n=this.saveTensorsForBackwardMode(b)}return w}}else{let{forwardFunc:p}=e,f=m=>{!r||(n=m.map(A=>this.keep(this.clone(A))))};i=()=>{let m=this.backend.numDataIds();o=this.tidy(()=>p(this.backend,f));let A=Array.isArray(o)?o:[o];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,m,A),A}}let{inputs:c,attrs:u}=e,h=bf(e)?null:e.backwardsFunc,d;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(d=this.profiler.profileKernel(l,c,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),r&&this.addTapeNode(l,c,t,h,n,u),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-a,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-s,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(c).map(p=>c[p]!=null?c[p].shape:null),outputShapes:t.map(p=>p.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(t=>this.keep(this.clone(t)))}getTensorsForGradient(e,t,n){let r=pf(e);if(r!=null){let a=r.inputsToSave||[],s=r.outputsToSave||[],i;r.saveAllInputs?(M(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(l=>t[l])):i=a.map(l=>t[l]);let 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n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*sf(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 Du||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*sf(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(r=>r.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let r of 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this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(d=this.profiler.profileKernel(l,c,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),r&&this.addTapeNode(l,c,t,h,n,u),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-a,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-s,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(c).map(p=>c[p]!=null?c[p].shape:null),outputShapes:t.map(p=>p.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(t=>this.keep(this.clone(t)))}getTensorsForGradient(e,t,n){let r=gf(e);if(r!=null){let a=r.inputsToSave||[],s=r.outputsToSave||[],i;r.saveAllInputs?(M(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(l=>t[l])):i=a.map(l=>t[l]);let 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n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*hf(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 $u||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*hf(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(r=>r.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let r of 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+          with dtype ${s.dtype}. `)}),n.length===1)return Rr(n[0]);let r=n,a={axis:t};return D.runKernel(io,r,a)}var rt=O({concat_:gS});function xS(e){let t={x:C(e,"x","sigmoid")};return D.runKernel(Us,t)}var Rn=O({sigmoid_:xS});function bS(e,t,n){let r=C(e,"x","slice","string_or_numeric");if(r.rank===0)throw new Error("Slicing scalar is not possible");let a={x:r},s={begin:t,size:n};return D.runKernel(Bo,a,s)}var Ce=O({slice_:bS});function wS(e){let t={x:C(e,"x","tanh")};return D.runKernel(Zs,t)}var ll=O({tanh_:wS});function _S(e,t,n,r,a,s){let i=C(e,"forgetBias","basicLSTMCell"),o=C(t,"lstmKernel","basicLSTMCell"),l=C(n,"lstmBias","basicLSTMCell"),c=C(r,"data","basicLSTMCell"),u=C(a,"c","basicLSTMCell"),h=C(s,"h","basicLSTMCell"),d=rt([c,h],1),p=Ge(d,o),f=se(p,l),m=f.shape[0],A=f.shape[1]/4,y=[m,A],g=Ce(f,[0,0],y),b=Ce(f,[0,A],y),w=Ce(f,[0,A*2],y),_=Ce(f,[0,A*3],y),x=se(P(Rn(g),ll(b)),P(u,Rn(se(i,w)))),N=P(ll(x),Rn(_));return[x,N]}var vS=O({basicLSTMCell_:_S});function kS(e,t,n){let r=C(e,"x","batchToSpaceND"),a=t.reduce((o,l)=>o*l);M(r.rank>=1+t.length,()=>`input rank is ${r.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(r.shape[0]%a==0,()=>`input tensor batch is ${r.shape[0]} but is not divisible by the product of the elements of blockShape ${t.join(" * ")} === ${a}`);let s={x:r},i={blockShape:t,crops:n};return D.runKernel(fu,s,i)}var ju=O({batchToSpaceND_:kS});function IS(e){let t;return e.rank===0||e.rank===1?t=H(e,[1,1,1,e.size]):e.rank===2?t=H(e,[1,1,e.shape[0],e.shape[1]]):e.rank===3?t=H(e,[1,e.shape[0],e.shape[1],e.shape[2]]):t=e,t}function NS(e,t,n,r,a,s){s==null&&(s=.001);let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),c;a!=null&&(c=C(a,"scale","batchNorm"));let u;r!=null&&(u=C(r,"offset","batchNorm")),M(o.rank===l.rank,()=>"Batch normalization gradient requires mean and variance to have equal 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${c.rank}.`),u!=null&&M(u.rank===2||u.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${u.rank}.`),ui(i,o,l,u,c,s)}var Fb=O({batchNorm2d_:SS});function TS(e,t,n,r,a,s){let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),c;a!=null&&(c=C(a,"scale","batchNorm"));let u;return r!=null&&(u=C(r,"offset","batchNorm")),M(i.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${i.rank}.`),M(o.rank===3||o.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${o.rank}.`),M(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`),c!=null&&M(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${c.rank}.`),u!=null&&M(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${u.rank}.`),ui(i,o,l,u,c,s)}var Db=O({batchNorm3d_:TS});function ES(e,t,n,r,a,s){let i=C(e,"x","batchNorm"),o=C(t,"mean","batchNorm"),l=C(n,"variance","batchNorm"),c;a!=null&&(c=C(a,"scale","batchNorm"));let u;return r!=null&&(u=C(r,"offset","batchNorm")),M(i.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${i.rank}.`),M(o.rank===4||o.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${o.rank}.`),M(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),c!=null&&M(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${c.rank}.`),u!=null&&M(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${u.rank}.`),ui(i,o,l,u,c,s)}var $b=O({batchNorm4d_:ES});function CS(e,t,n){let r=C(e,"x","bincount"),a=C(t,"weights","bincount");M(r.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${r.dtype}`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(a.size===r.size||a.size===0,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${r.shape}, weights shape: ${a.shape}.`);let s={x:r,weights:a},i={size:n};return D.runKernel(Ch,s,i)}var Ob=O({bincount_:CS});function RS(e,t){let n=C(e,"broadcastTo","x"),r=n.shape;if(t.some(l=>!(l>0)||l%1!=0))throw new Error(`broadcastTo(): Invalid broadcast shape [${t}].`);if(t.length<n.rank)throw new Error(`broadcastTo(): shape.length=${t.length} < input.rank=${n.rank}.`);if(t.length>n.rank){let l=n.shape.slice();for(;l.length<t.length;)l.unshift(1);n=H(n,l)}let a=n.shape,s=Array.from(t);for(let l=t.length-1;l>=0;l--)if(a[l]===t[l])s[l]=1;else if(n.shape[l]!==1)throw new Error(`broadcastTo(): [${r}] cannot be broadcast to [${t}].`);if(s.map((l,c)=>l>1?c:-1).filter(l=>l>=0).length===0)return Rr(n);let i={x:n},o={reps:s};return D.runKernel(Ia,i,o)}var Uu=O({broadcastTo_:RS});function MS(e){let t={x:C(e,"x","ceil")};return D.runKernel(hs,t)}var am=O({ceil_:MS});function FS(e,t,n){let r=C(e,"x","clipByValue");M(t<=n,()=>`Error in clip: min (${t}) must be less than or equal to max (${n}).`);let a={x:r},s={clipValueMin:t,clipValueMax:n};return D.runKernel(ka,a,s)}var wn=O({clipByValue_:FS});function DS(e){return rt(e,0)}var zb=O({concat1d_:DS});function $S(e,t){return rt(e,t)}var ul=O({concat2d_:$S});function OS(e,t){return rt(e,t)}var Pb=O({concat3d_:OS});function zS(e,t){return rt(e,t)}var Lb=O({concat4d_:zS});function PS(e,t,n,r,a="NHWC",s=[1,1],i){let o=C(e,"x","conv2d"),l=C(t,"filter","conv2d"),c=o,u=!1;o.rank===3&&(u=!0,c=H(o,[1,o.shape[0],o.shape[1],o.shape[2]])),M(c.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${c.rank}.`),M(l.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`),i!=null&&M(Vt(r),()=>`Error in conv2d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`);let h=a==="NHWC"?c.shape[3]:c.shape[1];M(h===l.shape[2],()=>`Error in conv2d: depth of input (${h}) must match input depth for filter ${l.shape[2]}.`),M(Fr(n,s),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${s}'`);let d={x:c,filter:l},p={strides:n,pad:r,dataFormat:a,dilations:s,dimRoundingMode:i},f=D.runKernel(ds,d,p);return u?H(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var na=O({conv2d_:PS});function LS(e,t,n,r,a="NWC",s=1,i){let o=C(e,"x","conv1d"),l=C(t,"filter","conv1d"),c=o,u=!1;o.rank===2&&(u=!0,c=H(o,[1,o.shape[0],o.shape[1]])),M(c.rank===3,()=>`Error in conv1d: input must be rank 3, but got rank ${c.rank}.`),M(l.rank===3,()=>`Error in conv1d: filter must be rank 3, but got rank ${l.rank}.`),i!=null&&M(Vt(r),()=>`Error in conv1d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`),M(c.shape[2]===l.shape[1],()=>`Error in conv1d: depth of input (${c.shape[2]}) must match input depth for filter ${l.shape[1]}.`),M(Fr(n,s),()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${n} and dilation '${s}'`),M(a==="NWC",()=>`Error in conv1d: got dataFormat of ${a} but only NWC is currently supported.`);let h=H(l,[1,l.shape[0],l.shape[1],l.shape[2]]),d=H(c,[c.shape[0],1,c.shape[1],c.shape[2]]),p=na(d,h,[1,n],r,"NHWC",[1,s],i);return u?H(p,[p.shape[2],p.shape[3]]):H(p,[p.shape[0],p.shape[2],p.shape[3]])}var yd=O({conv1d_:LS});function WS(e,t,n,r,a,s="NHWC",i){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let o=e,l=t,c=!1;t.rank===3&&(c=!0,l=H(t,[1,t.shape[0],t.shape[1],t.shape[2]]),o=[1,e[0],e[1],e[2]]),M(o.length===4,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${o.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 ${n.rank}`);let u=s==="NHWC"?o[3]:o[1],h=s==="NHWC"?l.shape[3]:l.shape[1];M(u===n.shape[2],()=>`Error in conv2dDerInput: depth of input (${u}) must match input depth for filter ${n.shape[2]}.`),M(h===n.shape[3],()=>`Error in conv2dDerInput: depth of output (${h}) must match output depth for filter ${n.shape[3]}.`),i!=null&&M(Vt(a),()=>`Error in conv2dDerInput: pad must be an integer when using, dimRoundingMode ${i} but got pad ${a}.`);let d={dy:l,filter:n},p={strides:r,pad:a,dataFormat:s,dimRoundingMode:i,inputShape:o},f=D.runKernel(ps,d,p);return c?H(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var sm=O({conv2DBackpropInput_:WS});function BS(e,t,n,r,a,s){let i=C(e,"x","conv2dTranspose"),o=C(t,"filter","conv2dTranspose");return sm(n,i,o,r,a,"NHWC",s)}var gd=O({conv2dTranspose_:BS});function VS(e,t,n,r,a="NDHWC",s=[1,1,1]){let i=C(e,"x","conv3d"),o=C(t,"filter","conv3d"),l=i,c=!1;i.rank===4&&(c=!0,l=H(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),M(l.rank===5,()=>`Error in conv3d: input must be rank 5, but got rank ${l.rank}.`),M(o.rank===5,()=>`Error in conv3d: filter must be rank 5, but got rank ${o.rank}.`),M(l.shape[4]===o.shape[3],()=>`Error in conv3d: depth of input (${l.shape[4]}) must match input depth for filter ${o.shape[3]}.`),M(Fr(n,s),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${n} and dilations '${s}'`),M(a==="NDHWC",()=>`Error in conv3d: got dataFormat of ${a} but only NDHWC is currently supported.`);let u={x:l,filter:o},h={strides:n,pad:r,dataFormat:a,dilations:s},d=D.runKernel(Au,u,h);return c?H(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var im=O({conv3d_:VS});function jS(e,t,n,r,a){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let s=e,i=t,o=!1;t.rank===4&&(o=!0,i=H(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),s=[1,e[0],e[1],e[2],e[3]]);let l=s[4],c=i.shape[4];M(s.length===5,()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${s.length}.`),M(i.rank===5,()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${i.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 ${n.shape[3]}.`),M(c===n.shape[4],()=>`Error in conv3dDerInput: depth of output (${c}) must match output depth for filter ${n.shape[4]}.`);let u={dy:i,filter:n},h={pad:a,strides:r,inputShape:s},d=D.runKernel(Dh,u,h);return o?H(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var Wb=O({conv3DBackpropInput_:jS});function US(e,t,n,r,a){let s=C(e,"x","conv3dTranspose"),i=C(t,"filter","conv3dTranspose");return Wb(n,s,i,r,a)}var HS=O({conv3dTranspose_:US});function GS(e){let t={x:C(e,"x","cos")};return D.runKernel(fs,t)}var Hu=O({cos_:GS});function qS(e){let t={x:C(e,"x","cosh")};return D.runKernel(oo,t)}var xd=O({cosh_:qS});function XS(e,t=0,n=!1,r=!1){let a={x:C(e,"x","cumsum")},s={axis:t,exclusive:n,reverse:r};return D.runKernel(ms,a,s)}var bd=O({cumsum_:XS});function KS(e,t,n,r=!1){let a=C(e,"x","denseBincount"),s=C(t,"weights","denseBincount");M(a.dtype==="int32",()=>`Error in denseBincount: input dtype must be int32, but got ${a.dtype}`),M(a.rank<=2,()=>`Error in denseBincount: input must be at most rank 2, but got rank ${a.rank}.`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(s.size===a.size||s.size===0,()=>`Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${a.shape}, weights shape: ${s.shape}.`);let i={x:a,weights:s},o={size:n,binaryOutput:r};return D.runKernel($h,i,o)}var Bb=O({denseBincount_:KS});function ZS(e,t,n="NHWC"){let r=C(e,"x","depthToSpace"),a=n==="NHWC"?r.shape[1]:r.shape[2],s=n==="NHWC"?r.shape[2]:r.shape[3],i=n==="NHWC"?r.shape[3]:r.shape[1];M(a*t>=0,()=>`Negative dimension size caused by overflow when multiplying
     ${a} and ${t}  for depthToSpace with input shape
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A=0;A<t.length;A++)t[A]>a&&c.push({score:t[A],boxIndex:A,suppressBeginIndex:0});c.sort(gw);let u=s>0?-.5/s:0,h=[],d=[];for(;h.length<n&&c.length>0;){let A=c.pop(),{score:y,boxIndex:g,suppressBeginIndex:b}=A;if(y<a)break;let w=!1;for(let _=h.length-1;_>=b;--_){let x=pR(e,g,h[_]);if(x>=r){w=!0;break}if(A.score=A.score*fR(r,u,x),A.score<=a)break}A.suppressBeginIndex=h.length,w||(A.score===y?(h.push(g),d.push(A.score)):A.score>a&&cR(c,A,gw))}let p=h.length,f=n-p;o&&f>0&&(h.push(...new Array(f).fill(0)),d.push(...new Array(f).fill(0)));let m={selectedIndices:h};return i&&(m.selectedScores=d),l&&(m.validOutputs=p),m}function pR(e,t,n){let r=e.subarray(t*4,t*4+4),a=e.subarray(n*4,n*4+4),s=Math.min(r[0],r[2]),i=Math.min(r[1],r[3]),o=Math.max(r[0],r[2]),l=Math.max(r[1],r[3]),c=Math.min(a[0],a[2]),u=Math.min(a[1],a[3]),h=Math.max(a[0],a[2]),d=Math.max(a[1],a[3]),p=(o-s)*(l-i),f=(h-c)*(d-u);if(p<=0||f<=0)return 0;let 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s=a,i=!1;a.rank===3&&(i=!0,s=H(a,[1,a.shape[0],a.shape[1],a.shape[2]]));let[]=t,o={images:s},l={alignCorners:n,halfPixelCenters:r,size:t},c=D.runKernel(Iu,o,l);return i?H(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var bw=O({resizeNearestNeighbor_:NR});function SR(e,t,n="nearest",r="constant",a=0,s){let i=C(e,"image","transform","float32"),o=C(t,"transforms","transform","float32");M(i.rank===4,()=>`Error in transform: image must be rank 4,but got rank ${i.rank}.`),M(o.rank===2&&(o.shape[0]===i.shape[0]||o.shape[0]===1)&&o.shape[1]===8,()=>"Error in transform: Input transform should be batch x 8 or 1 x 8"),M(s==null||s.length===2,()=>`Error in transform: outputShape must be [height, width] or null, but got ${s}.`);let l={image:i,transforms:o},c={interpolation:n,fillMode:r,fillValue:a,outputShape:s};return D.runKernel(td,l,c)}var TR=O({transform_:SR});function ER(e,t,n){M(t%1==0,()=>`bandPart(): numLower must be an integer, got ${t}.`),M(n%1==0,()=>`bandPart(): numUpper must be an integer, 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a=C(e,"labels","hingeLoss"),s=C(t,"predictions","hingeLoss"),i=null;n!=null&&(i=C(n,"weights","hingeLoss")),nn(a.shape,s.shape,"Error in hingeLoss: ");let o=ge(1);a=Ae(P(ge(2),a),o);let l=zr(Ae(o,P(a,s)));return sa(l,i,r)}var BR=O({hingeLoss_:WR});function VR(e,t,n,r=1,a=cn.SUM_BY_NONZERO_WEIGHTS){let s=C(e,"labels","huberLoss"),i=C(t,"predictions","huberLoss"),o=null;n!=null&&(o=C(n,"weights","huberLoss")),nn(s.shape,i.shape,"Error in huberLoss: ");let l=ge(r),c=$t(Ae(i,s)),u=ml(c,l),h=Ae(c,u),d=se(P(ge(.5),it(u)),P(l,h));return sa(d,o,a)}var jR=O({huberLoss_:VR});function UR(e,t,n,r=1e-7,a=cn.SUM_BY_NONZERO_WEIGHTS){let s=C(e,"labels","logLoss"),i=C(t,"predictions","logLoss"),o=null;n!=null&&(o=C(n,"weights","logLoss")),nn(s.shape,i.shape,"Error in logLoss: ");let l=ge(1),c=ge(r),u=_t(P(s,Mn(se(i,c)))),h=P(Ae(l,s),Mn(se(Ae(l,i),c))),d=Ae(u,h);return sa(d,o,a)}var HR=O({logLoss_:UR});function GR(e,t,n,r=cn.SUM_BY_NONZERO_WEIGHTS){let 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FM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,scale:s,offset:i,mean:o,variance:l}=t;v.assert(o.shape.length===l.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||o.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(s==null||o.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks."),_e([a,o,l,s,i],"batchNorm");let{varianceEpsilon:c}=r;c==null&&(c=.001);let u=n.data.get(a.dataId).values,h=n.data.get(o.dataId).values,d=n.data.get(l.dataId).values,p=s?n.data.get(s.dataId).values:new Float32Array([1]),f=i?n.data.get(i.dataId).values:new Float32Array([0]),m=new Float32Array(u.length),A=f.length,y=p.length,g=d.length,w=h.length,b=0,_=0,x=0,N=0;for(let T=0;T<u.length;++T)m[T]=f[b++]+(u[T]-h[_++])*p[x++]/Math.sqrt(d[N++]+c),b>=A&&(b=0),_>=w&&(_=0),x>=y&&(x=0),N>=g&&(N=0);return n.makeTensorInfo(a.shape,a.dtype,m)}var $M={kernelName:bs,backendName:"cpu",kernelFunc:FM};function DM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;_e([a],"batchToSpaceND");let o=s.reduce((y,g)=>y*g),l=R.getReshaped(a.shape,s,o),c=R.getPermuted(l.length,s.length),u=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(u,i,s.length),p=At({inputs:{x:a},backend:n,attrs:{shape:l}}),f=ir({inputs:{x:p},backend:n,attrs:{perm:c}}),m=At({inputs:{x:f},backend:n,attrs:{shape:u}}),A=yi({inputs:{x:m},backend:n,attrs:{begin:h,size:d}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),A}var OM={kernelName:fu,backendName:"cpu",kernelFunc:DM};function zM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.data.get(a.dataId).values,l=n.data.get(s.dataId).values,c=Fm(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var 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AF={kernelName:Oh,backendName:"cpu",kernelFunc:mF};function yF(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r;_e([a,s],"depthwiseConv2DNativeBackpropInput");let h=v.computeStrides(a.shape),d=v.computeStrides(s.shape),p=R.computeConv2DInfo(u,s.shape,i,o,l,c,!0),f=new $t(p.inShape,"float32"),m=f.values,[A,y,g]=f.strides,w=n.data.get(a.dataId).values,[b,_,x]=h,N=n.data.get(s.dataId).values,[T,E,F]=d,{batchSize:D,filterHeight:L,filterWidth:V,inChannels:U,inHeight:j,inWidth:X,outChannels:G,outHeight:ee,outWidth:Y,strideHeight:ae,strideWidth:te}=p,oe=L-1-p.padInfo.top,Q=V-1-p.padInfo.left,he=G/U;for(let le=0;le<D;++le)for(let fe=0;fe<U;++fe)for(let pe=0;pe<j;++pe){let ke=pe-oe,Se=Math.max(0,Math.ceil(ke/ae)),Me=Math.min(ee,(L+ke)/ae);for(let De=0;De<X;++De){let Fe=De-Q,Qe=Math.max(0,Math.ceil(Fe/te)),et=Math.min(Y,(V+Fe)/te),st=0;for(let Ke=Se;Ke<Me;++Ke){let dt=Ke*ae-ke;for(let Ve=Qe;Ve<et;++Ve){let 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VF={kernelName:Sh,backendName:"cpu",kernelFunc:BF};function jF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r;_e(a,"argMax");let i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=ir({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],R.assertAxesAreInnerMostDims("argMax",i,l.shape.length);let[u,h]=R.computeOutAndReduceShapes(l.shape,i),d=v.sizeFromShape(u),p=v.makeZerosTypedArray(d,"int32"),f=v.sizeFromShape(h),m=n.data.get(l.dataId).values;for(let A=0;A<p.length;++A){let y=A*f,g=m[y],b=0;for(let w=0;w<f;++w){let _=m[y+w];_>g&&(g=_,b=w)}p[A]=b}return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),n.makeTensorInfo(u,"int32",p)}var UF={kernelName:os,backendName:"cpu",kernelFunc:jF};function HF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r;_e(a,"argMin");let i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=ir({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],R.assertAxesAreInnerMostDims("argMin",i,l.shape.length);let[u,h]=R.computeOutAndReduceShapes(l.shape,i),d=v.sizeFromShape(u),p=v.makeZerosTypedArray(d,"int32"),f=v.sizeFromShape(h),m=n.data.get(l.dataId).values;for(let A=0;A<p.length;++A){let y=A*f,g=m[y],b=0;for(let w=0;w<f;++w){let _=m[y+w];_<g&&(g=_,b=w)}p[A]=b}return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),n.makeTensorInfo(u,"int32",p)}var GF={kernelName:du,backendName:"cpu",kernelFunc:HF},qF=at(to,e=>Math.asin(e)),XF={kernelName:to,backendName:"cpu",kernelFunc:qF},KF=at(no,e=>Math.asinh(e)),ZF={kernelName:no,backendName:"cpu",kernelFunc:KF},YF=at(ro,e=>Math.atan(e)),JF={kernelName:ro,backendName:"cpu",kernelFunc:YF},QF=Ct((e,t)=>Math.atan2(e,t)),eD=Ut(so,QF),tD={kernelName:so,backendName:"cpu",kernelFunc:eD},nD=at(ao,e=>Math.atanh(e)),rD={kernelName:ao,backendName:"cpu",kernelFunc:nD};function qm(e,t,n,r,a,s){let i=a.strideHeight,o=a.strideWidth,l=a.dilationHeight,c=a.dilationWidth,u=a.effectiveFilterHeight,h=a.effectiveFilterWidth,d=a.padInfo.top,p=a.padInfo.left,f=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=Be(a.outShape,n),A=m.values,y=a.outShape[1]*a.outShape[2]*a.outShape[3],g=a.outShape[2]*a.outShape[3],b=a.outShape[3];for(let w=0;w<a.batchSize;++w){let _=w*y,x=w*r[0];for(let N=0;N<a.inChannels;++N)for(let T=0;T<a.outHeight;++T){let 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he=Q*l-y,le=he;for(;le<0;)le+=h;let fe=Math.min(a.inWidth,f+he),pe=oe+Q*T,ke=g,Se=0,Fe=0;for(let De=U;De<X;De+=c){let Qe=$+De*r[1];for(let et=ae;et<te;et+=u){let st=Qe+et*r[2];for(let Ke=le;Ke<fe;Ke+=h){let dt=st+Ke*r[3],Ve=e[dt+L];if(s==="max"&&Ve>ke?ke=Ve:s==="avg"&&(Se+=Ve,Fe++),isNaN(ke))break}if(isNaN(ke))break}if(isNaN(ke))break}let Oe=pe+L;w[Oe]=s==="avg"?Se/Fe:ke}}}}return b}function aD(e,t){let n=Be(t.outShape,"int32"),r=t.strideDepth,a=t.strideHeight,s=t.strideWidth,i=t.dilationDepth,o=t.dilationHeight,l=t.dilationWidth,c=t.effectiveFilterDepth,u=t.effectiveFilterHeight,h=t.effectiveFilterWidth,d=t.padInfo.front,p=t.padInfo.top,f=t.padInfo.left;for(let m=0;m<t.batchSize;++m)for(let A=0;A<t.inChannels;++A)for(let y=0;y<t.outDepth;++y){let g=y*r-d,b=g;for(;b<0;)b+=i;let w=Math.min(t.inDepth,c+g);for(let _=0;_<t.outHeight;++_){let x=_*a-p,N=x;for(;N<0;)N+=o;let T=Math.min(t.inHeight,u+x);for(let E=0;E<t.outWidth;++E){let F=E*s-f,$=F;for(;$<0;)$+=l;let 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u=R.computePool3DInfo(s.shape,i,o,1,l,c),h=u.strideDepth,d=u.strideHeight,p=u.strideWidth,f=u.filterDepth,m=u.filterHeight,A=u.filterWidth,y=u.dilationDepth,g=u.dilationHeight,b=u.dilationWidth,w=u.effectiveFilterDepth,_=u.effectiveFilterHeight,x=u.effectiveFilterWidth,N=w-1-u.padInfo.front,T=x-1-u.padInfo.left,E=_-1-u.padInfo.top,F=Be(s.shape,"float32"),$=1/(f*m*A),L=n.bufferSync(a);for(let V=0;V<u.batchSize;++V)for(let j=0;j<u.inChannels;++j)for(let U=0;U<u.inDepth;++U)for(let X=0;X<u.inHeight;++X)for(let G=0;G<u.inWidth;++G){let ee=U-N,Y=X-E,ae=G-T,te=0;for(let oe=0;oe<w;oe+=y){let Q=(ee+oe)/h;if(!(Q<0||Q>=u.outDepth||Math.floor(Q)!==Q))for(let he=0;he<_;he+=g){let le=(Y+he)/d;if(!(le<0||le>=u.outHeight||Math.floor(le)!==le))for(let fe=0;fe<x;fe+=b){let pe=(ae+fe)/p;pe<0||pe>=u.outWidth||Math.floor(pe)!==pe||(te+=L.get(V,Q,le,pe,j))}}}F.set(te*$,V,U,X,G,j)}return n.makeTensorInfo(F.shape,F.dtype,F.values)}var cD={kernelName:Eh,backendName:"cpu",kernelFunc:uD};function hD(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;_e([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:c}=r,u=R.computePool2DInfo(i.shape,o,l,1,c),h=u.strideHeight,d=u.strideWidth,p=u.filterHeight,f=u.filterWidth,m=u.dilationHeight,A=u.dilationWidth,y=u.effectiveFilterHeight,g=u.effectiveFilterWidth,b=g-1-u.padInfo.left,w=y-1-u.padInfo.top,_=Be(i.shape,"float32"),x=1/(p*f),N=n.data.get(a.dataId).values,T=Be(a.shape,"float32",N);for(let E=0;E<u.batchSize;++E)for(let F=0;F<u.inChannels;++F)for(let $=0;$<u.inHeight;++$)for(let L=0;L<u.inWidth;++L){let V=$-w,j=L-b,U=0;for(let X=0;X<y;X+=m){let G=(V+X)/h;if(!(G<0||G>=u.outHeight||Math.floor(G)!==G))for(let ee=0;ee<g;ee+=A){let Y=(j+ee)/d;Y<0||Y>=u.outWidth||Math.floor(Y)!==Y||(U+=T.get(E,G,Y,F))}}_.set(U*x,E,$,L,F)}return n.makeTensorInfo(_.shape,_.dtype,_.values)}var dD={kernelName:Th,backendName:"cpu",kernelFunc:hD};function pD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,scale:s,offset:i,mean:o,variance:l}=t;v.assert(o.shape.length===l.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||o.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(s==null||o.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks."),_e([a,o,l,s,i],"batchNorm");let{varianceEpsilon:c}=r;c==null&&(c=.001);let u=n.data.get(a.dataId).values,h=n.data.get(o.dataId).values,d=n.data.get(l.dataId).values,p=s?n.data.get(s.dataId).values:new Float32Array([1]),f=i?n.data.get(i.dataId).values:new Float32Array([0]),m=new Float32Array(u.length),A=f.length,y=p.length,g=d.length,b=h.length,w=0,_=0,x=0,N=0;for(let T=0;T<u.length;++T)m[T]=f[w++]+(u[T]-h[_++])*p[x++]/Math.sqrt(d[N++]+c),w>=A&&(w=0),_>=b&&(_=0),x>=y&&(x=0),N>=g&&(N=0);return n.makeTensorInfo(a.shape,a.dtype,m)}var fD={kernelName:ws,backendName:"cpu",kernelFunc:pD};function mD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;_e([a],"batchToSpaceND");let o=s.reduce((y,g)=>y*g),l=R.getReshaped(a.shape,s,o),c=R.getPermuted(l.length,s.length),u=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(u,i,s.length),p=At({inputs:{x:a},backend:n,attrs:{shape:l}}),f=ir({inputs:{x:p},backend:n,attrs:{perm:c}}),m=At({inputs:{x:f},backend:n,attrs:{shape:u}}),A=yi({inputs:{x:m},backend:n,attrs:{begin:h,size:d}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),A}var AD={kernelName:fu,backendName:"cpu",kernelFunc:mD};function yD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.data.get(a.dataId).values,l=n.data.get(s.dataId).values,c=Pm(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var gD={kernelName:Ch,backendName:"cpu",kernelFunc:yD},xD=at(ka,(e,t)=>{let n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e}),bD={kernelName:ka,backendName:"cpu",kernelFunc:xD},wD=e=>{let{x:t}=e.inputs,n=e.backend,r=new Float32Array(v.sizeFromShape(t.shape)),a=n.data.get(t.dataId),s=a.complexTensorInfos.real,i=a.complexTensorInfos.imag,o=n.data.get(s.dataId).values,l=n.data.get(i.dataId).values;for(let c=0;c<o.length;c++){let u=o[c],h=l[c];r[c]=Math.hypot(u,h)}return n.makeOutput(r,t.shape,"float32")},_D={kernelName:mu,backendName:"cpu",kernelFunc:wD};function _l(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.data.get(r.dataId).complexTensorInfos.imag,s=n.data.get(a.dataId).values;return n.makeTensorInfo(a.shape,a.dtype,s)}var vD={kernelName:Uh,backendName:"cpu",kernelFunc:_l};function vl(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(m=>m.shape),s);if(v.sizeFromShape(i)===0)return 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ED={kernelName:ps,backendName:"cpu",kernelFunc:TD};function CD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r;_e([a,s],"conv3d");let c=R.computeConv3DInfo(a.shape,s.shape,i,l,o),{filterDepth:u,filterHeight:h,filterWidth:d,dilationDepth:p,dilationHeight:f,dilationWidth:m,padInfo:A}=c,y=A.front,g=A.left,b=A.top,w=new Dt(c.outShape,a.dtype),_=n.data.get(a.dataId).values,x=n.data.get(s.dataId).values,N=w.values,T=v.computeStrides(a.shape),E=v.computeStrides(s.shape);for(let F=0;F<c.batchSize;++F){let $=F*T[0],L=F*w.strides[0];for(let V=0;V<c.outDepth;++V){let j=L+V*w.strides[1],U=V*c.strideDepth-y;for(let X=0;X<u;++X){let G=U+X*p;if(G<0||G>=c.inDepth)continue;let ee=X*E[0],Y=$+G*T[1];for(let ae=0;ae<c.outHeight;++ae){let te=j+ae*w.strides[2],oe=ae*c.strideHeight-b;for(let Q=0;Q<h;++Q){let he=oe+Q*f;if(he<0||he>=c.inHeight)continue;let le=ee+Q*E[1],fe=Y+he*T[2];for(let pe=0;pe<c.outWidth;++pe){let ke=te+pe*c.outChannels,Se=pe*c.strideWidth-g;for(let 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UD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.data.get(a.dataId).values,c=n.data.get(s.dataId).values,u=Pm(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=Tw(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var HD={kernelName:$h,backendName:"cpu",kernelFunc:UD};function GD(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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e=Re.getNumber("WEBGL_VERSION");return e===0?0:sb(e)});Re.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Re.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!zu.isMobile());Re.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>ib(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Re.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Re.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Re.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>ob(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_FENCE_API_ENABLED",()=>lb(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Re.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Re.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}.`)});Re.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>zu.isMobile()&&Re.getBool("IS_CHROME")?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 ${e}.`)});function hn(){let e,t,n,r,a,s,i,o,l,c;return J().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",r="in",a="texture",s="outputColor",i="out vec4 outputColor;",o=`
+`))}function k_(e){return oa(e,()=>e.createProgram(),"Unable to create WebGLProgram.")}function I_(e,t){if(be(e,()=>e.linkProgram(t)),e.getProgramParameter(t,e.LINK_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Failed to link vertex and fragment shaders.")}function sp(e,t){if(be(e,()=>e.validateProgram(t)),e.getProgramParameter(t,e.VALIDATE_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Shader program validation failed.")}function N_(e,t){let n=oa(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),be(e,()=>e.bufferData(e.ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function S_(e,t){let n=oa(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return be(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,n)),be(e,()=>e.bufferData(e.ELEMENT_ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function bP(){return J().getNumber("WEBGL_VERSION")===2?1:4}function T_(e){return oa(e,()=>e.createTexture(),"Unable to create WebGLTexture.")}function E_(e,t){let n=J().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(e<=0||t<=0){let r=`[${e}x${t}]`;throw new Error("Requested texture size "+r+" is invalid.")}if(e>n||t>n){let r=`[${e}x${t}]`,a=`[${n}x${n}]`;throw new Error("Requested texture size "+r+" greater than WebGL maximum on this browser / GPU "+a+".")}}function C_(e){return oa(e,()=>e.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function Jm(e,t,n,r,a,s,i){let o=e.getAttribLocation(t,n);return o===-1?!1:(be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,r)),be(e,()=>e.vertexAttribPointer(o,a,e.FLOAT,!1,s,i)),be(e,()=>e.enableVertexAttribArray(o)),!0)}function R_(e,t,n){j_(e,n),be(e,()=>e.activeTexture(e.TEXTURE0+n)),be(e,()=>e.bindTexture(e.TEXTURE_2D,t))}function wP(e,t){j_(e,t),be(e,()=>e.activeTexture(e.TEXTURE0+t)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function M_(e,t,n){return oa(e,()=>e.getUniformLocation(t,n),'uniform "'+n+'" not present in program.')}function F_(e,t,n){return e.getUniformLocation(t,n)}function D_(e,t,n,r){be(e,()=>R_(e,t,r)),be(e,()=>e.uniform1i(n,r))}function _P(e){be(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),be(e,()=>e.viewport(0,0,e.canvas.width,e.canvas.height)),be(e,()=>e.scissor(0,0,e.canvas.width,e.canvas.height))}function ip(e,t,n){be(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,n)),be(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0))}function Qm(e,t){be(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,t)),be(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,null,0))}function oc(e){let t=e.checkFramebufferStatus(e.FRAMEBUFFER);if(t!==e.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+$_(e,t))}function $_(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 ${t}`}}function oa(e,t,n){let r=be(e,()=>t());if(r==null)throw new Error(n);return r}function j_(e,t){let n=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,r=t+e.TEXTURE0;if(r<e.TEXTURE0||r>n){let a=`[gl.TEXTURE0, gl.TEXTURE${n}]`;throw new Error(`textureUnit must be in ${a}.`)}}function gi(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function xi(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 op(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[gi(e),...xi(e)]),t}function O_(e,t=!1){let n=J().getNumber("WEBGL_MAX_TEXTURE_SIZE");t&&(n=n*2,e=e.map((a,s)=>s>=e.length-2?v.nearestLargerEven(e[s]):e[s]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=v.squeezeShape(e).newShape);let r=v.sizeFromShape(e);if(e.length<=1&&r<=n)return[1,r];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 a=gi(e),s=2,i=2;return e.length&&([s,i]=xi(e)),r=a*(s/2)*(i/2),v.sizeToSquarishShape(r).map(o=>o*2)}return v.sizeToSquarishShape(r)}function up(e){return e%2==0}function lc(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],r=t.slice(-1)[0];if(n===r||up(n)&&up(r)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&up(e[0])&&up(t[0])}var cp,hp;function z_(e){if(cp==null){let t=Wr(e);cp=t.getParameter(t.MAX_TEXTURE_SIZE)}return cp}function vP(){cp=null}function kP(){hp=null}function P_(e){if(hp==null){let t=Wr(e);hp=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,hp)}function L_(e){if(e===0)return 0;let t,n=Wr(e);return qn(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:qn(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function qn(e,t){return e.getExtension(t)!=null}function eA(e){try{if(Wr(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function W_(e){if(e===0)return!1;let t=Wr(e);if(e===1){if(!qn(t,"OES_texture_float"))return!1}else if(!qn(t,"EXT_color_buffer_float"))return!1;return rA(t)}function B_(e){if(e===0)return!1;let t=Wr(e);if(e===1){if(!qn(t,"OES_texture_float")||!qn(t,"WEBGL_color_buffer_float"))return!1}else{if(qn(t,"EXT_color_buffer_float"))return rA(t);let n="EXT_color_buffer_half_float";if(qn(t,n)){let r=t.getExtension(n);return DP(t,r)}return!1}return rA(t)}function rA(e){let t=nA(e),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let r=1,a=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,r,a,0,t.textureFormatFloat,t.textureTypeFloat,null);let s=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,s),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(s),i}function DP(e,t){let n=nA(e,t),r=e.createTexture();e.bindTexture(e.TEXTURE_2D,r);let a=1,s=1;e.texImage2D(e.TEXTURE_2D,0,n.internalFormatHalfFloat,a,s,0,n.textureFormatFloat,n.textureTypeHalfFloat,null);let i=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,i),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,r,0);let o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(r),e.deleteFramebuffer(i),o}function V_(e){return e!==2?!1:Wr(e).fenceSync!=null}function kl(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 Re=J();Re.registerFlag("HAS_WEBGL",()=>Re.getNumber("WEBGL_VERSION")>0);Re.registerFlag("WEBGL_VERSION",()=>eA(2)?2:eA(1)?1:0);Re.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Re.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Re.get("WEBGL_VERSION")===2);Re.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Re.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Re.registerFlag("WEBGL_PACK",()=>Re.getBool("HAS_WEBGL"));Re.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_PACK_CLIP",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>!1);Re.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_PACK_REDUCE",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_LAZILY_UNPACK",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_CONV_IM2COL",()=>Re.getBool("WEBGL_PACK"));Re.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>z_(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>P_(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=Re.getNumber("WEBGL_VERSION");return e===0?0:L_(e)});Re.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Re.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!zu.isMobile());Re.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>W_(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Re.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Re.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Re.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>B_(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_FENCE_API_ENABLED",()=>V_(Re.getNumber("WEBGL_VERSION")));Re.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Re.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Re.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}.`)});Re.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>zu.isMobile()&&Re.getBool("IS_CHROME")?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}.`)});function hn(){let e,t,n,r,a,s,i,o,l,c;return J().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",r="in",a="texture",s="outputColor",i="out vec4 outputColor;",o=`
       bool isnan_custom(float val) {
         return (val > 0.0 || val < 0.0) ? false : val != 0.0;
       }
@@ -74,11 +74,11 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       ivec4 round(vec4 value) {
         return ivec4(floor(value + vec4(0.5)));
       }
-    `),{version:e,attribute:t,varyingVs:n,varyingFs:r,texture2D:a,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:c}}function bi(e,t,n="index"){let r=v.computeStrides(t);return r.map((a,s)=>{let i=`int ${e[s]} = ${n} / ${a}`,o=s===r.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${a}`:`index -= ${e[s]} * ${a}`;return`${i}; ${o};`}).join("")}function Qm(e){let t=v.computeStrides(e).map(n=>n.toString());return`
+    `),{version:e,attribute:t,varyingVs:n,varyingFs:r,texture2D:a,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:c}}function wi(e,t,n="index"){let r=v.computeStrides(t);return r.map((a,s)=>{let i=`int ${e[s]} = ${n} / ${a}`,o=s===r.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${a}`:`index -= ${e[s]} * ${a}`;return`${i}; ${o};`}).join("")}function aA(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;
   }
-`}var cb=`
+`}var U_=`
   const float FLOAT_MAX = 1.70141184e38;
   const float FLOAT_MIN = 1.17549435e-38;
 
@@ -117,9 +117,9 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
     return c / 255.0;
   }
-`,tz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=uc.DENSE;let t=hc(e),n=hn();this.outputShape=e,this.userCode=`
+`,$P=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=uc.DENSE;let t=hc(e),n=hn();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
-        ${bi(["r","c","d"],e)}
+        ${wi(["r","c","d"],e)}
         return ivec3(r, c, d);
       }
 
@@ -138,9 +138,9 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${n.output} = result;
       }
-    `}},nz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=uc.DENSE;let t=hc(e),n=hn();this.outputShape=e,this.userCode=`
+    `}},OP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=uc.DENSE;let t=hc(e),n=hn();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
-        ${bi(["r","c","d"],e)}
+        ${wi(["r","c","d"],e)}
         return ivec3(r, c, d);
       }
 
@@ -159,23 +159,23 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${n.output} = result;
       }
-    `}},rz=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Xn.DOWNLOAD;let t=hn();this.outputShape=e,this.userCode=`
-      ${cb}
+    `}},zP=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Xn.DOWNLOAD;let t=hn();this.outputShape=e,this.userCode=`
+      ${U_}
 
       void main() {
         float x = getAAtOutCoords();
         ${t.output} = encode_float(x);
       }
-    `}},az=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Xn.DOWNLOAD;let t=hn();this.outputShape=e,this.userCode=`
-      ${cb}
+    `}},PP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Xn.DOWNLOAD;let t=hn();this.outputShape=e,this.userCode=`
+      ${U_}
 
       void main() {
         ivec3 coords = getOutputCoords();
         float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
         ${t.output} = encode_float(x);
       }
-    `}},sz=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=hn(),[a,s]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
-      ${Qm(e)}
+    `}},LP=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=hn(),[a,s]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
+      ${aA(e)}
 
       void main() {
         ivec3 coords = getOutputCoords();
@@ -204,7 +204,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${r.output} = vec4(${i}, 0., 0., 0.);
       }
-    `}},iz=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=hn(),[a,s]=t;this.outputShape=e;let i="",o="result";n&&(o="floor(result * 255. + 0.5)");for(let l=0;l<=1;l++)for(let c=0;c<=1;c++){let u=l*2+c;i+=`
+    `}},WP=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=hn(),[a,s]=t;this.outputShape=e;let i="",o="result";n&&(o="floor(result * 255. + 0.5)");for(let l=0;l<=1;l++)for(let c=0;c<=1;c++){let u=l*2+c;i+=`
           localCoords = coords;
           if(localCoords[2] + ${c} < ${e[2]}) {
             localCoords[2] += ${c};
@@ -233,7 +233,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
             }
           }
         `}this.userCode=`
-      ${Qm(e)}
+      ${aA(e)}
 
       void main() {
         ivec3 coords = getOutputCoords();
@@ -248,7 +248,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${r.output} = ${o};
       }
-    `}},hb={};Oe(hb,{bindVertexProgramAttributeStreams:()=>wb,createBufferFromOutputTexture:()=>vb,createFloat16MatrixTexture:()=>Ab,createFloat16PackedMatrixTexture:()=>xb,createFloat32MatrixTexture:()=>mb,createIndexBuffer:()=>fb,createPackedMatrixTexture:()=>gb,createUnsignedBytesMatrixTexture:()=>yb,createVertexBuffer:()=>pb,createVertexShader:()=>db,downloadByteEncodedFloatMatrixFromOutputTexture:()=>Ib,downloadFloat32MatrixFromBuffer:()=>kb,downloadMatrixFromPackedOutputTexture:()=>Sb,downloadPackedMatrixFromBuffer:()=>Nb,getInternalFormatForFloat16MatrixTexture:()=>tA,getInternalFormatForFloat16PackedMatrixTexture:()=>aA,getInternalFormatForFloat32MatrixTexture:()=>eA,getInternalFormatForPackedMatrixTexture:()=>rA,getInternalFormatForUnsignedBytesMatrixTexture:()=>nA,uploadDenseMatrixToTexture:()=>bb,uploadPixelDataToTexture:()=>_b});function db(e){let t=hn(),n=`${t.version}
+    `}},H_={};Me(H_,{bindVertexProgramAttributeStreams:()=>e3,createBufferFromOutputTexture:()=>r3,createFloat16MatrixTexture:()=>Z_,createFloat16PackedMatrixTexture:()=>Q_,createFloat32MatrixTexture:()=>K_,createIndexBuffer:()=>X_,createPackedMatrixTexture:()=>J_,createUnsignedBytesMatrixTexture:()=>Y_,createVertexBuffer:()=>q_,createVertexShader:()=>G_,downloadByteEncodedFloatMatrixFromOutputTexture:()=>s3,downloadFloat32MatrixFromBuffer:()=>a3,downloadMatrixFromPackedOutputTexture:()=>o3,downloadPackedMatrixFromBuffer:()=>i3,getInternalFormatForFloat16MatrixTexture:()=>iA,getInternalFormatForFloat16PackedMatrixTexture:()=>uA,getInternalFormatForFloat32MatrixTexture:()=>sA,getInternalFormatForPackedMatrixTexture:()=>lA,getInternalFormatForUnsignedBytesMatrixTexture:()=>oA,uploadDenseMatrixToTexture:()=>t3,uploadPixelDataToTexture:()=>n3});function G_(e){let t=hn(),n=`${t.version}
     precision highp float;
     ${t.attribute} vec3 clipSpacePos;
     ${t.attribute} vec2 uv;
@@ -257,22 +257,22 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
     void main() {
       gl_Position = vec4(clipSpacePos, 1);
       resultUV = uv;
-    }`;return Vw(e,n)}function pb(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 Gw(e,t)}function fb(e){let t=new Uint16Array([0,1,2,2,1,3]);return qw(e,t)}function dc(e,t,n,r,a,s){Kw(t,n);let i=Xw(e),o=e.TEXTURE_2D;return we(e,()=>e.bindTexture(o,i)),we(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),we(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),we(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),we(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),we(e,()=>e.texImage2D(o,0,r,t,n,0,a,s,null)),we(e,()=>e.bindTexture(e.TEXTURE_2D,null)),i}function eA(e){return e.internalFormatFloat}function mb(e,t,n,r){let[a,s]=cc(t,n);return dc(e,a,s,eA(r),r.textureFormatFloat,e.FLOAT)}function tA(e){return e.internalFormatHalfFloat}function Ab(e,t,n,r){let[a,s]=cc(t,n);return dc(e,a,s,tA(r),r.textureFormatFloat,r.textureTypeHalfFloat)}function nA(e){return e.downloadTextureFormat}function yb(e,t,n,r){let[a,s]=cc(t,n);return dc(e,a,s,nA(r),e.RGBA,e.UNSIGNED_BYTE)}function rA(e){return e.internalFormatPackedFloat}function gb(e,t,n,r){let[a,s]=Il(t,n);return dc(e,a,s,rA(r),e.RGBA,e.FLOAT)}function aA(e){return e.internalFormatPackedHalfFloat}function xb(e,t,n,r){let[a,s]=Il(t,n);return dc(e,a,s,aA(r),e.RGBA,r.textureTypeHalfFloat)}function wb(e,t,n){let r=0,a=3*4,s=3*4+2*4;return we(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),qm(e,t,"clipSpacePos",n,3,s,r)&&qm(e,t,"uv",n,2,s,a)}function bb(e,t,n,r,a,s){we(e,()=>e.bindTexture(e.TEXTURE_2D,t));let i,o,l;a instanceof Uint8Array?(i=new Uint8Array(n*r*4),o=e.UNSIGNED_BYTE,l=e.RGBA):(i=new Float32Array(n*r*4),o=e.FLOAT,l=s.internalFormatPackedFloat),i.set(a),we(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,r,0,e.RGBA,o,i)),we(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function _b(e,t,n){we(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?we(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):we(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),we(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function vb(e,t,n,r){let a=e.createBuffer();we(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,a));let s=4*4*t*n;return we(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),we(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),we(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),a}function kb(e,t,n){let r=e,a=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,t),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,a),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),a}function Ib(e,t,n,r){let[a,s]=cc(t,n),i=4,o=new Uint8Array(qO(t*n,i));return we(e,()=>e.readPixels(0,0,a,s,r.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function Nb(e,t,n,r,a,s,i,o){let l=e,c=new Float32Array(XO(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,c),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),c}function Sb(e,t,n){let r=new Float32Array(t*n*4);return we(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,r)),r}var dp=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=J().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,lp(t,e)):this.gl=Wr(t);let n="WEBGL_color_buffer_float",r="EXT_color_buffer_half_float";if(J().getNumber("WEBGL_VERSION")===1){let a="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=ic(this.gl,a),qn(this.gl,s))this.textureHalfFloatExtension=ic(this.gl,s);else if(J().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),qn(this.gl,r))this.colorBufferHalfFloatExtension=ic(this.gl,r);else if(J().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",qn(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(qn(this.gl,r))this.colorBufferHalfFloatExtension=this.gl.getExtension(r);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=pb(this.gl),this.indexBuffer=fb(this.gl),this.framebuffer=Zw(this.gl),this.textureConfig=Ym(this.gl,this.textureHalfFloatExtension)}get debug(){return J().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. 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+    }`;return __(e,n)}function q_(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 N_(e,t)}function X_(e){let t=new Uint16Array([0,1,2,2,1,3]);return S_(e,t)}function dc(e,t,n,r,a,s){E_(t,n);let i=T_(e),o=e.TEXTURE_2D;return be(e,()=>e.bindTexture(o,i)),be(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),be(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),be(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),be(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),be(e,()=>e.texImage2D(o,0,r,t,n,0,a,s,null)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null)),i}function sA(e){return e.internalFormatFloat}function K_(e,t,n,r){let[a,s]=cc(t,n);return dc(e,a,s,sA(r),r.textureFormatFloat,e.FLOAT)}function iA(e){return e.internalFormatHalfFloat}function Z_(e,t,n,r){let[a,s]=cc(t,n);return dc(e,a,s,iA(r),r.textureFormatFloat,r.textureTypeHalfFloat)}function oA(e){return e.downloadTextureFormat}function Y_(e,t,n,r){let[a,s]=cc(t,n);return dc(e,a,s,oA(r),e.RGBA,e.UNSIGNED_BYTE)}function lA(e){return e.internalFormatPackedFloat}function J_(e,t,n,r){let[a,s]=Il(t,n);return dc(e,a,s,lA(r),e.RGBA,e.FLOAT)}function uA(e){return e.internalFormatPackedHalfFloat}function Q_(e,t,n,r){let[a,s]=Il(t,n);return dc(e,a,s,uA(r),e.RGBA,r.textureTypeHalfFloat)}function e3(e,t,n){let r=0,a=3*4,s=3*4+2*4;return be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),Jm(e,t,"clipSpacePos",n,3,s,r)&&Jm(e,t,"uv",n,2,s,a)}function t3(e,t,n,r,a,s){be(e,()=>e.bindTexture(e.TEXTURE_2D,t));let i,o,l;a instanceof Uint8Array?(i=new Uint8Array(n*r*4),o=e.UNSIGNED_BYTE,l=e.RGBA):(i=new Float32Array(n*r*4),o=e.FLOAT,l=s.internalFormatPackedFloat),i.set(a),be(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,r,0,e.RGBA,o,i)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function n3(e,t,n){be(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?be(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):be(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function r3(e,t,n,r){let a=e.createBuffer();be(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,a));let s=4*4*t*n;return be(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),be(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),be(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),a}function a3(e,t,n){let r=e,a=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,t),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,a),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),a}function s3(e,t,n,r){let[a,s]=cc(t,n),i=4,o=new Uint8Array(SP(t*n,i));return be(e,()=>e.readPixels(0,0,a,s,r.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function i3(e,t,n,r,a,s,i,o){let l=e,c=new Float32Array(TP(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,c),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),c}function o3(e,t,n){let r=new Float32Array(t*n*4);return be(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,r)),r}var dp=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=J().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,lp(t,e)):this.gl=Wr(t);let n="WEBGL_color_buffer_float",r="EXT_color_buffer_half_float";if(J().getNumber("WEBGL_VERSION")===1){let a="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=ic(this.gl,a),qn(this.gl,s))this.textureHalfFloatExtension=ic(this.gl,s);else if(J().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),qn(this.gl,r))this.colorBufferHalfFloatExtension=ic(this.gl,r);else if(J().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",qn(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(qn(this.gl,r))this.colorBufferHalfFloatExtension=this.gl.getExtension(r);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=q_(this.gl),this.indexBuffer=X_(this.gl),this.framebuffer=C_(this.gl),this.textureConfig=nA(this.gl,this.textureHalfFloatExtension)}get debug(){return J().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;be(e,()=>e.finish()),be(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),be(e,()=>e.deleteFramebuffer(this.framebuffer)),be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),be(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),be(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),K_(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),Z_(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),Y_(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),n3(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,r){this.throwIfDisposed(),t3(this.gl,e,t,n,r,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),Q_(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),J_(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(Qm(this.gl,this.framebuffer),this.outputTexture=null),be(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>s3(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,r,a,s){return i3(this.gl,e,t,n,r,a,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return a3(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let r=r3(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),r}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,n;if(J().getBool("WEBGL_FENCE_API_ENABLED")){let r=e,a=r.fenceSync(r.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let s=r.clientWaitSync(a,0,0);return s===r.ALREADY_SIGNALED||s===r.CONDITION_SATISFIED},t=a}else J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>o3(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl,n=v_(t,e),r=G_(t),a=k_(t);return be(t,()=>t.attachShader(a,r)),be(t,()=>t.attachShader(a,n)),I_(t,a),this.debug&&sp(t,a),this.vertexAttrsAreBound||(this.setProgram(a),this.vertexAttrsAreBound=e3(t,this.program,this.vertexBuffer)),a}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&be(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&sp(this.gl,this.program),be(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?M_(this.gl,e,t):F_(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),be(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(),D_(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[r,a]=Il(t,n);this.setOutputMatrixTextureDriver(e,r,a)}setOutputMatrixWriteRegion(e,t,n,r){this.setOutputMatrixWriteRegionDriver(n,e,r,t)}setOutputPackedMatrixWriteRegion(e,t,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&sp(this.gl,this.program),oc(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),be(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),be(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=ic(this.gl,J().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(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,r=this.getQueryTimerExtensionWebGL2(),a=n.createQuery();return n.beginQuery(r.TIME_ELAPSED_EXT,a),a}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(J().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,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,J().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,r=this.getQueryTimerExtensionWebGL2(),a=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),a&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),r=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),r&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=BP(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(),ip(this.gl,e,this.framebuffer),this.debug&&oc(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(ip(this.gl,this.outputTexture,this.framebuffer),this.debug&&oc(this.gl)):Qm(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let n=t();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(e,t,n){this.throwIfDisposed();let r=this.gl;ip(r,e,this.framebuffer),this.debug&&oc(r),this.outputTexture=e,be(r,()=>r.viewport(0,0,t,n)),be(r,()=>r.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,r){this.throwIfDisposed(),be(this.gl,()=>this.gl.scissor(e,t,n,r))}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 BP(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{getBroadcastDims:l3}=R;function ZP(e,t,n,r){let a=[];e.forEach(p=>{let f=v.sizeFromShape(p.shapeInfo.logicalShape);p.shapeInfo.isUniform?a.push(`uniform float ${p.name}${f>1?`[${f}]`:""};`):(a.push(`uniform sampler2D ${p.name};`),a.push(`uniform int offset${p.name};`))});let s=a.join(`
+`),i=e.map(p=>VP(p,t,r)).join(`
+`),o=t.texShape,l=hn(),c=HP(l),u,h,d=XP(l);return t.isPacked?(u=jP(t.logicalShape,o),h=qP(l)):(u=UP(t.logicalShape,o),h=GP(l)),r&&(d+=KP),[d,c,h,s,u,i,n].join(`
+`)}function Nl(e){let t=e.shapeInfo.logicalShape;switch(t.length){case 0:return YP(e);case 1:return JP(e);case 2:return QP(e);case 3:return eL(e);case 4:return tL(e);case 5:return nL(e);case 6:return rL(e);default:throw new Error(`${t.length}-D input sampling is not yet supported`)}}function u3(e){switch(e.shapeInfo.logicalShape.length){case 0:return aL(e);case 1:return sL(e);case 2:return iL(e);case 3:return oL(e);default:return lL(e)}}function VP(e,t,n=!1){let r="";n?r+=u3(e):r+=Nl(e);let a=e.shapeInfo.logicalShape,s=t.logicalShape;return a.length<=s.length&&(n?r+=uL(e,t):r+=cL(e,t)),r}function jP(e,t){switch(e.length){case 0:return c3();case 1:return hL(e,t);case 2:return fL(e,t);case 3:return dL(e,t);default:return pL(e,t)}}function UP(e,t){switch(e.length){case 0:return c3();case 1:return mL(e,t);case 2:return bL(e,t);case 3:return AL(e,t);case 4:return yL(e,t);case 5:return gL(e,t);case 6:return xL(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function HP(e){return`
     float sampleTexture(sampler2D textureSampler, vec2 uv) {
       return ${e.texture2D}(textureSampler, uv).r;
     }
-  `}function dz(e){return`
+  `}function GP(e){return`
     void setOutput(float val) {
       ${e.output} = vec4(val, 0, 0, 0);
     }
-  `}function pz(e){return`
+  `}function qP(e){return`
     void setOutput(vec4 val) {
       ${e.output} = val;
     }
-  `}function fz(e){return`${e.version}
+  `}function XP(e){return`${e.version}
     precision highp float;
     precision highp int;
     precision highp sampler2D;
@@ -327,10 +327,10 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       return fract((p3.x + p3.y) * p3.z);
     }
 
-    ${Bz}
-    ${Vz}
-    ${Uz}
-  `}var Bz=`
+    ${wL}
+    ${_L}
+    ${vL}
+  `}var wL=`
 vec2 uvFromFlat(int texNumR, int texNumC, int index) {
   int texR = index / texNumC;
   int texC = index - texR * texNumC;
@@ -342,7 +342,7 @@ vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,Vz=`
+`,_L=`
 vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texNumC, int row, int col) {
   int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
@@ -350,7 +350,7 @@ vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,Uz=`
+`,vL=`
 vec2 packedUVfrom3D(int texNumR, int texNumC,
     int texelsInBatch, int texelsInLogicalRow, int b,
     int row, int col) {
@@ -359,7 +359,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   int texC = index - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,mz=`
+`,KP=`
   float getChannel(vec4 frag, vec2 innerDims) {
     vec2 modCoord = mod(innerDims, 2.);
     return modCoord.x == 0. ?
@@ -370,11 +370,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     float modCoord = mod(float(dim), 2.);
     return modCoord == 0. ? frag.r : frag.g;
   }
-`;function Cb(){return`
+`;function c3(){return`
     int getOutputCoords() {
       return 0;
     }
-  `}function Rz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?`
+  `}function hL(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?`
       int getOutputCoords() {
         return 2 * int(resultUV.x * ${n[1]}.0);
       }
@@ -388,7 +388,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${n[0]}, ${n[1]}));
       return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
     }
-  `}function Dz(e,t){return t[0]===1?`
+  `}function mL(e,t){return t[0]===1?`
       int getOutputCoords() {
         return int(resultUV.x * ${t[1]}.0);
       }
@@ -402,7 +402,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${t[0]}, ${t[1]}));
       return resTexRC.x * ${t[1]} + resTexRC.y;
     }
-  `}function Mz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
+  `}function dL(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${n[0]}, ${n[1]}));
@@ -416,7 +416,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec3(b, r, c);
     }
-  `}function Oz(e,t){let n=bi(["r","c","d"],e);return`
+  `}function AL(e,t){let n=wi(["r","c","d"],e);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${t[0]}, ${t[1]}));
@@ -424,7 +424,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${n}
       return ivec3(r, c, d);
     }
-  `}function Fz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),s=a,i="",o="b, r, c";for(let l=2;l<e.length-1;l++)s*=e[e.length-l-1],i=`
+  `}function pL(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),s=a,i="",o="b, r, c";for(let l=2;l<e.length-1;l++)s*=e[e.length-l-1],i=`
       int b${l} = index / ${s};
       index -= b${l} * ${s};
     `+i,o=`b${l}, `+o;return`
@@ -443,7 +443,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec${e.length}(${o});
     }
-  `}function zz(e,t){let n=bi(["r","c","d","d2"],e);return`
+  `}function yL(e,t){let n=wi(["r","c","d","d2"],e);return`
     ivec4 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${t[0]}, ${t[1]}));
@@ -451,7 +451,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${n}
       return ivec4(r, c, d, d2);
     }
-  `}function Pz(e,t){let n=bi(["r","c","d","d2","d3"],e);return`
+  `}function gL(e,t){let n=wi(["r","c","d","d2","d3"],e);return`
     ivec5 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
                              ${t[1]}));
@@ -463,7 +463,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec5 outShape = ivec5(r, c, d, d2, d3);
       return outShape;
     }
-  `}function Lz(e,t){let n=bi(["r","c","d","d2","d3","d4"],e);return`
+  `}function xL(e,t){let n=wi(["r","c","d","d2","d3","d4"],e);return`
     ivec6 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${t[0]}, ${t[1]}));
@@ -474,7 +474,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec6 result = ivec6(r, c, d, d2, d3, d4);
       return result;
     }
-  `}function $z(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return`
+  `}function fL(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return`
       ivec2 getOutputCoords() {
         return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
       }
@@ -489,7 +489,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec2(r, c);
     }
-  `}function Wz(e,t){return v.arraysEqual(e,t)?`
+  `}function bL(e,t){return v.arraysEqual(e,t)?`
       ivec2 getOutputCoords() {
         return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
       }
@@ -516,11 +516,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       int c = index - r * ${e[1]};
       return ivec2(r, c);
     }
-  `}function _i(e){return`offset${e}`}function kz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=hn();return`
+  `}function _i(e){return`offset${e}`}function aL(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=hn();return`
     vec4 ${n}() {
       return ${r.texture2D}(${t}, halfCR);
     }
-  `}function yz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${t};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
+  `}function YP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${t};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
       float ${n}() {
         return sampleTexture(${t}, halfCR);
       }
@@ -529,13 +529,13 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${s}, ${i}, ${o});
       return sampleTexture(${t}, uv);
     }
-  `}function Iz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=e.shapeInfo.texShape,a=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],s=hn();return`
+  `}function sL(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=e.shapeInfo.texShape,a=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],s=hn();return`
     vec4 ${n}(int index) {
       vec2 uv = packedUVfrom1D(
         ${a[0]}, ${a[1]}, index);
       return ${s.texture2D}(${t}, uv);
     }
-  `}function gz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
+  `}function JP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
       float ${n}(int index) {
         ${Sl(e)}
       }
@@ -558,7 +558,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${a}, ${s}, index + ${i});
       return sampleTexture(${t}, uv);
     }
-  `}function Nz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=a[0],i=a[1],o=hn();if(a!=null&&v.arraysEqual(t,a))return`
+  `}function iL(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=a[0],i=a[1],o=hn();if(a!=null&&v.arraysEqual(t,a))return`
       vec4 ${r}(int row, int col) {
         vec2 uv = (vec2(col, row) + halfCR) / vec2(${i}.0, ${s}.0);
 
@@ -569,7 +569,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = packedUVfrom2D(${c}, ${l[0]}, ${l[1]}, row, col);
       return ${o.texture2D}(${n}, uv);
     }
-  `}function xz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape;if(a!=null&&v.arraysEqual(t,a)){let h=a[0],d=a[1];return`
+  `}function QP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape;if(a!=null&&v.arraysEqual(t,a)){let h=a[0],d=a[1];return`
     float ${r}(int row, int col) {
       vec2 uv = (vec2(col, row) + halfCR) / vec2(${d}.0, ${h}.0);
       return sampleTexture(${n}, uv);
@@ -603,8 +603,8 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     vec2 uv = uvFromFlat(${l}, ${c}, index);
     return sampleTexture(${n}, uv);
   }
-`}function Sz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(t[0]===1){let h=t.slice(1),d=[1,2],p=Tl(e,h),f=["b","row","col"];return`
-        ${Eb(p)}
+`}function oL(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(t[0]===1){let h=t.slice(1),d=[1,2],p=Tl(e,h),f=["b","row","col"];return`
+        ${u3(p)}
         vec4 ${r}(int b, int row, int col) {
           return ${r}(${El(f,d)});
         }
@@ -614,7 +614,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         ${i}, ${o}, ${c}, ${l}, b, row, col);
       return ${u.texture2D}(${n}, uv);
     }
-  `}function wz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[1]*t[2],s=t[2],{newShape:i,keptDims:o}=v.squeezeShape(t),l=i;if(l.length<t.length){let f=Tl(e,l),m=["row","col","depth"];return`
+  `}function eL(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[1]*t[2],s=t[2],{newShape:i,keptDims:o}=v.squeezeShape(t),l=i;if(l.length<t.length){let f=Tl(e,l),m=["row","col","depth"];return`
         ${Nl(f)}
         float ${r}(int row, int col, int depth) {
           return ${r}(${El(m,o)});
@@ -647,7 +647,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         vec2 uv = uvFromFlat(${u}, ${h}, index);
         return sampleTexture(${n}, uv);
       }
-  `}function Tz(e){let t=e.shapeInfo.logicalShape,n=t.length,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],o=i[0],l=i[1],c=Math.ceil(t[n-1]/2),u=c*Math.ceil(t[n-2]/2),h="int b, int row, int col",d=`b * ${u} + (row / 2) * ${c} + (col / 2)`;for(let f=2;f<n-1;f++)h=`int b${f}, `+h,u*=t[n-f-1],d=`b${f} * ${u} + `+d;let p=hn();return`
+  `}function lL(e){let t=e.shapeInfo.logicalShape,n=t.length,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],o=i[0],l=i[1],c=Math.ceil(t[n-1]/2),u=c*Math.ceil(t[n-2]/2),h="int b, int row, int col",d=`b * ${u} + (row / 2) * ${c} + (col / 2)`;for(let f=2;f<n-1;f++)h=`int b${f}, `+h,u*=t[n-f-1],d=`b${f} * ${u} + `+d;let p=hn();return`
     vec4 ${a}(${h}) {
       int index = ${d};
       int texR = index / ${l};
@@ -655,7 +655,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${l}, ${o});
       return ${p.texture2D}(${r}, uv);
     }
-  `}function bz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[3],s=t[2]*a,i=t[1]*s,{newShape:o,keptDims:l}=v.squeezeShape(t);if(o.length<t.length){let f=Tl(e,o),m=["row","col","depth","depth2"];return`
+  `}function tL(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[3],s=t[2]*a,i=t[1]*s,{newShape:o,keptDims:l}=v.squeezeShape(t);if(o.length<t.length){let f=Tl(e,o),m=["row","col","depth","depth2"];return`
       ${Nl(f)}
       float ${r}(int row, int col, int depth, int depth2) {
         return ${r}(${El(m,l)});
@@ -693,7 +693,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${h}, ${d}, index + ${p});
       return sampleTexture(${n}, uv);
     }
-  `}function _z(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:c}=v.squeezeShape(t);if(l.length<t.length){let m=Tl(e,l),A=["row","col","depth","depth2","depth3"];return`
+  `}function nL(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:c}=v.squeezeShape(t);if(l.length<t.length){let m=Tl(e,l),A=["row","col","depth","depth2","depth3"];return`
       ${Nl(m)}
       float ${r}(int row, int col, int depth, int depth2, int depth3) {
         return ${r}(${El(A,c)});
@@ -734,7 +734,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${d}, ${p}, index);
       return sampleTexture(${n}, uv);
     }
-  `}function vz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:a,keptDims:s}=v.squeezeShape(t);if(a.length<t.length){let A=Tl(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
+  `}function rL(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:a,keptDims:s}=v.squeezeShape(t);if(a.length<t.length){let A=Tl(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
       ${Nl(A)}
       float ${r}(int row, int col, int depth,
                     int depth2, int depth3, int depth4) {
@@ -790,7 +790,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         return ${t}[i];
       }
     }
-  `}function Ez(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=Tb(e.shapeInfo.logicalShape,t.logicalShape),l=ot(i),c=i-s,u,h=["x","y","z","w","u","v"];s===0?u="":i<2&&o.length>=1?u="coords = 0;":u=o.map(A=>`coords.${h[A+c]} = 0;`).join(`
+  `}function uL(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=l3(e.shapeInfo.logicalShape,t.logicalShape),l=ot(i),c=i-s,u,h=["x","y","z","w","u","v"];s===0?u="":i<2&&o.length>=1?u="coords = 0;":u=o.map(A=>`coords.${h[A+c]} = 0;`).join(`
 `);let d="";i<2&&s>0?d="coords":d=e.shapeInfo.logicalShape.map((A,y)=>`coords.${h[y+c]}`).join(", ");let p="return outputValue;",f=v.sizeFromShape(e.shapeInfo.logicalShape)===1,m=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!f&&!m)p=`
       return vec4(outputValue.xy, outputValue.xy);
     `;else if(f&&!m)i===1?p=`
@@ -804,22 +804,22 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec4 outputValue = get${r}(${d});
       ${p}
     }
-  `}function Cz(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
+  `}function cL(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
       float ${a}() {
         return sampleTexture(${n}, resultUV);
       }
-    `;let c=ot(l),u=Tb(e.shapeInfo.logicalShape,t.logicalShape),h=l-o,d,p=["x","y","z","w","u","v"];o===0?d="":l<2&&u.length>=1?d="coords = 0;":d=u.map(m=>`coords.${p[m+h]} = 0;`).join(`
+    `;let c=ot(l),u=l3(e.shapeInfo.logicalShape,t.logicalShape),h=l-o,d,p=["x","y","z","w","u","v"];o===0?d="":l<2&&u.length>=1?d="coords = 0;":d=u.map(m=>`coords.${p[m+h]} = 0;`).join(`
 `);let f="";return l<2&&o>0?f="coords":f=e.shapeInfo.logicalShape.map((m,A)=>`coords.${p[A+h]}`).join(", "),`
     float ${a}() {
       ${c} coords = getOutputCoords();
       ${d}
       return get${r}(${f});
     }
-  `}function ot(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 ${e} is not yet supported`)}function Tl(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function El(e,t){return t.map(n=>e[n]).join(", ")}function jz(e,t,n,r){let a=t.userCode,s=n.map((p,f)=>{let m={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(m.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[f],shapeInfo:m}}),i=s.map(p=>p.shapeInfo),o={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},l=Az(s,o,a,t.packedInputs),c=e.createProgram(l),u=null,h=e.getUniformLocation(c,"NAN",!1);J().getNumber("WEBGL_VERSION")===1&&(u=e.getUniformLocation(c,"INFINITY",!1));let d={};for(let p=0;p<t.variableNames.length;p++){let f=t.variableNames[p],m=!1;d[f]=e.getUniformLocation(c,f,m),d[`offset${f}`]=e.getUniformLocation(c,`offset${f}`,m)}return{program:t,source:l,webGLProgram:c,uniformLocations:d,inShapeInfos:i,outShapeInfo:o,infLoc:u,nanLoc:h}}function Rb(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,r)=>{let a=n.logicalShape,s=t[r],i=s.shape;if(!v.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function Hz(e,t,n,r,a){Rb(t.inShapeInfos,n),Rb([t.outShapeInfo],[r]);let s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s,i[0],i[1]):e.setOutputMatrixTexture(s,i[0],i[1]),e.setProgram(t.webGLProgram),J().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,Infinity),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((o,l)=>{let c=t.program.variableNames[l],u=t.uniformLocations[c],h=t.uniformLocations[`offset${c}`];if(u!=null){if(o.isUniform){if(v.sizeFromShape(o.shape)<2)e.gl.uniform1f(u,o.uniformValues[0]);else{let d=o.uniformValues;d instanceof Float32Array||(d=new Float32Array(d)),e.gl.uniform1fv(u,d)}return}o.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,o.texData.slice.flatOffset),e.setInputMatrixTexture(o.texData.texture,u,l)}}),a!=null&&a(e,t.webGLProgram),e.executeProgram()}function Gz(e,t,n){let r="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0,l=i.isUniform?"uniform":i.texData.texShape;r+=`${i.shape}_${l}_${o}`});let a=e.userCode,s=e.constructor.name;return s+="_"+r+"_"+a,s}var{addImpl:qz,bincountImpl:Mb,bincountReduceImpl:Xz,ceilImpl:Kz,concatImpl:Zz,expImpl:Yz,expm1Impl:Jz,floorImpl:Qz,gatherV2Impl:eP,greaterImpl:tP,lessImpl:nP,linSpaceImpl:rP,logImpl:aP,maxImpl:sP,maximumImpl:iP,minimumImpl:oP,multiplyImpl:lP,negImpl:uP,prodImpl:cP,rangeImpl:hP,rsqrtImpl:dP,simpleAbsImpl:Fb,sliceImpl:pP,stridedSliceImpl:fP,subImpl:mP,tileImpl:AP,topKImpl:yP,transposeImpl:sA,uniqueImpl:gP}=Mm;function $b(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function dn(e,t){return t===1?[e]:$b(e,t)}function xP(e,t){if(e===1)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}var vP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
+  `}function ot(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 ${e} is not yet supported`)}function Tl(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function El(e,t){return t.map(n=>e[n]).join(", ")}function kL(e,t,n,r){let a=t.userCode,s=n.map((p,f)=>{let m={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(m.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[f],shapeInfo:m}}),i=s.map(p=>p.shapeInfo),o={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},l=ZP(s,o,a,t.packedInputs),c=e.createProgram(l),u=null,h=e.getUniformLocation(c,"NAN",!1);J().getNumber("WEBGL_VERSION")===1&&(u=e.getUniformLocation(c,"INFINITY",!1));let d={};for(let p=0;p<t.variableNames.length;p++){let f=t.variableNames[p],m=!1;d[f]=e.getUniformLocation(c,f,m),d[`offset${f}`]=e.getUniformLocation(c,`offset${f}`,m)}return{program:t,source:l,webGLProgram:c,uniformLocations:d,inShapeInfos:i,outShapeInfo:o,infLoc:u,nanLoc:h}}function h3(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,r)=>{let a=n.logicalShape,s=t[r],i=s.shape;if(!v.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function IL(e,t,n,r,a){h3(t.inShapeInfos,n),h3([t.outShapeInfo],[r]);let s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s,i[0],i[1]):e.setOutputMatrixTexture(s,i[0],i[1]),e.setProgram(t.webGLProgram),J().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,Infinity),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((o,l)=>{let c=t.program.variableNames[l],u=t.uniformLocations[c],h=t.uniformLocations[`offset${c}`];if(u!=null){if(o.isUniform){if(v.sizeFromShape(o.shape)<2)e.gl.uniform1f(u,o.uniformValues[0]);else{let d=o.uniformValues;d instanceof Float32Array||(d=new Float32Array(d)),e.gl.uniform1fv(u,d)}return}o.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,o.texData.slice.flatOffset),e.setInputMatrixTexture(o.texData.texture,u,l)}}),a!=null&&a(e,t.webGLProgram),e.executeProgram()}function NL(e,t,n){let r="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0,l=i.isUniform?"uniform":i.texData.texShape;r+=`${i.shape}_${l}_${o}`});let a=e.userCode,s=e.constructor.name;return s+="_"+r+"_"+a,s}var{addImpl:SL,bincountImpl:d3,bincountReduceImpl:TL,ceilImpl:EL,concatImpl:CL,expImpl:RL,expm1Impl:ML,floorImpl:FL,gatherV2Impl:DL,greaterImpl:$L,lessImpl:OL,linSpaceImpl:zL,logImpl:PL,maxImpl:LL,maximumImpl:WL,minimumImpl:BL,multiplyImpl:VL,negImpl:jL,prodImpl:UL,rangeImpl:HL,rsqrtImpl:GL,simpleAbsImpl:p3,sliceImpl:qL,stridedSliceImpl:XL,subImpl:KL,tileImpl:ZL,topKImpl:YL,transposeImpl:cA,uniqueImpl:JL}=zm;function f3(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function dn(e,t){return t===1?[e]:f3(e,t)}function QL(e,t){if(e===1)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}var rW=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
         void main() {
           setOutput(vec4(getA(), 0., 0., 0.));
         }
-      `;else{let n=dn("rc",t),r=ot(t),a=wP(t,e,n),s=bP(t,e[e.length-1],e[e.length-2],n),i=_P(e,n);this.userCode=`
+      `;else{let n=dn("rc",t),r=ot(t),a=eW(t,e,n),s=tW(t,e[e.length-1],e[e.length-2],n),i=nW(e,n);this.userCode=`
         void main() {
           ${r} rc = getOutputCoords();
 
@@ -831,7 +831,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             setOutput(vec4(${i}));
           }
         }
-      `}}};function kP(e,t){let n=[];for(let r=0;r<=1;r++)for(let a=0;a<=1;a++){let s=`${r===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let i=2;i<e;i++)s=`${t[t.length-1-i]},`+s;n.push(s)}return n}function wP(e,t,n){if(e===1)return`rc > ${t[0]}`;let r="";for(let a=e-2;a<e;a++)r+=`${n[a]} >= ${t[a]}`,a<e-1&&(r+="||");return r}function bP(e,t,n,r){if(e===1)return"";let a=r.slice(-2);return`
+      `}}};function aW(e,t){let n=[];for(let r=0;r<=1;r++)for(let a=0;a<=1;a++){let s=`${r===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let i=2;i<e;i++)s=`${t[t.length-1-i]},`+s;n.push(s)}return n}function eW(e,t,n){if(e===1)return`rc > ${t[0]}`;let r="";for(let a=e-2;a<e;a++)r+=`${n[a]} >= ${t[a]}`,a<e-1&&(r+="||");return r}function tW(e,t,n,r){if(e===1)return"";let a=r.slice(-2);return`
     int r = ${a[0]};
     int c = ${a[1]};
     int rp1 = r + 1;
@@ -839,12 +839,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
     bool cEdge = cp1 >= ${t};
     bool rEdge = rp1 >= ${n};
-  `}function _P(e,t){let n=e.length,r=kP(n,t);return n===1?`getA(rc),
+  `}function nW(e,t){let n=e.length,r=aW(n,t);return n===1?`getA(rc),
             rc + 1 >= ${e[0]} ? 0. : getA(rc + 1),
             0, 0`:`getA(${r[0]}),
           cEdge ? 0. : getA(${r[1]}),
           rEdge ? 0. : getA(${r[2]}),
-          rEdge || cEdge ? 0. : getA(${r[3]})`}var Db=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let r=0;r<4;r++){let a="thisRC = rc;";r%2==1&&(a+="thisRC.z += 1;"),r>1&&(a+="thisRC.y += 1;"),n+=`
+          rEdge || cEdge ? 0. : getA(${r[3]})`}var m3=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let r=0;r<4;r++){let a="thisRC = rc;";r%2==1&&(a+="thisRC.z += 1;"),r>1&&(a+="thisRC.y += 1;"),n+=`
         ${a}
         ${r>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
           int flatIndex = getFlatIndex(thisRC);
@@ -856,8 +856,8 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
         ${r>0?"}":""}
       `}this.userCode=`
-      ${IP(t)}
-      ${Qm(e)}
+      ${sW(t)}
+      ${aA(e)}
 
       void main() {
         ivec3 rc = getOutputCoords();
@@ -872,12 +872,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function IP(e){return`
+    `}};function sW(e){return`
     ivec3 inputCoordsFromReshapedOutCoords(int index) {
-      ${bi(["r","c","d"],e)}
+      ${wi(["r","c","d"],e)}
       return ivec3(r, c, d);
     }
-  `}var NP=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let r=zb(t,n),a=Pb(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=Ob(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return r===en.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===en.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===en.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===en.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===en.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,r){if(this.freeTextures==null)return;let a=zb(n,r),s=Pb(t,a,r);s in this.freeTextures||(this.freeTextures[s]=[]);let i=Ob(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),o=J().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],c=l.indexOf(e);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${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)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function SP(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function Ob(e,t,n,r,a){let s=TP(t,r),i;if(a){let[l,c]=Il(e[0],e[1]);i=l*c}else{let[l,c]=cc(e[0],e[1]);i=l*c}let o=SP(n,s);return i*o}function TP(e,t){switch(e){case en.PACKED_2X2_FLOAT32:return rA(t);case en.PACKED_2X2_FLOAT16:return aA(t);case en.UNPACKED_FLOAT32:return eA(t);case en.UNPACKED_FLOAT16:return tA(t);case en.PACKED_4X1_UNSIGNED_BYTE:return nA(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function EP(e){return J().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?en.PACKED_2X2_FLOAT32:en.UNPACKED_FLOAT32:e?en.PACKED_2X2_FLOAT16:en.UNPACKED_FLOAT16}function zb(e,t){if(e===Xn.UPLOAD)return en.PACKED_2X2_FLOAT32;if(e===Xn.RENDER||e==null)return EP(t);if(e===Xn.DOWNLOAD||e===Xn.PIXELS)return en.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function Pb(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var La=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+  `}var iW=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let r=y3(t,n),a=g3(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=A3(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return r===en.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===en.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===en.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===en.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===en.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,r){if(this.freeTextures==null)return;let a=y3(n,r),s=g3(t,a,r);s in this.freeTextures||(this.freeTextures[s]=[]);let i=A3(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),o=J().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],c=l.indexOf(e);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${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)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function oW(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function A3(e,t,n,r,a){let s=lW(t,r),i;if(a){let[l,c]=Il(e[0],e[1]);i=l*c}else{let[l,c]=cc(e[0],e[1]);i=l*c}let o=oW(n,s);return i*o}function lW(e,t){switch(e){case en.PACKED_2X2_FLOAT32:return lA(t);case en.PACKED_2X2_FLOAT16:return uA(t);case en.UNPACKED_FLOAT32:return sA(t);case en.UNPACKED_FLOAT16:return iA(t);case en.PACKED_4X1_UNSIGNED_BYTE:return oA(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function uW(e){return J().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?en.PACKED_2X2_FLOAT32:en.UNPACKED_FLOAT32:e?en.PACKED_2X2_FLOAT16:en.UNPACKED_FLOAT16}function y3(e,t){if(e===Xn.UPLOAD)return en.PACKED_2X2_FLOAT32;if(e===Xn.RENDER||e==null)return uW(t);if(e===Xn.DOWNLOAD||e===Xn.PIXELS)return en.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function g3(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var La=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       float unaryOperation(float x) {
         ${t}
       }
@@ -888,11 +888,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}},gr="if (isnan(x)) return x;",CP="return x;",Lb="return abs(x);",RP="return (x >= 0.0) ? x : (exp(x) - 1.0);",MP=gr+`
+    `}},gr="if (isnan(x)) return x;",cW="return x;",x3="return abs(x);",hW="return (x >= 0.0) ? x : (exp(x) - 1.0);",dW=gr+`
   return (x < 0.0) ? 0.0 : x;
-`,FP=gr+`
+`,pW=gr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,pp="return x;",$P="return x;",DP=`
+`,pp="return x;",fW="return x;",mW=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -901,7 +901,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,OP=`
+`,AW=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -911,7 +911,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,zP=`
+`,yW=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -932,14 +932,14 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}},PP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=dn("rc",t),r=ot(t),a=xP(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
+    `}},gW=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=dn("rc",t),r=ot(t),a=QL(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
       void main() {
         ${r} rc = getOutputCoords();
         vec4 packedInput = getA(${a});
 
         setOutput(getChannel(packedInput, ${i}));
       }
-    `}},LP=Pr.whereImpl,WP=1e-7,BP=1e-4,iA={};function VP(e){return e in iA||(iA[e]={}),iA[e]}var UP=128,jP=600;function HP(){return J().global.screen==null?1024:J().global.screen.height*J().global.screen.width*window.devicePixelRatio*jP/1024/1024}var Rl=class extends uu{constructor(e){super();if(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.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!J().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Wr(J().getNumber("WEBGL_VERSION"));this.binaryCache=VP(J().getNumber("WEBGL_VERSION")),this.gpgpu=new dp(t),this.canvas=t.canvas,this.gpgpuCreatedLocally=!0}else this.gpgpu=e,this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=e.gl.canvas;this.textureManager=new NP(this.gpgpu),this.numMBBeforeWarning=HP(),this.texData=new _h(this,Mr())}nextDataId(){return Rl.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((J().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||J().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 r={id:this.nextDataId()};return this.texData.set(r,{shape:t,dtype:n,values:e,usage:Xn.UPLOAD,refCount:1}),r}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,r,a){if(J().getBool("DEBUG")&&this.checkNumericalProblems(t),r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:r,values:t,usage:Xn.UPLOAD,refCount:a})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:a,slice:s,shape:i,isPacked:o}=t;if(s!=null){let h;o?h=new Cl(i,pp):h=new La(i,pp);let d=this.runWebGLProgram(h,[{dataId:e,shape:i,dtype:r}],r),p=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(r==="string")return n;let l=this.activeTimers!=null,c;l&&(c=v.now());let u;if(r==="complex64"){let h=this.readSync(a.real.dataId),d=this.readSync(a.imag.dataId);u=R.mergeRealAndImagArrays(h,d)}else u=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-c),this.convertAndCacheOnCPU(e,u)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(f=>p.push(f))}let t=this.texData.get(e),{values:n,shape:r,slice:a,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(a!=null){let p;o?p=new Cl(r,pp):p=new La(r,pp);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&J().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,c;if(s!=="complex64"&&J().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let p=this.texData.get(c.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...hc(r))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let u;if(s==="complex64"){let p=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=p[0],m=p[1];u=R.mergeRealAndImagArrays(f,m)}else if(l==null)u=this.getValuesFromTexture(e);else{let p=v.sizeFromShape(r);u=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}c!=null&&this.disposeIntermediateTensorInfo(c);let h=this.convertAndCacheOnCPU(e,u),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(p=>p(h)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&Mr().removeDataId(e,this),this.pendingDeletes--),h}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return Be(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!Ww(n))throw J().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 ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),a=v.sizeFromShape(t);if(J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),d=this.texData.get(h.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(d.texture,...hc(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),p}let s=J().getBool("WEBGL_PACK")&&r===!0,i=s?op(t):t,o=s?new az(i):new rz(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),c=this.texData.get(l.dataId),u=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture,c.texShape[0],c.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),u}timerAvailable(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,c)=>({name:s[c],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(J().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:r,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,s)));let c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return J().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Mr().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=UP){let n=this.getCPUBackend();return!J().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),n!=null&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){R.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return LP(e.shape,t)}packedUnaryOp(e,t,n){let r=new Cl(e.shape,t),a=this.compileAndRun(r,[e],n);return Mr().makeTensorFromDataId(a.dataId,a.shape,a.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let r=Fb(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,r)}if(J().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,Lb,e.dtype);let t=new La(e.shape,Lb),n=this.compileAndRun(t,[e]);return Mr().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let a=n.map(s=>v.encodeString(s));r=this.write(a,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:r}=this.makeTensorInfo(e,t,n);return Mr().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new PP(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new vP(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[gi(e.shape),...xi(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[gi(t),...xi(t)],s=new Db(a,n),i=!0,o=this.runWebGLProgram(s,[r],e.dtype,null,i);return{dataId:o.dataId,shape:t,dtype:o.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:r,dtype:a}=t,s=op(r),i;n?i=new nz(s):i=new tz(s);let o=!0,l=this.runWebGLProgram(i,[{shape:s,dtype:a,dataId:e}],a,null,o);return{dtype:a,shape:r,dataId:l.dataId}}runWebGLProgram(e,t,n,r,a=!1){let s=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(s.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===uc.DENSE){let m=hc(e.outputShape);i.texShape=m.map(A=>A*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(s.shape)===0)return i.values=v.getTypedArrayFromDType(s.dtype,0),s;let o=[],l=t.map(m=>{if(m.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let A=this.texData.get(m.dataId);if(A.texture==null){if(!e.packedInputs&&v.sizeFromShape(m.shape)<=J().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:A.values};e.packedInputs&&(A.isPacked=!0,A.shape=m.shape)}else if(!!A.isPacked!=!!e.packedInputs)m=A.isPacked?this.unpackTensor(m):this.packTensor(m),o.push(m),A=this.texData.get(m.dataId);else if(A.isPacked&&!lc(A.shape,m.shape)){let y=m,g=m.shape;m.shape=A.shape,m=this.packedReshape(m,g),o.push(m),A=this.texData.get(m.dataId),y.shape=g}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:A,isUniform:!1}});this.uploadToGPU(s.dataId);let c={shape:s.shape,texData:i,isUniform:!1},u=Gz(e,l,c),h=this.getAndSaveBinary(u,()=>jz(this.gpgpu,e,l,c)),d=this.activeTimers!=null,p;d&&(p=this.startTimer()),Hz(this.gpgpu,h,l,c,r),o.forEach(m=>this.disposeIntermediateTensorInfo(m)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=J().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=v.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!J().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let m=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),m}return s}compileAndRun(e,t,n,r,a=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(J().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),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=z(()=>{if(!J().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=J().getBool("DEBUG");J().set("DEBUG",!1);let t=this.abs(ge(1e-8)).dataSync()[0];if(J().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?WP:BP}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:r,values:a,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,c;l&&(c=v.now());let u=t.texShape;if(u==null&&(u=nb(n,o),t.texShape=u),a!=null){let h=op(n),d,p=u[1],f=u[0],m=a instanceof Uint8Array;o?([p,f]=Il(u[0],u[1]),d=new iz(h,[f,p],m)):d=new sz(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=Xn.PIXELS:this.texData.get(A.dataId).usage=Xn.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),w=this.texData.get(g.dataId);t.texture=w.texture,t.texShape=w.texShape,t.isPacked=w.isPacked,t.usage=w.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(g.dataId),t.values=null,l&&(this.uploadWaitMs+=v.now()-c)}else{let h=this.acquireTexture(u,i,r,o);t.texture=h}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),t!=null&&(n.values=GP(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}};Rl.nextDataId=0;function GP(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 r=0;r<n.length;++r)n[r]=Math.round(e[r]);return n}else throw new Error(`Unknown dtype ${t}`)}var Wb="3.3.0";function Bb(){J().set("WEBGL_FORCE_F16_TEXTURES",!0)}zu.isBrowser()&&il("webgl",()=>new Rl,2);var qP={forceHalfFloat:Bb},Vb=`
+    `}},xW=Pr.whereImpl,bW=1e-7,wW=1e-4,hA={};function _W(e){return e in hA||(hA[e]={}),hA[e]}var vW=128,kW=600;function IW(){return J().global.screen==null?1024:J().global.screen.height*J().global.screen.width*window.devicePixelRatio*kW/1024/1024}var Rl=class extends uu{constructor(e){super();if(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.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!J().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Wr(J().getNumber("WEBGL_VERSION"));this.binaryCache=_W(J().getNumber("WEBGL_VERSION")),this.gpgpu=new dp(t),this.canvas=t.canvas,this.gpgpuCreatedLocally=!0}else this.gpgpu=e,this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=e.gl.canvas;this.textureManager=new iW(this.gpgpu),this.numMBBeforeWarning=IW(),this.texData=new _h(this,Mr())}nextDataId(){return Rl.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((J().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||J().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 r={id:this.nextDataId()};return this.texData.set(r,{shape:t,dtype:n,values:e,usage:Xn.UPLOAD,refCount:1}),r}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,r,a){if(J().getBool("DEBUG")&&this.checkNumericalProblems(t),r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:r,values:t,usage:Xn.UPLOAD,refCount:a})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:a,slice:s,shape:i,isPacked:o}=t;if(s!=null){let h;o?h=new Cl(i,pp):h=new La(i,pp);let d=this.runWebGLProgram(h,[{dataId:e,shape:i,dtype:r}],r),p=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(r==="string")return n;let l=this.activeTimers!=null,c;l&&(c=v.now());let u;if(r==="complex64"){let h=this.readSync(a.real.dataId),d=this.readSync(a.imag.dataId);u=R.mergeRealAndImagArrays(h,d)}else u=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-c),this.convertAndCacheOnCPU(e,u)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(f=>p.push(f))}let t=this.texData.get(e),{values:n,shape:r,slice:a,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(a!=null){let p;o?p=new Cl(r,pp):p=new La(r,pp);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&J().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,c;if(s!=="complex64"&&J().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let p=this.texData.get(c.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...hc(r))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let u;if(s==="complex64"){let p=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=p[0],m=p[1];u=R.mergeRealAndImagArrays(f,m)}else if(l==null)u=this.getValuesFromTexture(e);else{let p=v.sizeFromShape(r);u=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}c!=null&&this.disposeIntermediateTensorInfo(c);let h=this.convertAndCacheOnCPU(e,u),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(p=>p(h)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&Mr().removeDataId(e,this),this.pendingDeletes--),h}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return Be(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!b_(n))throw J().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 ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),a=v.sizeFromShape(t);if(J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),d=this.texData.get(h.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(d.texture,...hc(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),p}let s=J().getBool("WEBGL_PACK")&&r===!0,i=s?op(t):t,o=s?new PP(i):new zP(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),c=this.texData.get(l.dataId),u=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture,c.texShape[0],c.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),u}timerAvailable(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,c)=>({name:s[c],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(J().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:r,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,s)));let c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return J().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Mr().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=vW){let n=this.getCPUBackend();return!J().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),n!=null&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){R.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return xW(e.shape,t)}packedUnaryOp(e,t,n){let r=new Cl(e.shape,t),a=this.compileAndRun(r,[e],n);return Mr().makeTensorFromDataId(a.dataId,a.shape,a.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let r=p3(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,r)}if(J().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,x3,e.dtype);let t=new La(e.shape,x3),n=this.compileAndRun(t,[e]);return Mr().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let a=n.map(s=>v.encodeString(s));r=this.write(a,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:r}=this.makeTensorInfo(e,t,n);return Mr().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new gW(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new rW(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[gi(e.shape),...xi(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[gi(t),...xi(t)],s=new m3(a,n),i=!0,o=this.runWebGLProgram(s,[r],e.dtype,null,i);return{dataId:o.dataId,shape:t,dtype:o.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:r,dtype:a}=t,s=op(r),i;n?i=new OP(s):i=new $P(s);let o=!0,l=this.runWebGLProgram(i,[{shape:s,dtype:a,dataId:e}],a,null,o);return{dtype:a,shape:r,dataId:l.dataId}}runWebGLProgram(e,t,n,r,a=!1){let s=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(s.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===uc.DENSE){let m=hc(e.outputShape);i.texShape=m.map(A=>A*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(s.shape)===0)return i.values=v.getTypedArrayFromDType(s.dtype,0),s;let o=[],l=t.map(m=>{if(m.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let A=this.texData.get(m.dataId);if(A.texture==null){if(!e.packedInputs&&v.sizeFromShape(m.shape)<=J().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:A.values};e.packedInputs&&(A.isPacked=!0,A.shape=m.shape)}else if(!!A.isPacked!=!!e.packedInputs)m=A.isPacked?this.unpackTensor(m):this.packTensor(m),o.push(m),A=this.texData.get(m.dataId);else if(A.isPacked&&!lc(A.shape,m.shape)){let y=m,g=m.shape;m.shape=A.shape,m=this.packedReshape(m,g),o.push(m),A=this.texData.get(m.dataId),y.shape=g}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:A,isUniform:!1}});this.uploadToGPU(s.dataId);let c={shape:s.shape,texData:i,isUniform:!1},u=NL(e,l,c),h=this.getAndSaveBinary(u,()=>kL(this.gpgpu,e,l,c)),d=this.activeTimers!=null,p;d&&(p=this.startTimer()),IL(this.gpgpu,h,l,c,r),o.forEach(m=>this.disposeIntermediateTensorInfo(m)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=J().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=v.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!J().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let m=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),m}return s}compileAndRun(e,t,n,r,a=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(J().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),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=z(()=>{if(!J().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=J().getBool("DEBUG");J().set("DEBUG",!1);let t=this.abs(ge(1e-8)).dataSync()[0];if(J().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?bW:wW}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:r,values:a,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,c;l&&(c=v.now());let u=t.texShape;if(u==null&&(u=O_(n,o),t.texShape=u),a!=null){let h=op(n),d,p=u[1],f=u[0],m=a instanceof Uint8Array;o?([p,f]=Il(u[0],u[1]),d=new WP(h,[f,p],m)):d=new LP(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=Xn.PIXELS:this.texData.get(A.dataId).usage=Xn.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),b=this.texData.get(g.dataId);t.texture=b.texture,t.texShape=b.texShape,t.isPacked=b.isPacked,t.usage=b.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(g.dataId),t.values=null,l&&(this.uploadWaitMs+=v.now()-c)}else{let h=this.acquireTexture(u,i,r,o);t.texture=h}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),t!=null&&(n.values=NW(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}};Rl.nextDataId=0;function NW(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 r=0;r<n.length;++r)n[r]=Math.round(e[r]);return n}else throw new Error(`Unknown dtype ${t}`)}var b3="3.3.0";function w3(){J().set("WEBGL_FORCE_F16_TEXTURES",!0)}zu.isBrowser()&&il("webgl",()=>new Rl,2);var SW={forceHalfFloat:w3},_3=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
 `,Ml=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
@@ -989,21 +989,21 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function On(e){let{inputs:t,backend:n}=e,{x:r}=t;return n.incRef(r.dataId),{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}var XP={kernelName:vs,backendName:"webgl",kernelFunc:On};function Wa(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.makeTensorInfo(r.shape,"complex64"),i=n.texData.get(s.dataId),o=On({inputs:{x:r},backend:n}),l=On({inputs:{x:a},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var KP={kernelName:Rh,backendName:"webgl",kernelFunc:Wa},Ub="return (a < 0.) ? b * a : a;",jb=`
+    `}};function On(e){let{inputs:t,backend:n}=e,{x:r}=t;return n.incRef(r.dataId),{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}var TW={kernelName:vs,backendName:"webgl",kernelFunc:On};function Wa(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.makeTensorInfo(r.shape,"complex64"),i=n.texData.get(s.dataId),o=On({inputs:{x:r},backend:n}),l=On({inputs:{x:a},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var EW={kernelName:Rh,backendName:"webgl",kernelFunc:Wa},v3="return (a < 0.) ? b * a : a;",k3=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function ZP(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new pc(jb,a.shape,i.shape):new Ml(Ub,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var YP={kernelName:ks,backendName:"webgl",kernelFunc:ZP},Hb="return (a < 0.) ? b * a : a;",Gb=`
+`;function CW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new pc(k3,a.shape,i.shape):new Ml(v3,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var RW={kernelName:ks,backendName:"webgl",kernelFunc:CW},I3="return (a < 0.) ? b * a : a;",N3=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function JP(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new pc(Gb,r.shape,a.shape):new Ml(Hb,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var QP={kernelName:Os,backendName:"webgl",kernelFunc:JP},qb="if (isnan(x)) return x;",eL=`
+`;function MW(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new pc(N3,r.shape,a.shape):new Ml(I3,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var FW={kernelName:Os,backendName:"webgl",kernelFunc:MW},S3="if (isnan(x)) return x;",DW=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
-`,tL=`
+`,$W=`
   result.r = isNaN.r > 0. ? NAN : result.r;
   result.g = isNaN.g > 0. ? NAN : result.g;
   result.b = isNaN.b > 0. ? NAN : result.b;
   result.a = isNaN.a > 0. ? NAN : result.a;
-`;function Xe({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=r||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let h=o.texData.get(i.dataId),d=n(h.values,l);return o.makeTensorInfo(i.shape,l,d)}let c=J().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,u;return c?u=new Cl(i.shape,t):u=new La(i.shape,e),o.runWebGLProgram(u,[i],l)}}function tn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:c}=i,u=o;if(r&&l.dtype==="complex64"){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(w=>{let[b,_]=w,x={dataId:b.dataId,dtype:b.dtype,shape:l.shape},N={dataId:_.dataId,dtype:_.dtype,shape:c.shape},T=new Ml(e,l.shape,c.shape);return u.runWebGLProgram(T,[x,N],nr(b.dtype,_.dtype))}),g=Wa({inputs:{real:A,imag:y},backend:u});return u.disposeIntermediateTensorInfo(A),u.disposeIntermediateTensorInfo(y),g}let h=s||nr(l.dtype,c.dtype);if(u.shouldExecuteOnCPU([l,c])&&a!=null){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=a(l.shape,c.shape,f.values,m.values,h),g=u.makeTensorInfo(y,h),w=u.texData.get(g.dataId);return w.values=A,g}let d=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new pc(t,l.shape,c.shape,n):p=new Ml(e,l.shape,c.shape),u.runWebGLProgram(p,[l,c],h)}}function mp(e,t=!1){if(e==="linear")return t?$P:CP;if(e==="relu")return t?OP:MP;if(e==="elu")return t?DP:RP;if(e==="relu6")return t?zP:FP;if(e==="prelu")return t?Gb:Hb;if(e==="leakyrelu")return t?jb:Ub;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var Xb=class{constructor(e,t,n,r=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let c=r?e[1]:e[2],u=Math.ceil(c/2),h=r?"i * 2, rc.y":"rc.y, i * 2",d=a?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",A="";i&&(o?m=`vec4 activation(vec4 a) {
+`;function Xe({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=r||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let h=o.texData.get(i.dataId),d=n(h.values,l);return o.makeTensorInfo(i.shape,l,d)}let c=J().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,u;return c?u=new Cl(i.shape,t):u=new La(i.shape,e),o.runWebGLProgram(u,[i],l)}}function tn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:c}=i,u=o;if(r&&l.dtype==="complex64"){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(b=>{let[w,_]=b,x={dataId:w.dataId,dtype:w.dtype,shape:l.shape},N={dataId:_.dataId,dtype:_.dtype,shape:c.shape},T=new Ml(e,l.shape,c.shape);return u.runWebGLProgram(T,[x,N],nr(w.dtype,_.dtype))}),g=Wa({inputs:{real:A,imag:y},backend:u});return u.disposeIntermediateTensorInfo(A),u.disposeIntermediateTensorInfo(y),g}let h=s||nr(l.dtype,c.dtype);if(u.shouldExecuteOnCPU([l,c])&&a!=null){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=a(l.shape,c.shape,f.values,m.values,h),g=u.makeTensorInfo(y,h),b=u.texData.get(g.dataId);return b.values=A,g}let d=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new pc(t,l.shape,c.shape,n):p=new Ml(e,l.shape,c.shape),u.runWebGLProgram(p,[l,c],h)}}function mp(e,t=!1){if(e==="linear")return t?fW:cW;if(e==="relu")return t?AW:dW;if(e==="elu")return t?mW:hW;if(e==="relu6")return t?yW:pW;if(e==="prelu")return t?N3:I3;if(e==="leakyrelu")return t?k3:v3;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var T3=class{constructor(e,t,n,r=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let c=r?e[1]:e[2],u=Math.ceil(c/2),h=r?"i * 2, rc.y":"rc.y, i * 2",d=a?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",A="";i&&(o?m=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${i}
         }`:l?m=`vec4 activation(vec4 a) {
@@ -1011,7 +1011,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           ${i}
         }`:m=`vec4 activation(vec4 x) {
           ${i}
-        }`,A="result = activation(result);");let y=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let g="rc.x",w="rc.x";e[0]<t[0]?g=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(w=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
+        }`,A="result = activation(result);");let y=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let g="rc.x",b="rc.x";e[0]<t[0]?g=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(b=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
       ${m}
 
       const float sharedDimension = ${u}.0;
@@ -1020,7 +1020,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         vec4 result = vec4(0);
         for (int i = 0; i < ${u}; i++) {
           int batchA = ${g};
-          int batchB = ${w};
+          int batchB = ${b};
           vec4 a = getMatrixA(batchA, ${h});
           vec4 b = getMatrixB(batchB, ${d});
 
@@ -1042,7 +1042,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}},Kb={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},Zb=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
+    `}},E3={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},C3=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
       float binaryOpComplex(
           float areal, float aimag, float breal, float bimag) {
         ${e}
@@ -1055,7 +1055,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float bimag = getBImagAtOutCoords();
         setOutput(binaryOpComplex(areal, aimag, breal, bimag));
       }
-    `}},Yb="return a * b;";function Jb(e){let{inputs:t,backend:n}=e,{a:r,b:a}=t,s=R.upcastType(r.dtype,a.dtype);if(r.dtype==="complex64"){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),c=new Zb(Kb.REAL,r.shape,a.shape),u=new Zb(Kb.IMAG,r.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:r.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Wa({inputs:{real:d,imag:p},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,a])){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),[c,u]=lP(r.shape,a.shape,o.values,l.values,s),h=n.makeTensorInfo(u,s),d=n.texData.get(h.dataId);return d.values=c,h}let i;return J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new pc(Yb,r.shape,a.shape):i=new Ml(Yb,r.shape,a.shape),n.runWebGLProgram(i,[r,a],s)}var nL={kernelName:Ms,backendName:"webgl",kernelFunc:Jb};function rL(e,t,n){let r=[gi(e.shape),...xi(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},s=[gi(t),...xi(t)],i=new Db(s,r),o=!0,l=n.runWebGLProgram(i,[a],e.dtype,null,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function xe(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=n,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),c=v.sizeFromShape(l);v.assert(o===c,()=>`The new shape (${l}) has ${c} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let u=i.texData.get(a.dataId);return u.isPacked&&!lc(a.shape,l)&&!(u.texture!==null&&lc(u.shape,l))?rL(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var aL={kernelName:zo,backendName:"webgl",kernelFunc:xe},Qb=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let u=1/t;l=`sumValue += dot(values * ${v.isInt(u)?u.toPrecision(2):u}, ones);`}let c="";a%n>0&&(c=`
+    `}},R3="return a * b;";function M3(e){let{inputs:t,backend:n}=e,{a:r,b:a}=t,s=R.upcastType(r.dtype,a.dtype);if(r.dtype==="complex64"){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),c=new C3(E3.REAL,r.shape,a.shape),u=new C3(E3.IMAG,r.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:r.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Wa({inputs:{real:d,imag:p},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,a])){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),[c,u]=VL(r.shape,a.shape,o.values,l.values,s),h=n.makeTensorInfo(u,s),d=n.texData.get(h.dataId);return d.values=c,h}let i;return J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new pc(R3,r.shape,a.shape):i=new Ml(R3,r.shape,a.shape),n.runWebGLProgram(i,[r,a],s)}var OW={kernelName:Ms,backendName:"webgl",kernelFunc:M3};function zW(e,t,n){let r=[gi(e.shape),...xi(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},s=[gi(t),...xi(t)],i=new m3(s,r),o=!0,l=n.runWebGLProgram(i,[a],e.dtype,null,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function xe(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=n,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),c=v.sizeFromShape(l);v.assert(o===c,()=>`The new shape (${l}) has ${c} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let u=i.texData.get(a.dataId);return u.isPacked&&!lc(a.shape,l)&&!(u.texture!==null&&lc(u.shape,l))?zW(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var PW={kernelName:zo,backendName:"webgl",kernelFunc:xe},F3=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let u=1/t;l=`sumValue += dot(values * ${v.isInt(u)?u.toPrecision(2):u}, ones);`}let c="";a%n>0&&(c=`
         if (inIdx < 0 || inIdx >= ${a}) {
           return 0.0;
         }
@@ -1108,7 +1108,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(sumValue);
       }
-    `}},sL=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let c=Math.floor(n/4)*4,u=n%4,h=`
+    `}},LW=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let c=Math.floor(n/4)*4,u=n%4,h=`
       if (${t==="sum"}) {
         sumValue += dot(values, ones);
       } else if (${t==="prod"}) {
@@ -1193,12 +1193,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(${l});
       }
-    `}};function iL(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],r=R.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function vi(e,t,n,r){let a=iL(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:c}=a[i],u,h;n==="mean"?u=i===0?new Qb({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},o):new Qb({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c}):u=new sL({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},n),h=s,s=r.runWebGLProgram(u,[s],t),h.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(h)}return s}var lL=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let r=ot(this.rank),a=oL(t);this.userCode=`
+    `}};function WW(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],r=R.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function vi(e,t,n,r){let a=WW(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:c}=a[i],u,h;n==="mean"?u=i===0?new F3({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},o):new F3({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c}):u=new LW({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},n),h=s,s=r.runWebGLProgram(u,[s],t),h.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(h)}return s}var VW=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let r=ot(this.rank),a=BW(t);this.userCode=`
     void main() {
       ${r} resRC = getOutputCoords();
       setOutput(getA(${a}));
     }
-    `}};function oL(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t);for(let a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}var uL=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let c=0;c<n.length;c++)n[c]=e[t[c]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let r=ot(this.rank),a=$b("rc",this.rank),s=new Array(this.rank);for(let c=0;c<t.length;c++)s[t[c]]=a[c];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
+    `}};function BW(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t);for(let a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}var jW=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let c=0;c<n.length;c++)n[c]=e[t[c]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let r=ot(this.rank),a=f3("rc",this.rank),s=new Array(this.rank);for(let c=0;c<t.length;c++)s[t[c]]=a[c];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
     void main() {
       ${r} rc = getOutputCoords();
       vec4 result = vec4(0.);
@@ -1215,14 +1215,14 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       }
       setOutput(result);
     }
-    `}};function Ap(e,t,n){let r=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new uL(e.shape,t):new lL(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function cL(e,t,n,r){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=R.getAxesPermutation(o,s),c=l!=null,u=e;c&&(u=Ap(e,l,r),o=R.getInnerMostAxes(o.length,s)),R.assertAxesAreInnerMostDims("sum",o,s);let[h,d]=R.computeOutAndReduceShapes(u.shape,o),p=h;n&&(p=R.expandShapeToKeepDim(h,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,A=xe({inputs:{x:u},attrs:{shape:[m,f]},backend:r}),y=ld(e.dtype),g=vi(A,y,"sum",r),w=xe({inputs:{x:g},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(g),c&&r.disposeIntermediateTensorInfo(u),w}function oA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;return cL(a,s,i,n)}var hL={kernelName:Gs,backendName:"webgl",kernelFunc:oA};function In(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:s}=r,i=n,o=a.shape.length,l=new Array(o);for(let u=0;u<l.length;u++)l[u]=a.shape[s[u]];let c;if(i.shouldExecuteOnCPU([a])){let u=i.texData.get(a.dataId).values,h=sA(u,a.shape,a.dtype,s,l);c=i.makeTensorInfo(l,a.dtype);let d=i.texData.get(c.dataId);d.values=h}else c=Ap(a,s,i);return c}var dL={kernelName:Ys,backendName:"webgl",kernelFunc:In},e_=1e3;function yp({a:e,b:t,transposeA:n,transposeB:r,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let c=e.shape.length,u=t.shape.length,h=n?e.shape[c-2]:e.shape[c-1],d=r?t.shape[u-1]:t.shape[u-2],p=n?e.shape[c-1]:e.shape[c-2],f=r?t.shape[u-2]:t.shape[u-1],m=e.shape.slice(0,-2),A=t.shape.slice(0,-2),y=v.sizeFromShape(m),g=v.sizeFromShape(A),w=y===g||y===1||g===1;v.assert(c>=2&&u>=2&&w,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${A}).`);let b=(y>g?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);v.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let _=n?[y,h,p]:[y,p,h],x=r?[g,f,d]:[g,d,f],N=xe({inputs:{x:e},backend:a,attrs:{shape:_}}),T=xe({inputs:{x:t},backend:a,attrs:{shape:x}}),E=[N,T],F=Math.max(y,g),D=n?N.shape[1]:N.shape[2],L=s!=null,V=i!=null,U=l==="leakyrelu",j=l!=null?mp(l,!0):null,X=L||V||U||j!=null,G;if((p===1||f===1)&&D>e_&&X===!1){let Y=N,ae=T;n&&(Y=In({inputs:{x:N},backend:a,attrs:{perm:[0,2,1]}}),E.push(Y)),r&&(ae=In({inputs:{x:T},backend:a,attrs:{perm:[0,2,1]}}),E.push(ae));let te=f!==1,oe=f===1,Q=Y;te&&(Q=xe({inputs:{x:Y},backend:a,attrs:{shape:[F,D,1]}}),E.push(Q));let he=f===1?2:1,le=ae;oe&&(le=xe({inputs:{x:ae},backend:a,attrs:{shape:[F,1,D]}}),E.push(le));let fe=Jb({inputs:{a:Q,b:le},backend:a});G=oA({inputs:{x:fe},backend:a,attrs:{axis:he,keepDims:!0}}),E.push(fe)}else{let Y=nr(e.dtype,t.dtype),ae=new Xb(_,x,[F,p,f],n,r,L,j,V,U),te=[N,T];if(s!=null&&te.push(s),V&&te.push(i),U){let oe=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));te.push(oe),E.push(oe)}G=a.runWebGLProgram(ae,te,Y)}let ee=xe({inputs:{x:G},backend:a,attrs:{shape:b}});E.push(G);for(let Y of E)a.disposeIntermediateTensorInfo(Y);return ee}function pL(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:c,activation:u,leakyreluAlpha:h}=r;return yp({a,b:s,transposeA:l,transposeB:c,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:u})}var fL={kernelName:Js,backendName:"webgl",kernelFunc:pL},t_="return abs(x);";function mL(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let s=n.texData.get(r.dataId),i=Fb(s.values);return n.makeTensorInfo(r.shape,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Cl(r.shape,t_):a=new La(r.shape,t_),n.runWebGLProgram(a,[r],r.dtype)}var AL={kernelName:Ji,backendName:"webgl",kernelFunc:mL},yL=gr+`
+    `}};function Ap(e,t,n){let r=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new jW(e.shape,t):new VW(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function UW(e,t,n,r){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=R.getAxesPermutation(o,s),c=l!=null,u=e;c&&(u=Ap(e,l,r),o=R.getInnerMostAxes(o.length,s)),R.assertAxesAreInnerMostDims("sum",o,s);let[h,d]=R.computeOutAndReduceShapes(u.shape,o),p=h;n&&(p=R.expandShapeToKeepDim(h,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,A=xe({inputs:{x:u},attrs:{shape:[m,f]},backend:r}),y=ld(e.dtype),g=vi(A,y,"sum",r),b=xe({inputs:{x:g},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(g),c&&r.disposeIntermediateTensorInfo(u),b}function dA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;return UW(a,s,i,n)}var HW={kernelName:Gs,backendName:"webgl",kernelFunc:dA};function In(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:s}=r,i=n,o=a.shape.length,l=new Array(o);for(let u=0;u<l.length;u++)l[u]=a.shape[s[u]];let c;if(i.shouldExecuteOnCPU([a])){let u=i.texData.get(a.dataId).values,h=cA(u,a.shape,a.dtype,s,l);c=i.makeTensorInfo(l,a.dtype);let d=i.texData.get(c.dataId);d.values=h}else c=Ap(a,s,i);return c}var GW={kernelName:Ys,backendName:"webgl",kernelFunc:In},D3=1e3;function yp({a:e,b:t,transposeA:n,transposeB:r,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let c=e.shape.length,u=t.shape.length,h=n?e.shape[c-2]:e.shape[c-1],d=r?t.shape[u-1]:t.shape[u-2],p=n?e.shape[c-1]:e.shape[c-2],f=r?t.shape[u-2]:t.shape[u-1],m=e.shape.slice(0,-2),A=t.shape.slice(0,-2),y=v.sizeFromShape(m),g=v.sizeFromShape(A),b=y===g||y===1||g===1;v.assert(c>=2&&u>=2&&b,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${A}).`);let w=(y>g?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);v.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let _=n?[y,h,p]:[y,p,h],x=r?[g,f,d]:[g,d,f],N=xe({inputs:{x:e},backend:a,attrs:{shape:_}}),T=xe({inputs:{x:t},backend:a,attrs:{shape:x}}),E=[N,T],F=Math.max(y,g),$=n?N.shape[1]:N.shape[2],L=s!=null,V=i!=null,j=l==="leakyrelu",U=l!=null?mp(l,!0):null,X=L||V||j||U!=null,G;if((p===1||f===1)&&$>D3&&X===!1){let Y=N,ae=T;n&&(Y=In({inputs:{x:N},backend:a,attrs:{perm:[0,2,1]}}),E.push(Y)),r&&(ae=In({inputs:{x:T},backend:a,attrs:{perm:[0,2,1]}}),E.push(ae));let te=f!==1,oe=f===1,Q=Y;te&&(Q=xe({inputs:{x:Y},backend:a,attrs:{shape:[F,$,1]}}),E.push(Q));let he=f===1?2:1,le=ae;oe&&(le=xe({inputs:{x:ae},backend:a,attrs:{shape:[F,1,$]}}),E.push(le));let fe=M3({inputs:{a:Q,b:le},backend:a});G=dA({inputs:{x:fe},backend:a,attrs:{axis:he,keepDims:!0}}),E.push(fe)}else{let Y=nr(e.dtype,t.dtype),ae=new T3(_,x,[F,p,f],n,r,L,U,V,j),te=[N,T];if(s!=null&&te.push(s),V&&te.push(i),j){let oe=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));te.push(oe),E.push(oe)}G=a.runWebGLProgram(ae,te,Y)}let ee=xe({inputs:{x:G},backend:a,attrs:{shape:w}});E.push(G);for(let Y of E)a.disposeIntermediateTensorInfo(Y);return ee}function qW(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:c,activation:u,leakyreluAlpha:h}=r;return yp({a,b:s,transposeA:l,transposeB:c,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:u})}var XW={kernelName:Js,backendName:"webgl",kernelFunc:qW},$3="return abs(x);";function KW(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let s=n.texData.get(r.dataId),i=p3(s.values);return n.makeTensorInfo(r.shape,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Cl(r.shape,$3):a=new La(r.shape,$3),n.runWebGLProgram(a,[r],r.dtype)}var ZW={kernelName:Ji,backendName:"webgl",kernelFunc:KW},YW=gr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return acos(x);
-`,gL=Xe({opSnippet:yL}),xL={kernelName:Qi,backendName:"webgl",kernelFunc:gL},wL=gr+`
+`,JW=Xe({opSnippet:YW}),QW={kernelName:Qi,backendName:"webgl",kernelFunc:JW},eB=gr+`
   if (x < 1.0) return NAN;
-return log(x + sqrt(x * x - 1.0));`,bL=Xe({opSnippet:wL}),_L={kernelName:eo,backendName:"webgl",kernelFunc:bL},n_="return a + b;",vL=tn({opSnippet:n_,packedOpSnippet:n_,supportsComplex:!0,cpuKernelImpl:qz}),kL={kernelName:va,backendName:"webgl",kernelFunc:vL},IL=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`float v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
+return log(x + sqrt(x * x - 1.0));`,tB=Xe({opSnippet:eB}),nB={kernelName:eo,backendName:"webgl",kernelFunc:tB},O3="return a + b;",rB=tn({opSnippet:O3,packedOpSnippet:O3,supportsComplex:!0,cpuKernelImpl:SL}),aB={kernelName:va,backendName:"webgl",kernelFunc:rB},sB=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`float v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
       void main() {
         ${n.join(`
         `)}
@@ -1230,7 +1230,7 @@ return log(x + sqrt(x * x - 1.0));`,bL=Xe({opSnippet:wL}),_L={kernelName:eo,back
         float result = ${r};
         setOutput(result);
       }
-    `}},NL=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`vec4 v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
+    `}},iB=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`vec4 v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
       void main() {
         ${n.join(`
         `)}
@@ -1238,7 +1238,7 @@ return log(x + sqrt(x * x - 1.0));`,bL=Xe({opSnippet:wL}),_L={kernelName:eo,back
         vec4 result = ${r};
         setOutput(result);
       }
-    `}};function gp(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return On({inputs:{x:r[0]},backend:n});if(r.length>J().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(r.length/2),l=gp({inputs:r.slice(0,o),backend:n}),c=gp({inputs:r.slice(o),backend:n});return gp({inputs:[l,c],backend:n})}let a=r.map(o=>o.dtype).reduce((o,l)=>nr(o,l)),s=r.map(o=>o.shape),i=J().getBool("WEBGL_PACK")?new NL(r[0].shape,s):new IL(r[0].shape,s);return n.runWebGLProgram(i,r,a)}var SL={kernelName:is,backendName:"webgl",kernelFunc:gp};function TL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("all",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"all",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var EL={kernelName:Nh,backendName:"webgl",kernelFunc:TL};function CL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("any",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"any",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var RL={kernelName:Sh,backendName:"webgl",kernelFunc:CL},ML=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:r,batchSize:a,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
+    `}};function gp(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return On({inputs:{x:r[0]},backend:n});if(r.length>J().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(r.length/2),l=gp({inputs:r.slice(0,o),backend:n}),c=gp({inputs:r.slice(o),backend:n});return gp({inputs:[l,c],backend:n})}let a=r.map(o=>o.dtype).reduce((o,l)=>nr(o,l)),s=r.map(o=>o.shape),i=J().getBool("WEBGL_PACK")?new iB(r[0].shape,s):new sB(r[0].shape,s);return n.runWebGLProgram(i,r,a)}var oB={kernelName:is,backendName:"webgl",kernelFunc:gp};function lB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("all",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"all",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var uB={kernelName:Nh,backendName:"webgl",kernelFunc:lB};function cB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("any",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"any",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var hB={kernelName:Sh,backendName:"webgl",kernelFunc:cB},dB=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:r,batchSize:a,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
@@ -1258,7 +1258,7 @@ return log(x + sqrt(x * x - 1.0));`,bL=Xe({opSnippet:wL}),_L={kernelName:eo,back
         }
         setOutput(float(bestIndex));
       }
-    `}},FL=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=ot(o),c=dn("coords",o),u,h;if(s===1){h=o+1;let N=ot(h);u=`
+    `}},pB=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=ot(o),c=dn("coords",o),u,h;if(s===1){h=o+1;let N=ot(h);u=`
         ${N} sourceLocR = ${N}(${c.join()}, 0);
         ++${c[o-1]};
         ${N} sourceLocG = ${N}(${c.join()}, 0);
@@ -1274,7 +1274,7 @@ return log(x + sqrt(x * x - 1.0));`,bL=Xe({opSnippet:wL}),_L={kernelName:eo,back
         ${l} sourceLocA = coords;
         --${c[o-1]};
         ${l} sourceLocB = coords;
-        --${c[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(N=>"int "+N),m=dn("sourceLocR",h-1).concat("inIdx.r"),A=dn("sourceLocG",h-1).concat("inIdx.g"),y=dn("sourceLocB",h-1).concat("inIdx.b"),g=dn("sourceLocA",h-1).concat("inIdx.a"),w=n==="max"?"greaterThan":"lessThan",b=r?"":`
+        --${c[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(N=>"int "+N),m=dn("sourceLocR",h-1).concat("inIdx.r"),A=dn("sourceLocG",h-1).concat("inIdx.g"),y=dn("sourceLocB",h-1).concat("inIdx.b"),g=dn("sourceLocA",h-1).concat("inIdx.a"),b=n==="max"?"greaterThan":"lessThan",w=r?"":`
           inIdx = round(vec4(getBestIndicesAChannel(${m.join()}),
                              getBestIndicesAChannel(${A.join()}),
                              getBestIndicesAChannel(${y.join()}),
@@ -1305,11 +1305,11 @@ return log(x + sqrt(x * x - 1.0));`,bL=Xe({opSnippet:wL}),_L={kernelName:eo,back
 
         for (int i = 0; i < ${t}; i++) {
           inIdx = srcIdx;
-          ${b}
+          ${w}
           vec4 candidate = ${_};
           bvec4 nan = isnan(candidate);
           bvec4 replace = bvec4(
-            vec4(${w}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));
+            vec4(${b}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));
 
           bestValue = vec4(replace.x  ? candidate.x : bestValue.x,
                            replace.y  ? candidate.y : bestValue.y,
@@ -1320,23 +1320,23 @@ return log(x + sqrt(x * x - 1.0));`,bL=Xe({opSnippet:wL}),_L={kernelName:eo,back
         }
         setOutput(bestIndex);
       }
-    `}};function r_(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=R.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new ML(o,n,r==null),c=[t];r!=null&&c.push(r);let u=e.runWebGLProgram(l,c,"int32");if(u.shape[1]===1)return u;let h=r_(e,t,n,u);return e.disposeIntermediateTensorInfo(u),h}function a_(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=R.computeOptimalWindowSize(s),o=new FL(a,i,n,r==null),l=r==null?[t]:[t,r],c=e.runWebGLProgram(o,l,"int32");if(c.shape.length===t.shape.length){let u=a_(e,t,n,c);return e.disposeIntermediateTensorInfo(c),u}return c}function s_(e,t,n,r){let a=[n];if(R.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!J().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=R.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),c=xe({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(c);let u=r_(e,c,r);s.push(u);let h=xe({inputs:{x:u},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return a_(e,t,r)}function $L(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=In({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let u=s_(n,l,i[0],"max");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var DL={kernelName:os,backendName:"webgl",kernelFunc:$L};function OL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=In({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let u=s_(n,l,i[0],"min");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var zL={kernelName:du,backendName:"webgl",kernelFunc:OL},PL=gr+`
+    `}};function z3(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=R.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new dB(o,n,r==null),c=[t];r!=null&&c.push(r);let u=e.runWebGLProgram(l,c,"int32");if(u.shape[1]===1)return u;let h=z3(e,t,n,u);return e.disposeIntermediateTensorInfo(u),h}function P3(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=R.computeOptimalWindowSize(s),o=new pB(a,i,n,r==null),l=r==null?[t]:[t,r],c=e.runWebGLProgram(o,l,"int32");if(c.shape.length===t.shape.length){let u=P3(e,t,n,c);return e.disposeIntermediateTensorInfo(c),u}return c}function L3(e,t,n,r){let a=[n];if(R.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!J().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=R.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),c=xe({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(c);let u=z3(e,c,r);s.push(u);let h=xe({inputs:{x:u},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return P3(e,t,r)}function fB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=In({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let u=L3(n,l,i[0],"max");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var mB={kernelName:os,backendName:"webgl",kernelFunc:fB};function AB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=In({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let u=L3(n,l,i[0],"min");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var yB={kernelName:du,backendName:"webgl",kernelFunc:AB},gB=gr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return asin(x);
-`,LL=Xe({opSnippet:PL}),WL={kernelName:to,backendName:"webgl",kernelFunc:LL},BL=gr+"return log(x + sqrt(x * x + 1.0));",VL=Xe({opSnippet:BL}),UL={kernelName:no,backendName:"webgl",kernelFunc:VL},jL=gr+`
+`,xB=Xe({opSnippet:gB}),bB={kernelName:to,backendName:"webgl",kernelFunc:xB},wB=gr+"return log(x + sqrt(x * x + 1.0));",_B=Xe({opSnippet:wB}),vB={kernelName:no,backendName:"webgl",kernelFunc:_B},kB=gr+`
   return atan(x);
-`,HL=Xe({opSnippet:jL}),GL={kernelName:ro,backendName:"webgl",kernelFunc:HL},qL=eL+`
+`,IB=Xe({opSnippet:kB}),NB={kernelName:ro,backendName:"webgl",kernelFunc:IB},SB=DW+`
   return atan(a, b);
-`,XL=`
+`,TB=`
   vec4 result = atan(a, b);
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+tL+`
+  `+$W+`
   return result;
-`,KL=tn({opSnippet:qL,packedOpSnippet:XL}),ZL={kernelName:so,backendName:"webgl",kernelFunc:KL},YL=gr+`
+`,EB=tn({opSnippet:SB,packedOpSnippet:TB}),CB={kernelName:so,backendName:"webgl",kernelFunc:EB},RB=gr+`
   if ((x < -1.0) || (x > 1.0)) return NAN;
-return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelName:ao,backendName:"webgl",kernelFunc:JL},fc=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let N=">=";this.userCode=`
+return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,MB=Xe({opSnippet:RB}),FB={kernelName:ao,backendName:"webgl",kernelFunc:MB},fc=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let N=">=";this.userCode=`
         const ivec2 strides = ivec2(${i}, ${o});
         const ivec2 pads = ivec2(${d}, ${p});
 
@@ -1387,7 +1387,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
           }
           setOutput(float(minMaxPosition));
         }
-      `;return}let g="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / count");let b=Math.floor(s/4)*4,_=s%4,x=`
+      `;return}let g="max",b=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(b="avgValue / count");let w=Math.floor(s/4)*4,_=s%4,x=`
       if (${f}) {
         avgValue += dot(values, ones);
       } else {
@@ -1432,7 +1432,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
             continue;
           }
 
-          for (int wC = 0; wC < ${b}; wC += 4) {
+          for (int wC = 0; wC < ${w}; wC += 4) {
             int xC = xCCorner + wC * ${c};
 
             vec4 values = vec4(
@@ -1445,7 +1445,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
             ${x}
           }
 
-          int xC = xCCorner + ${b};
+          int xC = xCCorner + ${w};
           if (${_===1}) {
             vec4 values = vec4(
               getValue(batch, xR, xC, d),
@@ -1475,9 +1475,9 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
             ${x}
           }
         }
-        setOutput(${w});
+        setOutput(${b});
       }
-    `}},lA=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,c=e.dilationDepth,u=e.dilationHeight,h=e.dilationWidth,d=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,A=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let g=t==="avg",w="0.0";if(g||(w="-1.0 / 1e-20"),n){let E=">=";this.userCode=`
+    `}},pA=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,c=e.dilationDepth,u=e.dilationHeight,h=e.dilationWidth,d=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,A=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let g=t==="avg",b="0.0";if(g||(b="-1.0 / 1e-20"),n){let E=">=";this.userCode=`
         const ivec3 strides =
             ivec3(${i}, ${o}, ${l});
         const ivec3 pads = ivec3(${m}, ${A}, ${y});
@@ -1539,17 +1539,17 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
           }
           setOutput(float(minMaxPosition));
         }
-      `;return}let b="max",_=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(_="avgValue / count");let x=Math.floor(s/4)*4,N=s%4,T=`
+      `;return}let w="max",_=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(_="avgValue / count");let x=Math.floor(s/4)*4,N=s%4,T=`
       if (${g}) {
         avgValue += dot(values, ones);
       } else {
-        minMaxValue = ${b}(values, minMaxValue);
+        minMaxValue = ${w}(values, minMaxValue);
       }
     `;this.userCode=`
       const ivec3 strides =
         ivec3(${i}, ${o}, ${l});
       const ivec3 pads = ivec3(${m}, ${A}, ${y});
-      const float initializationValue = ${w};
+      const float initializationValue = ${b};
       const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
 
       float count = 0.0;
@@ -1574,7 +1574,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
 
         // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
         // ? = to be determined
-        vec4 minMaxValue = vec4(${w});
+        vec4 minMaxValue = vec4(${b});
         float avgValue = 0.0;
         count = 0.0;
 
@@ -1640,7 +1640,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
           setOutput(${_});
         }
       }
-    `}};function eW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return On({inputs:{x:a},backend:n});let h=new fc(u,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var tW={kernelName:ls,backendName:"webgl",kernelFunc:eW};function nW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,l,c),d=new lA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var rW={kernelName:pu,backendName:"webgl",kernelFunc:nW},aW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,c=o-1-e.padInfo.top,u=l-1-e.padInfo.left,h=1/(t*n);this.userCode=`
+    `}};function DB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return On({inputs:{x:a},backend:n});let h=new fc(u,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var $B={kernelName:ls,backendName:"webgl",kernelFunc:DB};function OB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,l,c),d=new pA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var zB={kernelName:pu,backendName:"webgl",kernelFunc:OB},PB=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,c=o-1-e.padInfo.top,u=l-1-e.padInfo.left,h=1/(t*n);this.userCode=`
       const ivec2 pads = ivec2(${c}, ${u});
       const float avgMultiplier = float(${h});
 
@@ -1682,7 +1682,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},sW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=u-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=`
+    `}},LB=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=u-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=`
       const ivec3 pads = ivec3(${p}, ${f}, ${m});
       const float avgMultiplier = float(${A});
 
@@ -1738,7 +1738,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function iW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new sW(d);return n.runWebGLProgram(p,[a],i.dtype)}var oW={kernelName:Eh,backendName:"webgl",kernelFunc:iW};function lW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;kl([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:c}=r,u=R.computePool2DInfo(i.shape,o,l,1,c),h=new aW(u);return n.runWebGLProgram(h,[a],i.dtype)}var uW={kernelName:Th,backendName:"webgl",kernelFunc:lW};function cW(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return yp({a,b:s,transposeA:i,transposeB:o,backend:n})}var hW={kernelName:us,backendName:"webgl",kernelFunc:cW},dW=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}};function WB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new LB(d);return n.runWebGLProgram(p,[a],i.dtype)}var BB={kernelName:Eh,backendName:"webgl",kernelFunc:WB};function VB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;kl([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:c}=r,u=R.computePool2DInfo(i.shape,o,l,1,c),h=new PB(u);return n.runWebGLProgram(h,[a],i.dtype)}var jB={kernelName:Th,backendName:"webgl",kernelFunc:VB};function UB(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return yp({a,b:s,transposeA:i,transposeB:o,backend:n})}var HB={kernelName:us,backendName:"webgl",kernelFunc:UB},GB=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         float x = getXAtOutCoords();
         float mean = getMeanAtOutCoords();
@@ -1748,7 +1748,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         float inv = scale * inversesqrt(variance + float(${s}));
         setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
       }
-    `}},pW=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}},qB=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         vec4 offset = ${i};
         vec4 scale = ${o};
@@ -1761,7 +1761,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
 
         setOutput((x - mean) * inv + offset);
       }
-    `}},fW=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let c=[r,a,s],u=null;i!=null&&(u=i.shape,c.push(i));let h=null;o!=null&&(h=o.shape,c.push(o));let d=J().getBool("WEBGL_PACK_NORMALIZATION")?new pW(r.shape,a.shape,s.shape,u,h,l):new dW(r.shape,a.shape,s.shape,u,h,l);return t.runWebGLProgram(d,c,c[0].dtype)},mW={kernelName:bs,backendName:"webgl",kernelFunc:fW},yW=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ot(this.rank),n=`uniform int start[${this.rank}];`,r=AW(this.rank),a,s=e.map((i,o)=>`sourceLoc.${uA[o]} = start[${o}] + coords.${uA[o]};`);a=`
+    `}},XB=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let c=[r,a,s],u=null;i!=null&&(u=i.shape,c.push(i));let h=null;o!=null&&(h=o.shape,c.push(o));let d=J().getBool("WEBGL_PACK_NORMALIZATION")?new qB(r.shape,a.shape,s.shape,u,h,l):new GB(r.shape,a.shape,s.shape,u,h,l);return t.runWebGLProgram(d,c,c[0].dtype)},KB={kernelName:ws,backendName:"webgl",kernelFunc:XB},YB=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ot(this.rank),n=`uniform int start[${this.rank}];`,r=ZB(this.rank),a,s=e.map((i,o)=>`sourceLoc.${fA[o]} = start[${o}] + coords.${fA[o]};`);a=`
         ${t} sourceLoc;
         ${t} coords = getOutputCoords();
         ${s.join(`
@@ -1772,7 +1772,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         ${a}
         setOutput(getSource(${r}));
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}},uA=["x","y","z","w","u","v"];function AW(e){if(e===1)return"sourceLoc";if(e<=6)return uA.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var gW=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=ot(this.rank),n=dn("coords",this.rank),r=dn("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${r.slice(-2).join()})`,s=`getChannel(getSource(${r.join()}), ${a})`,i=`
+    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}},fA=["x","y","z","w","u","v"];function ZB(e){if(e===1)return"sourceLoc";if(e<=6)return fA.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var JB=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=ot(this.rank),n=dn("coords",this.rank),r=dn("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${r.slice(-2).join()})`,s=`getChannel(getSource(${r.join()}), ${a})`,i=`
       result.x = ${s};
       if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
         ++${r[this.rank-1]};
@@ -1802,7 +1802,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         ${o}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function xW(e,t,n,r){let a=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=ln.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,l+1),s}function mc(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=ln.parseSliceParams(a,s,i);if(ln.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,a.dtype,[]);if(n.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=n.texData.get(a.dataId),d=pP(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:c}=n.texData.get(a.dataId),u=ln.isSliceContinous(a.shape,o,l);if(c||!u){let h=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new gW(l):new yW(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),xW(a,o,l,n)}var wW={kernelName:Bo,backendName:"webgl",kernelFunc:mc},bW=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((g,w)=>g*w),l=R.getReshaped(a.shape,s,o),c=R.getPermuted(l.length,s.length),u=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(u,i,s.length),p=[],f=xe({inputs:{x:a},backend:n,attrs:{shape:l}}),m=In({inputs:{x:f},backend:n,attrs:{perm:c}}),A=xe({inputs:{x:m},backend:n,attrs:{shape:u}}),y=mc({inputs:{x:A},backend:n,attrs:{begin:h,size:d}});return p.push(f),p.push(m),p.push(A),p.forEach(g=>n.disposeIntermediateTensorInfo(g)),y},_W={kernelName:fu,backendName:"webgl",kernelFunc:bW};function vW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.readSync(a.dataId),l=n.readSync(s.dataId),c=Mb(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var kW={kernelName:Ch,backendName:"webgl",kernelFunc:vW},IW="return float(a != b);",i_=tn({opSnippet:IW,dtype:"bool"}),NW={kernelName:Eo,backendName:"webgl",kernelFunc:i_};function Ac(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return On({inputs:{x:a.complexTensorInfos.real},backend:n})}var SW={kernelName:Yh,backendName:"webgl",kernelFunc:Ac},TW="return float(int(x));";function EW(e,t){let n=new La(e.shape,TW),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function cA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return On({inputs:{x:a},backend:n});let i=Et(a.shape),o=cA({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Wa({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=Ac({inputs:{input:a},backend:n}),o=cA({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=On({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return EW(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=i_({inputs:{a,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var CW={kernelName:cs,backendName:"webgl",kernelFunc:cA},o_="return ceil(x);",RW=Xe({opSnippet:o_,packedOpSnippet:o_,cpuKernelImpl:Kz}),MW={kernelName:hs,backendName:"webgl",kernelFunc:RW},FW=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function QB(e,t,n,r){let a=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=ln.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,l+1),s}function mc(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=ln.parseSliceParams(a,s,i);if(ln.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,a.dtype,[]);if(n.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=n.texData.get(a.dataId),d=qL(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:c}=n.texData.get(a.dataId),u=ln.isSliceContinous(a.shape,o,l);if(c||!u){let h=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new JB(l):new YB(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),QB(a,o,l,n)}var eV={kernelName:Bo,backendName:"webgl",kernelFunc:mc},tV=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((g,b)=>g*b),l=R.getReshaped(a.shape,s,o),c=R.getPermuted(l.length,s.length),u=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(u,i,s.length),p=[],f=xe({inputs:{x:a},backend:n,attrs:{shape:l}}),m=In({inputs:{x:f},backend:n,attrs:{perm:c}}),A=xe({inputs:{x:m},backend:n,attrs:{shape:u}}),y=mc({inputs:{x:A},backend:n,attrs:{begin:h,size:d}});return p.push(f),p.push(m),p.push(A),p.forEach(g=>n.disposeIntermediateTensorInfo(g)),y},nV={kernelName:fu,backendName:"webgl",kernelFunc:tV};function rV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.readSync(a.dataId),l=n.readSync(s.dataId),c=d3(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var aV={kernelName:Ch,backendName:"webgl",kernelFunc:rV},sV="return float(a != b);",W3=tn({opSnippet:sV,dtype:"bool"}),iV={kernelName:Eo,backendName:"webgl",kernelFunc:W3};function Ac(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return On({inputs:{x:a.complexTensorInfos.real},backend:n})}var oV={kernelName:Yh,backendName:"webgl",kernelFunc:Ac},lV="return float(int(x));";function uV(e,t){let n=new La(e.shape,lV),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function mA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return On({inputs:{x:a},backend:n});let i=Et(a.shape),o=mA({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Wa({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=Ac({inputs:{input:a},backend:n}),o=mA({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=On({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return uV(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=W3({inputs:{a,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var cV={kernelName:cs,backendName:"webgl",kernelFunc:mA},B3="return ceil(x);",hV=Xe({opSnippet:B3,packedOpSnippet:B3,cpuKernelImpl:EL}),dV={kernelName:hs,backendName:"webgl",kernelFunc:hV},pV=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1815,7 +1815,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
 
         setOutput(clamp(value, minVal, maxVal));
       }
-    `}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}},$W=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}},fV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1829,7 +1829,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
 
         setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
       }
-    `}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}};function DW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o;J().getBool("WEBGL_PACK_CLIP")?o=new $W(a.shape):o=new FW(a.shape);let l=o.getCustomSetupFunc(s,i);return n.runWebGLProgram(o,[a],a.dtype,l)}var OW={kernelName:ka,backendName:"webgl",kernelFunc:DW},zW=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}};function mV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o;J().getBool("WEBGL_PACK_CLIP")?o=new fV(a.shape):o=new pV(a.shape);let l=o.getCustomSetupFunc(s,i);return n.runWebGLProgram(o,[a],a.dtype,l)}var AV={kernelName:ka,backendName:"webgl",kernelFunc:mV},yV=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
       void main() {
         float re = abs(getRealAtOutCoords());
         float im = abs(getImagAtOutCoords());
@@ -1842,7 +1842,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
           mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
         );
       }
-    `}};function l_(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function PW(e){let{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),s=new zW(r.shape),i=[l_(r,a.complexTensorInfos.real),l_(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var LW={kernelName:mu,backendName:"webgl",kernelFunc:PW},WW=class{constructor(e){this.outputShape=[],this.outputShape=R.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let r=t.length,a=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${a}));`),this.userCode=`
+    `}};function V3(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function gV(e){let{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),s=new yV(r.shape),i=[V3(r,a.complexTensorInfos.real),V3(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var xV={kernelName:mu,backendName:"webgl",kernelFunc:gV},bV=class{constructor(e){this.outputShape=[],this.outputShape=R.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let r=t.length,a=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${a}));`),this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int yR = coords.x;
@@ -1851,7 +1851,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         ${n.join(`
         `)}
       }
-    `}},BW=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=R.computeOutShape(e,t);let n=this.outputShape,r=n.length,a=ot(r),s=dn("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],c=i.slice(-2),u=i.join(),h=`if (${l} < ${o[0]}) {
+    `}},wV=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=R.computeOutShape(e,t);let n=this.outputShape,r=n.length,a=ot(r),s=dn("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],c=i.slice(-2),u=i.join(),h=`if (${l} < ${o[0]}) {
         return getChannel(
             getT0(${u}), vec2(${c.join()}));
         }`;for(let f=1;f<o.length;f++){let m=o[f-1];h+=`
@@ -1888,18 +1888,18 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         }
         setOutput(result);
       }
-    `}};function xp(e,t,n){let r=e.indexOf(t);return e.map((a,s)=>s===r?`${a} - ${n}`:a).join()}function wp(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return On({inputs:{x:a.complexTensorInfos.imag},backend:n})}var VW={kernelName:jh,backendName:"webgl",kernelFunc:wp};function Fl(e,t,n){let r=e[0].dtype;if(r==="complex64"){let c=e.map(f=>Ac({inputs:{input:f},backend:n})),u=e.map(f=>wp({inputs:{input:f},backend:n})),h=Fl(c,t,n),d=Fl(u,t,n),p=Wa({inputs:{real:h,imag:d},backend:n});return c.forEach(f=>n.disposeIntermediateTensorInfo(f)),u.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),p}if(r==="string"){let{tensors2D:c,outShape:u}=u_(e,t,n),h=c.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),d=c[0].shape[0]===1,p=Zz(h,u,r,d),f=R.computeOutShape(e.map(A=>A.shape),t),m=n.makeTensorInfo(f,r,p);return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),m}if(e.length>J().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let c=Math.floor(e.length/2),u=Fl(e.slice(0,c),t,n),h=Fl(e.slice(c),t,n),d=Fl([u,h],t,n);return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),d}if(J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let c=new BW(e.map(u=>u.shape),t);return n.runWebGLProgram(c,e,r)}let{tensors2D:a,outShape:s}=u_(e,t,n),i=new WW(a.map(c=>c.shape)),o=n.runWebGLProgram(i,a,r);a.forEach(c=>n.disposeIntermediateTensorInfo(c));let l=xe({inputs:{x:o},attrs:{shape:s},backend:n});return n.disposeIntermediateTensorInfo(o),l}function u_(e,t,n){let r=R.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>xe({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function c_(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(c=>c.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(c=>v.sizeFromShape(c.shape)>0);if(o.length===1)return On({inputs:{x:o[0]},backend:n});let l=o.map(c=>c.shape);return R.assertParamsConsistent(l,s),Fl(o,s,n)}var UW={kernelName:io,backendName:"webgl",kernelFunc:c_},h_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,c=e.dilationHeight,u=e.dilationWidth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",A=m?1:2,y=m?2:3,g=m?3:1,w="",b="";n&&(r?w=`float activation(float a) {
+    `}};function xp(e,t,n){let r=e.indexOf(t);return e.map((a,s)=>s===r?`${a} - ${n}`:a).join()}function bp(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return On({inputs:{x:a.complexTensorInfos.imag},backend:n})}var _V={kernelName:Uh,backendName:"webgl",kernelFunc:bp};function Fl(e,t,n){let r=e[0].dtype;if(r==="complex64"){let c=e.map(f=>Ac({inputs:{input:f},backend:n})),u=e.map(f=>bp({inputs:{input:f},backend:n})),h=Fl(c,t,n),d=Fl(u,t,n),p=Wa({inputs:{real:h,imag:d},backend:n});return c.forEach(f=>n.disposeIntermediateTensorInfo(f)),u.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),p}if(r==="string"){let{tensors2D:c,outShape:u}=j3(e,t,n),h=c.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),d=c[0].shape[0]===1,p=CL(h,u,r,d),f=R.computeOutShape(e.map(A=>A.shape),t),m=n.makeTensorInfo(f,r,p);return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),m}if(e.length>J().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let c=Math.floor(e.length/2),u=Fl(e.slice(0,c),t,n),h=Fl(e.slice(c),t,n),d=Fl([u,h],t,n);return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),d}if(J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let c=new wV(e.map(u=>u.shape),t);return n.runWebGLProgram(c,e,r)}let{tensors2D:a,outShape:s}=j3(e,t,n),i=new bV(a.map(c=>c.shape)),o=n.runWebGLProgram(i,a,r);a.forEach(c=>n.disposeIntermediateTensorInfo(c));let l=xe({inputs:{x:o},attrs:{shape:s},backend:n});return n.disposeIntermediateTensorInfo(o),l}function j3(e,t,n){let r=R.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>xe({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function U3(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(c=>c.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(c=>v.sizeFromShape(c.shape)>0);if(o.length===1)return On({inputs:{x:o[0]},backend:n});let l=o.map(c=>c.shape);return R.assertParamsConsistent(l,s),Fl(o,s,n)}var vV={kernelName:io,backendName:"webgl",kernelFunc:U3},H3=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,c=e.dilationHeight,u=e.dilationWidth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",A=m?1:2,y=m?2:3,g=m?3:1,b="",w="";n&&(r?b=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${n}
-        }`:a?w=`float activation(float a) {
+        }`:a?b=`float activation(float a) {
           float b = getLeakyreluAlphaAtOutCoords();
           ${n}
-        }`:w=`
+        }`:b=`
           float activation(float x) {
             ${n}
           }
-        `,b="result = activation(result);");let _=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
-      ${w}
+        `,w="result = activation(result);");let _=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
+      ${b}
 
       const ivec2 strides = ivec2(${o}, ${l});
       const ivec2 pads = ivec2(${s}, ${i});
@@ -2019,10 +2019,10 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
 
         float result = dotProd;
         ${_}
-        ${b}
+        ${w}
         setOutput(result);
       }
-    `}},jW=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
+    `}},kV=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
       const ivec3 strides = ivec3(${a}, ${s}, ${i});
       const ivec3 pads = ivec3(${t}, ${n}, ${r});
 
@@ -2110,9 +2110,9 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},HW=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:a,strideWidth:s,strideHeight:i,padInfo:o,outWidth:l,dilationWidth:c,dilationHeight:u,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=hn(),A=h==="channelsLast",y=A?0:1,g=A?1:2,w="";for(let b=0;b<=1;b++)for(let _=0;_<=1;_++)w+=`
+    `}},IV=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:a,strideWidth:s,strideHeight:i,padInfo:o,outWidth:l,dilationWidth:c,dilationHeight:u,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=hn(),A=h==="channelsLast",y=A?0:1,g=A?1:2,b="";for(let w=0;w<=1;w++)for(let _=0;_<=1;_++)b+=`
           blockIndex = rc.y + ${_};
-          pos = rc.x + ${b};
+          pos = rc.x + ${w};
 
           if(blockIndex < ${e[1]} && pos < ${e[0]}) {
             offsetY = int(blockIndex / (${l})) * ${i} - ${p};
@@ -2129,12 +2129,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
 
                 if (${A}) {
                   innerDims = vec2(d1, ch);
-                  result[${b*2+_}] = getChannel(
+                  result[${w*2+_}] = getChannel(
                     getA(d0, int(innerDims.x),
                     int(innerDims.y)), innerDims);
                 } else {
                   innerDims = vec2(d0, d1);
-                  result[${b*2+_}] = getChannel(
+                  result[${w*2+_}] = getChannel(
                     getA(ch, int(innerDims.x),
                     int(innerDims.y)), innerDims);
                 }
@@ -2150,11 +2150,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
         vec2 innerDims;
 
-        ${w}
+        ${b}
 
         ${m.output} = result;
       }
-    `}};function d_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,c=r.texData.get(e.dataId),u=n.inChannels,h=l[0]*l[1]*l[2],d=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,A,y=[],g=(h===1||d===1)&&u>e_,w=l[2]%2!=0&&!!c.isPacked;if(g||!J().getBool("WEBGL_LAZILY_UNPACK")||!J().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let b=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=xe({inputs:{x:e},backend:r,attrs:{shape:[1,b,n.inChannels]}}),x=xe({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),N=yp({a:_,b:x,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=xe({inputs:{x:N},backend:r,attrs:{shape:n.outShape}}),y.push(_),y.push(x),y.push(N)}else{let b=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},x=c.shape;c.shape=c.shape.slice(),c.shape[c.shape.length-2]++,v.assert(lc(c.shape,_.shape),()=>`packed reshape ${c.shape} to ${_.shape} isn't free`);let N=xe({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(N);let T=yp({a:_,b:N,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),E=r.texData.get(T.dataId);v.assert(E.isPacked,()=>"batchMatMul result is expected to be packed"),c.shape=x,E.shape=n.outShape,A=On({inputs:{x:T},backend:r}),A.shape=n.outShape,y.push(T)}for(let b of y)r.disposeIntermediateTensorInfo(b);return A}function p_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:c,inChannels:u,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*c*u,A=d*h,y=[m,A],g=!0,w=!1,b=[],_=xe({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),x=xe({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(_),b.push(x);let N=new HW(y,_.shape,n),T=r.runWebGLProgram(N,[_],"float32"),E=xe({inputs:{x:T},backend:r,attrs:{shape:[1,y[0],y[1]]}});b.push(T),b.push(E);let F=a!=null,D=s!=null,L=o==="leakyrelu",V=o?mp(o,!0):null,U=new Xb(E.shape,x.shape,[1,A,n.outChannels],g,w,F,V,D,L),j=[E,x];if(a&&j.push(a),D&&j.push(s),L){let Y=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));j.push(Y),b.push(Y)}let X=r.runWebGLProgram(U,j,"float32"),G=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=xe({inputs:{x:X},backend:r,attrs:{shape:G}});b.push(X);for(let Y of b)r.disposeIntermediateTensorInfo(Y);return ee}function GW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!1,h),p;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"))p=d_({x:a,filter:s,convInfo:d,backend:n});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=p_({x:a,filter:s,convInfo:d,backend:n});else{let m=new h_(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=xe({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var qW={kernelName:ds,backendName:"webgl",kernelFunc:GW},XW=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
+    `}};function G3({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,c=r.texData.get(e.dataId),u=n.inChannels,h=l[0]*l[1]*l[2],d=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,A,y=[],g=(h===1||d===1)&&u>D3,b=l[2]%2!=0&&!!c.isPacked;if(g||!J().getBool("WEBGL_LAZILY_UNPACK")||!J().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!b){let w=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=xe({inputs:{x:e},backend:r,attrs:{shape:[1,w,n.inChannels]}}),x=xe({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),N=yp({a:_,b:x,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=xe({inputs:{x:N},backend:r,attrs:{shape:n.outShape}}),y.push(_),y.push(x),y.push(N)}else{let w=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:e.dataId,shape:[1,w,n.inChannels],dtype:e.dtype},x=c.shape;c.shape=c.shape.slice(),c.shape[c.shape.length-2]++,v.assert(lc(c.shape,_.shape),()=>`packed reshape ${c.shape} to ${_.shape} isn't free`);let N=xe({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(N);let T=yp({a:_,b:N,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),E=r.texData.get(T.dataId);v.assert(E.isPacked,()=>"batchMatMul result is expected to be packed"),c.shape=x,E.shape=n.outShape,A=On({inputs:{x:T},backend:r}),A.shape=n.outShape,y.push(T)}for(let w of y)r.disposeIntermediateTensorInfo(w);return A}function q3({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:c,inChannels:u,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*c*u,A=d*h,y=[m,A],g=!0,b=!1,w=[],_=xe({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),x=xe({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});w.push(_),w.push(x);let N=new IV(y,_.shape,n),T=r.runWebGLProgram(N,[_],"float32"),E=xe({inputs:{x:T},backend:r,attrs:{shape:[1,y[0],y[1]]}});w.push(T),w.push(E);let F=a!=null,$=s!=null,L=o==="leakyrelu",V=o?mp(o,!0):null,j=new T3(E.shape,x.shape,[1,A,n.outChannels],g,b,F,V,$,L),U=[E,x];if(a&&U.push(a),$&&U.push(s),L){let Y=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));U.push(Y),w.push(Y)}let X=r.runWebGLProgram(j,U,"float32"),G=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=xe({inputs:{x:X},backend:r,attrs:{shape:G}});w.push(X);for(let Y of w)r.disposeIntermediateTensorInfo(Y);return ee}function NV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!1,h),p;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"))p=G3({x:a,filter:s,convInfo:d,backend:n});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=q3({x:a,filter:s,convInfo:d,backend:n});else{let m=new H3(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=xe({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var SV={kernelName:ds,backendName:"webgl",kernelFunc:NV},TV=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2196,7 +2196,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},KW=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,c=s?2:3,u=s?3:1;this.userCode=`
+    `}},EV=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,c=s?2:3,u=s?3:1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${o});
 
       void main() {
@@ -2249,7 +2249,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},ZW=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
+    `}},CV=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
       void main() {
         ivec5 coords = getOutputCoords();
         int wF = coords.x;
@@ -2291,7 +2291,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},YW=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,c=r-1-e.padInfo.left;this.userCode=`
+    `}},RV=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,c=r-1-e.padInfo.left;this.userCode=`
       const ivec3 pads = ivec3(${o}, ${l}, ${c});
 
       void main() {
@@ -2348,12 +2348,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function JW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:c,filterShape:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,u,i,1,o,c,!1,h),p=new XW(d);return n.runWebGLProgram(p,[a,s],"float32")}var QW={kernelName:Mh,backendName:"webgl",kernelFunc:JW};function eB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(c),d=R.computeConv2DInfo(i,s.shape,o,1,l,u,!1,h),p=new KW(d);return n.runWebGLProgram(p,[a,s],"float32")}var tB={kernelName:ps,backendName:"webgl",kernelFunc:eB};function nB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeConv3DInfo(a.shape,s.shape,i,l,o),u=new jW(c);return n.runWebGLProgram(u,[a,s],"float32")}var rB={kernelName:Au,backendName:"webgl",kernelFunc:nB};function aB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,c=R.computeConv3DInfo(a.shape,l,i,1,o),u=new ZW(c);return n.runWebGLProgram(u,[a,s],"float32")}var sB={kernelName:Fh,backendName:"webgl",kernelFunc:aB};function iB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,c=R.computeConv3DInfo(l,s.shape,o,1,i),u=new YW(c);return n.runWebGLProgram(u,[a,s],"float32")}var oB={kernelName:$h,backendName:"webgl",kernelFunc:iB},lB=qb+`
+    `}};function MV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:c,filterShape:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,u,i,1,o,c,!1,h),p=new TV(d);return n.runWebGLProgram(p,[a,s],"float32")}var FV={kernelName:Mh,backendName:"webgl",kernelFunc:MV};function DV(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(c),d=R.computeConv2DInfo(i,s.shape,o,1,l,u,!1,h),p=new EV(d);return n.runWebGLProgram(p,[a,s],"float32")}var $V={kernelName:ps,backendName:"webgl",kernelFunc:DV};function OV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeConv3DInfo(a.shape,s.shape,i,l,o),u=new kV(c);return n.runWebGLProgram(u,[a,s],"float32")}var zV={kernelName:Au,backendName:"webgl",kernelFunc:OV};function PV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,c=R.computeConv3DInfo(a.shape,l,i,1,o),u=new CV(c);return n.runWebGLProgram(u,[a,s],"float32")}var LV={kernelName:Fh,backendName:"webgl",kernelFunc:PV};function WV(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,c=R.computeConv3DInfo(l,s.shape,o,1,i),u=new RV(c);return n.runWebGLProgram(u,[a,s],"float32")}var BV={kernelName:Dh,backendName:"webgl",kernelFunc:WV},VV=S3+`
   return cos(x);
-`,uB=Xe({opSnippet:lB}),cB={kernelName:fs,backendName:"webgl",kernelFunc:uB},hB=`
+`,jV=Xe({opSnippet:VV}),UV={kernelName:fs,backendName:"webgl",kernelFunc:jV},HV=`
   float e2x = exp(-x);
   return (e2x + 1.0 / e2x) / 2.0;
-`,dB=Xe({opSnippet:hB}),pB={kernelName:oo,backendName:"webgl",kernelFunc:dB},fB=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[c]=t,[u,h]=n;this.outputShape=[c,u,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=u>1?[`${(i-1)/(u-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,w,b]=h>1?[`${(o-1)/(h-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
+`,GV=Xe({opSnippet:HV}),qV={kernelName:oo,backendName:"webgl",kernelFunc:GV},XV=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[c]=t,[u,h]=n;this.outputShape=[c,u,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=u>1?[`${(i-1)/(u-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,b,w]=h>1?[`${(o-1)/(h-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(${g});
       void main() {
@@ -2376,14 +2376,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         }
 
         float height_scale = ${A};
-        float width_scale = ${w};
+        float width_scale = ${b};
 
         float in_y = ${y};
         if( in_y < 0.0 || in_y > ${p} ) {
           setOutput(float(${a}));
           return;
         }
-        float in_x = ${b};
+        float in_x = ${w};
         if( in_x < 0.0 || in_x > ${f} ) {
           setOutput(float(${a}));
           return;
@@ -2414,21 +2414,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
           setOutput(newValue);
         }
       }
-    `}},mB=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:c}=r,u=new fB(a.shape,s.shape,o,l,c);return n.runWebGLProgram(u,[a,s,i],"float32")},AB={kernelName:lo,backendName:"webgl",kernelFunc:mB},A_=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${f_(r,"coords")})`,s=e[e.length-1],i="",o="";t?(i=n?`end != ${s-1}`:"end != 0",o=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${s}`:"end >= pow2",o=n?"end + pow2":"end - pow2"),this.userCode=`
+    `}},KV=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:c}=r,u=new XV(a.shape,s.shape,o,l,c);return n.runWebGLProgram(u,[a,s,i],"float32")},ZV={kernelName:lo,backendName:"webgl",kernelFunc:KV},Z3=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${X3(r,"coords")})`,s=e[e.length-1],i="",o="";t?(i=n?`end != ${s-1}`:"end != 0",o=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${s}`:"end >= pow2",o=n?"end + pow2":"end - pow2"),this.userCode=`
       uniform float index;
       void main() {
         ${ot(r)} coords = getOutputCoords();
-        int end = ${m_(r,"coords")};
+        int end = ${K3(r,"coords")};
         float val = ${a};
         int pow2 = int(pow(2.0, index));
         if (${i}) {
           int idx = ${o};
-          ${m_(r,"coords")} = idx;
-          val += getX(${f_(r,"coords")});
+          ${K3(r,"coords")} = idx;
+          val += getX(${X3(r,"coords")});
         }
         setOutput(val);
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.index==null&&(this.index=t.getUniformLocation(n,"index")),t.gl.uniform1f(this.index,e)}}};function f_(e,t){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 sum for rank ${e} is not yet supported`)}function m_(e,t){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative sum for rank ${e} is not yet supported`)}function yB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,c=R.getAxesPermutation([s],l),u=a;c!=null&&(u=In({inputs:{x:a},backend:n,attrs:{perm:c}}));let h=R.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=u.shape[h],p=On({inputs:{x:u},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new A_(u.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new A_(u.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(c!=null){let f=R.getUndoAxesPermutation(c),m=In({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(u),m}return p}var gB={kernelName:ms,backendName:"webgl",kernelFunc:yB};function xB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),c=n.readSync(s.dataId),u=Mb(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=Xz(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var wB={kernelName:Dh,backendName:"webgl",kernelFunc:xB},bB=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=n,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.index==null&&(this.index=t.getUniformLocation(n,"index")),t.gl.uniform1f(this.index,e)}}};function X3(e,t){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 sum for rank ${e} is not yet supported`)}function K3(e,t){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative sum for rank ${e} is not yet supported`)}function YV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,c=R.getAxesPermutation([s],l),u=a;c!=null&&(u=In({inputs:{x:a},backend:n,attrs:{perm:c}}));let h=R.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=u.shape[h],p=On({inputs:{x:u},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new Z3(u.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new Z3(u.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(c!=null){let f=R.getUndoAxesPermutation(c),m=In({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(u),m}return p}var JV={kernelName:ms,backendName:"webgl",kernelFunc:YV};function QV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),c=n.readSync(s.dataId),u=d3(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=TL(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var ej={kernelName:$h,backendName:"webgl",kernelFunc:QV},tj=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];
@@ -2447,7 +2447,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
       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 _B(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],c=i==="NHWC"?a.shape[2]:a.shape[3],u=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=c*s,p=u/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new bB(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var vB={kernelName:uo,backendName:"webgl",kernelFunc:_B},y_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,A="",y="";n&&(r?A=`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 nj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],c=i==="NHWC"?a.shape[2]:a.shape[3],u=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=c*s,p=u/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new tj(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var rj={kernelName:uo,backendName:"webgl",kernelFunc:nj},Y3=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,A="",y="";n&&(r?A=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:a?A=`float activation(float a) {
@@ -2503,24 +2503,24 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         ${y}
         setOutput(result);
       }
-    `}},g_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let b=0;b<p;b++)for(let _=0;_<f;_++)A+=`
-          vec4 xTexelR${b}C${_*2} = vec4(0.);
-          vec4 wR${b}C${_} = vec4(0.);
-          vec4 xR${b}C${_} = vec4(0.);`;for(let b=0;b<p;b++)for(let _=0;_<m;_++){let x=_*2;if(A+=`
-          xR = xRCorner + ${b*h};
+    `}},J3=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let w=0;w<p;w++)for(let _=0;_<f;_++)A+=`
+          vec4 xTexelR${w}C${_*2} = vec4(0.);
+          vec4 wR${w}C${_} = vec4(0.);
+          vec4 xR${w}C${_} = vec4(0.);`;for(let w=0;w<p;w++)for(let _=0;_<m;_++){let x=_*2;if(A+=`
+          xR = xRCorner + ${w*h};
           xC = xCCorner + ${x*d};
         `,u===1){if(x<f&&(l%2==1?A+=`
                 xCOffset = xC + 1;
                 if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) {
-                  xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1);
+                  xTexelR${w}C${x} = getX(batch, xR, xCOffset, d1);
 
                   // Need to manually clear unused channels in case
                   // we're reading from recycled texture.
                   if(xCOffset + 1 >= ${i}) {
-                    xTexelR${b}C${x}.zw = vec2(0.);
+                    xTexelR${w}C${x}.zw = vec2(0.);
                   }
                 } else {
-                  xTexelR${b}C${x} = vec4(0.);
+                  xTexelR${w}C${x} = vec4(0.);
                 }
 
                 xCOffset = xC + 1 - 2;
@@ -2533,96 +2533,96 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
                     previous.zw = vec2(0.);
                   }
 
-                  xR${b}C${x} = vec4(previous.zw, xTexelR${b}C${x}.xy);
+                  xR${w}C${x} = vec4(previous.zw, xTexelR${w}C${x}.xy);
                 } else {
-                  xR${b}C${x} = vec4(0, 0, xTexelR${b}C${x}.xy);
+                  xR${w}C${x} = vec4(0, 0, xTexelR${w}C${x}.xy);
                 }
               `:A+=`
                 if(xR >= 0 && xR < ${s} && xC >= 0 && xC < ${i}) {
-                  xTexelR${b}C${x} = getX(batch, xR, xC, d1);
+                  xTexelR${w}C${x} = getX(batch, xR, xC, d1);
                 } else {
-                  xTexelR${b}C${x} = vec4(0.);
+                  xTexelR${w}C${x} = vec4(0.);
                 }
 
-                xR${b}C${x} = xTexelR${b}C${x};
+                xR${w}C${x} = xTexelR${w}C${x};
               `,x+1<f)){let N=l%2==0?v.nearestLargerEven(d):d;d%2==0&&l%2==1||d%2!=0&&l%2!=1?(A+=`
                   xCOffset = xC + ${l%2} + ${N};
 
                   if(xR >= 0 && xR < ${s} &&
                     xCOffset >= 0 && xCOffset < ${i}) {
-                    xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1);
+                    xTexelR${w}C${x+2} = getX(batch, xR, xCOffset, d1);
                   }
                 `,d>1&&(A+=`
                     xCOffset -= 2;
                     if(xR >= 0 && xR < ${s} &&
                       xCOffset >= 0 && xCOffset < ${i}) {
-                      xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1);
+                      xTexelR${w}C${x} = getX(batch, xR, xCOffset, d1);
                     } else {
-                      xTexelR${b}C${x} = vec4(0.);
+                      xTexelR${w}C${x} = vec4(0.);
                     }
                   `),A+=`
-                  xR${b}C${x+1} = vec4(
-                    xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.xy);
+                  xR${w}C${x+1} = vec4(
+                    xTexelR${w}C${x}.zw, xTexelR${w}C${x+2}.xy);
                 `):A+=`
                   xCOffset = xC + ${N};
 
                   if(xR >= 0 && xR < ${s} &&
                     xCOffset >= 0 && xCOffset < ${i}) {
-                    xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1);
+                    xTexelR${w}C${x+2} = getX(batch, xR, xCOffset, d1);
                   }
 
-                  xR${b}C${x+1} = xTexelR${b}C${x+2};
+                  xR${w}C${x+1} = xTexelR${w}C${x+2};
                 `}}else x<f&&(A+=`
               if(xR >= 0 && xR < ${s}) {
             `,l%2==1?(A+=`
                 xCOffset = xC + 1 - ${u};
                 if(xCOffset >= 0 && xCOffset < ${i}) {
-                  xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1);
+                  xTexelR${w}C${x} = getX(batch, xR, xCOffset, d1);
                 } else {
-                  xTexelR${b}C${x} = vec4(0.);
+                  xTexelR${w}C${x} = vec4(0.);
                 }
 
                 if(xC + 1 >= 0 && xC + 1 < ${i}) {
-                  xTexelR${b}C${x+2} = getX(batch, xR, xC + 1, d1);
+                  xTexelR${w}C${x+2} = getX(batch, xR, xC + 1, d1);
                 } else {
-                  xTexelR${b}C${x+2} = vec4(0.);
+                  xTexelR${w}C${x+2} = vec4(0.);
                 }
 
-                xR${b}C${x} = vec4(
-                  xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.zw);
+                xR${w}C${x} = vec4(
+                  xTexelR${w}C${x}.zw, xTexelR${w}C${x+2}.zw);
               `,x+1<f&&(A+=`
                   vec4 final = vec4(0.);
                   xCOffset = xC + 1 + ${u};
                   if(xCOffset >= 0 && xCOffset < ${i}) {
                     final = getX(batch, xR, xCOffset, d1);
                   }
-                  xR${b}C${x+1} = vec4(xTexelR${b}C${x+2}.xy, final.xy);
+                  xR${w}C${x+1} = vec4(xTexelR${w}C${x+2}.xy, final.xy);
                 `)):(A+=`
                 if(xC >= 0 && xC < ${i}) {
-                  xTexelR${b}C${x} = getX(batch, xR, xC, d1);
+                  xTexelR${w}C${x} = getX(batch, xR, xC, d1);
                 } else {
-                  xTexelR${b}C${x} = vec4(0.);
+                  xTexelR${w}C${x} = vec4(0.);
                 }
 
                 xCOffset = xC + ${u};
                 if(xCOffset >= 0 && xCOffset < ${i}) {
-                  xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1);
+                  xTexelR${w}C${x+2} = getX(batch, xR, xCOffset, d1);
                 } else {
-                  xTexelR${b}C${x+2} = vec4(0.);
+                  xTexelR${w}C${x+2} = vec4(0.);
                 }
 
-                xR${b}C${x} = vec4(
-                  xTexelR${b}C${x}.xy, xTexelR${b}C${x+2}.xy);
+                xR${w}C${x} = vec4(
+                  xTexelR${w}C${x}.xy, xTexelR${w}C${x+2}.xy);
               `,x+1<f&&(A+=`
-                  xR${b}C${x+1} = vec4(
-                    xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.zw);
+                  xR${w}C${x+1} = vec4(
+                    xTexelR${w}C${x}.zw, xTexelR${w}C${x+2}.zw);
                 `)),A+="}");x<f&&(A+=`
-            vec4 wTexelR${b}C${x} = getW(${b}, ${x}, d1, q);
-            wR${b}C${x} = vec4(wTexelR${b}C${x}.xz, wTexelR${b}C${x}.xz);
+            vec4 wTexelR${w}C${x} = getW(${w}, ${x}, d1, q);
+            wR${w}C${x} = vec4(wTexelR${w}C${x}.xz, wTexelR${w}C${x}.xz);
           `,x+1<f&&(A+=`
-              vec4 wTexelR${b}C${x+1} = getW(${b}, ${x+1}, d1, q);
-              wR${b}C${x+1} =
-                vec4(wTexelR${b}C${x+1}.xz, wTexelR${b}C${x+1}.xz);`))}for(let b=0;b<p;b++)for(let _=0;_<f;_++)A+=`dotProd += xR${b}C${_} * wR${b}C${_};`;let y="",g="";n&&(r?y=`vec4 activation(vec4 a) {
+              vec4 wTexelR${w}C${x+1} = getW(${w}, ${x+1}, d1, q);
+              wR${w}C${x+1} =
+                vec4(wTexelR${w}C${x+1}.xz, wTexelR${w}C${x+1}.xz);`))}for(let w=0;w<p;w++)for(let _=0;_<f;_++)A+=`dotProd += xR${w}C${_} * wR${w}C${_};`;let y="",g="";n&&(r?y=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:a?y=`vec4 activation(vec4 a) {
@@ -2630,7 +2630,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
           ${n}
         }`:y=`vec4 activation(vec4 x) {
           ${n}
-        }`,g="result = activation(result);");let w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
+        }`,g="result = activation(result);");let b=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
       ${y}
 
       const ivec2 strides = ivec2(${c}, ${u});
@@ -2652,11 +2652,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         ${A}
 
         vec4 result = dotProd;
-        ${w}
+        ${b}
         ${g}
         setOutput(result);
       }
-    `}};function kB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:c}=r,u=l;u==null&&(u=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let h=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!0),d;return J().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new g_(h):d=new y_(h),n.runWebGLProgram(d,[a,s],"float32")}var IB={kernelName:As,backendName:"webgl",kernelFunc:kB},NB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
+    `}};function aj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:c}=r,u=l;u==null&&(u=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let h=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!0),d;return J().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new J3(h):d=new Y3(h),n.runWebGLProgram(d,[a,s],"float32")}var sj={kernelName:As,backendName:"webgl",kernelFunc:aj},ij=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2691,7 +2691,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},SB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
+    `}},oj=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
       const ivec2 pads = ivec2(${s}, ${i});
 
       void main() {
@@ -2736,13 +2736,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function TB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,filterShape:u}=r,h=R.computeConv2DInfo(a.shape,u,i,o,l,c,!0),d=new NB(h);return n.runWebGLProgram(d,[a,s],"float32")}var EB={kernelName:Oh,backendName:"webgl",kernelFunc:TB};function CB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r,h=R.computeConv2DInfo(u,s.shape,i,o,l,c,!0),d=new SB(h);return n.runWebGLProgram(d,[a,s],"float32")}var RB={kernelName:zh,backendName:"webgl",kernelFunc:CB},MB=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
+    `}};function lj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,filterShape:u}=r,h=R.computeConv2DInfo(a.shape,u,i,o,l,c,!0),d=new ij(h);return n.runWebGLProgram(d,[a,s],"float32")}var uj={kernelName:Oh,backendName:"webgl",kernelFunc:lj};function cj(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r,h=R.computeConv2DInfo(u,s.shape,i,o,l,c,!0),d=new oj(h);return n.runWebGLProgram(d,[a,s],"float32")}var hj={kernelName:zh,backendName:"webgl",kernelFunc:cj},dj=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 FB(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=xe({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new MB(s),l=n.runWebGLProgram(o,[i],i.dtype),c=xe({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),c}var $B={kernelName:Ph,backendName:"webgl",kernelFunc:FB},DB=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:c}=e,{top:u,left:h}=r;this.userCode=`
+    `}};function pj(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=xe({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new dj(s),l=n.runWebGLProgram(o,[i],i.dtype),c=xe({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),c}var fj={kernelName:Ph,backendName:"webgl",kernelFunc:pj},mj=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:c}=e,{top:u,left:h}=r;this.userCode=`
       const ivec2 strides = ivec2(${a}, ${s});
       const ivec2 pads = ivec2(${u}, ${h});
       const float neg_infinity = -3.4e38;
@@ -2780,7 +2780,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         float result = curVal;
         setOutput(result);
       }
-    `}};function OB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),u,h=new DB(c);u=n.runWebGLProgram(h,[a,s],"float32");let d=xe({inputs:{x:u},backend:n,attrs:{shape:c.outShape}});return n.disposeIntermediateTensorInfo(u),d}var zB={kernelName:yu,backendName:"webgl",kernelFunc:OB},PB="return (x >= 0.0) ? x : (exp(x) - 1.0);",LB=`
+    `}};function Aj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),u,h=new mj(c);u=n.runWebGLProgram(h,[a,s],"float32");let d=xe({inputs:{x:u},backend:n,attrs:{shape:c.outShape}});return n.disposeIntermediateTensorInfo(u),d}var yj={kernelName:yu,backendName:"webgl",kernelFunc:Aj},gj="return (x >= 0.0) ? x : (exp(x) - 1.0);",xj=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -2789,12 +2789,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,WB=Xe({opSnippet:PB,packedOpSnippet:LB}),BB={kernelName:co,backendName:"webgl",kernelFunc:WB},VB="return (b >= 1.0) ? a : a * (b + 1.0);",UB=`
+`,bj=Xe({opSnippet:gj,packedOpSnippet:xj}),wj={kernelName:co,backendName:"webgl",kernelFunc:bj},_j="return (b >= 1.0) ? a : a * (b + 1.0);",vj=`
   vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
   return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
-`,jB=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new pc(UB,r.shape,a.shape):new Ml(VB,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},HB={kernelName:Bh,backendName:"webgl",kernelFunc:jB},GB=`
+`,kj=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new pc(vj,r.shape,a.shape):new Ml(_j,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},Ij={kernelName:Bh,backendName:"webgl",kernelFunc:kj},Nj=`
   return vec4(equal(a, b));
-`,qB="return float(a == b);",XB=tn({opSnippet:qB,packedOpSnippet:GB,dtype:"bool"}),KB={kernelName:po,backendName:"webgl",kernelFunc:XB},ZB=`
+`,Sj="return float(a == b);",Tj=tn({opSnippet:Sj,packedOpSnippet:Nj,dtype:"bool"}),Ej={kernelName:po,backendName:"webgl",kernelFunc:Tj},Cj=`
   // Error function is calculated approximately with elementary function.
   // See "Handbook of Mathematical Functions with Formulas,
   // Graphs, and Mathematical Tables", Abramowitz and Stegun.
@@ -2809,7 +2809,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
   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));
-`,YB=Xe({opSnippet:ZB}),JB={kernelName:ho,backendName:"webgl",kernelFunc:YB},x_="return exp(x);",w_=Xe({opSnippet:x_,packedOpSnippet:x_,cpuKernelImpl:Yz}),QB={kernelName:gs,backendName:"webgl",kernelFunc:w_};function hA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),xe({inputs:{x:s},backend:r,attrs:{shape:o}})}var eV={kernelName:fo,backendName:"webgl",kernelFunc:hA},b_="return exp(x) - 1.0;",tV=Xe({opSnippet:b_,packedOpSnippet:b_,cpuKernelImpl:Jz}),nV={kernelName:mo,backendName:"webgl",kernelFunc:tV},__=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${r}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
+`,Rj=Xe({opSnippet:Cj}),Mj={kernelName:ho,backendName:"webgl",kernelFunc:Rj},Q3="return exp(x);",e7=Xe({opSnippet:Q3,packedOpSnippet:Q3,cpuKernelImpl:RL}),Fj={kernelName:gs,backendName:"webgl",kernelFunc:e7};function AA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),xe({inputs:{x:s},backend:r,attrs:{shape:o}})}var Dj={kernelName:fo,backendName:"webgl",kernelFunc:AA},t7="return exp(x) - 1.0;",$j=Xe({opSnippet:t7,packedOpSnippet:t7,cpuKernelImpl:ML}),Oj={kernelName:mo,backendName:"webgl",kernelFunc:$j},n7=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${r}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
       const float exponentMultiplier = ${a};
 
       float unaryOpComplex(float real, float expR, float imag, float expI) {
@@ -2842,13 +2842,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         ivec2 coords = getOutputCoords();
         setOutput(mulMatDFT(coords[0], coords[1]));
       }
-    `}};function v_(e,t,n){let r=n.texData.get(e.dataId),a=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=xe({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,c=new __("real",l,t),u=new __("imag",l,t),h=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:l},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Wa({inputs:{real:d,imag:p},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p);let m=xe({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),m}function rV(e){let{inputs:t,backend:n}=e,{input:r}=t;return v_(r,!1,n)}var aV={kernelName:Vh,backendName:"webgl",kernelFunc:rV},sV=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.outputShape=e,this.userCode=`
+    `}};function r7(e,t,n){let r=n.texData.get(e.dataId),a=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=xe({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,c=new n7("real",l,t),u=new n7("imag",l,t),h=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:l},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Wa({inputs:{real:d,imag:p},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p);let m=xe({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),m}function zj(e){let{inputs:t,backend:n}=e,{input:r}=t;return r7(r,!1,n)}var Pj={kernelName:Vh,backendName:"webgl",kernelFunc:zj},Lj=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.outputShape=e,this.userCode=`
       uniform float value;
       void main() {
         // Input can be obtained from uniform value.
         setOutput(value);
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function dA(e){let{backend:t,attrs:n}=e,{shape:r,value:a}=n,{dtype:s}=n;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(r));return i.fill(a),t.makeTensorInfo(r,s,i)}else{let i=new sV(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var iV={kernelName:gu,backendName:"webgl",kernelFunc:dA},oV=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function yA(e){let{backend:t,attrs:n}=e,{shape:r,value:a}=n,{dtype:s}=n;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(r));return i.fill(a),t.makeTensorInfo(r,s,i)}else{let i=new Lj(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var Wj={kernelName:gu,backendName:"webgl",kernelFunc:yA},Bj=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];
@@ -2862,7 +2862,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
           }
           setOutput(outputValue);
         }
-    `}},lV={kernelName:Ao,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new oV(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},k_="return floor(x);",uV=Xe({opSnippet:k_,packedOpSnippet:k_,cpuKernelImpl:Qz}),cV={kernelName:xs,backendName:"webgl",kernelFunc:uV},hV=`
+    `}},Vj={kernelName:Ao,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new Bj(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},a7="return floor(x);",jj=Xe({opSnippet:a7,packedOpSnippet:a7,cpuKernelImpl:FL}),Uj={kernelName:xs,backendName:"webgl",kernelFunc:jj},Hj=`
   float s = sign(a) * sign(b);
   int ia = round(a);
   int ib = round(b);
@@ -2872,7 +2872,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
   } else {
     return NAN;
   }
-`,dV=`
+`,Gj=`
   ivec4 ia = round(a);
   ivec4 ib = round(b);
   bvec4 cond = notEqual(ib, ivec4(0));
@@ -2893,7 +2893,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
     result[3] = idiv(ia[3], ib[3], s[3]);
   }
   return vec4(result);
-`,pV=tn({opSnippet:hV,packedOpSnippet:dV,dtype:"int32"}),fV={kernelName:ws,backendName:"webgl",kernelFunc:pV},mV=class{constructor(e){this.variableNames=["A"];let t=hn(),[n,r]=e;this.outputShape=e,this.userCode=`
+`,qj=tn({opSnippet:Hj,packedOpSnippet:Gj,dtype:"int32"}),Xj={kernelName:bs,backendName:"webgl",kernelFunc:qj},Kj=class{constructor(e){this.variableNames=["A"];let t=hn(),[n,r]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -2915,7 +2915,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
 
         setOutput(floor(value * 255.0 + 0.5));
       }
-    `}},AV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=hn(),[n,r]=e;this.outputShape=e,this.userCode=`
+    `}},Zj=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=hn(),[n,r]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -2949,7 +2949,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
 
         ${t.output} = result;
       }
-    `}},gV={kernelName:rd,backendName:"webgl",kernelFunc:yV},$l;function yV(e){let{inputs:t,backend:n,attrs:r}=e,{pixels:a}=t,{numChannels:s}=r,i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,[l,c]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],u=[c,l],h=[c,l,s];(o||i)&&($l==null&&($l=document.createElement("canvas").getContext("2d")),$l.canvas.width=l,$l.canvas.height=c,$l.drawImage(a,0,0,l,c),a=$l.canvas);let d=n.makeTensorInfo(u,"int32");n.texData.get(d.dataId).usage=Xn.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),a);let p=J().getBool("WEBGL_PACK")?new AV(h):new mV(h),f=n.runWebGLProgram(p,[d],"int32");return n.disposeData(d.dataId),f}function xV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=R.convertConv2DDataFormat(u),A=R.computeConv2DInfo(a.shape,s.shape,l,h,c,d,!1,m),y,g=[];if(A.filterHeight===1&&A.filterWidth===1&&A.dilationHeight===1&&A.dilationWidth===1&&A.strideHeight===1&&A.strideWidth===1&&(A.padInfo.type==="SAME"||A.padInfo.type==="VALID"))y=d_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=p_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let b=i!=null,_=o!=null,x=p==="leakyrelu",N=p?mp(p,!1):null,T=new h_(A,b,N,_,x),E=[a,s];if(i&&E.push(i),o&&E.push(o),x){let F=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));E.push(F),g.push(F)}y=n.runWebGLProgram(T,E,"float32")}let w=xe({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(b=>n.disposeIntermediateTensorInfo(b)),w}var wV={kernelName:Qs,backendName:"webgl",kernelFunc:xV};function bV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dilations:u,dimRoundingMode:h,activation:d,leakyreluAlpha:p}=r,f=[],m=u;m==null&&(m=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let A=R.computeConv2DInfo(a.shape,s.shape,l,m,c,h,!0),y=J().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,g=d?mp(d,y):null,w=[a,s],b=i!=null,_=o!=null,x=d==="leakyrelu";if(b&&w.push(i),_&&w.push(o),x){let E=n.makeTensorInfo([],"float32",v.createScalarValue(p,"float32"));w.push(E),f.push(E)}let N;y?N=new g_(A,b,g,_,x):N=new y_(A,b,g,_,x);let T=n.runWebGLProgram(N,w,"float32");return f.forEach(E=>n.disposeIntermediateTensorInfo(E)),T}var _V={kernelName:ei,backendName:"webgl",kernelFunc:bV},vV=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=ot(t.length),a=ot(n.length),s=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
+    `}},Jj={kernelName:rd,backendName:"webgl",kernelFunc:Yj},Dl;function Yj(e){let{inputs:t,backend:n,attrs:r}=e,{pixels:a}=t,{numChannels:s}=r,i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,[l,c]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],u=[c,l],h=[c,l,s];(o||i)&&(Dl==null&&(Dl=document.createElement("canvas").getContext("2d")),Dl.canvas.width=l,Dl.canvas.height=c,Dl.drawImage(a,0,0,l,c),a=Dl.canvas);let d=n.makeTensorInfo(u,"int32");n.texData.get(d.dataId).usage=Xn.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),a);let p=J().getBool("WEBGL_PACK")?new Zj(h):new Kj(h),f=n.runWebGLProgram(p,[d],"int32");return n.disposeData(d.dataId),f}function Qj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=R.convertConv2DDataFormat(u),A=R.computeConv2DInfo(a.shape,s.shape,l,h,c,d,!1,m),y,g=[];if(A.filterHeight===1&&A.filterWidth===1&&A.dilationHeight===1&&A.dilationWidth===1&&A.strideHeight===1&&A.strideWidth===1&&(A.padInfo.type==="SAME"||A.padInfo.type==="VALID"))y=G3({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=q3({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let w=i!=null,_=o!=null,x=p==="leakyrelu",N=p?mp(p,!1):null,T=new H3(A,w,N,_,x),E=[a,s];if(i&&E.push(i),o&&E.push(o),x){let F=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));E.push(F),g.push(F)}y=n.runWebGLProgram(T,E,"float32")}let b=xe({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(w=>n.disposeIntermediateTensorInfo(w)),b}var eU={kernelName:Qs,backendName:"webgl",kernelFunc:Qj};function tU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dilations:u,dimRoundingMode:h,activation:d,leakyreluAlpha:p}=r,f=[],m=u;m==null&&(m=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let A=R.computeConv2DInfo(a.shape,s.shape,l,m,c,h,!0),y=J().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,g=d?mp(d,y):null,b=[a,s],w=i!=null,_=o!=null,x=d==="leakyrelu";if(w&&b.push(i),_&&b.push(o),x){let E=n.makeTensorInfo([],"float32",v.createScalarValue(p,"float32"));b.push(E),f.push(E)}let N;y?N=new J3(A,w,g,_,x):N=new Y3(A,w,g,_,x);let T=n.runWebGLProgram(N,b,"float32");return f.forEach(E=>n.disposeIntermediateTensorInfo(E)),T}var nU={kernelName:ei,backendName:"webgl",kernelFunc:tU},rU=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=ot(t.length),a=ot(n.length),s=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
         ${r} strides = ${r}(${this.strides});
          void main() {
           ${a} coords = getOutputCoords();
@@ -2960,21 +2960,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
           }
           setOutput(getX(flattenIndex, coords[1]));
         }
-      `}};function kV(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=a.shape,i=s[s.length-1],[o,l,c,u]=R.prepareAndValidate(r,a),h=xe({inputs:{x:a},backend:n,attrs:{shape:[l,i]}}),d=xe({inputs:{x:r},backend:n,attrs:{shape:[v.sizeFromShape(r.shape)/c,c]}}),p=new vV(i,u,[l,c]),f=n.runWebGLProgram(p,[d,h],d.dtype),m=xe({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}var IV={kernelName:go,backendName:"webgl",kernelFunc:kV},SV=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=ot(this.rank),r=NV(e,2);this.userCode=`
+      `}};function aU(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=a.shape,i=s[s.length-1],[o,l,c,u]=R.prepareAndValidate(r,a),h=xe({inputs:{x:a},backend:n,attrs:{shape:[l,i]}}),d=xe({inputs:{x:r},backend:n,attrs:{shape:[v.sizeFromShape(r.shape)/c,c]}}),p=new rU(i,u,[l,c]),f=n.runWebGLProgram(p,[d,h],d.dtype),m=xe({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}var sU={kernelName:go,backendName:"webgl",kernelFunc:aU},oU=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=ot(this.rank),r=iU(e,2);this.userCode=`
       void main() {
         ${n} resRC = getOutputCoords();
         setOutput(getA(${r}));
       }
-    `}};function NV(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let a=0;a<e.length;a++)a===2?r.push("int(getIndices(resRC.x, resRC.z))"):r.push(`${n[a]}`);return r.join()}function TV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],c=R.segment_util.collectGatherOpShapeInfo(a,s,l,o),u=v.sizeFromShape(s.shape),h=[],d=xe({inputs:{x:a},backend:n,attrs:{shape:[c.batchSize,c.outerSize,c.dimSize,c.sliceSize]}}),p=xe({inputs:{x:s},backend:n,attrs:{shape:[c.batchSize,u/c.batchSize]}});h.push(d),h.push(p);let f=[c.batchSize,c.outerSize,u/c.batchSize,c.sliceSize];if(n.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let g=n.bufferSync(p),w=n.bufferSync(d),b=eP(w,g,f);return h.forEach(_=>n.disposeIntermediateTensorInfo(_)),n.makeTensorInfo(c.outputShape,b.dtype,b.values)}let m=new SV(d.shape,f),A=n.runWebGLProgram(m,[d,p],d.dtype);h.push(A);let y=xe({inputs:{x:A},backend:n,attrs:{shape:c.outputShape}});return h.forEach(g=>n.disposeIntermediateTensorInfo(g)),y}var EV={kernelName:yo,backendName:"webgl",kernelFunc:TV},CV="return float(a > b);",RV=`
+    `}};function iU(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let a=0;a<e.length;a++)a===2?r.push("int(getIndices(resRC.x, resRC.z))"):r.push(`${n[a]}`);return r.join()}function lU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],c=R.segment_util.collectGatherOpShapeInfo(a,s,l,o),u=v.sizeFromShape(s.shape),h=[],d=xe({inputs:{x:a},backend:n,attrs:{shape:[c.batchSize,c.outerSize,c.dimSize,c.sliceSize]}}),p=xe({inputs:{x:s},backend:n,attrs:{shape:[c.batchSize,u/c.batchSize]}});h.push(d),h.push(p);let f=[c.batchSize,c.outerSize,u/c.batchSize,c.sliceSize];if(n.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let g=n.bufferSync(p),b=n.bufferSync(d),w=DL(b,g,f);return h.forEach(_=>n.disposeIntermediateTensorInfo(_)),n.makeTensorInfo(c.outputShape,w.dtype,w.values)}let m=new oU(d.shape,f),A=n.runWebGLProgram(m,[d,p],d.dtype);h.push(A);let y=xe({inputs:{x:A},backend:n,attrs:{shape:c.outputShape}});return h.forEach(g=>n.disposeIntermediateTensorInfo(g)),y}var uU={kernelName:yo,backendName:"webgl",kernelFunc:lU},cU="return float(a > b);",hU=`
   return vec4(greaterThan(a, b));
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+`,dU=tn({opSnippet:cU,packedOpSnippet:hU,cpuKernelImpl:$L,dtype:"bool"}),pU={kernelName:xo,backendName:"webgl",kernelFunc:dU},fU="return float(a >= b);",mU=`
   return vec4(greaterThanEqual(a, b));
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+`,AU=tn({opSnippet:fU,packedOpSnippet:mU,dtype:"bool"}),yU={kernelName:_s,backendName:"webgl",kernelFunc:AU};function gU(e){let{inputs:t,backend:n}=e,{input:r}=t;return r7(r,!0,n)}var xU={kernelName:jh,backendName:"webgl",kernelFunc:gU},bU="return float(!isnan(x) && !isinf(x));",wU=Xe({opSnippet:bU,dtype:"bool"}),_U={kernelName:bo,backendName:"webgl",kernelFunc:wU},vU="return float(isinf(x));",kU=Xe({opSnippet:vU,dtype:"bool"}),IU={kernelName:wo,backendName:"webgl",kernelFunc:kU},NU="return float(isnan(x));",SU=Xe({opSnippet:NU,dtype:"bool"}),TU={kernelName:_o,backendName:"webgl",kernelFunc:SU},EU="return float(a < b);",CU=`
   return vec4(lessThan(a, b));
-`,YV=tn({opSnippet:KV,packedOpSnippet:ZV,cpuKernelImpl:nP,dtype:"bool"}),JV={kernelName:vo,backendName:"webgl",kernelFunc:YV},QV="return float(a <= b);",eU=`
+`,RU=tn({opSnippet:EU,packedOpSnippet:CU,cpuKernelImpl:OL,dtype:"bool"}),MU={kernelName:vo,backendName:"webgl",kernelFunc:RU},FU="return float(a <= b);",DU=`
   return vec4(lessThanEqual(a, b));
-`,tU=tn({opSnippet:QV,packedOpSnippet:eU,dtype:"bool"}),nU={kernelName:ko,backendName:"webgl",kernelFunc:tU};function rU(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=rP(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var aU={kernelName:Hh,backendName:"webgl",kernelFunc:rU},sU=`if (x < 0.0) return NAN;
-  return log(x);`,iU=`
+`,$U=tn({opSnippet:FU,packedOpSnippet:DU,dtype:"bool"}),OU={kernelName:ko,backendName:"webgl",kernelFunc:$U};function zU(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=zL(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var PU={kernelName:Hh,backendName:"webgl",kernelFunc:zU},LU=`if (x < 0.0) return NAN;
+  return log(x);`,WU=`
   vec4 result = log(x);
   vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
   result.r = isNaN.r == 1.0 ? NAN : result.r;
@@ -2983,16 +2983,16 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
   result.a = isNaN.a == 1.0 ? NAN : result.a;
 
   return result;
-`,oU=Xe({opSnippet:sU,packedOpSnippet:iU,cpuKernelImpl:aP}),lU={kernelName:Is,backendName:"webgl",kernelFunc:oU},uU="return log(1.0 + x);",cU=Xe({opSnippet:uU}),hU={kernelName:Io,backendName:"webgl",kernelFunc:cU},dU="return float(a >= 1.0 && b >= 1.0);",pU=`
+`,BU=Xe({opSnippet:LU,packedOpSnippet:WU,cpuKernelImpl:PL}),VU={kernelName:Is,backendName:"webgl",kernelFunc:BU},jU="return log(1.0 + x);",UU=Xe({opSnippet:jU}),HU={kernelName:Io,backendName:"webgl",kernelFunc:UU},GU="return float(a >= 1.0 && b >= 1.0);",qU=`
   return vec4(
     vec4(greaterThanEqual(a, vec4(1.0))) *
     vec4(greaterThanEqual(b, vec4(1.0))));
-`,fU=tn({opSnippet:dU,packedOpSnippet:pU,dtype:"bool"}),mU={kernelName:No,backendName:"webgl",kernelFunc:fU},AU="return float(!(x >= 1.0));",yU=Xe({opSnippet:AU}),gU={kernelName:xu,backendName:"webgl",kernelFunc:yU},xU="return float(a >= 1.0 || b >= 1.0);",wU=`
+`,XU=tn({opSnippet:GU,packedOpSnippet:qU,dtype:"bool"}),KU={kernelName:No,backendName:"webgl",kernelFunc:XU},ZU="return float(!(x >= 1.0));",YU=Xe({opSnippet:ZU}),JU={kernelName:xu,backendName:"webgl",kernelFunc:YU},QU="return float(a >= 1.0 || b >= 1.0);",eH=`
   return min(
     vec4(greaterThanEqual(a, vec4(1.0))) +
     vec4(greaterThanEqual(b, vec4(1.0))),
     vec4(1.0));
-`,bU=tn({opSnippet:xU,packedOpSnippet:wU,dtype:"bool"}),_U={kernelName:wu,backendName:"webgl",kernelFunc:bU},vU=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
+`,tH=tn({opSnippet:QU,packedOpSnippet:eH,dtype:"bool"}),nH={kernelName:bu,backendName:"webgl",kernelFunc:tH},rH=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3011,7 +3011,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         float val = x * ${o};
         setOutput(val);
       }
-    `}},kU=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
+    `}},aH=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords.x;
@@ -3073,7 +3073,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         vec4 result = xAtOutputCoords * ${o};
         setOutput(result);
       }
-    `}},IU=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,c=J().getBool("WEBGL_PACK_NORMALIZATION")?new kU(a.shape,s,i,o,l):new vU(a.shape,s,i,o,l);return n.runWebGLProgram(c,[a],a.dtype)},NU={kernelName:bu,backendName:"webgl",kernelFunc:IU},SU=class{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode=`
+    `}},sH=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,c=J().getBool("WEBGL_PACK_NORMALIZATION")?new aH(a.shape,s,i,o,l):new rH(a.shape,s,i,o,l);return n.runWebGLProgram(c,[a],a.dtype)},iH={kernelName:wu,backendName:"webgl",kernelFunc:sH},oH=class{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3128,14 +3128,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
       }
       setOutput(result);
       }
-    `}},TU=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:c,beta:u}=r,h=new SU(a.shape,o,l,c,u);return n.runWebGLProgram(h,[a,s,i],a.dtype)},EU={kernelName:Gh,backendName:"webgl",kernelFunc:TU};function CU(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=xe({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,e.dtype,"max",r),l=xe({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function I_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,w=new Array(o);for(let x=0;x<w.length;x++)w[x]=a.shape[u[x]];let b=sA(g,a.shape,a.dtype,u,w);p=n.makeTensorInfo(w,a.dtype);let _=n.texData.get(p.dataId);_.values=b}else p=Ap(a,u,n);c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("max",c,o);let[f,m]=R.computeOutAndReduceShapes(p.shape,c),A=f;i&&(A=R.expandShapeToKeepDim(f,l));let y;if(d){let g=n.texData.get(p.dataId).values,w=sP(g,v.sizeFromShape(m),A,a.dtype);y=n.makeTensorInfo(A,a.dtype);let b=n.texData.get(y.dataId);b.values=w}else y=CU(p,m,A,n);return h&&n.disposeIntermediateTensorInfo(p),y}var RU={kernelName:Ns,backendName:"webgl",kernelFunc:I_},MU=Vb+`
+    `}},lH=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:c,beta:u}=r,h=new oH(a.shape,o,l,c,u);return n.runWebGLProgram(h,[a,s,i],a.dtype)},uH={kernelName:Gh,backendName:"webgl",kernelFunc:lH};function cH(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=xe({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,e.dtype,"max",r),l=xe({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function s7(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,b=new Array(o);for(let x=0;x<b.length;x++)b[x]=a.shape[u[x]];let w=cA(g,a.shape,a.dtype,u,b);p=n.makeTensorInfo(b,a.dtype);let _=n.texData.get(p.dataId);_.values=w}else p=Ap(a,u,n);c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("max",c,o);let[f,m]=R.computeOutAndReduceShapes(p.shape,c),A=f;i&&(A=R.expandShapeToKeepDim(f,l));let y;if(d){let g=n.texData.get(p.dataId).values,b=LL(g,v.sizeFromShape(m),A,a.dtype);y=n.makeTensorInfo(A,a.dtype);let w=n.texData.get(y.dataId);w.values=b}else y=cH(p,m,A,n);return h&&n.disposeIntermediateTensorInfo(p),y}var hH={kernelName:Ns,backendName:"webgl",kernelFunc:s7},dH=_3+`
   return max(a, b);
-`,FU=`
+`,pH=`
   vec4 result = vec4(max(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
   `+fp+`
   return result;
-`,$U=tn({opSnippet:MU,packedOpSnippet:FU,cpuKernelImpl:iP}),DU={kernelName:Ss,backendName:"webgl",kernelFunc:$U};function OU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return On({inputs:{x:a},backend:n});let h=new fc(u,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var zU={kernelName:Ts,backendName:"webgl",kernelFunc:OU};function PU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,c,l),d=new lA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var LU={kernelName:_u,backendName:"webgl",kernelFunc:PU},WU=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
+`,fH=tn({opSnippet:dH,packedOpSnippet:pH,cpuKernelImpl:WL}),mH={kernelName:Ss,backendName:"webgl",kernelFunc:fH};function AH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return On({inputs:{x:a},backend:n});let h=new fc(u,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var yH={kernelName:Ts,backendName:"webgl",kernelFunc:AH};function gH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,c,l),d=new pA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var xH={kernelName:_u,backendName:"webgl",kernelFunc:gH},bH=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${o});
 
       void main() {
@@ -3181,7 +3181,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},BU=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,c=e.effectiveFilterWidth,u=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=c-1-e.padInfo.left,p=o*l*c-1;this.userCode=`
+    `}},wH=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,c=e.effectiveFilterWidth,u=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=c-1-e.padInfo.left,p=o*l*c-1;this.userCode=`
       const ivec3 pads = ivec3(${u}, ${h}, ${d});
 
       void main() {
@@ -3245,14 +3245,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function VU(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new lA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new BU(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var UU={kernelName:Xh,backendName:"webgl",kernelFunc:VU};function jU(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;kl([s,i],"maxPoolGrad");let{filterSize:l,strides:c,pad:u,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,c,1,u,h),p=!0,f=new fc(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new WU(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var HU={kernelName:qh,backendName:"webgl",kernelFunc:jU};function GU(e,t,n,r){let a=new fc(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new fc(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var qU={kernelName:Kh,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let c=[1,1];v.assert(R.eitherStridesOrDilationsAreOne(s,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${c}'`);let u=R.computePool2DInfo(r.shape,a,s,c,i),[h,d]=GU(r,o,u,l);return[h,d]}};function XU(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=xe({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,"float32","mean",r),l=xe({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var KU={kernelName:Es,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:a,axis:s}=t,i=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let w=i.texData.get(f.dataId).values,b=new Array(o);for(let N=0;N<b.length;N++)b[N]=r.shape[u[N]];let _=sA(w,r.shape,r.dtype,u,b);f=i.makeTensorInfo(b,r.dtype);let x=i.texData.get(f.dataId);x.values=_}else f=Ap(r,u,i);p.push(f),c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("sum",c,o);let[m,A]=R.computeOutAndReduceShapes(f.shape,c),y=m;a&&(y=R.expandShapeToKeepDim(m,l));let g=XU(f,A,y,i);for(let w of p)i.disposeIntermediateTensorInfo(w);return g}};function ZU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,a.shape.length)),R.assertAxesAreInnerMostDims("min",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"min",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var YU={kernelName:Cs,backendName:"webgl",kernelFunc:ZU},JU=Vb+`
+    `}};function _H(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new pA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new wH(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var vH={kernelName:Xh,backendName:"webgl",kernelFunc:_H};function kH(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;kl([s,i],"maxPoolGrad");let{filterSize:l,strides:c,pad:u,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,c,1,u,h),p=!0,f=new fc(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new bH(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var IH={kernelName:qh,backendName:"webgl",kernelFunc:kH};function NH(e,t,n,r){let a=new fc(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new fc(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var SH={kernelName:Kh,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let c=[1,1];v.assert(R.eitherStridesOrDilationsAreOne(s,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${c}'`);let u=R.computePool2DInfo(r.shape,a,s,c,i),[h,d]=NH(r,o,u,l);return[h,d]}};function TH(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=xe({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,"float32","mean",r),l=xe({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var EH={kernelName:Es,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:a,axis:s}=t,i=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let b=i.texData.get(f.dataId).values,w=new Array(o);for(let N=0;N<w.length;N++)w[N]=r.shape[u[N]];let _=cA(b,r.shape,r.dtype,u,w);f=i.makeTensorInfo(w,r.dtype);let x=i.texData.get(f.dataId);x.values=_}else f=Ap(r,u,i);p.push(f),c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("sum",c,o);let[m,A]=R.computeOutAndReduceShapes(f.shape,c),y=m;a&&(y=R.expandShapeToKeepDim(m,l));let g=TH(f,A,y,i);for(let b of p)i.disposeIntermediateTensorInfo(b);return g}};function CH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,a.shape.length)),R.assertAxesAreInnerMostDims("min",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"min",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=xe({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=xe({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var RH={kernelName:Cs,backendName:"webgl",kernelFunc:CH},MH=_3+`
   return min(a, b);
-`,QU=`
+`,FH=`
   vec4 result = vec4(min(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
   `+fp+`
   return result;
-`,ej=tn({opSnippet:JU,packedOpSnippet:QU,cpuKernelImpl:oP}),tj={kernelName:Rs,backendName:"webgl",kernelFunc:ej},nj=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((c,u)=>c[0]+e[u]+c[1]);let r=e.length,a=ot(r),s=t.map(c=>c[0]).join(","),i=t.map((c,u)=>c[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),l=n==="reflect"?0:1;if(r===1){this.userCode=`
+`,DH=tn({opSnippet:MH,packedOpSnippet:FH,cpuKernelImpl:BL}),$H={kernelName:Rs,backendName:"webgl",kernelFunc:DH},OH=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((c,u)=>c[0]+e[u]+c[1]);let r=e.length,a=ot(r),s=t.map(c=>c[0]).join(","),i=t.map((c,u)=>c[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),l=n==="reflect"?0:1;if(r===1){this.userCode=`
         int start = ${s};
         int end = ${i};
 
@@ -3281,7 +3281,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         ${a} coords = outC - start;
         setOutput(getX(${o}));
       }
-    `}},rj=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,f)=>p[0]+e[f]+p[1]);let r=e.length,a=ot(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=dn("rc",r),l=dn("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=n==="reflect"?0:1,d="";if(r===1){let p=`
+    `}},zH=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,f)=>p[0]+e[f]+p[1]);let r=e.length,a=ot(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=dn("rc",r),l=dn("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=n==="reflect"?0:1,d="";if(r===1){let p=`
         ${a} source = rc;
         if (source < start) {
           source = start * 2 - source - ${h};
@@ -3337,13 +3337,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         ${d}
         setOutput(result);
       }
-    `}},aj=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new rj(r.shape,a,s):new nj(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},sj={kernelName:vu,backendName:"webgl",kernelFunc:aj},ij=`if (b == 0.0) return NAN;
-  return mod(a, b);`,oj=`
+    `}},PH=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new zH(r.shape,a,s):new OH(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},LH={kernelName:vu,backendName:"webgl",kernelFunc:PH},WH=`if (b == 0.0) return NAN;
+  return mod(a, b);`,BH=`
   vec4 result = mod(a, b);
   vec4 isNaN = vec4(equal(b, vec4(0.0)));
   `+fp+`
   return result;
-`,lj=tn({opSnippet:ij,packedOpSnippet:oj}),uj={kernelName:So,backendName:"webgl",kernelFunc:lj},cj=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=`
+`,VH=tn({opSnippet:WH,packedOpSnippet:BH}),jH={kernelName:So,backendName:"webgl",kernelFunc:VH},UH=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=`
       uniform float seed;
 
       void main() {
@@ -3365,11 +3365,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,JL=Xe({opSnippet:YL}),QL={kernelNam
         // If no other event happened, last event happened.
         setOutput(float(${t-1}));
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(n,"seed")),t.gl.uniform1f(this.seedLoc,e)}}},hj=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(n,"seed")),t.gl.uniform1f(this.seedLoc,e)}}},HH=`
 if (a == b) {
   return 1.0;
 };
-return a / b;`,dj=`
+return a / b;`,GH=`
   // vec4 one = vec4(equal(a, b));
   // return one + (vec4(1.0) - one) * a / b;
   vec4 result = a / b;
@@ -3387,14 +3387,14 @@ return a / b;`,dj=`
   }
 
   return result;
-`,N_=tn({opSnippet:hj,packedOpSnippet:dj,checkOutOfBounds:!0}),pj={kernelName:ys,backendName:"webgl",kernelFunc:N_},S_="return a - b;",T_=tn({opSnippet:S_,packedOpSnippet:S_,supportsComplex:!0,cpuKernelImpl:mP}),fj={kernelName:Ks,backendName:"webgl",kernelFunc:T_};function E_(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=I_({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=R.expandShapeToKeepDim(o.shape,i),c=xe({inputs:{x:o},backend:n,attrs:{shape:l}}),u=T_({inputs:{a,b:c},backend:n}),h=w_({inputs:{x:u},backend:n}),d=oA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=xe({inputs:{x:d},backend:n,attrs:{shape:l}}),f=N_({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var mj={kernelName:qs,backendName:"webgl",kernelFunc:E_};function Aj(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:E_({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),c=l.shape[0],u=l.shape[1],h=new cj(c,u,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var yj={kernelName:Zh,backendName:"webgl",kernelFunc:Aj},C_="return -x;";function gj(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=uP(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Cl(r.shape,C_):a=new La(r.shape,C_),n.runWebGLProgram(a,[r],r.dtype)}var xj={kernelName:To,backendName:"webgl",kernelFunc:gj},wj=Pr.nonMaxSuppressionV3Impl;function bj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,c=n.readSync(a.dataId),u=n.readSync(s.dataId),{selectedIndices:h}=wj(c,u,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var _j={kernelName:Co,backendName:"webgl",kernelFunc:bj},vj=Pr.nonMaxSuppressionV4Impl;function kj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=vj(u,h,i,o,l,c);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var Ij={kernelName:Ro,backendName:"webgl",kernelFunc:kj},Nj=Pr.nonMaxSuppressionV5Impl;function Sj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=c,{selectedIndices:A,selectedScores:y}=Nj(u,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var Tj={kernelName:Mo,backendName:"webgl",kernelFunc:Sj},Ej=class{constructor(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
+`,i7=tn({opSnippet:HH,packedOpSnippet:GH,checkOutOfBounds:!0}),qH={kernelName:ys,backendName:"webgl",kernelFunc:i7},o7="return a - b;",l7=tn({opSnippet:o7,packedOpSnippet:o7,supportsComplex:!0,cpuKernelImpl:KL}),XH={kernelName:Ks,backendName:"webgl",kernelFunc:l7};function u7(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=s7({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=R.expandShapeToKeepDim(o.shape,i),c=xe({inputs:{x:o},backend:n,attrs:{shape:l}}),u=l7({inputs:{a,b:c},backend:n}),h=e7({inputs:{x:u},backend:n}),d=dA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=xe({inputs:{x:d},backend:n,attrs:{shape:l}}),f=i7({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var KH={kernelName:qs,backendName:"webgl",kernelFunc:u7};function ZH(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:u7({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),c=l.shape[0],u=l.shape[1],h=new UH(c,u,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var YH={kernelName:Zh,backendName:"webgl",kernelFunc:ZH},c7="return -x;";function JH(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=jL(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Cl(r.shape,c7):a=new La(r.shape,c7),n.runWebGLProgram(a,[r],r.dtype)}var QH={kernelName:To,backendName:"webgl",kernelFunc:JH},eG=Pr.nonMaxSuppressionV3Impl;function tG(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,c=n.readSync(a.dataId),u=n.readSync(s.dataId),{selectedIndices:h}=eG(c,u,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var nG={kernelName:Co,backendName:"webgl",kernelFunc:tG},rG=Pr.nonMaxSuppressionV4Impl;function aG(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=rG(u,h,i,o,l,c);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var sG={kernelName:Ro,backendName:"webgl",kernelFunc:aG},iG=Pr.nonMaxSuppressionV5Impl;function oG(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=c,{selectedIndices:A,selectedScores:y}=iG(u,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var lG={kernelName:Mo,backendName:"webgl",kernelFunc:oG},uG=class{constructor(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int index = round(getIndices(coords.x));
         setOutput(mix(float(${r}), float(${n}),
                       float(index == coords.y)));
       }
-    `}},Cj=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),c=new Ej(l,s,i,o),u=xe({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(c,[u],a.dtype);n.disposeIntermediateTensorInfo(u);let d=[...a.shape,s],p=xe({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},Rj={kernelName:Fs,backendName:"webgl",kernelFunc:Cj};function bp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=Ac({inputs:{input:r},backend:n}),s=bp({inputs:{x:a},backend:n}),i=wp({inputs:{input:r},backend:n}),o=bp({inputs:{x:i},backend:n}),l=Wa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return dA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var Mj={kernelName:Zo,backendName:"webgl",kernelFunc:bp};function R_(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let a=Ac({inputs:{input:r},backend:n}),s=R_({inputs:{x:a},backend:n}),i=wp({inputs:{input:r},backend:n}),o=bp({inputs:{x:i},backend:n}),l=Wa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return dA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var Fj={kernelName:Fo,backendName:"webgl",kernelFunc:R_};function $j(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return hA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(u=>{v.assertShapesMatch(s,u.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===u.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(u=>{let h=hA({inputs:{input:u},backend:n,attrs:{dim:a}});return o.push(h),h}),c=c_({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(u=>n.disposeIntermediateTensorInfo(u)),c}var Dj={kernelName:$o,backendName:"webgl",kernelFunc:$j},Oj=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,c)=>l[0]+e[c]+l[1]);let r=e.length,a=ot(r),s=t.map(l=>l[0]).join(","),i=t.map((l,c)=>l[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);if(r===1){this.userCode=`
+    `}},cG=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),c=new uG(l,s,i,o),u=xe({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(c,[u],a.dtype);n.disposeIntermediateTensorInfo(u);let d=[...a.shape,s],p=xe({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},hG={kernelName:Fs,backendName:"webgl",kernelFunc:cG};function wp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=Ac({inputs:{input:r},backend:n}),s=wp({inputs:{x:a},backend:n}),i=bp({inputs:{input:r},backend:n}),o=wp({inputs:{x:i},backend:n}),l=Wa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return yA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var dG={kernelName:Zo,backendName:"webgl",kernelFunc:wp};function h7(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let a=Ac({inputs:{input:r},backend:n}),s=h7({inputs:{x:a},backend:n}),i=bp({inputs:{input:r},backend:n}),o=wp({inputs:{x:i},backend:n}),l=Wa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return yA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var pG={kernelName:Fo,backendName:"webgl",kernelFunc:h7};function fG(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return AA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(u=>{v.assertShapesMatch(s,u.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===u.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(u=>{let h=AA({inputs:{input:u},backend:n,attrs:{dim:a}});return o.push(h),h}),c=U3({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(u=>n.disposeIntermediateTensorInfo(u)),c}var mG={kernelName:Do,backendName:"webgl",kernelFunc:fG},AG=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,c)=>l[0]+e[c]+l[1]);let r=e.length,a=ot(r),s=t.map(l=>l[0]).join(","),i=t.map((l,c)=>l[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);if(r===1){this.userCode=`
         int start = ${s};
         int end = ${i};
         uniform float value;
@@ -3421,7 +3421,7 @@ return a / b;`,dj=`
           setOutput(getX(${o}));
         }
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},zj=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,a=ot(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=dn("rc",r),l=dn("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1;
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},yG=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,a=ot(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=dn("rc",r),l=dn("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1;
        if(${c}) {
       `,r===1?"":`}
        rc = outputLoc;
@@ -3446,7 +3446,7 @@ return a / b;`,dj=`
         ${p}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},M_=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new zj(a.shape,s,i):new Oj(a.shape,s,i),l=o.getCustomSetupFunc(i);return n.runWebGLProgram(o,[a],a.dtype,l)},Pj={kernelName:$s,backendName:"webgl",kernelFunc:M_},Lj=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},d7=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new yG(a.shape,s,i):new AG(a.shape,s,i),l=o.getCustomSetupFunc(i);return n.runWebGLProgram(o,[a],a.dtype,l)},gG={kernelName:Ds,backendName:"webgl",kernelFunc:d7},xG=`
   if(a < 0.0 && floor(b) < b){
     return NAN;
   }
@@ -3455,7 +3455,7 @@ return a / b;`,dj=`
   }
   return (round(mod(b, 2.0)) != 1) ?
       pow(abs(a), b) : sign(a) * pow(abs(a), b);
-`,Wj=`
+`,bG=`
   // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
   vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
   vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
@@ -3471,9 +3471,9 @@ return a / b;`,dj=`
   vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
   `+fp+`
   return result;
-`,Bj=tn({opSnippet:Lj,packedOpSnippet:Wj}),Vj={kernelName:Ds,backendName:"webgl",kernelFunc:Bj};function Uj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],c=v.parseAxisParam(s,a.shape),u=c,h=R.getAxesPermutation(u,o),d=a;h!=null&&(d=In({inputs:{x:a},backend:n,attrs:{perm:h}}),u=R.getInnerMostAxes(u.length,o),l.push(d)),R.assertAxesAreInnerMostDims("prod",u,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=cP(d.shape,d.dtype,f,u);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=R.computeOutAndReduceShapes(d.shape,u),A=v.sizeFromShape(m),y=xe({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=ld(a.dtype),w=vi(y,g,"prod",n);p=xe({inputs:{x:w},backend:n,attrs:{shape:f}}),l.push(y),l.push(w)}if(i){l.push(p);let f=R.expandShapeToKeepDim(p.shape,c);p=xe({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var jj={kernelName:Do,backendName:"webgl",kernelFunc:Uj},F_=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=hP(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},Hj={kernelName:ku,backendName:"webgl",kernelFunc:F_},Gj="return 1.0 / x;",qj=Xe({opSnippet:Gj}),Xj={kernelName:Oo,backendName:"webgl",kernelFunc:qj},Kj=gr+`
+`,wG=tn({opSnippet:xG,packedOpSnippet:bG}),_G={kernelName:$s,backendName:"webgl",kernelFunc:wG};function vG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],c=v.parseAxisParam(s,a.shape),u=c,h=R.getAxesPermutation(u,o),d=a;h!=null&&(d=In({inputs:{x:a},backend:n,attrs:{perm:h}}),u=R.getInnerMostAxes(u.length,o),l.push(d)),R.assertAxesAreInnerMostDims("prod",u,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=UL(d.shape,d.dtype,f,u);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=R.computeOutAndReduceShapes(d.shape,u),A=v.sizeFromShape(m),y=xe({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=ld(a.dtype),b=vi(y,g,"prod",n);p=xe({inputs:{x:b},backend:n,attrs:{shape:f}}),l.push(y),l.push(b)}if(i){l.push(p);let f=R.expandShapeToKeepDim(p.shape,c);p=xe({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var kG={kernelName:$o,backendName:"webgl",kernelFunc:vG},p7=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=HL(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},IG={kernelName:ku,backendName:"webgl",kernelFunc:p7},NG="return 1.0 / x;",SG=Xe({opSnippet:NG}),TG={kernelName:Oo,backendName:"webgl",kernelFunc:SG},EG=gr+`
   return (x < 0.0) ? 0.0 : x;
-`,Zj=`
+`,CG=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3483,9 +3483,9 @@ return a / b;`,dj=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,Yj=Xe({opSnippet:Kj,packedOpSnippet:Zj}),Jj={kernelName:zs,backendName:"webgl",kernelFunc:Yj},Qj=gr+`
+`,RG=Xe({opSnippet:EG,packedOpSnippet:CG}),MG={kernelName:zs,backendName:"webgl",kernelFunc:RG},FG=gr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,eH=`
+`,DG=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3495,7 +3495,7 @@ return a / b;`,dj=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,tH=Xe({opSnippet:Qj,packedOpSnippet:eH}),nH={kernelName:Ls,backendName:"webgl",kernelFunc:tH},rH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+`,$G=Xe({opSnippet:FG,packedOpSnippet:DG}),OG={kernelName:Ls,backendName:"webgl",kernelFunc:$G},zG=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
           ${c[0]/u[0]},
           ${c[1]/u[1]});
@@ -3528,7 +3528,7 @@ return a / b;`,dj=`
 
         setOutput(newValue);
       }
-    `}},aH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}},PG=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec3 effectiveInputOverOutputRatioRC = vec3(
           ${c[0]/u[0]},
           ${c[1]/u[1]},
@@ -3605,7 +3605,7 @@ return a / b;`,dj=`
 
         setOutput(newValue);
       }
-    `}};function sH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=J().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new aH(a.shape,l,c,s,i):new rH(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],"float32")}var iH={kernelName:Ps,backendName:"webgl",kernelFunc:sH},oH=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
+    `}};function LG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=J().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new PG(a.shape,l,c,s,i):new zG(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],"float32")}var WG={kernelName:Ps,backendName:"webgl",kernelFunc:LG},BG=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3686,7 +3686,7 @@ return a / b;`,dj=`
 
         setOutput(accumulator);
       }
-    `}};function lH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new oH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var uH={kernelName:Qh,backendName:"webgl",kernelFunc:lH},cH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0",d;a?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}};function VG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new BG(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var jG={kernelName:Qh,backendName:"webgl",kernelFunc:VG},UG=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0",d;a?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
           ${c[0]/u[0]},
           ${c[1]/u[1]});
@@ -3708,7 +3708,7 @@ return a / b;`,dj=`
 
         setOutput(newValue);
       }
-    `}};function hH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=new cH(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],a.dtype)}var dH={kernelName:Iu,backendName:"webgl",kernelFunc:hH},pH=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
+    `}};function HG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=new UG(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],a.dtype)}var GG={kernelName:Iu,backendName:"webgl",kernelFunc:HG},qG=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3778,7 +3778,7 @@ return a / b;`,dj=`
 
         setOutput(accumulator);
       }
-    `}};function fH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new pH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var mH={kernelName:Jh,backendName:"webgl",kernelFunc:fH},AH=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
+    `}};function XG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new qG(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var KG={kernelName:Jh,backendName:"webgl",kernelFunc:XG},ZG=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${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));
@@ -3788,7 +3788,7 @@ return a / b;`,dj=`
         ${s} coords = getOutputCoords();
         setOutput(getX(${a}));
       }
-    `}},yH=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let r=dn("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=ot(n);n===1?this.userCode=`
+    `}},YG=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let r=dn("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=ot(n);n===1?this.userCode=`
         void main(){
           int rc = getOutputCoords();
           vec4 result = vec4(0.);
@@ -3816,7 +3816,7 @@ return a / b;`,dj=`
           }
           setOutput(result);
         }
-    `;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function c(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function u(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function gH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return On({inputs:{x:a},backend:n});let l=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new yH(a.shape,o):new AH(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var xH={kernelName:Ws,backendName:"webgl",kernelFunc:gH},wH=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let n=e[1],r=e[2];this.outputShape=e;let a="";typeof t=="number"?a=`float outputValue = ${t.toFixed(2)};`:a=`
+    `;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function c(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function u(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function JG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return On({inputs:{x:a},backend:n});let l=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new YG(a.shape,o):new ZG(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var QG={kernelName:Ws,backendName:"webgl",kernelFunc:JG},eq=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let n=e[1],r=e[2];this.outputShape=e;let a="";typeof t=="number"?a=`float outputValue = ${t.toFixed(2)};`:a=`
         vec3 fill = vec3(${t.join(",")});
         float outputValue = fill[coords[3]];`,this.userCode=`
         uniform vec4 params;
@@ -3836,7 +3836,7 @@ return a / b;`,dj=`
           }
           setOutput(outputValue);
         }
-    `}getCustomSetupFunc(e,t,n,r){return(a,s)=>{this.paramsLoc==null&&(this.paramsLoc=a.getUniformLocationNoThrow(s,"params")),a.gl.uniform4f(this.paramsLoc,e,t,n,r)}}},bH={kernelName:Yo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new wH(r.shape,s),[c,u]=R.getImageCenter(i,r.shape[1],r.shape[2]),h=l.getCustomSetupFunc(c,u,Math.sin(a),Math.cos(a));return o.runWebGLProgram(l,[r],r.dtype,h)}},_H=`
+    `}getCustomSetupFunc(e,t,n,r){return(a,s)=>{this.paramsLoc==null&&(this.paramsLoc=a.getUniformLocationNoThrow(s,"params")),a.gl.uniform4f(this.paramsLoc,e,t,n,r)}}},tq={kernelName:Yo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new eq(r.shape,s),[c,u]=R.getImageCenter(i,r.shape[1],r.shape[2]),h=l.getCustomSetupFunc(c,u,Math.sin(a),Math.cos(a));return o.runWebGLProgram(l,[r],r.dtype,h)}},nq=`
   // OpenGL ES does not support round function.
   // The algorithm is based on banker's rounding.
   float base = floor(x);
@@ -3851,7 +3851,7 @@ return a / b;`,dj=`
       return base + 1.0;
     }
   }
-`,vH=Xe({opSnippet:_H}),kH={kernelName:Bs,backendName:"webgl",kernelFunc:vH},IH="return inversesqrt(x);",NH=Xe({opSnippet:IH,cpuKernelImpl:dP}),SH={kernelName:Vs,backendName:"webgl",kernelFunc:NH},$_=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=ot(a.length),l=ot(s.length),c="";n===1?c="i":n===2&&(c="i, j");let u=`getIndices(${c})`,h="";r===1?h="i":r===2&&(h="i, coords[1]");let d=`getUpdates(${h})`,p=t>1?"strides[j]":"strides";this.userCode=`
+`,rq=Xe({opSnippet:nq}),aq={kernelName:Bs,backendName:"webgl",kernelFunc:rq},sq="return inversesqrt(x);",iq=Xe({opSnippet:sq,cpuKernelImpl:GL}),oq={kernelName:Vs,backendName:"webgl",kernelFunc:iq},f7=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=ot(a.length),l=ot(s.length),c="";n===1?c="i":n===2&&(c="i, j");let u=`getIndices(${c})`,h="";r===1?h="i":r===2&&(h="i, coords[1]");let d=`getUpdates(${h})`,p=t>1?"strides[j]":"strides";this.userCode=`
         ${o} strides = ${o}(${a});
 
         void main() {
@@ -3871,7 +3871,7 @@ return a / b;`,dj=`
           }
           setOutput(mix(getDefaultValue(), sum, float(found)));
         }
-      `}};function TH(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:c,strides:u,outputSize:h}=R.calculateShapes(s,a,i),d=[h/c,c];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=xe({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=xe({inputs:{x:s},backend:n,attrs:{shape:[l,c]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new $_(l,o,p.shape.length,f.shape.length,u,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=xe({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var EH={kernelName:Po,backendName:"webgl",kernelFunc:TH},CH=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let c=0;c<t.length;c++)l.push(`${i[c]}`),c<e&&o.push(`${i[c]}`);r=o.join(),a=l.join()}let s=ot(n);this.userCode=`
+      `}};function lq(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:c,strides:u,outputSize:h}=R.calculateShapes(s,a,i),d=[h/c,c];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=xe({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=xe({inputs:{x:s},backend:n,attrs:{shape:[l,c]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new f7(l,o,p.shape.length,f.shape.length,u,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=xe({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var uq={kernelName:Po,backendName:"webgl",kernelFunc:lq},cq=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let c=0;c<t.length;c++)l.push(`${i[c]}`),c<e&&o.push(`${i[c]}`);r=o.join(),a=l.join()}let s=ot(n);this.userCode=`
       void main() {
         ${s} resRC = getOutputCoords();
         float cVal = getC(${r});
@@ -3881,21 +3881,21 @@ return a / b;`,dj=`
           setOutput(getB(${a}));
         }
       }
-    `}};function RH(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new CH(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],nr(a.dtype,s.dtype))}var MH={kernelName:Lo,backendName:"webgl",kernelFunc:RH},FH=`
+    `}};function hq(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new cq(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],nr(a.dtype,s.dtype))}var dq={kernelName:Lo,backendName:"webgl",kernelFunc:hq},pq=`
   // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
   // see: https://arxiv.org/abs/1706.02515
   float scaleAlpha = ${R.SELU_SCALEALPHA};
   float scale = ${R.SELU_SCALE};
   return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
-`,$H=Xe({opSnippet:FH}),DH={kernelName:Wo,backendName:"webgl",kernelFunc:$H},OH="return 1.0 / (1.0 + exp(-1.0 * x));",zH=Xe({opSnippet:OH}),PH={kernelName:js,backendName:"webgl",kernelFunc:zH},LH=`
+`,fq=Xe({opSnippet:pq}),mq={kernelName:Wo,backendName:"webgl",kernelFunc:fq},Aq="return 1.0 / (1.0 + exp(-1.0 * x));",yq=Xe({opSnippet:Aq}),gq={kernelName:Us,backendName:"webgl",kernelFunc:yq},xq=`
   if (isnan(x)) { return 0.0; }
   return sign(x);
-`,WH=Xe({opSnippet:LH}),BH={kernelName:Uo,backendName:"webgl",kernelFunc:WH},VH=qb+`
+`,bq=Xe({opSnippet:xq}),wq={kernelName:jo,backendName:"webgl",kernelFunc:bq},_q=S3+`
   return sin(x);
-`,UH=Xe({opSnippet:VH}),jH={kernelName:Us,backendName:"webgl",kernelFunc:UH},HH=`
+`,vq=Xe({opSnippet:_q}),kq={kernelName:js,backendName:"webgl",kernelFunc:vq},Iq=`
   float e2x = exp(x);
   return (e2x - 1.0 / e2x) / 2.0;
-`,GH=Xe({opSnippet:HH}),qH={kernelName:Vo,backendName:"webgl",kernelFunc:GH},XH=`
+`,Nq=Xe({opSnippet:Iq}),Sq={kernelName:Vo,backendName:"webgl",kernelFunc:Nq},Tq=`
   float epsilon = 1.1920928955078125e-7;
   float threshold = log(epsilon) + 2.0;
 
@@ -3915,9 +3915,9 @@ return a / b;`,dj=`
     result = log(exp_x + 1.0);
   }
   return result;
-`,KH=Xe({opSnippet:XH}),ZH={kernelName:jo,backendName:"webgl",kernelFunc:KH},YH=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,paddings:i}=r;v.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,g)=>y*g),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<a.shape.length;++y)l.push([0,0]);let c=[],u=M_({inputs:{x:a},backend:n,attrs:{paddings:l,constantValue:0}}),h=R.getReshaped(u.shape,s,o,!1),d=R.getPermuted(h.length,s.length,!1),p=R.getReshapedPermuted(u.shape,s,o,!1),f=xe({inputs:{x:u},backend:n,attrs:{shape:h}}),m=In({inputs:{x:f},backend:n,attrs:{perm:d}}),A=xe({inputs:{x:m},backend:n,attrs:{shape:p}});return c.push(u),c.push(f),c.push(m),c.forEach(y=>n.disposeIntermediateTensorInfo(y)),A},JH={kernelName:Nu,backendName:"webgl",kernelFunc:YH};function QH(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:c,strides:u,outputSize:h}=R.calculateShapes(s,a,o),d=!1,p=new $_(c,l,a.shape.length,s.shape.length,u,[h,1],d),f=n.runWebGLProgram(p,[s,a,i],s.dtype),m=xe({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),m}var eG={kernelName:ed,backendName:"webgl",kernelFunc:QH};function tG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=r,o=v.parseAxisParam(i,a.shape)[0],l=R.prepareSplitSize(a,s,o),c=a.shape.length,u=new Array(c).fill(0),h=a.shape.slice();return l.map(d=>{let p=[...h];p[o]=d;let f=mc({inputs:{x:a},backend:n,attrs:{begin:u,size:p}});return u[o]+=d,f})}var nG={kernelName:Ho,backendName:"webgl",kernelFunc:tG},rG="return sqrt(x);",aG=Xe({opSnippet:rG}),sG={kernelName:Hs,backendName:"webgl",kernelFunc:aG},iG="return x * x;",oG=Xe({opSnippet:iG}),lG={kernelName:Su,backendName:"webgl",kernelFunc:oG},D_="return (a - b) * (a - b);",uG=tn({opSnippet:D_,packedOpSnippet:D_}),cG={kernelName:Xs,backendName:"webgl",kernelFunc:uG};function hG({inputs:e,attrs:t,backend:n}){let{x:r}=e,a=gr+`
+`,Eq=Xe({opSnippet:Tq}),Cq={kernelName:Uo,backendName:"webgl",kernelFunc:Eq},Rq=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,paddings:i}=r;v.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,g)=>y*g),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<a.shape.length;++y)l.push([0,0]);let c=[],u=d7({inputs:{x:a},backend:n,attrs:{paddings:l,constantValue:0}}),h=R.getReshaped(u.shape,s,o,!1),d=R.getPermuted(h.length,s.length,!1),p=R.getReshapedPermuted(u.shape,s,o,!1),f=xe({inputs:{x:u},backend:n,attrs:{shape:h}}),m=In({inputs:{x:f},backend:n,attrs:{perm:d}}),A=xe({inputs:{x:m},backend:n,attrs:{shape:p}});return c.push(u),c.push(f),c.push(m),c.forEach(y=>n.disposeIntermediateTensorInfo(y)),A},Mq={kernelName:Nu,backendName:"webgl",kernelFunc:Rq};function Fq(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:c,strides:u,outputSize:h}=R.calculateShapes(s,a,o),d=!1,p=new f7(c,l,a.shape.length,s.shape.length,u,[h,1],d),f=n.runWebGLProgram(p,[s,a,i],s.dtype),m=xe({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),m}var Dq={kernelName:ed,backendName:"webgl",kernelFunc:Fq};function $q(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=r,o=v.parseAxisParam(i,a.shape)[0],l=R.prepareSplitSize(a,s,o),c=a.shape.length,u=new Array(c).fill(0),h=a.shape.slice();return l.map(d=>{let p=[...h];p[o]=d;let f=mc({inputs:{x:a},backend:n,attrs:{begin:u,size:p}});return u[o]+=d,f})}var Oq={kernelName:Ho,backendName:"webgl",kernelFunc:$q},zq="return sqrt(x);",Pq=Xe({opSnippet:zq}),Lq={kernelName:Hs,backendName:"webgl",kernelFunc:Pq},Wq="return x * x;",Bq=Xe({opSnippet:Wq}),Vq={kernelName:Su,backendName:"webgl",kernelFunc:Bq},m7="return (a - b) * (a - b);",jq=tn({opSnippet:m7,packedOpSnippet:m7}),Uq={kernelName:Xs,backendName:"webgl",kernelFunc:jq};function Hq({inputs:e,attrs:t,backend:n}){let{x:r}=e,a=gr+`
     return x > 0.0 ? 1.0 : float(${t.alpha});
-  `,s=new La(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var dG={kernelName:Na,backendName:"webgl",kernelFunc:hG},pG=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=ot(n.length),s=ot(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,c)=>(o++,n.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${o-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
+  `,s=new La(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var Gq={kernelName:Na,backendName:"webgl",kernelFunc:Hq},qq=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=ot(n.length),s=ot(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,c)=>(o++,n.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${o-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
       ${a} begin = ${a}(${e});
       ${a} strides = ${a}(${t});
 
@@ -3925,15 +3925,15 @@ return a / b;`,dj=`
         ${s} coords = getOutputCoords();
         setOutput(getX(${i}));
       }
-    `}};function fG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:c,ellipsisMask:u,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=ln.sliceInfo(a.shape,s,i,o,l,c,u,h,d),w=xe({inputs:{x:a},backend:n,attrs:{shape:y}}),b;if(p){let x=mc({inputs:{x:w},backend:n,attrs:{begin:f,size:A}});b=xe({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))b=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([w])){let x=n.texData.get(w.dataId).values,N=Be(w.shape,w.dtype,x),T=fP(g,N,m,f);b=n.makeTensorInfo(g,w.dtype,T.values)}else{let x=new pG(f,m,g);b=n.runWebGLProgram(x,[w],w.dtype)}let _=xe({inputs:{x:b},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(b),_}var mG={kernelName:Go,backendName:"webgl",kernelFunc:fG},AG="return tan(x);",yG=Xe({opSnippet:AG}),gG={kernelName:qo,backendName:"webgl",kernelFunc:yG},xG=`
+    `}};function Xq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:c,ellipsisMask:u,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=ln.sliceInfo(a.shape,s,i,o,l,c,u,h,d),b=xe({inputs:{x:a},backend:n,attrs:{shape:y}}),w;if(p){let x=mc({inputs:{x:b},backend:n,attrs:{begin:f,size:A}});w=xe({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))w=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([b])){let x=n.texData.get(b.dataId).values,N=Be(b.shape,b.dtype,x),T=XL(g,N,m,f);w=n.makeTensorInfo(g,b.dtype,T.values)}else{let x=new qq(f,m,g);w=n.runWebGLProgram(x,[b],b.dtype)}let _=xe({inputs:{x:w},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(w),_}var Kq={kernelName:Go,backendName:"webgl",kernelFunc:Xq},Zq="return tan(x);",Yq=Xe({opSnippet:Zq}),Jq={kernelName:qo,backendName:"webgl",kernelFunc:Yq},Qq=`
   float e2x = exp(-2.0 * abs(x));
   return sign(x) * (1.0 - e2x) / (1.0 + e2x);
-`,wG=Xe({opSnippet:xG}),bG={kernelName:Zs,backendName:"webgl",kernelFunc:wG},vG=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.rank=n.length;let r=ot(this.rank),a=_G(e);this.userCode=`
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+    `}};function nX(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[];for(let a=0;a<e.length;a++)r.push(`imod(${n[a]}, ${e[a]})`);return r.join()}function A7(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reps:s}=r;if(a.dtype==="string"){let o=n.readSync(a.dataId).map(u=>v.decodeString(u)),l=Be(a.shape,a.dtype,o),c=ZL(l,s);return n.makeTensorInfo(c.shape,c.dtype,c.values)}let i=new rX(a.shape,s);return n.runWebGLProgram(i,[a],a.dtype)}var aX={kernelName:Ia,backendName:"webgl",kernelFunc:A7};function sX(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r,o=n.readSync(a.dataId),[l,c]=YL(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(c.shape,c.dtype,c.values)]}var iX={kernelName:Xo,backendName:"webgl",kernelFunc:sX},oX=class{constructor(e,t,n,r,a,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=n==="nearest"?1:2,o;switch(r){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
             float mapCoord(float outCoord, float len) {
               float inCoord = outCoord;
               if(${o} == 2) {
@@ -4045,7 +4045,7 @@ return a / b;`,dj=`
               }
               setOutput(outputValue);
             }
-        `}};function TG(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:c}=r,[u,h,d,p]=a.shape,[f,m]=c!=null?c:[h,d],A=[u,f,m,p],y=new SG(h,d,i,o,l,A);return n.runWebGLProgram(y,[a,s],"float32")}var EG={kernelName:td,backendName:"webgl",kernelFunc:TG};function CG(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;kl(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=r.readSync(s.dataId),{outputValues:o,outputShape:l,indices:c}=gP(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([c.length],"int32",c)]}var RG={kernelName:nd,backendName:"webgl",kernelFunc:CG};function MG(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],c=new Array(o-1),u=0;for(let m=0;m<o;m++)m!==s&&(c[u++]=i.shape[m]);let h=[],d=new Array(o).fill(0),p=i.shape.slice();p[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let A=mc({inputs:{x:i},backend:n,attrs:{begin:d,size:p}}),y=xe({inputs:{x:A},backend:n,attrs:{shape:c}});f[m]=y,h.push(A)}return h.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var FG={kernelName:Ko,backendName:"webgl",kernelFunc:MG},$G=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,r=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/n);this.outputShape=[r,i];let o="0.0",l="sumValue",c=Math.floor(n/4)*4,u=n%4,h=`
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         sumValue += dot(values, segFilter);
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         if (inIdx < 0 || inIdx >= ${a}) {
@@ -4151,26 +4151,26 @@ return a / b;`,dj=`
         }
         setOutput(${l});
       }
-    `}};function DG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,segmentIds:s}=t,{numSegments:i}=r,o=a.shape.length,l=[],c=0,u=R.getAxesPermutation([c],o),h=a;u!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:u}}),l.push(h),c=R.getInnerMostAxes(1,o)[0]);let d=R.segment_util.computeOutShape(h.shape,c,i),p=v.sizeFromShape([h.shape[c]]),f=xe({inputs:{x:h},backend:n,attrs:{shape:[-1,p]}});l.push(f);let m=ld(a.dtype),A=(b,_,x,N,T)=>{let E=b.shape[0],F=b.shape[1],D=R.segment_util.segOpComputeOptimalWindowSize(F,T),L={windowSize:D,inSize:F,batchSize:E,numSegments:T},V=new $G(L,_),U=n.compileAndRun(V,[b,x],N);if(l.push(U),U.shape[1]===T)return U;let j=F_({backend:n,attrs:{start:0,stop:T,step:1,dtype:"float32"}}),X=O_({inputs:{x:j},backend:n,attrs:{reps:[F/D]}});return l.push(j),l.push(X),A(U,_,X,N,T)},y=A(f,"unsortedSegmentSum",s,m,i),g=xe({inputs:{x:y},backend:n,attrs:{shape:d}}),w=g;if(u!=null){l.push(g);let b=R.getUndoAxesPermutation(u);w=In({inputs:{x:w},backend:n,attrs:{perm:b}})}return 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They will not be included in the serialized model (and thus will be missing at deserialization time).`),p={}}if(h.inboundLayers.length>0){let f=[];for(let m=0;m<h.inboundLayers.length;m++){let A=h.inboundLayers[m],y=h.nodeIndices[m],g=h.tensorIndices[m],w=Hr.nodeKey(A,y),b=t[w];b==null&&(b=0),f.push([A.name,b,g,p])}l.push(f)}}}let c={};c.name=s.name,c.className=i,c.config=o,c.inboundNodes=l,n.push(c)}e.layers=n;let r=[];for(let s=0;s<this.inputLayers.length;s++){let i=this.inputLayers[s],o=this.inputLayersNodeIndices[s],l=Hr.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let c=t[l];c==null&&(c=0);let u=this.inputLayersTensorIndices[s];r.push([i.name,c,u])}e.inputLayers=r;let a=[];for(let s=0;s<this.outputLayers.length;s++){let i=this.outputLayers[s],o=this.outputLayersNodeIndices[s],l=Hr.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let c=t[l];c==null&&(c=0);let u=this.outputLayersTensorIndices[s];a.push([i.name,c,u])}return e.outputLayers=a,e}static fromConfig(e,t,n={},r=!1){let a={},s={};function i(m,A){m.name in s?s[m.name].push(A):s[m.name]=[A]}function o(m,A){let y=[],g;for(let w of A){let b=w[0],_=w[1],x=w[2];if(g=w[3]==null?{}:w[3],!(b in a)){i(m,A);return}let N=a[b];if(N.inboundNodes.length<=_){i(m,A);return}let T=N.inboundNodes[_];y.push(T.outputTensors[x])}y.length>0&&m.apply(Sn(y),g)}function l(m){let A=m.name,y=kr(m,t.customObjects!=null?t.customObjects:{});y.setFastWeightInitDuringBuild(r),a[A]=y,m.inboundNodes.forEach(g=>{if(!(g instanceof Array))throw new B(`Corrupted configuration, expected array for nodeData: ${g}`);i(y,g)})}let c=t.name,u=t.layers;for(let m of u)l(m);for(;!PJ(s);)for(let m of u){let A=a[m.name];if(A.name in s){let y=s[A.name];delete s[A.name];for(let g of y)o(A,g)}}let h=[],d=[],p=t.inputLayers;for(let m of p){let A=m[0],y=m[1],g=m[2];Br(A in a);let w=a[A].inboundNodes[y].outputTensors;h.push(w[g])}let f=t.outputLayers;for(let m of f){let A=m[0],y=m[1],g=m[2];Br(A in a);let w=a[A].inboundNodes[y].outputTensors;d.push(w[g])}return new e({inputs:h,outputs:d,name:c})}get stateful(){if(this._stateful)throw new B("Container instance unexpectedly has _stateful = true. 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Provided ${n} not understood: ${JSON.stringify(e)}`)}function M7(e,t){return pte(e,t,"classWeight")}async function F7(e,t,n,r){if(t!=null||r!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let a=z(()=>{if(e.shape.length===1)return e.clone();if(e.shape.length===2)if(e.shape[1]>1){let o=1;return e.argMax(o)}else{if(e.shape[1]===1)return e.reshape([e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${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.`)}),s=Array.from(await a.data());ve(a);let i=[];return s.forEach(o=>{if(n[o]==null)throw new Error(`classWeight must contain all classes in the training data. 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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(!r||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()`. 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t}makeTrainFunction(){return e=>{let t=[],n=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),a=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+this.outputs.length*2),s=[],i=()=>{let c=[];for(let p=0;p<this.inputs.length;++p)c.push({key:this.inputs[p],value:n[p]});let u=new Ci(c),h=Rc(this.outputs,u,{training:!0}),d;for(let p=0;p<this.lossFunctions.length;++p){let f=this.lossFunctions[p](r[p],h[p]);a[p]!=null&&(f=fte(f,a[p]));let m=vt(f);t.push(m),p===0?d=f:d=se(d,f)}for(let p=0;p<this.metricsTensors.length;++p){let f;if(this.outputs.length>1&&p<this.outputs.length)f=t[p];else{let m=this.metricsTensors[p][0],A=this.metricsTensors[p][1];f=vt(m(r[A],h[A]))}Ut(f),s.push(f)}return d=vt(d),this.calculateLosses().forEach(p=>{d=se(d,p)}),d},o=this.collectedTrainableWeights.map(c=>c.read()),l=!0;return[this.optimizer_.minimize(i,l,o)].concat(s)}}makeTestFunction(){this.testFunction=e=>z(()=>{let t=[],n,r=e.slice(0,this.inputs.length),a=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),s=[];for(let l=0;l<this.inputs.length;++l)s.push({key:this.inputs[l],value:r[l]});let i=new Ci(s),o=Rc(this.outputs,i);for(let l=0;l<this.lossFunctions.length;++l){let c=this.lossFunctions[l],u=vt(c(a[l],o[l]));l===0?n=u:n=se(n,u),t.push(n)}for(let l=0;l<this.metricsTensors.length;++l){let c=this.metricsTensors[l][0],u=this.metricsTensors[l][1],h=vt(c(a[u],o[u]));t.push(h)}return t})}async fit(e,t,n={}){return _te(this,e,t,n)}async fitDataset(e,t){return gte(this,e,t)}async trainOnBatch(e,t){let n=await this.standardizeUserData(e,t),r=n[0],a=n[1],s=this.makeTrainFunction()(r.concat(a)),i=[];for(let o of s){let l=await o.data();i.push(l[0])}return ve(s),Sn(i)}getNamedWeights(e){let t=[],n=e!=null&&e.trainableOnly,r=n?this.trainableWeights:this.weights,a=this.getWeights(n);for(let s=0;s<r.length;++s)n&&!r[s].trainable||t.push({name:r[s].originalName,tensor:a[s]});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=pd().numTensors;this.optimizer_.dispose(),e.numDisposedVariables+=t-pd().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 r of t)if(typeof n[r]=="string")e[r]=ua(n[r]);else throw new Error("Serialization of non-string loss is not supported.")}return e}getMetricIdentifiers(){if(typeof this.metrics=="string"||typeof 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e.metrics)a[s]=Ii(e.metrics[s])}this.compile({loss:r,metrics:a,optimizer:n})}async save(e,t){if(typeof e=="string"){let i=wn.getSaveHandlers(e);if(i.length===0)throw new B(`Cannot find any save handlers for URL '${e}'`);if(i.length>1)throw new B(`Found more than one (${i.length}) save handlers for URL '${e}'`);e=i[0]}if(e.save==null)throw new B("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await wn.encodeWeights(this.getNamedWeights(t)),r=!1,a=null,s={modelTopology:this.toJSON(a,r),format:Ste,generatedBy:`TensorFlow.js tfjs-layers v${YA}`,convertedBy:null};if((t==null?!1:t.includeOptimizer)&&this.optimizer!=null){s.trainingConfig=this.getTrainingConfig();let i="optimizer",{data:o,specs:l}=await wn.encodeWeights(await this.optimizer.getWeights(),i);n.specs.push(...l),n.data=wn.concatenateArrayBuffers([n.data,o])}if(this.userDefinedMetadata!=null){let i=!0;T7(this.userDefinedMetadata,this.name,i),s.userDefinedMetadata=this.userDefinedMetadata}return s.weightData=n.data,s.weightSpecs=n.specs,e.save(s)}setUserDefinedMetadata(e){T7(e,this.name),this.userDefinedMetadata=e}getUserDefinedMetadata(){return this.userDefinedMetadata}};ca.className="Model";re.registerClass(ca);var B7=class extends ca{};B7.className="Functional";re.registerClass(B7);async function Tte(e,t){"modelTopology"in e||(e={modelTopology:e}),e=e;let n=e.modelTopology;n.model_config!=null&&(n=n.model_config);let r=Cc(n),a=kr(r,t);if(e.weightsManifest!=null){let s=await wn.loadWeights(e.weightsManifest,e.pathPrefix,a.weights.map(o=>o.originalName)),i={};for(let o of a.weights)i[o.originalName]=s[o.originalName];a.loadWeights(i),ve(s)}return a}async function Cte(e,t){if(t==null&&(t={}),typeof e=="string"){let n=wn.getLoadHandlers(e,t);if(n.length===0)n.push(wn.browserHTTPRequest(e,t));else if(n.length>1)throw new B(`Found more than one (${n.length}) load handlers for URL '${e}'`);e=n[0]}return Ete(e,void 0,t)}async function Ete(e,t,n){if(n==null&&(n={}),e.load==null)throw new B("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let r=await e.load(),a=r.modelTopology;a.model_config!=null&&(a=a.model_config);let s=n.strict==null?!0:n.strict,i=r.weightData!=null&&r.weightSpecs!=null&&s,o=kr(Cc(a),t,i),l=r.trainingConfig;if(l!=null&&o.loadTrainingConfig(l),r.userDefinedMetadata!=null&&o.setUserDefinedMetadata(r.userDefinedMetadata),r.weightData!=null){if(r.weightSpecs==null)throw new B("LayersModel artifacts contains weight data, but not weight specs. 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e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};cy.className="ThresholdedReLU";re.registerClass(cy);var hy=class extends qe{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new ry().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Pe(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}};hy.className="Softmax";re.registerClass(hy);function Vl(e,t,n){if(typeof e=="number")return ki(e,t);if(e.length!==t)throw new B(`The ${n} argument must be an integer or tuple of ${t} integers. 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Received: ${JSON.stringify(e)} including a non-integer number ${a}`)}return e}function Ir(e,t,n,r,a=1){if(e==null)return e;let s=t+(t-1)*(a-1),i;return n==="same"?i=e:i=e-s+1,Math.floor((i+r-1)/r)}function Zp(e,t,n,r){if(e==null)return null;if(r==="valid")e=e*t+Ua([n-t,0]);else if(r==="same")e=e*t;else throw new B(`Unsupport padding mode: ${r}.`);return e}function dy(e,t){return z(()=>(St(t),t==="channelsFirst"?nt(e,[0,2,3,1]):e))}function rv(e,t){return z(()=>(St(t),t==="channelsFirst"?nt(e,[0,2,3,4,1]):e))}function Pte(e,t,n,r=1,a="valid",s,i=1){return z(()=>{if(s==null&&(s=wr()),St(s),e.shape.length!==3)throw new B(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new B(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new B(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(s==="channelsFirst"&&(e=nt(e,[0,2,1])),a==="causal")throw new $e("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=yd(e,t,r,a==="same"?"same":"valid","NWC",i);return n!=null&&(o=Ur(o,n)),o})}function av(e,t,n,r=[1,1],a="valid",s,i,o=null){return z(()=>{if(s==null&&(s=wr()),St(s),e.rank!==3&&e.rank!==4)throw new B(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new B(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=dy(e,s);if(a==="causal")throw new $e("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=za.conv2d({x:l,filter:t,strides:r,pad:a==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=nt(l,[0,3,1,2])),l})}function Lte(e,t,n,r=[1,1,1],a="valid",s,i){return z(()=>{if(s==null&&(s=wr()),St(s),e.rank!==4&&e.rank!==5)throw new B(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new B(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=rv(e,s);if(a==="causal")throw new $e("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=tm(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Ur(o,n)),s==="channelsFirst"&&(o=nt(o,[0,4,1,2,3])),o})}var py=class extends qe{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",py.verifyArgs(t),this.rank=e,Ht(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new $e(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Vl(t.kernelSize,e,"kernelSize"),this.strides=Vl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Kn(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,St(this.dataFormat),this.activation=Ga(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=yt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Wt(t.biasConstraint),this.biasRegularizer=gt(t.biasRegularizer),this.activityRegularizer=gt(t.activityRegularizer),this.dilationRate=Vl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new B(`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 B(`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 B(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Br("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!bA(e.kernelSize,"number",1,3))throw new B(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:Ha(this.activation),useBias:this.useBias,biasInitializer:kt(this.biasInitializer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),biasConstraint:Lt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},$c=class extends py{constructor(e,t){super(e,t);this.kernel=null,$c.verifyArgs(t),this.filters=t.filters,Ht(this.filters,"filters"),this.kernelInitializer=yt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Wt(t.kernelConstraint),this.kernelRegularizer=gt(t.kernelRegularizer)}build(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new B(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],r=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",r,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 z(()=>{e=Pe(e);let n,r=this.bias==null?null:this.bias.read(),a=U3(this.activation.getClassName());if(a!=null&&this.rank===2)n=av(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate,a);else{if(this.rank===1)n=Pte(e,this.kernel.read(),r,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=av(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=Lte(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new $e("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=lt(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let a=0;a<n.length;++a){let s=Ir(n[a],this.kernelSize[a],this.padding,this.strides[a],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[a]);t.push(s)}let r=[e[0]];return this.dataFormat==="channelsLast"?(r=r.concat(t),r.push(this.filters)):(r.push(this.filters),r=r.concat(t)),r}getConfig(){let e={filters:this.filters,kernelInitializer:kt(this.kernelInitializer),kernelRegularizer:ut(this.kernelRegularizer),kernelConstraint:Lt(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 B(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Dc=class extends $c{constructor(e){super(2,e);Dc.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!bA(e.kernelSize,"number",1,2))throw new B(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Dc.className="Conv2D";re.registerClass(Dc);var Yp=class extends $c{constructor(e){super(3,e);Yp.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 B(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};Yp.className="Conv3D";re.registerClass(Yp);var fy=class extends Dc{constructor(e){super(e);if(this.inputSpec=[new Gt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new B(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=lt(e),e.length!==4)throw new B("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new B("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Gt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return z(()=>{let n=Pe(e);if(n.shape.length!==4)throw new B(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let r=n.shape,a=r[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=r[s],l=r[i],c=this.kernelSize[0],u=this.kernelSize[1],h=this.strides[0],d=this.strides[1],p=Zp(o,h,c,this.padding),f=Zp(l,d,u,this.padding),m=[a,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=nt(n,[0,2,3,1]));let A=gd(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=nt(A,[0,3,1,2])),this.bias!=null&&(A=Ur(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=lt(e);let t=e.slice(),n,r,a;this.dataFormat==="channelsFirst"?(n=1,r=2,a=3):(n=3,r=1,a=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[r]=Zp(t[r],o,s,this.padding),t[a]=Zp(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};fy.className="Conv2DTranspose";re.registerClass(fy);var sv=class extends $c{constructor(e,t){super(e,t);if(this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new B("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new B("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(t.padding!=null&&t.padding!=="same"&&t.padding!=="valid")throw new B(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=yt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=gt(t.depthwiseRegularizer),this.depthwiseConstraint=Wt(t.depthwiseConstraint),this.pointwiseInitializer=yt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=gt(t.pointwiseRegularizer),this.pointwiseConstraint=Wt(t.pointwiseConstraint)}build(e){if(e=lt(e),e.length<this.rank+2)throw new B(`Inputs to SeparableConv${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 B(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Gt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return z(()=>{e=Pe(e);let n;if(this.rank===1)throw new $e("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=nt(e,[0,2,3,1])),n=xm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Ur(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=nt(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=kt(this.depthwiseInitializer),e.pointwiseInitializer=kt(this.pointwiseInitializer),e.depthwiseRegularizer=ut(this.depthwiseRegularizer),e.pointwiseRegularizer=ut(this.pointwiseRegularizer),e.depthwiseConstraint=Lt(this.depthwiseConstraint),e.pointwiseConstraint=Lt(this.pointwiseConstraint),e}};sv.className="SeparableConv";var my=class extends sv{constructor(e){super(2,e)}};my.className="SeparableConv2D";re.registerClass(my);var Jp=class extends $c{constructor(e){super(1,e);Jp.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"&&!bA(e.kernelSize,"number",1,1))throw new B(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Jp.className="Conv1D";re.registerClass(Jp);var Ay=class extends qe{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 z(()=>{if(e=Pe(e),this.dataFormat==="channelsLast"){let n=Tp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Tp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Tp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Tp(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}};Ay.className="Cropping2D";re.registerClass(Ay);var yy=class extends qe{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,St(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,iQ(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 z(()=>{let n=Pe(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=nt(n,[0,2,3,1]);let a=this.size[0]*r[2],s=this.size[1]*r[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s]);return nt(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};yy.className="UpSampling2D";re.registerClass(yy);function Wte(e,t,n=[1,1],r="valid",a,s){return z(()=>{a==null&&(a=wr()),St(a);let i=dy(e,a);if(e.rank!==4)throw new B(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new B(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=cl(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=nt(i,[0,3,1,2])),i})}var gy=class extends py{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=yt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Wt(e.depthwiseConstraint),this.depthwiseRegularizer=gt(e.depthwiseRegularizer)}build(e){if(e=lt(e),e.length<4)throw new B(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new B(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],r=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",r,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 z(()=>{e=Pe(e);let n=Wte(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Ur(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Ir(t,this.kernelSize[0],this.padding,this.strides[0]),s=Ir(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=kt(this.depthwiseInitializer),e.depthwiseRegularizer=ut(this.depthwiseRegularizer),e.depthwiseConstraint=Lt(this.depthwiseRegularizer),e}};gy.className="DepthwiseConv2D";re.registerClass(gy);function iv(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new B("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),n=a(n),{inputs:e,initialState:t,constants:n}}function ov(e,t,n,r=!1,a,s,i=!1,o=!1){return z(()=>{let l=t.shape.length;if(l<3)throw new B(`Input should be at least 3D, but is ${l}D.`);let c=[1,0].concat(_r(2,l));if(t=nt(t,c),s!=null)throw new $e("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=a.asType("bool").asType("float32"),a.rank===l-1&&(a=Jt(a,-1)),a=nt(a,c)),r&&(t=$n(t,0),a!=null&&(a=$n(a,0)));let u=[],h,d=n,p=t.shape[0],f=sr(t),m;a!=null&&(m=sr(a));for(let y=0;y<p;++y){let g=f[y],w=z(()=>e(g,d));if(a==null)h=w[0],d=w[1];else{let b=z(()=>{let _=m[y],x=Fn(_).sub(_),N=w[0].mul(_).add(d[0].mul(x)),T=d.map((E,F)=>w[1][F].mul(_).add(E.mul(x)));return{output:N,newStates:T}});h=b.output,d=b.newStates}o&&u.push(h)}let A;return o&&(A=un(u,1)),[h,A,d]})}var jr=class extends qe{constructor(e){super(e);let t;if(e.cell==null)throw new B("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Qp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new B("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 Gt({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 _r(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){BA(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return z(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(a=>null);return[n].concat(r)}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){let t=null;if(this.numConstants!=null)throw new $e("Constants support is not implemented in RNN yet.");BA(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Gt({shape:[n,null,...r]});let a=[e[0]].concat(e.slice(2));if(t!=null)throw new $e("Constants support is not implemented in RNN yet.");this.cell.build(a);let s;if(Array.isArray(this.cell.stateSize)?s=this.cell.stateSize:s=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),s))throw new B(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=s.map(i=>new Gt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){z(()=>{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 B("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(r=>Et([n,r])):this.states_=[Et([n,this.cell.stateSize])];else if(e==null)ve(this.states_),this.keptStates!=null&&(ve(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Et([n,r])):this.states_[0]=Et([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`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()):ve(this.states_);for(let r=0;r<this.states_.length;++r){let a=e[r],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[r]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(a.shape,i))throw new B(`State ${r} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${a.shape}`);this.states_[r]=a}}this.states_=this.states_.map(r=>Ut(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=iv(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Gt({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof vr){let o=[e].concat(s),l=this.inputSpec.concat(i),c=this.inputSpec;this.inputSpec=l;let u=super.apply(o,t);return this.inputSpec=c,u}else return super.apply(e,t)}call(e,t){return z(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Pe(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new B(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:r},o=ov((d,p)=>{let f=this.cell.call([d].concat(p),i);return[f[0],f.slice(1)]},e,a,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],c=o[1],u=o[2];this.stateful&&this.resetStates(u,r);let h=this.returnSequences?c:l;return this.returnState?[h].concat(u):h})}getInitialState(e){return z(()=>{let t=Et(e.shape);return t=Ee(t,[1,2]),t=Ic(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?SA(t,[1,n]):t):this.cell.stateSize>1?[SA(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 r=t.cell,a=kr(r,n);return new e(Object.assign(t,{cell:a}))}};jr.className="RNN";re.registerClass(jr);var Tc=class extends qe{},e0=class extends Tc{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,Ht(this.units,"units"),this.activation=Ga(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=zl([1,Ua([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ua([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=lt(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 z(()=>{if(e=e,e.length!==2)throw new B(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let r=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=Vr(P(e,s),this.kernel.read()):a=Vr(e,this.kernel.read()),this.bias!=null&&(a=Ur(a,this.bias.read())),i!=null&&(n=P(n,i));let o=se(a,Vr(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ha(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),recurrentRegularizer:ut(this.recurrentRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),recurrentConstraint:Lt(this.recurrentConstraint),biasConstraint:Lt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};e0.className="SimpleRNNCell";re.registerClass(e0);var xy=class extends jr{constructor(e){e.cell=new e0(e),super(e)}call(e,t){return z(()=>{this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};xy.className="SimpleRNN";re.registerClass(xy);var t0=class extends Tc{constructor(e){super(e);if(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 B("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Ht(this.units,"units"),this.activation=Ga(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ga(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=zl([1,Ua([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ua([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=lt(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 z(()=>{if(e=e,e.length!==2)throw new B(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,r=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=P(e,a[0]));let c=Vr(e,this.kernel.read());this.useBias&&(c=Ur(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,s[0]));let u=this.recurrentKernel.read(),[h,d]=zt(u,[2*this.units,this.units],u.rank-1),p=Vr(r,h),[f,m,A]=zt(c,3,c.rank-1),[y,g]=zt(p,2,p.rank-1);i=this.recurrentActivation.apply(se(f,y)),o=this.recurrentActivation.apply(se(m,g));let w=Vr(P(o,r),d);l=this.activation.apply(se(A,w));let b=se(P(i,r),P(se(1,_t(i)),l));return[b,b]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ha(this.activation),recurrentActivation:Ha(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),recurrentRegularizer:ut(this.recurrentRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),recurrentConstraint:Lt(this.recurrentConstraint),biasConstraint:Lt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};t0.className="GRUCell";re.registerClass(t0);var wy=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 t0(e),super(e)}call(e,t){return z(()=>{this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};wy.className="GRU";re.registerClass(wy);var Oc=class extends Tc{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,Ht(this.units,"units"),this.activation=Ga(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ga(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=zl([1,Ua([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ua([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=lt(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 r;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;r=new(t=class extends lr{apply(i,o){let l=a.apply([s]),c=new Cp().apply([s]),u=a.apply([s*2]);return Q3(Q3(l,c),u)}},t.className="CustomInit",t)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return z(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new B(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,c,u;0<this.dropout&&this.dropout<1&&(e=P(e,s[0]));let h=Vr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,i[0])),h=se(h,Vr(r,this.recurrentKernel.read())),this.useBias&&(h=Ur(h,this.bias.read()));let[d,p,f,m]=zt(h,4,h.rank-1);o=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(p),c=se(P(l,a),P(o,this.activation.apply(f))),u=this.recurrentActivation.apply(m);let A=P(u,this.activation.apply(c));return[A,A,c]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ha(this.activation),recurrentActivation:Ha(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:ut(this.kernelRegularizer),recurrentRegularizer:ut(this.recurrentRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),recurrentConstraint:Lt(this.recurrentConstraint),biasConstraint:Lt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Oc.className="LSTMCell";re.registerClass(Oc);var by=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 Oc(e),super(e)}call(e,t){return z(()=>{this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};by.className="LSTM";re.registerClass(by);var Qp=class extends Tc{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 z(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=r[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),a.push(s.slice(1))}n=[];for(let i of a.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){BA(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,r)=>{Si(`RNNCell_${r}`,()=>{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()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,n={}){let r=[];for(let a of t.cells)r.push(kr(a,n));return new e({cells:r})}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 VA(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],a[s]])}UA(t)}};Qp.className="StackedRNNCells";re.registerClass(Qp);function qa(e){let{ones:t,rate:n,training:r=!1,count:a=1}=e,s=()=>t7(t(),n),i=()=>Sc(s,t,r);return!a||a<=1?Ut(i().clone()):Array(a).fill(void 0).map(i).map(o=>Ut(o.clone()))}var Bte=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]]);return n},lv=class extends jr{constructor(e){if(e.unroll)throw new $e("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new $e("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Gt({ndim:5})]}call(e,t){return z(()=>{if(this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new B("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}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 z(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=Et(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){z(()=>{if(!this.stateful)throw new la("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new B("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(()=>Et(a)):this.states_=[Et(a)];else if(e==null)ve(this.states_),this.keptStates!=null&&(ve(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Et(a)):this.states_[0]=Et(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`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()):ve(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!v.arraysEqual(i.shape,o))throw new B(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>Ut(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:r,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],c=e[o?4:3],u=Ir(l,r[0],a,s[0],i[0]),h=Ir(c,r[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[n,u,h]:[u,h,n]]}};lv.className="ConvRNN2D";var n0=class extends Oc{constructor(e){let{filters:t,kernelSize:n,strides:r,padding:a,dataFormat:s,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,Ht(this.filters,"filters"),this.kernelSize=Vl(n,2,"kernelSize"),this.kernelSize.forEach(o=>Ht(o,"kernelSize")),this.strides=Vl(r||1,2,"strides"),this.strides.forEach(o=>Ht(o,"strides")),this.padding=a||"valid",Kn(this.padding),this.dataFormat=s||"channelsLast",St(this.dataFormat),this.dilationRate=Vl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Ht(o,"dilationRate"))}build(e){var t;e=lt(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new B(`The channel dimension of the input should be defined. Found ${e[n]}`);let r=e[n],a=4,s=this.kernelSize.concat([r,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,c=this.filters;o=new(t=class extends lr{apply(u,h){let d=l.apply([c]),p=Or([c]),f=l.apply([c*2]);return EA([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return z(()=>{if(e.length!==3)throw new B(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(Y,ae,te)=>!ae||!ae[te]?Y:P(ae[te],Y),c=l(r,o,0),u=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[w,b,_,x]=zt(this.kernel.read(),i,g),[N,T,E,F]=this.useBias?zt(this.bias.read(),i):[null,null,null,null];c=this.inputConv(c,w,N,this.padding),u=this.inputConv(u,b,T,this.padding),h=this.inputConv(h,_,E,this.padding),d=this.inputConv(d,x,F,this.padding);let[D,L,V,U]=zt(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,D),m=this.recurrentConv(m,L),A=this.recurrentConv(A,V),y=this.recurrentConv(y,U);let j=this.recurrentActivation.apply(se(c,f)),X=this.recurrentActivation.apply(se(u,m)),G=se(P(X,s),P(j,this.activation.apply(se(h,A)))),ee=P(this.recurrentActivation.apply(se(d,y)),this.activation.apply(G));return[ee,ee,G]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=Bte(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=na(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Ur(a,n,this.dataFormat):a}recurrentConv(e,t){return na(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};n0.className="ConvLSTM2DCell";re.registerClass(n0);var _y=class extends lv{constructor(e){let t=new n0(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};_y.className="ConvLSTM2D";re.registerClass(_y);var r0=class extends qe{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 r=0;r<this.noiseShape.length;++r)n.push(this.noiseShape[r]==null?t[r]:this.noiseShape[r]);return n}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,a=this.getNoiseShape(n);return Sc(()=>t7(n,this.rate,a,this.seed),()=>n,r)}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()}};r0.className="Dropout";re.registerClass(r0);var vy=class extends r0{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};vy.className="SpatialDropout1D";re.registerClass(vy);var ky=class extends qe{constructor(e){super(e);if(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,Ht(this.units,"units"),this.activation=Ga(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Wt(e.kernelConstraint),this.biasConstraint=Wt(e.biasConstraint),this.kernelRegularizer=gt(e.kernelRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.activityRegularizer=gt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=lt(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=lt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=U3(this.activation.getClassName()),a;return r!=null?a=Vr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=Vr(n,this.kernel.read()),this.bias!=null&&(a=Ur(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:Ha(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),biasConstraint:Lt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};ky.className="Dense";re.registerClass(ky);var Iy=class extends qe{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=lt(e);for(let t of e.slice(1))if(t==null)throw new B(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). 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z(()=>(e=Pe(e),cQ(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};Sy.className="RepeatVector";re.registerClass(Sy);var Ty=class extends qe{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.",r=t.slice(),a=1,s=null;for(let o=0;o<r.length;++o){let l=r[o];if(this.isUnknown(l))if(s===null)s=o;else throw new B("Can only specifiy one unknown dimension.");else a*=l}let i=Va(e);if(s!==null){if(a===0||i%a!=0)throw new B(n);r[s]=i/a}else if(i!==a)throw new B(n);return r}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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=n.shape,a=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};Ty.className="Reshape";re.registerClass(Ty);var Ey=class extends qe{constructor(e){super(e);if(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=_r(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 Gt({ndim:this.dims.length+1})]}computeOutputShape(e){e=lt(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return nt(Pe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Ey.className="Permute";re.registerClass(Ey);var Cy=class extends qe{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=Pe(e),r=-1;return Wu(pi(n,this.maskValue),r)}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=-1,a=!0,s=Wu(pi(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};Cy.className="Masking";re.registerClass(Cy);var Ry=class extends qe{constructor(e){super(e);if(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(pt(e.inputLength))}this.inputDim=e.inputDim,Ht(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Ht(this.outputDim,"outputDim"),this.embeddingsInitializer=yt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=gt(e.embeddingsRegularizer),this.activityRegularizer=gt(e.activityRegularizer),this.embeddingsConstraint=Wt(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 z(()=>this.maskZero?(e=Pe(e),pi(e,je(e))):null)}computeOutputShape(e){if(e=lt(e),this.inputLength==null)return[...e,this.outputDim];let t=pt(this.inputLength);if(t.length!==e.length-1)throw new B(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let r=0;r<t.length;++r){let a=t[r],s=e[r+1];if(a!=null&&s!=null&&a!==s)throw new B(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);a==null&&(t[n]=s),n++}}return[e[0],...t,this.outputDim]}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return n.dtype!=="int32"&&(n=kc(n,"int32")),e7(this.embeddings.read(),n.as1D()).reshape(lt(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:kt(this.embeddingsInitializer),embeddingsRegularizer:ut(this.embeddingsRegularizer),activityRegularizer:ut(this.activityRegularizer),embeddingsConstraint:Lt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Ry.className="Embedding";re.registerClass(Ry);var Mi=class extends qe{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new $e}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 r=0;r<t.length;++r){let a=e[e.length-t.length+r],s=t[r];if(a==null||s==null||a<0||s<0)n.push(null);else if(a===1)n.push(s);else if(s===1)n.push(a);else{if(a!==s)throw new B("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[lt(e)]),e=e,e.length<2)throw new B(`A merge layer should be called on an Array of at least 2 inputs. 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e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};zy.className="Concatenate";re.registerClass(zy);function zc(e,t){for(;e<0;)e+=t;return e}function Vte(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new $e("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 $e("batchDot is not implemented for complex64-type Tensors yet.");let r=e.shape.length,a=t.shape.length;n==null&&(n=[r-1,a-2]);let s=n;return z(()=>{let i;if(r>a){i=r-a;let l=[];for(let c=0;c<i;++c)l.push(1);t=t.reshape(t.shape.concat(l))}else if(a>r){i=a-r;let l=[];for(let c=0;c<i;++c)l.push(1);e=e.reshape(e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=e.mul(t).sum(s[0]):o=e.transpose([1,0]).mul(t).sum(s[1]);else{let l=s[0]!==e.shape.length-1,c=s[1]===t.shape.length-1;o=e.matMul(t,l,c)}if(i>0){let l;r>a?l=r+a-3:l=r-1;let c=[];for(let u=l;u<l+i;++u)c.push(u);o=o.squeeze(c)}return o.shape.length===1&&(o=o.expandDims(1)),o})}var Py=class extends Mi{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 $e("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new B(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new B(`A \`Dot\` layer must be called on exactly 2 inputs, but 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Ly=class extends qe{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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return Sc(()=>Ep(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};Ly.className="GaussianNoise";re.registerClass(Ly);var Wy=class extends qe{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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.rate>0&&this.rate<1?Sc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(Ep(n.shape,1,r))},()=>n,t.training||!1):n})}};Wy.className="GaussianDropout";re.registerClass(Wy);var By=class extends qe{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Pe(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 z(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return Sc(()=>{let r=Pe(e),a=1.6732632423543772,s=1.0507009873554805,i=-a*s,o=Da(Al(n),this.rate);o=kc(o,"float32");let l=((1-this.rate)*(1+this.rate*i**2))**-.5,c=-l*i*this.rate;return r.mul(o).add(o.add(-1).mul(i)).mul(l).add(c)},()=>Pe(e),t.training||!1)}return e})}};By.className="AlphaDropout";re.registerClass(By);function Pc(e,t,n,r,a,s=.001){let i;if(e.rank===2)i=Q5(e,t,n,r,a,s);else if(e.rank===3)i=ex(e,t,n,r,a,s);else if(e.rank===4)i=tx(e,t,n,r,a,s);else throw new $e(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function Ute(e,t,n,r,a=.001){return z(()=>{let s=Sd(e,r),i=s.mean,o=s.variance;return[Pc(e,i,o,n,t,a),i,o]})}function jte(e,t,n,r,a=.001){return z(()=>{let s=Sd(e,r),i=s.mean,o=s.variance,l=[];for(let p of 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qe{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=yt(e.betaInitializer||"zeros"),this.gammaInitializer=yt(e.gammaInitializer||"ones"),this.movingMeanInitializer=yt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=yt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Wt(e.betaConstraint),this.gammaConstraint=Wt(e.gammaConstraint),this.betaRegularizer=gt(e.betaRegularizer),this.gammaRegularizer=gt(e.gammaRegularizer)}build(e){e=lt(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new B(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Gt({ndim:e.length,axes:{[t]:n}})];let r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return z(()=>{let n=t.training==null?!1:t.training,r=Pe(e),a=r.shape,s=a.length,i=_r(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=ki(1,s);l[o]=a[o];let c=i.slice();c.sort();let u=!v.arraysEqual(c,_r(0,s).slice(0,s-1)),h=()=>{if(u){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,w=this.scale?this.gamma.read().reshape(l):null;return Pc(r,A,y,g,w,this.epsilon)}else return 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extends qe{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=yt(e.betaInitializer||"zeros"),this.gammaInitializer=yt(e.gammaInitializer||"ones"),this.betaRegularizer=gt(e.betaRegularizer),this.gammaRegularizer=gt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=lt(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a<this.axis.length;++a)this.axis[a]<0&&(this.axis[a]+=t);for(let a of this.axis)if(a<0||a>=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==Ba(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(a=>e[a]),r=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,r):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,r):this.beta=null,this.built=!0}call(e,t){let n=Pe(e),r=n.shape,a=r.length;return z(()=>{let s=!0,{mean:i,variance:o}=Sd(n,this.axis,s),l=ki(1,a);for(let f of this.axis)l[f]=r[f];let c=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,u=c(this.gamma.read()),h=c(this.beta.read()),d=[],p=[];for(let f=0;f<a;++f)this.axis.indexOf(f)!==-1?(d.push(r[f]),p.push(1)):(d.push(1),p.push(r[f]));return i=i.tile(d),o=o.tile(d),u=u.tile(p),h=h.tile(p),Pc(n,i,o,h,u,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:kt(this.betaInitializer),gammaInitializer:kt(this.gammaInitializer),betaRegularizer:ut(this.betaRegularizer),gammaRegularizer:ut(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};Uy.className="LayerNormalization";re.registerClass(Uy);function Gte(e,t,n){return z(()=>{if(e.rank!==4)throw new B(`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 B("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=wr()),n!=="channelsLast"&&n!=="channelsFirst")throw new B(`Unknown data format: ${n}. 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s==="max"?i=Ku(e,t,n,o):i=Vu(e,t,n,o),a==="channelsFirst"&&(i=nt(i,[0,3,1,2])),i})}function uv(e,t,n,r,a,s){return z(()=>{St(a),q3(s),Kn(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=wr()),s==null&&(s="max"),e=rv(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=dm(e,t,n,o):i=Jf(e,t,n,o),a==="channelsFirst"&&(i=nt(i,[0,4,1,2,3])),i})}var cv=class extends qe{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 B(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Ht(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 B(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Ht(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,Kn(this.padding),this.inputSpec=[new Gt({ndim:3})]}computeOutputShape(e){e=lt(e);let t=Ir(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return z(()=>{this.invokeCallHook(e,t),e=Ic(Pe(e),2);let n=this.poolingFunction(Pe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return Oa(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},Hy=class extends cv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"max")}};Hy.className="MaxPooling1D";re.registerClass(Hy);var Gy=class extends cv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return 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t=Ir(t,this.poolSize[0],this.padding,this.strides[0]),n=Ir(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 z(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(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}},qy=class extends hv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"max")}};qy.className="MaxPooling2D";re.registerClass(qy);var Xy=class extends hv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"avg")}};Xy.className="AveragePooling2D";re.registerClass(Xy);var dv=class extends qe{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 B(`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];Ht(this.poolSize,"poolSize"),Ht(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,St(this.dataFormat),Kn(this.padding),this.inputSpec=[new Gt({ndim:5})]}computeOutputShape(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Ir(t,this.poolSize[0],this.padding,this.strides[0]),n=Ir(n,this.poolSize[1],this.padding,this.strides[1]),r=Ir(r,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}call(e,t){return z(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(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}},Ky=class extends dv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),uv(e,t,n,r,a,"max")}};Ky.className="MaxPooling3D";re.registerClass(Ky);var Zy=class extends dv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),uv(e,t,n,r,a,"avg")}};Zy.className="AveragePooling3D";re.registerClass(Zy);var pv=class extends qe{constructor(e){super(e);this.inputSpec=[new Gt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new $e}},Yy=class extends pv{constructor(e){super(e||{})}call(e,t){return z(()=>{let n=Pe(e);return vt(n,1)})}};Yy.className="GlobalAveragePooling1D";re.registerClass(Yy);var Jy=class extends pv{constructor(e){super(e||{})}call(e,t){return z(()=>{let n=Pe(e);return vn(n,1)})}};Jy.className="GlobalMaxPooling1D";re.registerClass(Jy);var fv=class extends qe{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,St(this.dataFormat),this.inputSpec=[new Gt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new $e}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Qy=class extends fv{call(e,t){return z(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?vt(n,[1,2]):vt(n,[2,3])})}};Qy.className="GlobalAveragePooling2D";re.registerClass(Qy);var e2=class extends fv{call(e,t){return z(()=>{let n=Pe(e);return 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e(s)}},t2=class extends mv{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=lt(e),e.length<3)throw new B(`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=lt(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))}call(e,t){return z(()=>(e=Pe(e),ov((n,r)=>[Pe(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};t2.className="TimeDistributed";re.registerClass(t2);function qte(e){Ni(sQ,"BidirectionalMergeMode",e)}var Xte="concat",n2=class extends mv{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=kr(n),t.goBackwards=t.goBackwards!==!0;let r={};if(r.className=e.layer.getClassName(),r.config=t,this.backwardLayer=kr(r),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?Xte:e.mergeMode,qte(this.mergeMode),e.weights)throw new $e("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,r,a;return this.returnState&&(a=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,r=[n]):this.mergeMode==null?r=[n,n.slice()]:r=[n],this.returnState?this.mergeMode==null?r.concat(a).concat(a.slice()):[n].concat(a).concat(a.slice()):Sn(r)}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=iv(e,n,r,this.numConstants);if(e=a.inputs,n=a.initialState,r=a.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&r==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new B("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let c=n.map(u=>new 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i;return this.mergeMode==="concat"?i=EA([r,a]):this.mergeMode==="sum"?i=se(r,a):this.mergeMode==="ave"?i=P(.5,se(r,a)):this.mergeMode==="mul"?i=P(r,a):this.mergeMode==null&&(i=[r,a]),this.returnState?this.mergeMode==null?i.concat(s):[i].concat(s):i})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){Si(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),Si(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 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r=e[t];return r&&r.shape?jv(r.shape):n}function h2(e,t,n){let r=e[t];return r?((r.list.f&&r.list.f.length?r.list.f:r.list.i)||[]).map(a=>typeof a=="number"?a:parseInt(a,10)):n}function d2(e,t,n,r=!1){let a=e[t];return a&&a.list&&a.list.s?a.list.s.map(s=>Uv(s,r)):n}function p2(e,t,n){let r=e[t];return r&&r.list&&r.list.shape?r.list.shape.map(a=>jv(a)):n}function f2(e,t,n){let r=e[t];return r&&r.list&&r.list.b?r.list.b:n}var One=class{constructor(e,t,n){this.node=e,this.tensorMap=t,this.context=n,this.inputs=[],this.attrs={},this.inputs=e.inputNames.map(r=>this.getInput(r)),e.rawAttrs!=null&&(this.attrs=Object.keys(e.rawAttrs).reduce((r,a)=>(r[a]=this.getAttr(a),r),{}))}getInput(e){return En(e,this.tensorMap,this.context)}getAttr(e,t){let n=this.node.rawAttrs[e];if(n.tensor!=null)return En(e,this.tensorMap,this.context);if(n.i!=null||n.f!=null)return i2(this.node.rawAttrs,e,t);if(n.s!=null)return a2(this.node.rawAttrs,e,t);if(n.b!=null)return s2(this.node.rawAttrs,e,t);if(n.shape!=null)return c2(this.node.rawAttrs,e,t);if(n.type!=null)return l2(this.node.rawAttrs,e,t);if(n.list!=null){if(n.list.i!=null||n.list.f!=null)return h2(this.node.rawAttrs,e,t);if(n.list.s!=null)return d2(this.node.rawAttrs,e,t);if(n.list.shape!=null)return p2(this.node.rawAttrs,e,t);if(n.list.b!=null)return f2(this.node.rawAttrs,e,t);if(n.list.type!=null)return u2(this.node.rawAttrs,e,t)}return t}},zne=(e,t,n)=>{switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[se(k("a",e,t,n),k("b",e,t,n))];case"AddN":return[Ra(k("tensors",e,t,n))];case"FloorMod":case"Mod":return[fm(k("a",e,t,n),k("b",e,t,n))];case"Mul":return[P(k("a",e,t,n),k("b",e,t,n))];case"RealDiv":case"Div":return[me(k("a",e,t,n),k("b",e,t,n))];case"DivNoNan":return[am(k("a",e,t,n),k("b",e,t,n))];case"FloorDiv":return[fd(k("a",e,t,n),k("b",e,t,n))];case"Sub":return[Ae(k("a",e,t,n),k("b",e,t,n))];case"Minimum":return[ml(k("a",e,t,n),k("b",e,t,n))];case"Maximum":return[Dr(k("a",e,t,n),k("b",e,t,n))];case"Pow":return[aa(k("a",e,t,n),k("b",e,t,n))];case"SquaredDifference":return[Pd(k("a",e,t,n),k("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not 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extends lr{constructor(e){super();if(this.DEFAULT_GAIN=1,this.gain=e.gain==null?this.DEFAULT_GAIN:e.gain,this.seed=e.seed,this.seed!=null)throw new $e("Random seed is not implemented for Orthogonal Initializer yet.")}apply(e,t){return z(()=>{if(e.length<2)throw new $e("Shape must be at least 2D.");e[0]*e[1]>2e3&&console.warn(`Orthogonal initializer is being called on a matrix with more than 2000 (${e[0]*e[1]}) elements: Slowness may result.`);let n=e[0]>e[1]?[e[1],e[0]]:e,r=Ep(n,0,1,"float32"),a=_w.gramSchmidt(r);return e[0]>e[1]&&(a=a.transpose()),P(this.gain,a)})}getConfig(){return{gain:this.gain,seed:this.seed}}};VA.className="Orthogonal";re.registerClass(VA);var Ov={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 zv(e,t={}){return wc(e,re.SerializationMap.getMap().classNameMap,t,"initializer")}function kt(e){return kA(e)}function yt(e){if(typeof e=="string"){let t=e in Ov?Ov[e]:e;if(t==="GlorotNormal")return new Mp;if(t==="GlorotUniform")return new Rp;if(t==="HeNormal")return new Fp;if(t==="HeUniform")return new Dp;if(t==="LeCunNormal")return new $p;if(t==="LeCunUniform")return new Op;{let n={};return n.className=t,n.config={},zv(n)}}else return e instanceof lr?e:zv(e)}function bee(){return new OA}function wee(){return new Cp}function _ee(e){return new zA(e)}function vee(e){return new PA(e)}function kee(e){return new LA(e)}function Iee(e){return new WA(e)}function Nee(e){return new BA(e)}function See(e){return new Tn(e)}function Tee(e){return new Rp(e)}function Eee(e){return new Mp(e)}function Cee(e){return new Fp(e)}function Ree(e){return new Dp(e)}function Mee(e){return new $p(e)}function Fee(e){return new Op(e)}function Dee(e){return new VA(e)}var Pv={};Me(Pv,{Layer:()=>qe,RNN:()=>Ur,RNNCell:()=>Tc,activation:()=>Ate,add:()=>Ite,alphaDropout:()=>lne,average:()=>Nte,averagePooling1d:()=>jA,averagePooling2d:()=>UA,averagePooling3d:()=>HA,avgPool1d:()=>$te,avgPool2d:()=>zte,avgPool3d:()=>Lte,avgPooling1d:()=>Ote,avgPooling2d:()=>Pte,avgPooling3d:()=>Wte,batchNormalization:()=>Mte,bidirectional:()=>ene,concatenate:()=>Ste,conv1d:()=>lte,conv2d:()=>ute,conv2dTranspose:()=>cte,conv3d:()=>hte,convLstm2d:()=>Zte,convLstm2dCell:()=>Yte,cropping2D:()=>pte,dense:()=>yte,depthwiseConv2d:()=>mte,dot:()=>Rte,dropout:()=>gte,elu:()=>nte,embedding:()=>kte,flatten:()=>bte,gaussianDropout:()=>one,gaussianNoise:()=>ine,globalAveragePooling1d:()=>Bte,globalAveragePooling2d:()=>Vte,globalMaxPool1d:()=>nne,globalMaxPool2d:()=>rne,globalMaxPooling1d:()=>Wv,globalMaxPooling2d:()=>Bv,gru:()=>Ute,gruCell:()=>Hte,input:()=>Lv,inputLayer:()=>tte,layerNormalization:()=>Fte,leakyReLU:()=>ate,lstm:()=>Gte,lstmCell:()=>qte,masking:()=>une,maxPool1d:()=>ane,maxPool2d:()=>sne,maxPooling1d:()=>Vv,maxPooling2d:()=>jv,maxPooling3d:()=>jte,maximum:()=>Tte,minimum:()=>Ete,multiply:()=>Cte,permute:()=>vte,prelu:()=>ste,reLU:()=>rte,repeatVector:()=>wte,reshape:()=>_te,rnn:()=>Jte,separableConv2d:()=>dte,simpleRNN:()=>Xte,simpleRNNCell:()=>Kte,softmax:()=>ite,spatialDropout1d:()=>xte,stackedRNNCells:()=>Qte,thresholdedReLU:()=>ote,timeDistributed:()=>tne,upSampling2d:()=>fte,zeroPadding2d:()=>Dte});var cne=0;function Uv(){return cne++}var zp={};function Pp(e=""){return e in zp||(zp[e]=0),zp[e]+=1,e+zp[e].toString()}function GA(e){return Array.isArray(e)&&Array.isArray(e[0])}function Lp(e){return e.length===0?[]:Array.isArray(e[0])?e:[e]}function Pe(e){let t;if(Array.isArray(e)){if(e.length!==1)throw new B(`Expected Tensor length to be 1; got ${e.length}`);t=e[0]}else t=e;return t}function lt(e){if(Array.isArray(e)&&Array.isArray(e[0])){if(e.length===1)return e=e,e[0];throw new B(`Expected exactly 1 Shape; got ${e.length}`)}else return e}function Wp(e){let t=0;for(let n of e)n.shape.length===0?t+=1:t+=n.shape.reduce((r,a)=>r*a);return t}var Hv="Variable",Gv=class{constructor(e,t="float32",n=Hv,r=!0,a=null){this.dtype=t==null?"float32":t,this.shape=e.shape,this.id=Uv(),n=n==null?Hv:n,this.originalName=Cv(n),this.name=Rv(this.originalName),this.trainable_=r,this.constraint=a,this.val=aw(e,this.trainable_,this.name,this.dtype)}read(){return this.assertNotDisposed(),this.val}write(e){return this.assertNotDisposed(),hne(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 hne(e,t){if(e.shape.toString()!==t.shape.toString())throw new Error("Shape mismatch: "+JSON.stringify(e.shape)+" vs. "+JSON.stringify(t.shape))}function qA(e){return e.map(t=>t.read())}function XA(e){e.forEach(t=>{t[0].write(t[1])})}var Gt=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||{}}},vr=class{constructor(e,t,n,r,a,s,i){this.dtype=e,this.shape=t,this.sourceLayer=n,this.inputs=r,this.callArgs=a,this.outputTensorIndex=i,this.id=Uv(),s!=null&&(this.originalName=Cv(s),this.name=Rv(this.originalName)),this.rank=t.length}},dne=0,Bp=class{constructor(e,t){this.callArgs=t,this.id=dne++,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}}},pne=0,qe=class extends re.Serializable{constructor(e={}){super();this._callHook=null,this._addedWeightNames=[],this._stateful=!1,this.id=pne++,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)+"_"+Pp(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 a=null;e.batchSize!=null&&(a=e.batchSize),n=[a].concat(e.inputShape)}this.batchInputShape=n;let r=e.dtype;r==null&&(r=e.inputDType),r==null&&(r="float32"),this.dtype=r}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 wr(`The layer has never been called and thus has no defined ${t}.`);if(this.inboundNodes.length<=e)throw new B(`Asked to get ${t} at node ${e}, but the layer has only ${this.inboundNodes.length} inbound nodes.`);return this.inboundNodes[e]}getInputAt(e){return Sn(this.getNodeAtIndex(e,"input").inputTensors)}getOutputAt(e){return Sn(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. 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Input received: ${e}`);for(let n=0;n<e.length;n++){let r=e[n],a=t[n];if(a==null)continue;let s=r.rank;if(a.ndim!=null&&s!==a.ndim)throw new B(`Input ${n} is incompatible with layer ${this.name}: expected ndim=${a.ndim}, found ndim=${s}`);if(a.maxNDim!=null&&s>a.maxNDim)throw new B(`Input ${n} is incompatible with layer ${this.name}: expected max_ndim=${a.maxNDim}, found ndim=${s}`);if(a.minNDim!=null&&s<a.minNDim)throw new B(`Input ${n} is incompatible with layer ${this.name}: expected min_ndim=${a.minNDim}, found ndim=${s}.`);if(a.dtype!=null&&r.dtype!==a.dtype)throw new B(`Input ${n} is incompatible with layer ${this.name} : expected dtype=${a.dtype}, found dtype=${r.dtype}.`);if(a.axes){let i=r.shape;for(let o in a.axes){let l=Number(o),c=a.axes[o],u=l>=0?i[l]:i[i.length+l];if(c!=null&&[c,null].indexOf(u)===-1)throw new B(`Input ${n} is incompatible with layer ${this.name}: expected axis ${l} of input shape to have value ${c} but got shape ${i}.`)}}if(a.shape!=null)for(let i=0;i<a.shape.length;++i){let o=a.shape[i],l=r.shape[i];if(o!=null&&l!=null&&o!==l)throw new B(`Input ${n} is incompatible with layer ${this.name}: expected shape=${a.shape}, found shape=${r.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=pt(e),r=!0;for(let s of n)if(!(s instanceof vr)){r=!1;break}let a=!0;for(let s of n)if(s instanceof vr){a=!1;break}if(r===a)throw new B("Arguments to apply() must be all SymbolicTensors or all Tensors");return Si(this.name,()=>{if(!this.built){this.assertInputCompatibility(e);let s=[];for(let i of pt(e))s.push(i.shape);this.build(Sn(s)),this.built=!0,this.initialWeights&&this.setWeights(this.initialWeights),this._refCount===null&&a&&(this._refCount=1)}if(this.assertInputCompatibility(e),a){let s=this.call(e,t),i=pt(s),o=[];for(let l of i)n.indexOf(l)!==-1&&(l=l.clone()),o.push(l);if(s=Sn(o),this.activityRegularizer!=null)throw new $e("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return s}else{let s=fne(e),i=this.computeOutputShape(s),o,l=mne(e);if(this.warnOnIncompatibleInputShape(Array.isArray(e)?s[0]:s),i!=null&&i.length>0&&Array.isArray(i[0])?o=i.map((c,u)=>new vr(l,c,this,pt(e),t,this.name,u)):o=new vr(l,i,this,pt(e),t,this.name),this.addInboundNode(e,o,null,null,s,i,t),this._refCount++,this.activityRegularizer!=null)throw new $e("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return o}})}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 ${this.name}`);else{let t=!1;this.batchInputShape.forEach((n,r)=>{n!=null&&e[r]!=null&&e[r]!==n&&(t=!0)}),t&&console.warn(`The shape of the input tensor (${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 wr(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);return Wp(this.weights)}build(e){this.built=!0}getWeights(e=!1){return qA(e?this.trainableWeights:this.weights)}setWeights(e){z(()=>{let t=this.weights;if(t.length!==e.length)throw new B(`You called setWeights(weights) on layer "${this.name}" with a weight list of length ${e.length}, but the layer was expecting ${t.length} weights. 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gt(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in $6?$6[e]:e,config:{}};return O6(t)}else return e instanceof D6?e:O6(e)}var hy=class extends qe{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=Pe(e);let n=zr(e);return this.maxValue!=null&&(n=wn(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};hy.className="ReLU";re.registerClass(hy);var dy=class extends qe{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=Pe(e);return qu(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};dy.className="LeakyReLU";re.registerClass(dy);var py=class extends qe{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=yt(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=gt(e.alphaRegularizer),this.alphaConstraint=Wt(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 B(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=lt(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let r of this.sharedAxes)t[r-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let r=1;r<e.length;++r)n[r]=e[r];this.inputSpec=[new Gt({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=Pe(e),Yu(e,this.alpha.read())}getConfig(){let e={alphaInitializer:kt(this.alphaInitializer),alphaRegularizer:ut(this.alphaRegularizer),alphaConstraint:Lt(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};py.className="PReLU";re.registerClass(py);var fy=class extends qe{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new $e(`Non-default alpha value (${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=Pe(e);return hl(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};fy.className="ELU";re.registerClass(fy);var my=class extends qe{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=Pe(e);return n.mul(kc(n.greater(this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};my.className="ThresholdedReLU";re.registerClass(my);var Ay=class extends qe{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new ly().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Pe(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}};Ay.className="Softmax";re.registerClass(Ay);function Vl(e,t,n){if(typeof e=="number")return ki(e,t);if(e.length!==t)throw new B(`The ${n} argument must be an integer or tuple of ${t} integers. 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B(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new B(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=z6(e,s);if(a==="causal")throw new $e("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=im(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=jr(o,n)),s==="channelsFirst"&&(o=nt(o,[0,4,1,2,3])),o})}var gy=class extends qe{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",gy.verifyArgs(t),this.rank=e,Ht(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new $e(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Vl(t.kernelSize,e,"kernelSize"),this.strides=Vl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Kn(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,St(this.dataFormat),this.activation=Ga(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=yt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Wt(t.biasConstraint),this.biasRegularizer=gt(t.biasRegularizer),this.activityRegularizer=gt(t.activityRegularizer),this.dilationRate=Vl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new B(`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 B(`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 B(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Br("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!NA(e.kernelSize,"number",1,3))throw new B(`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:Ha(this.activation),useBias:this.useBias,biasInitializer:kt(this.biasInitializer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),biasConstraint:Lt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Dc=class extends gy{constructor(e,t){super(e,t);this.kernel=null,Dc.verifyArgs(t),this.filters=t.filters,Ht(this.filters,"filters"),this.kernelInitializer=yt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Wt(t.kernelConstraint),this.kernelRegularizer=gt(t.kernelRegularizer)}build(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new B(`The channel dimension of the input should be defined. 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t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null||e[t]<0)throw new B(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Gt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return z(()=>{e=Pe(e);let n;if(this.rank===1)throw new $e("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=nt(e,[0,2,3,1])),n=km(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=jr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=nt(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=kt(this.depthwiseInitializer),e.pointwiseInitializer=kt(this.pointwiseInitializer),e.depthwiseRegularizer=ut(this.depthwiseRegularizer),e.pointwiseRegularizer=ut(this.pointwiseRegularizer),e.depthwiseConstraint=Lt(this.depthwiseConstraint),e.pointwiseConstraint=Lt(this.pointwiseConstraint),e}};L6.className="SeparableConv";var by=class extends L6{constructor(e){super(2,e)}};by.className="SeparableConv2D";re.registerClass(by);var Jp=class extends Dc{constructor(e){super(1,e);Jp.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"&&!NA(e.kernelSize,"number",1,1))throw new B(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Jp.className="Conv1D";re.registerClass(Jp);var wy=class extends qe{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 z(()=>{if(e=Pe(e),this.dataFormat==="channelsLast"){let n=Tp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Tp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Tp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Tp(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}};wy.className="Cropping2D";re.registerClass(wy);var _y=class extends qe{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,St(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,Wee(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 z(()=>{let n=Pe(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=nt(n,[0,2,3,1]);let a=this.size[0]*r[2],s=this.size[1]*r[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s]);return nt(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};_y.className="UpSampling2D";re.registerClass(_y);function bre(e,t,n=[1,1],r="valid",a,s){return z(()=>{a==null&&(a=br()),St(a);let i=yy(e,a);if(e.rank!==4)throw new B(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new B(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=cl(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=nt(i,[0,3,1,2])),i})}var vy=class extends gy{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=yt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Wt(e.depthwiseConstraint),this.depthwiseRegularizer=gt(e.depthwiseRegularizer)}build(e){if(e=lt(e),e.length<4)throw new B(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new B(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],r=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",r,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 z(()=>{e=Pe(e);let n=bre(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=jr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Ir(t,this.kernelSize[0],this.padding,this.strides[0]),s=Ir(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=kt(this.depthwiseInitializer),e.depthwiseRegularizer=ut(this.depthwiseRegularizer),e.depthwiseConstraint=Lt(this.depthwiseRegularizer),e}};vy.className="DepthwiseConv2D";re.registerClass(vy);function W6(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new B("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),n=a(n),{inputs:e,initialState:t,constants:n}}function B6(e,t,n,r=!1,a,s,i=!1,o=!1){return z(()=>{let l=t.shape.length;if(l<3)throw new B(`Input should be at least 3D, but is ${l}D.`);let c=[1,0].concat(_r(2,l));if(t=nt(t,c),s!=null)throw new $e("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=a.asType("bool").asType("float32"),a.rank===l-1&&(a=Jt(a,-1)),a=nt(a,c)),r&&(t=Dn(t,0),a!=null&&(a=Dn(a,0)));let u=[],h,d=n,p=t.shape[0],f=sr(t),m;a!=null&&(m=sr(a));for(let y=0;y<p;++y){let g=f[y],b=z(()=>e(g,d));if(a==null)h=b[0],d=b[1];else{let w=z(()=>{let _=m[y],x=Fn(_).sub(_),N=b[0].mul(_).add(d[0].mul(x)),T=d.map((E,F)=>b[1][F].mul(_).add(E.mul(x)));return{output:N,newStates:T}});h=w.output,d=w.newStates}o&&u.push(h)}let A;return o&&(A=un(u,1)),[h,A,d]})}var Ur=class extends qe{constructor(e){super(e);let t;if(e.cell==null)throw new B("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Qp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new B("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 Gt({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 _r(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){GA(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return z(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(a=>null);return[n].concat(r)}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){let t=null;if(this.numConstants!=null)throw new $e("Constants support is not implemented in RNN yet.");GA(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Gt({shape:[n,null,...r]});let a=[e[0]].concat(e.slice(2));if(t!=null)throw new $e("Constants support is not implemented in RNN yet.");this.cell.build(a);let s;if(Array.isArray(this.cell.stateSize)?s=this.cell.stateSize:s=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),s))throw new B(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=s.map(i=>new Gt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){z(()=>{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 B("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(r=>Et([n,r])):this.states_=[Et([n,this.cell.stateSize])];else if(e==null)ve(this.states_),this.keptStates!=null&&(ve(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Et([n,r])):this.states_[0]=Et([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`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()):ve(this.states_);for(let r=0;r<this.states_.length;++r){let a=e[r],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[r]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(a.shape,i))throw new B(`State ${r} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${a.shape}`);this.states_[r]=a}}this.states_=this.states_.map(r=>jt(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=W6(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Gt({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof vr){let o=[e].concat(s),l=this.inputSpec.concat(i),c=this.inputSpec;this.inputSpec=l;let u=super.apply(o,t);return this.inputSpec=c,u}else return super.apply(e,t)}call(e,t){return z(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Pe(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new B(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:r},o=B6((d,p)=>{let f=this.cell.call([d].concat(p),i);return[f[0],f.slice(1)]},e,a,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],c=o[1],u=o[2];this.stateful&&this.resetStates(u,r);let h=this.returnSequences?c:l;return this.returnState?[h].concat(u):h})}getInitialState(e){return z(()=>{let t=Et(e.shape);return t=Ee(t,[1,2]),t=Ic(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?MA(t,[1,n]):t):this.cell.stateSize>1?[MA(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()===Ur.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let r=t.cell,a=kr(r,n);return new e(Object.assign(t,{cell:a}))}};Ur.className="RNN";re.registerClass(Ur);var Tc=class extends qe{},e0=class extends Tc{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,Ht(this.units,"units"),this.activation=Ga(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=zl([1,ja([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,ja([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=lt(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 z(()=>{if(e=e,e.length!==2)throw new B(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let r=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=Vr(P(e,s),this.kernel.read()):a=Vr(e,this.kernel.read()),this.bias!=null&&(a=jr(a,this.bias.read())),i!=null&&(n=P(n,i));let o=se(a,Vr(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ha(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),recurrentRegularizer:ut(this.recurrentRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),recurrentConstraint:Lt(this.recurrentConstraint),biasConstraint:Lt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};e0.className="SimpleRNNCell";re.registerClass(e0);var ky=class extends Ur{constructor(e){e.cell=new e0(e),super(e)}call(e,t){return z(()=>{this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};ky.className="SimpleRNN";re.registerClass(ky);var t0=class extends Tc{constructor(e){super(e);if(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 B("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Ht(this.units,"units"),this.activation=Ga(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ga(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=zl([1,ja([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,ja([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=lt(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 z(()=>{if(e=e,e.length!==2)throw new B(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,r=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=P(e,a[0]));let c=Vr(e,this.kernel.read());this.useBias&&(c=jr(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,s[0]));let u=this.recurrentKernel.read(),[h,d]=zt(u,[2*this.units,this.units],u.rank-1),p=Vr(r,h),[f,m,A]=zt(c,3,c.rank-1),[y,g]=zt(p,2,p.rank-1);i=this.recurrentActivation.apply(se(f,y)),o=this.recurrentActivation.apply(se(m,g));let b=Vr(P(o,r),d);l=this.activation.apply(se(A,b));let w=se(P(i,r),P(se(1,_t(i)),l));return[w,w]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ha(this.activation),recurrentActivation:Ha(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),recurrentRegularizer:ut(this.recurrentRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),recurrentConstraint:Lt(this.recurrentConstraint),biasConstraint:Lt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};t0.className="GRUCell";re.registerClass(t0);var Iy=class extends Ur{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 t0(e),super(e)}call(e,t){return z(()=>{this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Iy.className="GRU";re.registerClass(Iy);var Oc=class extends Tc{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,Ht(this.units,"units"),this.activation=Ga(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ga(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=zl([1,ja([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,ja([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=lt(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 r;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;r=new(t=class extends lr{apply(i,o){let l=a.apply([s]),c=new Cp().apply([s]),u=a.apply([s*2]);return Fv(Fv(l,c),u)}},t.className="CustomInit",t)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return z(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new B(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,c,u;0<this.dropout&&this.dropout<1&&(e=P(e,s[0]));let h=Vr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,i[0])),h=se(h,Vr(r,this.recurrentKernel.read())),this.useBias&&(h=jr(h,this.bias.read()));let[d,p,f,m]=zt(h,4,h.rank-1);o=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(p),c=se(P(l,a),P(o,this.activation.apply(f))),u=this.recurrentActivation.apply(m);let A=P(u,this.activation.apply(c));return[A,A,c]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ha(this.activation),recurrentActivation:Ha(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:ut(this.kernelRegularizer),recurrentRegularizer:ut(this.recurrentRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),recurrentConstraint:Lt(this.recurrentConstraint),biasConstraint:Lt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Oc.className="LSTMCell";re.registerClass(Oc);var Ny=class extends Ur{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 Oc(e),super(e)}call(e,t){return z(()=>{this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Ny.className="LSTM";re.registerClass(Ny);var Qp=class extends Tc{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 z(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=r[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),a.push(s.slice(1))}n=[];for(let i of a.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){GA(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,r)=>{Si(`RNNCell_${r}`,()=>{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()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,n={}){let r=[];for(let a of t.cells)r.push(kr(a,n));return new e({cells:r})}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 qA(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],a[s]])}XA(t)}};Qp.className="StackedRNNCells";re.registerClass(Qp);function qa(e){let{ones:t,rate:n,training:r=!1,count:a=1}=e,s=()=>$v(t(),n),i=()=>Sc(s,t,r);return!a||a<=1?jt(i().clone()):Array(a).fill(void 0).map(i).map(o=>jt(o.clone()))}var wre=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]]);return n},V6=class extends Ur{constructor(e){if(e.unroll)throw new $e("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new $e("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Gt({ndim:5})]}call(e,t){return z(()=>{if(this.cell.dropoutMask!=null&&(ve(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ve(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new B("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}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 z(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=Et(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){z(()=>{if(!this.stateful)throw new la("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new B("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(()=>Et(a)):this.states_=[Et(a)];else if(e==null)ve(this.states_),this.keptStates!=null&&(ve(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Et(a)):this.states_[0]=Et(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`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()):ve(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!v.arraysEqual(i.shape,o))throw new B(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>jt(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:r,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],c=e[o?4:3],u=Ir(l,r[0],a,s[0],i[0]),h=Ir(c,r[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[n,u,h]:[u,h,n]]}};V6.className="ConvRNN2D";var n0=class extends Oc{constructor(e){let{filters:t,kernelSize:n,strides:r,padding:a,dataFormat:s,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,Ht(this.filters,"filters"),this.kernelSize=Vl(n,2,"kernelSize"),this.kernelSize.forEach(o=>Ht(o,"kernelSize")),this.strides=Vl(r||1,2,"strides"),this.strides.forEach(o=>Ht(o,"strides")),this.padding=a||"valid",Kn(this.padding),this.dataFormat=s||"channelsLast",St(this.dataFormat),this.dilationRate=Vl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Ht(o,"dilationRate"))}build(e){var t;e=lt(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new B(`The channel dimension of the input should be defined. Found ${e[n]}`);let r=e[n],a=4,s=this.kernelSize.concat([r,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,c=this.filters;o=new(t=class extends lr{apply(u,h){let d=l.apply([c]),p=Or([c]),f=l.apply([c*2]);return DA([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return z(()=>{if(e.length!==3)throw new B(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=qa({ones:()=>Fn(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(Y,ae,te)=>!ae||!ae[te]?Y:P(ae[te],Y),c=l(r,o,0),u=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=qa({ones:()=>Fn(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[b,w,_,x]=zt(this.kernel.read(),i,g),[N,T,E,F]=this.useBias?zt(this.bias.read(),i):[null,null,null,null];c=this.inputConv(c,b,N,this.padding),u=this.inputConv(u,w,T,this.padding),h=this.inputConv(h,_,E,this.padding),d=this.inputConv(d,x,F,this.padding);let[$,L,V,j]=zt(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,$),m=this.recurrentConv(m,L),A=this.recurrentConv(A,V),y=this.recurrentConv(y,j);let U=this.recurrentActivation.apply(se(c,f)),X=this.recurrentActivation.apply(se(u,m)),G=se(P(X,s),P(U,this.activation.apply(se(h,A)))),ee=P(this.recurrentActivation.apply(se(d,y)),this.activation.apply(G));return[ee,ee,G]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=wre(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=na(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?jr(a,n,this.dataFormat):a}recurrentConv(e,t){return na(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};n0.className="ConvLSTM2DCell";re.registerClass(n0);var Sy=class extends V6{constructor(e){let t=new n0(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};Sy.className="ConvLSTM2D";re.registerClass(Sy);var r0=class extends qe{constructor(e){super(e);this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,n=[];for(let r=0;r<this.noiseShape.length;++r)n.push(this.noiseShape[r]==null?t[r]:this.noiseShape[r]);return n}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,a=this.getNoiseShape(n);return Sc(()=>$v(n,this.rate,a,this.seed),()=>n,r)}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()}};r0.className="Dropout";re.registerClass(r0);var Ty=class extends r0{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};Ty.className="SpatialDropout1D";re.registerClass(Ty);var Ey=class extends qe{constructor(e){super(e);if(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,Ht(this.units,"units"),this.activation=Ga(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Wt(e.kernelConstraint),this.biasConstraint=Wt(e.biasConstraint),this.kernelRegularizer=gt(e.kernelRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.activityRegularizer=gt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=lt(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=lt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=vv(this.activation.getClassName()),a;return r!=null?a=Vr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=Vr(n,this.kernel.read()),this.bias!=null&&(a=jr(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:Ha(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ut(this.kernelRegularizer),biasRegularizer:ut(this.biasRegularizer),activityRegularizer:ut(this.activityRegularizer),kernelConstraint:Lt(this.kernelConstraint),biasConstraint:Lt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Ey.className="Dense";re.registerClass(Ey);var Cy=class extends qe{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=lt(e);for(let t of e.slice(1))if(t==null)throw new B(`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],Va(e,1)]}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let r=[0];for(let a=2;a<n.rank;++a)r.push(a);r.push(1),n=n.transpose(r)}return Gee(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};Cy.className="Flatten";re.registerClass(Cy);var Ry=class extends qe{constructor(e){super(e);this.supportsMasking=!0,this.activation=Ga(e.activation)}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.activation.apply(n)})}getConfig(){let e={activation:Ha(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};Ry.className="Activation";re.registerClass(Ry);var My=class extends qe{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 z(()=>(e=Pe(e),Uee(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};My.className="RepeatVector";re.registerClass(My);var Fy=class extends qe{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.",r=t.slice(),a=1,s=null;for(let o=0;o<r.length;++o){let l=r[o];if(this.isUnknown(l))if(s===null)s=o;else throw new B("Can only specifiy one unknown dimension.");else a*=l}let i=Va(e);if(s!==null){if(a===0||i%a!=0)throw new B(n);r[s]=i/a}else if(i!==a)throw new B(n);return r}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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=n.shape,a=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};Fy.className="Reshape";re.registerClass(Fy);var Dy=class extends qe{constructor(e){super(e);if(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=_r(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 Gt({ndim:this.dims.length+1})]}computeOutputShape(e){e=lt(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return nt(Pe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Dy.className="Permute";re.registerClass(Dy);var $y=class extends qe{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Pe(e),r=-1;return Wu(pi(n,this.maskValue),r)}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=-1,a=!0,s=Wu(pi(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};$y.className="Masking";re.registerClass($y);var Oy=class extends qe{constructor(e){super(e);if(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(pt(e.inputLength))}this.inputDim=e.inputDim,Ht(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Ht(this.outputDim,"outputDim"),this.embeddingsInitializer=yt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=gt(e.embeddingsRegularizer),this.activityRegularizer=gt(e.activityRegularizer),this.embeddingsConstraint=Wt(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 z(()=>this.maskZero?(e=Pe(e),pi(e,Ue(e))):null)}computeOutputShape(e){if(e=lt(e),this.inputLength==null)return[...e,this.outputDim];let t=pt(this.inputLength);if(t.length!==e.length-1)throw new B(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let r=0;r<t.length;++r){let a=t[r],s=e[r+1];if(a!=null&&s!=null&&a!==s)throw new B(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);a==null&&(t[n]=s),n++}}return[e[0],...t,this.outputDim]}call(e,t){return z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return n.dtype!=="int32"&&(n=kc(n,"int32")),Dv(this.embeddings.read(),n.as1D()).reshape(lt(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:kt(this.embeddingsInitializer),embeddingsRegularizer:ut(this.embeddingsRegularizer),activityRegularizer:ut(this.activityRegularizer),embeddingsConstraint:Lt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Oy.className="Embedding";re.registerClass(Oy);var Mi=class extends qe{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new $e}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 r=0;r<t.length;++r){let a=e[e.length-t.length+r],s=t[r];if(a==null||s==null||a<0||s<0)n.push(null);else if(a===1)n.push(s);else if(s===1)n.push(a);else{if(a!==s)throw new B("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[lt(e)]),e=e,e.length<2)throw new B(`A merge layer should be called on an Array of at least 2 inputs. 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e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Vy.className="Concatenate";re.registerClass(Vy);function zc(e,t){for(;e<0;)e+=t;return e}function _re(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new $e("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 $e("batchDot is not implemented for complex64-type Tensors yet.");let r=e.shape.length,a=t.shape.length;n==null&&(n=[r-1,a-2]);let s=n;return z(()=>{let i;if(r>a){i=r-a;let l=[];for(let c=0;c<i;++c)l.push(1);t=t.reshape(t.shape.concat(l))}else if(a>r){i=a-r;let l=[];for(let c=0;c<i;++c)l.push(1);e=e.reshape(e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=e.mul(t).sum(s[0]):o=e.transpose([1,0]).mul(t).sum(s[1]);else{let l=s[0]!==e.shape.length-1,c=s[1]===t.shape.length-1;o=e.matMul(t,l,c)}if(i>0){let l;r>a?l=r+a-3:l=r-1;let c=[];for(let u=l;u<l+i;++u)c.push(u);o=o.squeeze(c)}return o.shape.length===1&&(o=o.expandDims(1)),o})}var jy=class extends Mi{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 $e("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new B(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new B(`A \`Dot\` layer must be called on exactly 2 inputs, but 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Uy=class extends qe{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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return Sc(()=>Ep(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};Uy.className="GaussianNoise";re.registerClass(Uy);var Hy=class extends qe{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 z(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.rate>0&&this.rate<1?Sc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(Ep(n.shape,1,r))},()=>n,t.training||!1):n})}};Hy.className="GaussianDropout";re.registerClass(Hy);var Gy=class extends qe{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return 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r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return z(()=>{let n=t.training==null?!1:t.training,r=Pe(e),a=r.shape,s=a.length,i=_r(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=ki(1,s);l[o]=a[o];let c=i.slice();c.sort();let u=!v.arraysEqual(c,_r(0,s).slice(0,s-1)),h=()=>{if(u){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,b=this.scale?this.gamma.read().reshape(l):null;return Pc(r,A,y,g,b,this.epsilon)}else return 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extends qe{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=yt(e.betaInitializer||"zeros"),this.gammaInitializer=yt(e.gammaInitializer||"ones"),this.betaRegularizer=gt(e.betaRegularizer),this.gammaRegularizer=gt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=lt(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a<this.axis.length;++a)this.axis[a]<0&&(this.axis[a]+=t);for(let a of this.axis)if(a<0||a>=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==Ba(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(a=>e[a]),r=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,r):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,r):this.beta=null,this.built=!0}call(e,t){let n=Pe(e),r=n.shape,a=r.length;return z(()=>{let s=!0,{mean:i,variance:o}=Sd(n,this.axis,s),l=ki(1,a);for(let f of this.axis)l[f]=r[f];let c=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,u=c(this.gamma.read()),h=c(this.beta.read()),d=[],p=[];for(let f=0;f<a;++f)this.axis.indexOf(f)!==-1?(d.push(r[f]),p.push(1)):(d.push(1),p.push(r[f]));return i=i.tile(d),o=o.tile(d),u=u.tile(p),h=h.tile(p),Pc(n,i,o,h,u,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:kt(this.betaInitializer),gammaInitializer:kt(this.gammaInitializer),betaRegularizer:ut(this.betaRegularizer),gammaRegularizer:ut(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};Xy.className="LayerNormalization";re.registerClass(Xy);function Nre(e,t,n){return z(()=>{if(e.rank!==4)throw new B(`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 B("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=br()),n!=="channelsLast"&&n!=="channelsFirst")throw new B(`Unknown data format: ${n}. 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s==="max"?i=Ku(e,t,n,o):i=Vu(e,t,n,o),a==="channelsFirst"&&(i=nt(i,[0,3,1,2])),i})}function j6(e,t,n,r,a,s){return z(()=>{St(a),Sv(s),Kn(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=br()),s==null&&(s="max"),e=z6(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=ym(e,t,n,o):i=rm(e,t,n,o),a==="channelsFirst"&&(i=nt(i,[0,4,1,2,3])),i})}var U6=class extends qe{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 B(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Ht(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 B(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Ht(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,Kn(this.padding),this.inputSpec=[new Gt({ndim:3})]}computeOutputShape(e){e=lt(e);let t=Ir(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return z(()=>{this.invokeCallHook(e,t),e=Ic(Pe(e),2);let n=this.poolingFunction(Pe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return Oa(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},Zy=class extends U6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"max")}};Zy.className="MaxPooling1D";re.registerClass(Zy);var Yy=class extends U6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"avg")}};Yy.className="AveragePooling1D";re.registerClass(Yy);var H6=class extends qe{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 B(`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];Ht(this.poolSize,"poolSize"),Ht(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,St(this.dataFormat),Kn(this.padding),this.inputSpec=[new Gt({ndim:4})]}computeOutputShape(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Ir(t,this.poolSize[0],this.padding,this.strides[0]),n=Ir(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 z(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(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}},Jy=class extends H6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"max")}};Jy.className="MaxPooling2D";re.registerClass(Jy);var Qy=class extends H6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),a0(e,t,n,r,a,"avg")}};Qy.className="AveragePooling2D";re.registerClass(Qy);var G6=class extends qe{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 B(`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];Ht(this.poolSize,"poolSize"),Ht(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,St(this.dataFormat),Kn(this.padding),this.inputSpec=[new Gt({ndim:5})]}computeOutputShape(e){e=lt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Ir(t,this.poolSize[0],this.padding,this.strides[0]),n=Ir(n,this.poolSize[1],this.padding,this.strides[1]),r=Ir(r,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}call(e,t){return z(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(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}},e2=class extends G6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),j6(e,t,n,r,a,"max")}};e2.className="MaxPooling3D";re.registerClass(e2);var t2=class extends G6{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return St(a),Kn(r),j6(e,t,n,r,a,"avg")}};t2.className="AveragePooling3D";re.registerClass(t2);var q6=class extends qe{constructor(e){super(e);this.inputSpec=[new Gt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new $e}},n2=class extends q6{constructor(e){super(e||{})}call(e,t){return z(()=>{let n=Pe(e);return vt(n,1)})}};n2.className="GlobalAveragePooling1D";re.registerClass(n2);var r2=class extends q6{constructor(e){super(e||{})}call(e,t){return z(()=>{let n=Pe(e);return vn(n,1)})}};r2.className="GlobalMaxPooling1D";re.registerClass(r2);var X6=class extends qe{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,St(this.dataFormat),this.inputSpec=[new Gt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new $e}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},a2=class extends X6{call(e,t){return z(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?vt(n,[1,2]):vt(n,[2,3])})}};a2.className="GlobalAveragePooling2D";re.registerClass(a2);var s2=class extends X6{call(e,t){return z(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?vn(n,[1,2]):vn(n,[2,3])})}};s2.className="GlobalMaxPooling2D";re.registerClass(s2);var K6=class extends qe{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 r=t.layer,a=kr(r,n);delete t.layer;let s={layer:a};return Object.assign(s,t),new e(s)}},i2=class extends K6{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=lt(e),e.length<3)throw new B(`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=lt(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))}call(e,t){return z(()=>(e=Pe(e),B6((n,r)=>[Pe(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};i2.className="TimeDistributed";re.registerClass(i2);function Sre(e){Ni(Lee,"BidirectionalMergeMode",e)}var Tre="concat",o2=class extends K6{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=kr(n),t.goBackwards=t.goBackwards!==!0;let r={};if(r.className=e.layer.getClassName(),r.config=t,this.backwardLayer=kr(r),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?Tre:e.mergeMode,Sre(this.mergeMode),e.weights)throw new $e("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,r,a;return this.returnState&&(a=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,r=[n]):this.mergeMode==null?r=[n,n.slice()]:r=[n],this.returnState?this.mergeMode==null?r.concat(a).concat(a.slice()):[n].concat(a).concat(a.slice()):Sn(r)}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=W6(e,n,r,this.numConstants);if(e=a.inputs,n=a.initialState,r=a.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&r==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new B("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let c=n.map(u=>new 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r=k("size",e,t,n),a=k("dtype",e,t,n),s=k("elementShape",e,t,n),i=k("dynamicSize",e,t,n),o=k("clearAfterRead",e,t,n),l=k("identicalElementShapes",e,t,n),c=k("name",e,t,n),u=new Lne(c,a,r,s,l,i,o);return n.addTensorArray(u),[u.idTensor,ge(1)]}case"TensorArrayWriteV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.write(a,s),[i.idTensor]}case"TensorArrayReadV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n);return[n.getTensorArray(r.id).read(a)]}case"TensorArrayGatherV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("dtype",e,t,n);return[n.getTensorArray(r.id).gather(a,s)]}case"TensorArrayScatterV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.scatter(a,s),[i.idTensor]}case"TensorArrayConcatV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id),s=k("dtype",e,t,n);return[a.concat(s)]}case"TensorArraySplitV3":{let r=k("tensorArrayId",e,t,n),a=k("tensor",e,t,n),s=k("lengths",e,t,n),i=n.getTensorArray(r.id);return i.split(s,a),[i.idTensor]}case"TensorArraySizeV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return[ge(a.size(),"int32")]}case"TensorArrayCloseV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return a.clearAndClose(),[a.idTensor]}case"TensorListSetItem":{let r=k("tensorListId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorList(r.id);return i.setItem(a,s),[i.idTensor]}case"TensorListGetItem":{let r=k("tensorListId",e,t,n),a=k("index",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).getItem(a,s,i)]}case"TensorListScatterV2":case"TensorListScatter":{let r=k("indices",e,t,n),a=k("tensor",e,t,n),s=k("elementShape",e,t,n),i=k("numElements",e,t,n),o=Vne(a,r,s,i);return n.addTensorList(o),[o.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let r=k("elementShape",e,t,n),a=k("elementDType",e,t,n),s;e.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=k(s,e,t,n),o=Bne(r,a,i);return n.addTensorList(o),[o.idTensor]}case"TensorListGather":{let r=k("tensorListId",e,t,n),a=k("indices",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).gather(a,i,s)]}case"TensorListStack":{let r=k("tensorListId",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=k("numElements",e,t,n);return[n.getTensorList(r.id).stack(a,s,i)]}case"TensorListFromTensor":{let r=k("tensor",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=Wne(r,a,s);return n.addTensorList(i),[i.idTensor]}case"TensorListConcat":{let r=k("tensorListId",e,t,n),a=n.getTensorList(r.id),s=k("dtype",e,t,n),i=k("elementShape",e,t,n);return[a.concat(s,i)]}case"TensorListPushBack":{let r=k("tensorListId",e,t,n),a=k("tensor",e,t,n),s=n.getTensorList(r.id);return s.pushBack(a),[s.idTensor]}case"TensorListPopBack":{let 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in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let r=this._signature.inputs[n];t[r.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[r]=Ln(n);return this.graph.nodes[r]==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]=Ln(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},dre=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in 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t=wn.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(wn.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}async load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=await this.handler.load();return this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,n;this.artifacts.userDefinedMetadata!=null&&this.artifacts.userDefinedMetadata.signature!=null?n=this.artifacts.userDefinedMetadata.signature:n=this.artifacts.signature,this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let r=wn.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new y2(Vv.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let a=Vv.Instance.transformGraph(e.modelInitializer);this.initializer=new y2(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=wn.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${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){return this.execute(e,this.outputNodes)}normalizeInputs(e){if(!(e instanceof We)&&!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,r)=>(t[n]=e[r],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]}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 ct(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. 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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=si.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return z(()=>{let t=Jt(ye(e,"float32"),0),n;n=ze.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let r=n.shape;return H(n,r.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},m6=class{},A6=class extends qt{split(e){return new Xre(this,e)}},Xre=class extends A6{constructor(e,t){super();this.upstream=e,this.impl=new Kre(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Kre=class extends w2{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},Yre=class extends qt{decodeUTF8(){return new Zre(this)}},Zre=class extends A6{constructor(e){super();this.upstream=e,this.impl=new Jre(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Jre=class extends w2{constructor(e){super();if(this.upstream=e,J().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=z8();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return J().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},y6=class extends Yre{constructor(e,t={}){super();this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(J().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 ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((e,t)=>{let n=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,n)));else{let r=new FileReader;r.onload=s=>{let i=r.result;if(i instanceof 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cae=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],hae=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],dae=[33,133,362,263,1,78,308],nhe=cae.map(e=>Uc[e]),rhe=hae.map(e=>Uc[e]),ahe=dae.map(e=>Uc[e]);var V2=Xr.leftEyeLower0,U2=Xr.rightEyeLower0,ql={leftBounds:[V2[0],V2[V2.length-1]],rightBounds:[U2[0],U2[U2.length-1]]},N0={count:468,mouth:13,symmetryLine:[13,Xr.midwayBetweenEyes[0]]},C6={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Xl={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function S0(e,t,n,r){for(let a=0;a<B2.length;a++){let{key:s,indices:i}=B2[a],o=Xr[`${n}${s}`];if(!r||r.includes(s))for(let l=0;l<i.length;l++){let c=i[l];e[o[l]]=[t[c][0],t[c][1],(t[c][2]+e[o[l]][2])/2]}}}var j2=class{constructor(t,n,r){var a,s;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=r,this.boxSize=((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((s=t==null?void 0:t.model)==null?void 0:s.inputs[0].shape[2]),this.irisSize=(r==null?void 0:r.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(t,n,r,a){let s=Vc({startPoint:n.startPoint,endPoint:n.endPoint}),i=t.map(h=>[s[0]/this.meshSize*(h[0]-this.meshSize/2),s[1]/this.meshSize*(h[1]-this.meshSize/2),h[2]]),o=r!==0?I0(r,[0,0]):k0,l=r!==0?i.map(h=>[...E6(h,o),h[2]]):i,c=r!==0?T6(a):k0,u=[...Hl({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(h=>[h[0]+Ya(u,c[0]),h[1]+Ya(u,c[1]),h[2]])}getLeftToRightEyeDepthDifference(t){let n=t[ql.leftBounds[0]][2],r=t[ql.rightBounds[0]][2];return n-r}getEyeBox(t,n,r,a,s=!1){let i=v0(_0(this.calculateLandmarksBoundingBox([t[r],t[a]]),this.irisEnlarge)),o=Vc(i),l=ze.cropAndResize(n,[[i.startPoint[1]/this.meshSize,i.startPoint[0]/this.meshSize,i.endPoint[1]/this.meshSize,i.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return s&&fr.flags.IS_BROWSER&&(l=ze.flipLeftRight(l)),{box:i,boxSize:o,crop:l}}getEyeCoords(t,n,r,a=!1){let s=[];for(let i=0;i<Xl.numCoordinates;i++){let o=t[i*3],l=t[i*3+1],c=t[i*3+2];s.push([(a?1-o/this.irisSize:o/this.irisSize)*r[0]+n.startPoint[0],l/this.irisSize*r[1]+n.startPoint[1],c])}return{rawCoords:s,iris:s.slice(Xl.index)}}getAdjustedIrisCoords(t,n,r){let a=t[Xr[`${r}EyeUpper0`][Xl.upperCenter]][2],s=t[Xr[`${r}EyeLower0`][Xl.lowerCenter]][2],i=(a+s)/2;return n.map((o,l)=>{let c=i;return l===2?c=a:l===4&&(c=s),[o[0],o[1],c]})}async predict(t,n){let r=!1,a;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(a=await this.boundingBoxDetector.getBoundingBoxes(t),this.skipped=0),n.videoOptimized&&this.skipped++,!n.videoOptimized||a&&a.boxes&&(!n.face.mesh.enabled||a.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let i of a.boxes)this.storedBoxes.push({startPoint:i.box.startPoint.dataSync(),endPoint:i.box.endPoint.dataSync(),landmarks:i.landmarks,confidence:i.confidence});this.storedBoxes.length>0&&(r=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),r){if(!a||!a.boxes||a.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let i=0;i<this.storedBoxes.length;i++){let o=I6({startPoint:this.storedBoxes[i].startPoint,endPoint:this.storedBoxes[i].endPoint},a.scaleFactor),l=_0(o),c=v0(l),u=this.storedBoxes[i].landmarks.arraySync(),h=this.storedBoxes[i].confidence;this.storedBoxes[i]={...c,confidence:h,landmarks:u}}}a&&a.boxes&&a.boxes.forEach(i=>{i.box.startPoint.dispose(),i.box.endPoint.dispose(),i.landmarks.dispose()});let s=z(()=>this.storedBoxes.map((i,o)=>{let l=i.confidence,c,u=0,h;if(n.face.detector.rotation&&n.face.mesh.enabled&&fr.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=N0.count?N0.symmetryLine:C6.symmetryLine;u=W2(i.landmarks[_],i.landmarks[x]);let N=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],E=ze.rotateWithOffset(t,u,0,T);h=I0(-u,N),n.face.mesh.enabled?c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.meshSize,this.meshSize]).div(255):c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.boxSize,this.boxSize]).div(255)}else{h=k0;let _=t.clone();n.face.mesh.enabled?c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.meshSize,this.meshSize]).div(255):c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:i,faceConfidence:null,boxConfidence:l,confidence:i.confidence,image:c};let[,d,p]=this.meshDetector.predict(c),f=d.dataSync()[0];if(f<n.face.detector.minConfidence)return null;let A=H(p,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:_,boxSize:x,crop:N}=this.getEyeBox(A,c,ql.leftBounds[0],ql.leftBounds[1],!0),{box:T,boxSize:E,crop:F}=this.getEyeBox(A,c,ql.rightBounds[0],ql.rightBounds[1]),L=this.irisModel.predict(rt([N,F])).dataSync(),V=L.slice(0,Xl.numCoordinates*3),{rawCoords:U,iris:j}=this.getEyeCoords(V,_,x,!0),X=L.slice(Xl.numCoordinates*3),{rawCoords:G,iris:ee}=this.getEyeCoords(X,T,E),Y=this.getLeftToRightEyeDepthDifference(A);Math.abs(Y)<30?(S0(A,U,"left",null),S0(A,G,"right",null)):Y<1?S0(A,U,"left",["EyeUpper0","EyeLower0"]):S0(A,G,"right",["EyeUpper0","EyeLower0"]);let ae=this.getAdjustedIrisCoords(A,j,"left"),te=this.getAdjustedIrisCoords(A,ee,"right");A=A.concat(ae).concat(te)}let y=this.transformRawCoords(A,i,u,h);i=_0(this.calculateLandmarksBoundingBox(y),1.5);let g=kn(y);if(n.face.detector.rotation&&n.face.mesh.enabled&&(n.face.description.enabled||n.face.embedding.enabled)&&fr.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=N0.count?N0.symmetryLine:C6.symmetryLine;u=W2(i.landmarks[_],i.landmarks[x]);let N=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],E=ze.rotateWithOffset(t,u,0,T);h=I0(-u,N),c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.meshSize,this.meshSize]).div(255)}let w={coords:g,box:i,faceConfidence:f,boxConfidence:l,image:c,rawCoords:A},b=v0(i);return this.storedBoxes[o]={...b,landmarks:y,confidence:i.confidence,faceConfidence:f},w}));return s=s.filter(i=>i!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(i=>i.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s,landmarks:t}}};var G2=class{constructor(t,n,r,a){this.facePipeline=new j2(t,n,r),this.config=a}async estimateFaces(t,n){let r=await this.facePipeline.predict(t,n),a=[];for(let s of r||[]){if(s.isDisposedInternal)continue;let i=s.coords?s.coords.arraySync():[],o=i.map(h=>[h[0]/t.shape[2],h[1]/t.shape[1],h[2]/this.facePipeline.meshSize]),l={};if(i&&i.length>0)for(let h of Object.keys(Xr))l[h]=Xr[h].map(d=>i[d]);let c=s.box?[Math.max(0,s.box.startPoint[0]),Math.max(0,s.box.startPoint[1]),Math.min(t.shape[2],s.box.endPoint[0])-Math.max(0,s.box.startPoint[0]),Math.min(t.shape[1],s.box.endPoint[1])-Math.max(0,s.box.startPoint[1])]:0,u=s.box?[s.box.startPoint[0]/t.shape[2],s.box.startPoint[1]/t.shape[1],(s.box.endPoint[0]-s.box.startPoint[0])/t.shape[2],(s.box.endPoint[1]-s.box.startPoint[1])/t.shape[1]]:[];a.push({confidence:Math.round(100*s.faceConfidence||100*s.boxConfidence||0)/100,boxConfidence:Math.round(100*s.boxConfidence)/100,faceConfidence:Math.round(100*s.faceConfidence)/100,box:c,boxRaw:u,mesh:i,meshRaw:o,annotations:l,image:s.image?s.image.clone():null}),s.coords&&s.coords.dispose(),s.image&&s.image.dispose()}return a}},$i=[null,null,null];async function q2(e){$i=await Promise.all([!$i[0]&&e.face.enabled?k6(e):null,!$i[1]&&e.face.mesh.enabled?ct(e.face.mesh.modelPath,{fromTFHub:e.face.mesh.modelPath.includes("tfhub.dev")}):null,!$i[2]&&e.face.iris.enabled?ct(e.face.iris.modelPath,{fromTFHub:e.face.iris.modelPath.includes("tfhub.dev")}):null]);let t=new G2($i[0],$i[1],$i[2],e);return e.face.mesh.enabled&&e.debug&&Ne(`load model: ${e.face.mesh.modelPath.match(/\/(.*)\./)[1]}`),e.face.iris.enabled&&e.debug&&Ne(`load model: ${e.face.iris.modelPath.match(/\/(.*)\./)[1]}`),t}var R6=Fi,M6=Uc;var rg={};Jn(rg,{PoseNet:()=>ag,load:()=>sg});function pae(e){let[t,n,r,a]=e;return{offsets:t,heatmap:n,displacementFwd:r,displacementBwd:a}}var X2=class{constructor(t){this.model=t}predict(t){return z(()=>{let r=t.toFloat().div(127.5).sub(1).expandDims(0),s=this.model.predict(r).map(o=>o.squeeze([0])),i=pae(s);return{heatmapScores:i.heatmap.sigmoid(),offsets:i.offsets,displacementFwd:i.displacementFwd,displacementBwd:i.displacementBwd}})}dispose(){this.model.dispose()}};function K2(e){return Math.floor(e/2)}var Z2=class{constructor(t,n){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(K2(t),t);)this.exchange(t,K2(t)),t=K2(t)}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 r=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[n],this.priorityQueue[n]=r}};function fae(e,t,n,r,a,s){let[i,o]=s.shape,l=!0,c=Math.max(n-a,0),u=Math.min(n+a+1,i);for(let h=c;h<u;++h){let d=Math.max(r-a,0),p=Math.min(r+a+1,o);for(let f=d;f<p;++f)if(s.get(h,f,e)>t){l=!1;break}if(!l)break}return l}function F6(e,t,n){let[r,a,s]=n.shape,i=new Z2(r*a*s,({score:o})=>o);for(let o=0;o<r;++o)for(let l=0;l<a;++l)for(let c=0;c<s;++c){let u=n.get(o,l,c);u<e||fae(c,u,o,l,t,n)&&i.enqueue({score:u,part:{heatmapY:o,heatmapX:l,id:c}})}return i}var Kl=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],Zl=Kl.length,jc=Kl.reduce((e,t,n)=>(e[t]=n,e),{}),mae=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],bhe=mae.map(([e,t])=>[jc[e],jc[t]]),$6=[["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 Y2(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+Zl)}}function T0(e,t,n){let{heatmapY:r,heatmapX:a,id:s}=e,{y:i,x:o}=Y2(r,a,s,n);return{x:e.heatmapX*t+o,y:e.heatmapY*t+i}}function J2(e,t,n){return e<t?t:e>n?n:e}function D6(e,t,n,r){let a=n-e,s=r-t;return a*a+s*s}function Q2(e,t){return{x:e.x+t.x,y:e.y+t.y}}function O6(e,t){let n=t.shape[0],r=new Float32Array(n);for(let a=0;a<n;a++){let s=t.get(a,0),i=t.get(a,1);r[a]=e.get(s,i,a)}return r}function Aae(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+Zl)}}function yae(e,t){let n=[];for(let r=0;r<Zl;r++){let a=e.get(r,0).valueOf(),s=e.get(r,1).valueOf(),{x:i,y:o}=Aae(a,s,r,t);n.push(o),n.push(i)}return kn(n,[Zl,2])}function z6(e,t,n){return z(()=>e.toTensor().mul(ge(t,"int32")).toFloat().add(yae(e,n)))}function gae(e,t){return z(()=>{let n=e.div(ge(t,"int32"));return e.sub(n.mul(ge(t,"int32")))})}function P6(e){let[t,n,r]=e.shape;return z(()=>{let s=e.reshape([t*n,r]).argMax(0),i=s.div(ge(n,"int32")).expandDims(1),o=gae(s,n).expandDims(1);return rt([i,o],1)})}var L6=$6.map(([e,t])=>[jc[e],jc[t]]),eg=L6.map(([,e])=>e),W6=L6.map(([e])=>e),xae=16;function wae(e,t,n){let r=n.shape[2]/2;return{y:n.get(t.y,t.x,e),x:n.get(t.y,t.x,r+e)}}function tg(e,t,n,r){return{y:J2(Math.round(e.y/t),0,n-1),x:J2(Math.round(e.x/t),0,r-1)}}function B6(e,t,n,r,a,s,i,o=2){let[l,c]=r.shape,u=tg(t.position,s,l,c),h=wae(e,u,i),p=Q2(t.position,h);for(let A=0;A<o;A++){let y=tg(p,s,l,c),g=Y2(y.y,y.x,n,a);p=Q2({x:y.x*s,y:y.y*s},{x:g.x,y:g.y})}let f=tg(p,s,l,c),m=r.get(f.y,f.x,n);return{position:p,part:Kl[n],score:m}}function V6(e,t,n,r,a,s){let i=t.shape[2],o=eg.length,l=new Array(i),{part:c,score:u}=e,h=T0(c,r,n);l[c.id]={score:u,part:Kl[c.id],position:h};for(let d=o-1;d>=0;--d){let p=eg[d],f=W6[d];l[p]&&!l[f]&&(l[f]=B6(d,l[p],f,t,n,r,s))}for(let d=0;d<o;++d){let p=W6[d],f=eg[d];l[p]&&!l[f]&&(l[f]=B6(d,l[p],f,t,n,r,a))}return l}async function U6(e,t,n){let r=0,a=P6(e),s=await Promise.all([e.buffer(),t.buffer(),a.buffer()]),i=s[0],o=s[1],l=s[2],c=z6(l,xae,o),u=await c.buffer(),d=Array.from(O6(i,l)).map((f,m)=>(r+=f,{position:{y:u.get(m,0),x:u.get(m,1)},part:Kl[m],score:f})),p=d.filter(f=>f.score>n);return a.dispose(),c.dispose(),{keypoints:p,score:r/d.length}}var bae=1,j6=16;function H6(e,t,{x:n,y:r},a){return e.some(({keypoints:s})=>{let i=s[a].position;return D6(r,n,i.y,i.x)<=t})}function _ae(e,t,n){return n.reduce((a,{position:s,score:i},o)=>(H6(e,t,s,o)||(a+=i),a),0)/n.length}function G6(e,t,n,r,a,s,i){let o=[],l=F6(i,bae,e),c=a^2;for(;o.length<s&&!l.empty();){let u=l.dequeue(),h=T0(u.part,j6,t);if(H6(o,c,h,u.part.id))continue;let d=V6(u,e,t,j6,n,r),p=_ae(o,c,d);p>i&&o.push({keypoints:d,score:Math.round(100*p)/100})}return o}async function q6(e){return Promise.all(e.map(t=>t.buffer()))}function vae(e,t,n){return{score:e.score,keypoints:e.keypoints.map(({score:r,part:a,position:s})=>({score:r,part:a,position:{x:Math.trunc(s.x*n),y:Math.trunc(s.y*t)}}))}}function X6(e,[t,n]){let r=e.squeeze(0),a=r.resizeBilinear([t,n]);return r.dispose(),a}function ng(e,[t,n],[r,a]){return e.map(i=>vae(i,t/r,n/a))}async function kae(e,t,n,r){return new Promise(async a=>{let s=await q6([t.heatmapScores,t.offsets,t.displacementFwd,t.displacementBwd]),i=s[0],o=s[1],l=s[2],c=s[3],u=await G6(i,o,l,c,n.body.nmsRadius,n.body.maxDetections,n.body.scoreThreshold),h=ng(u,[e.shape[1],e.shape[2]],[r,r]);a(h)})}async function Iae(e,t,n,r){return new Promise(async a=>{let s=await U6(t.heatmapScores,t.offsets,n.body.scoreThreshold),i=ng([s],[e.shape[1],e.shape[2]],[r,r]);a(i)})}var ag=class{constructor(t){this.baseModel=t,this.inputSize=t.model.inputs[0].shape[1],this.inputSize<128&&(this.inputSize=257)}async estimatePoses(t,n){let r=X6(t,[this.inputSize,this.inputSize]),a=this.baseModel.predict(r,n),s=n.body.maxDetections<2?await Iae(t,a,n,this.inputSize):await kae(t,a,n,this.inputSize);return a.heatmapScores.dispose(),a.offsets.dispose(),a.displacementFwd.dispose(),a.displacementBwd.dispose(),r.dispose(),s}dispose(){this.baseModel.dispose()}};async function sg(e){let t=await ct(e.body.modelPath),n=new X2(t);return e.debug&&Ne(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`),new ag(n)}var cg={};Jn(cg,{HandPose:()=>dg,load:()=>pg});function E0(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function Hc(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function K6(e,t,n){let r=t.shape[1],a=t.shape[2],s=[[e.startPoint[1]/r,e.startPoint[0]/a,e.endPoint[1]/r,e.endPoint[0]/a]];return ze.cropAndResize(t,s,[0],n)}function Z6(e,t){let 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g=A.dataSync()[0];if(A.dispose(),g>=n.hand.minConfidence){let w=H(y,[-1,3]),b=w.arraySync();y.dispose(),w.dispose();let _=this.transformRawCoords(b,p,l,d),x=this.getBoxForHandLandmarks(_);this.storedBoxes[i]=x;let N={landmarks:_,confidence:g,box:{topLeft:x.startPoint,bottomRight:x.endPoint}};s.push(N)}else this.storedBoxes[i]=null;y.dispose()}else{let l=C0(R0(o),t4),c={confidence:o.confidence,box:{topLeft:l.startPoint,bottomRight:l.endPoint}};s.push(c)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s}}};var 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a4=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],s4=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var hr;async function mg(e){return hr||(hr=await ct(e.body.modelPath),hr.width=parseInt(hr.signature.inputs["input_1:0"].tensorShape.dim[2].size),hr.height=parseInt(hr.signature.inputs["input_1:0"].tensorShape.dim[1].size),e.debug&&Ne(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`)),hr}async function Ag(e,t){if(!hr||!t.body.enabled)return null;let n={width:e.shape[2],height:e.shape[1]},r=ze.resizeBilinear(e,[hr.width,hr.height],!1),a=me(r,[255]);r.dispose();let s;if(t.profile){let u=await an(()=>hr.predict(a));s=u.result.find(h=>h.size===195||h.size===155).dataSync(),u.result.forEach(h=>h.dispose()),fn("blazepose",u)}else{let u=await hr.predict(a);s=u.find(h=>h.size===195||h.size===155).dataSync(),u.forEach(h=>h.dispose())}a.dispose();let i=[],o=s.length===195?a4:s4,l=5;for(let 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t=bn.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(bn.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}async load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=await this.handler.load();return this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,n;this.artifacts.userDefinedMetadata!=null&&this.artifacts.userDefinedMetadata.signature!=null?n=this.artifacts.userDefinedMetadata.signature:n=this.artifacts.signature,this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let r=bn.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new _2(_4.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let a=_4.Instance.transformGraph(e.modelInitializer);this.initializer=new _2(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=bn.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${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){return this.execute(e,this.outputNodes)}normalizeInputs(e){if(!(e instanceof We)&&!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 ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,r)=>(t[n]=e[r],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function ct(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&e.load==null&&(e.endsWith("/")||(e=e+"/"),e=`${e}${Xae}${qae}`);let n=new R4(e,t);return await n.load(),n}var Kae="3.3.0",M4={};Me(M4,{CSVDataset:()=>D4,Dataset:()=>jl,FileDataSource:()=>$4,TextLineDataset:()=>F4,URLDataSource:()=>O4,array:()=>Zae,csv:()=>Jae,func:()=>Qae,generator:()=>ese,microphone:()=>nse,version_data:()=>rse,webcam:()=>tse,zip:()=>Yae});var ase=Ki(qg()),sse=Ki(qg());function ise(e,t){return l0(e,t)}function l0(e,t,n=new Map,r=new Set){if(e==null)return null;if(r.has(e))throw new Error("Circular references are not supported.");if(n.has(e))return n.get(e);let a=t(e);if(a.recurse&&a.value!==null)throw new Error("A deep map function may not return both a value and recurse=true.");if(a.recurse)if(Ul(e)){let s=Array.isArray(e)?[]:{};r.add(e);for(let i in e){let o=e[i],l=l0(o,t,n,r);s[i]=l}return r.delete(e),s}else throw new Error(`Can't recurse into non-iterable type: ${e}`);else return n.set(e,a.value),a.value}function ose(e,t=P4){return z4(e,t)}function z4(e,t,n=new Set){let r=e[0];if(n.has(r))throw new Error("Circular references are not supported.");let a=t(e);if(a.recurse&&a.value!==null)throw new Error("A deep zip function may not return both a value and recurse=true.");if(a.recurse)if(Ul(r)){let s=Array.isArray(r)?[]:{};n.add(r);for(let i in r){let o=e.map(c=>c[i]),l=z4(o,t,n);s[i]=l}return n.delete(r),s}else throw new Error(`Can't recurse into non-iterable type: ${r}`);else return a.value}function P4(e){return e===null?null:Ul(e[0])?{value:null,recurse:!0}:{value:e,recurse:!1}}async function L4(e,t){let n=new Map;l0(e,t,n);for(let r of Array.from(n.keys())){let a=n.get(r);if(v.isPromise(a)){let s=await a;n.set(r,s)}}return l0(e,t,n)}function Ul(e){return e!=null&&!ArrayBuffer.isView(e)&&(Array.isArray(e)||typeof e=="object"&&!(e instanceof We))}function use(e){return e==null||lse(e)||Array.isArray(e)||typeof e=="object"&&e instanceof 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Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},q4=class extends qt{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(J().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new q4(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 r=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(r,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let r=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(r,[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(r=>{let a=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&r({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(a),r({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((r,a)=>n.set(r,a*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),yr(n,t)}},X4=class extends qt{constructor(e,t){super();if(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=sn([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,r=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,a=(1-n)/2,s=(1-r)/2,i=a+n,o=r+s;this.cropBox=kn([s,a,o,i],[1,4])}else this.cropBox=kn([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(J().get("IS_NODE"))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 X4(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=si.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return z(()=>{let t=Jt(ye(e,"float32"),0),n;n=ze.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let r=n.shape;return H(n,r.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},K4=class{},Z4=class extends qt{split(e){return new Tse(this,e)}},Tse=class extends Z4{constructor(e,t){super();this.upstream=e,this.impl=new Ese(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Ese=class extends I2{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},Rse=class extends qt{decodeUTF8(){return new Cse(this)}},Cse=class extends Z4{constructor(e){super();this.upstream=e,this.impl=new Mse(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Mse=class extends I2{constructor(e){super();if(this.upstream=e,J().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=y9();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return J().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},Y4=class extends Rse{constructor(e,t={}){super();this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(J().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((e,t)=>{let n=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,n)));else{let r=new FileReader;r.onload=s=>{let i=r.result;if(i instanceof ArrayBuffer&&(i=new Uint8Array(i)),!(i instanceof Uint8Array))return t(new TypeError("FileReader returned unknown type."));e(i)},r.onabort=s=>t(new Error("Aborted")),r.onerror=s=>t(new Error(s.type));let a=this.file.slice(this.offset,n);r.readAsArrayBuffer(a)}this.offset=n}),done:!1}}};async function Dse(e,t={}){let n,r;typeof e=="string"?n=e:(n=e.url,r=Fse(e));let a=await v.fetch(n,r);if(a.ok){let s=new Uint8Array(await a.arrayBuffer());return new Y4(s,t)}else throw new Error(a.statusText)}var Fse=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 J4(e){return typeof e=="string"&&e.substr(0,7)==="file://"}var $4=class extends K4{constructor(e,t={}){super();this.input=e,this.options=t}async iterator(){if(J4(this.input)&&J().get("IS_NODE")){let e=require("fs");this.input=e.readFileSync(this.input.substr(7))}return new Y4(this.input,this.options)}},O4=class extends K4{constructor(e,t={}){super();this.url=e,this.fileOptions=t}async iterator(){return J4(this.url)?new $4(this.url,this.fileOptions).iterator():Dse(this.url,this.fileOptions)}};function Jae(e,t={}){return new D4(new O4(e),t)}function Qae(e){let t=k2(e);return Wn(async()=>t)}function ese(e){return Wn(async()=>{let t=await e();return k2(()=>t.next())})}async function tse(e,t){return X4.create(e,t)}async function nse(e){return q4.create(e)}var rse="3.3.0",$se={tfjs:(sf==null?void 0:sf.version)||void 0,"tfjs-core":(of==null?void 0:of.version)||void 0,"tfjs-data":(lf==null?void 0:lf.version)||void 0,"tfjs-layers":(uf==null?void 0:uf.version)||void 0,"tfjs-converter":(cf==null?void 0:cf.version)||void 0,"tfjs-backend-cpu":Jw||void 0,"tfjs-backend-webgl":b3||void 0,"tfjs-backend-wasm":cv||void 0};var 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Use=[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],Hse=[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],Gse=[33,133,362,263,1,78,308],Ode=Use.map(e=>jc[e]),zde=Hse.map(e=>jc[e]),Pde=Gse.map(e=>jc[e]);var q2=Xr.leftEyeLower0,X2=Xr.rightEyeLower0,ql={leftBounds:[q2[0],q2[q2.length-1]],rightBounds:[X2[0],X2[X2.length-1]]},N0={count:468,mouth:13,symmetryLine:[13,Xr.midwayBetweenEyes[0]]},c8={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Xl={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function S0(e,t,n,r){for(let a=0;a<G2.length;a++){let{key:s,indices:i}=G2[a],o=Xr[`${n}${s}`];if(!r||r.includes(s))for(let l=0;l<i.length;l++){let c=i[l];e[o[l]]=[t[c][0],t[c][1],(t[c][2]+e[o[l]][2])/2]}}}var K2=class{constructor(t,n,r){var a,s;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=r,this.boxSize=((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((s=t==null?void 0:t.model)==null?void 0:s.inputs[0].shape[2]),this.irisSize=(r==null?void 0:r.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(t,n,r,a){let s=Vc({startPoint:n.startPoint,endPoint:n.endPoint}),i=t.map(h=>[s[0]/this.meshSize*(h[0]-this.meshSize/2),s[1]/this.meshSize*(h[1]-this.meshSize/2),h[2]]),o=r!==0?I0(r,[0,0]):k0,l=r!==0?i.map(h=>[...u8(h,o),h[2]]):i,c=r!==0?l8(a):k0,u=[...Hl({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(h=>[h[0]+Ya(u,c[0]),h[1]+Ya(u,c[1]),h[2]])}getLeftToRightEyeDepthDifference(t){let n=t[ql.leftBounds[0]][2],r=t[ql.rightBounds[0]][2];return n-r}getEyeBox(t,n,r,a,s=!1){let i=v0(_0(this.calculateLandmarksBoundingBox([t[r],t[a]]),this.irisEnlarge)),o=Vc(i),l=ze.cropAndResize(n,[[i.startPoint[1]/this.meshSize,i.startPoint[0]/this.meshSize,i.endPoint[1]/this.meshSize,i.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return s&&fr.flags.IS_BROWSER&&(l=ze.flipLeftRight(l)),{box:i,boxSize:o,crop:l}}getEyeCoords(t,n,r,a=!1){let s=[];for(let i=0;i<Xl.numCoordinates;i++){let o=t[i*3],l=t[i*3+1],c=t[i*3+2];s.push([(a?1-o/this.irisSize:o/this.irisSize)*r[0]+n.startPoint[0],l/this.irisSize*r[1]+n.startPoint[1],c])}return{rawCoords:s,iris:s.slice(Xl.index)}}getAdjustedIrisCoords(t,n,r){let a=t[Xr[`${r}EyeUpper0`][Xl.upperCenter]][2],s=t[Xr[`${r}EyeLower0`][Xl.lowerCenter]][2],i=(a+s)/2;return n.map((o,l)=>{let c=i;return l===2?c=a:l===4&&(c=s),[o[0],o[1],c]})}async predict(t,n){let r=!1,a;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(a=await this.boundingBoxDetector.getBoundingBoxes(t),this.skipped=0),n.videoOptimized&&this.skipped++,!n.videoOptimized||a&&a.boxes&&(!n.face.mesh.enabled||a.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let i of a.boxes)this.storedBoxes.push({startPoint:i.box.startPoint.dataSync(),endPoint:i.box.endPoint.dataSync(),landmarks:i.landmarks,confidence:i.confidence});this.storedBoxes.length>0&&(r=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),r){if(!a||!a.boxes||a.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let i=0;i<this.storedBoxes.length;i++){let o=s8({startPoint:this.storedBoxes[i].startPoint,endPoint:this.storedBoxes[i].endPoint},a.scaleFactor),l=_0(o),c=v0(l),u=this.storedBoxes[i].landmarks.arraySync(),h=this.storedBoxes[i].confidence;this.storedBoxes[i]={...c,confidence:h,landmarks:u}}}a&&a.boxes&&a.boxes.forEach(i=>{i.box.startPoint.dispose(),i.box.endPoint.dispose(),i.landmarks.dispose()});let s=z(()=>this.storedBoxes.map((i,o)=>{let l=i.confidence,c,u=0,h;if(n.face.detector.rotation&&n.face.mesh.enabled&&fr.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=N0.count?N0.symmetryLine:c8.symmetryLine;u=H2(i.landmarks[_],i.landmarks[x]);let N=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],E=ze.rotateWithOffset(t,u,0,T);h=I0(-u,N),n.face.mesh.enabled?c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.meshSize,this.meshSize]).div(255):c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.boxSize,this.boxSize]).div(255)}else{h=k0;let _=t.clone();n.face.mesh.enabled?c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.meshSize,this.meshSize]).div(255):c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:i,faceConfidence:null,boxConfidence:l,confidence:i.confidence,image:c};let[,d,p]=this.meshDetector.predict(c),f=d.dataSync()[0];if(f<n.face.detector.minConfidence)return null;let A=H(p,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:_,boxSize:x,crop:N}=this.getEyeBox(A,c,ql.leftBounds[0],ql.leftBounds[1],!0),{box:T,boxSize:E,crop:F}=this.getEyeBox(A,c,ql.rightBounds[0],ql.rightBounds[1]),L=this.irisModel.predict(rt([N,F])).dataSync(),V=L.slice(0,Xl.numCoordinates*3),{rawCoords:j,iris:U}=this.getEyeCoords(V,_,x,!0),X=L.slice(Xl.numCoordinates*3),{rawCoords:G,iris:ee}=this.getEyeCoords(X,T,E),Y=this.getLeftToRightEyeDepthDifference(A);Math.abs(Y)<30?(S0(A,j,"left",null),S0(A,G,"right",null)):Y<1?S0(A,j,"left",["EyeUpper0","EyeLower0"]):S0(A,G,"right",["EyeUpper0","EyeLower0"]);let ae=this.getAdjustedIrisCoords(A,U,"left"),te=this.getAdjustedIrisCoords(A,ee,"right");A=A.concat(ae).concat(te)}let y=this.transformRawCoords(A,i,u,h);i=_0(this.calculateLandmarksBoundingBox(y),1.5);let g=kn(y);if(n.face.detector.rotation&&n.face.mesh.enabled&&(n.face.description.enabled||n.face.embedding.enabled)&&fr.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=N0.count?N0.symmetryLine:c8.symmetryLine;u=H2(i.landmarks[_],i.landmarks[x]);let N=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],E=ze.rotateWithOffset(t,u,0,T);h=I0(-u,N),c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.meshSize,this.meshSize]).div(255)}let b={coords:g,box:i,faceConfidence:f,boxConfidence:l,image:c,rawCoords:A},w=v0(i);return this.storedBoxes[o]={...w,landmarks:y,confidence:i.confidence,faceConfidence:f},b}));return s=s.filter(i=>i!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(i=>i.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s,landmarks:t}}};var Y2=class{constructor(t,n,r,a){this.facePipeline=new K2(t,n,r),this.config=a}async estimateFaces(t,n){let r=await this.facePipeline.predict(t,n),a=[];for(let s of r||[]){if(s.isDisposedInternal)continue;let i=s.coords?s.coords.arraySync():[],o=i.map(h=>[h[0]/t.shape[2],h[1]/t.shape[1],h[2]/this.facePipeline.meshSize]),l={};if(i&&i.length>0)for(let h of Object.keys(Xr))l[h]=Xr[h].map(d=>i[d]);let c=s.box?[Math.max(0,s.box.startPoint[0]),Math.max(0,s.box.startPoint[1]),Math.min(t.shape[2],s.box.endPoint[0])-Math.max(0,s.box.startPoint[0]),Math.min(t.shape[1],s.box.endPoint[1])-Math.max(0,s.box.startPoint[1])]:0,u=s.box?[s.box.startPoint[0]/t.shape[2],s.box.startPoint[1]/t.shape[1],(s.box.endPoint[0]-s.box.startPoint[0])/t.shape[2],(s.box.endPoint[1]-s.box.startPoint[1])/t.shape[1]]:[];a.push({confidence:Math.round(100*s.faceConfidence||100*s.boxConfidence||0)/100,boxConfidence:Math.round(100*s.boxConfidence)/100,faceConfidence:Math.round(100*s.faceConfidence)/100,box:c,boxRaw:u,mesh:i,meshRaw:o,annotations:l,image:s.image?s.image.clone():null}),s.coords&&s.coords.dispose(),s.image&&s.image.dispose()}return a}},Di=[null,null,null];async function J2(e){Di=await Promise.all([!Di[0]&&e.face.enabled?a8(e):null,!Di[1]&&e.face.mesh.enabled?ct(e.face.mesh.modelPath,{fromTFHub:e.face.mesh.modelPath.includes("tfhub.dev")}):null,!Di[2]&&e.face.iris.enabled?ct(e.face.iris.modelPath,{fromTFHub:e.face.iris.modelPath.includes("tfhub.dev")}):null]);let t=new Y2(Di[0],Di[1],Di[2],e);return e.face.mesh.enabled&&e.debug&&Ne(`load model: ${e.face.mesh.modelPath.match(/\/(.*)\./)[1]}`),e.face.iris.enabled&&e.debug&&Ne(`load model: ${e.face.iris.modelPath.match(/\/(.*)\./)[1]}`),t}var h8=Fi,d8=jc;var lg={};Jn(lg,{PoseNet:()=>ug,load:()=>cg});function qse(e){let[t,n,r,a]=e;return{offsets:t,heatmap:n,displacementFwd:r,displacementBwd:a}}var Q2=class{constructor(t){this.model=t}predict(t){return z(()=>{let r=t.toFloat().div(127.5).sub(1).expandDims(0),s=this.model.predict(r).map(o=>o.squeeze([0])),i=qse(s);return{heatmapScores:i.heatmap.sigmoid(),offsets:i.offsets,displacementFwd:i.displacementFwd,displacementBwd:i.displacementBwd}})}dispose(){this.model.dispose()}};function eg(e){return Math.floor(e/2)}var tg=class{constructor(t,n){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(eg(t),t);)this.exchange(t,eg(t)),t=eg(t)}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 r=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[n],this.priorityQueue[n]=r}};function Xse(e,t,n,r,a,s){let[i,o]=s.shape,l=!0,c=Math.max(n-a,0),u=Math.min(n+a+1,i);for(let h=c;h<u;++h){let d=Math.max(r-a,0),p=Math.min(r+a+1,o);for(let f=d;f<p;++f)if(s.get(h,f,e)>t){l=!1;break}if(!l)break}return l}function p8(e,t,n){let[r,a,s]=n.shape,i=new tg(r*a*s,({score:o})=>o);for(let o=0;o<r;++o)for(let l=0;l<a;++l)for(let c=0;c<s;++c){let u=n.get(o,l,c);u<e||Xse(c,u,o,l,t,n)&&i.enqueue({score:u,part:{heatmapY:o,heatmapX:l,id:c}})}return i}var Kl=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],Zl=Kl.length,Uc=Kl.reduce((e,t,n)=>(e[t]=n,e),{}),Kse=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],tpe=Kse.map(([e,t])=>[Uc[e],Uc[t]]),f8=[["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 ng(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+Zl)}}function T0(e,t,n){let{heatmapY:r,heatmapX:a,id:s}=e,{y:i,x:o}=ng(r,a,s,n);return{x:e.heatmapX*t+o,y:e.heatmapY*t+i}}function rg(e,t,n){return e<t?t:e>n?n:e}function m8(e,t,n,r){let a=n-e,s=r-t;return a*a+s*s}function ag(e,t){return{x:e.x+t.x,y:e.y+t.y}}function A8(e,t){let n=t.shape[0],r=new Float32Array(n);for(let a=0;a<n;a++){let s=t.get(a,0),i=t.get(a,1);r[a]=e.get(s,i,a)}return r}function Zse(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+Zl)}}function Yse(e,t){let n=[];for(let r=0;r<Zl;r++){let a=e.get(r,0).valueOf(),s=e.get(r,1).valueOf(),{x:i,y:o}=Zse(a,s,r,t);n.push(o),n.push(i)}return kn(n,[Zl,2])}function y8(e,t,n){return z(()=>e.toTensor().mul(ge(t,"int32")).toFloat().add(Yse(e,n)))}function Jse(e,t){return z(()=>{let n=e.div(ge(t,"int32"));return e.sub(n.mul(ge(t,"int32")))})}function g8(e){let[t,n,r]=e.shape;return z(()=>{let s=e.reshape([t*n,r]).argMax(0),i=s.div(ge(n,"int32")).expandDims(1),o=Jse(s,n).expandDims(1);return rt([i,o],1)})}var x8=f8.map(([e,t])=>[Uc[e],Uc[t]]),sg=x8.map(([,e])=>e),b8=x8.map(([e])=>e),Qse=16;function eie(e,t,n){let r=n.shape[2]/2;return{y:n.get(t.y,t.x,e),x:n.get(t.y,t.x,r+e)}}function ig(e,t,n,r){return{y:rg(Math.round(e.y/t),0,n-1),x:rg(Math.round(e.x/t),0,r-1)}}function w8(e,t,n,r,a,s,i,o=2){let[l,c]=r.shape,u=ig(t.position,s,l,c),h=eie(e,u,i),p=ag(t.position,h);for(let A=0;A<o;A++){let y=ig(p,s,l,c),g=ng(y.y,y.x,n,a);p=ag({x:y.x*s,y:y.y*s},{x:g.x,y:g.y})}let f=ig(p,s,l,c),m=r.get(f.y,f.x,n);return{position:p,part:Kl[n],score:m}}function _8(e,t,n,r,a,s){let i=t.shape[2],o=sg.length,l=new Array(i),{part:c,score:u}=e,h=T0(c,r,n);l[c.id]={score:u,part:Kl[c.id],position:h};for(let d=o-1;d>=0;--d){let p=sg[d],f=b8[d];l[p]&&!l[f]&&(l[f]=w8(d,l[p],f,t,n,r,s))}for(let d=0;d<o;++d){let p=b8[d],f=sg[d];l[p]&&!l[f]&&(l[f]=w8(d,l[p],f,t,n,r,a))}return l}async function v8(e,t,n){let r=0,a=g8(e),s=await Promise.all([e.buffer(),t.buffer(),a.buffer()]),i=s[0],o=s[1],l=s[2],c=y8(l,Qse,o),u=await c.buffer(),d=Array.from(A8(i,l)).map((f,m)=>(r+=f,{position:{y:u.get(m,0),x:u.get(m,1)},part:Kl[m],score:f})),p=d.filter(f=>f.score>n);return a.dispose(),c.dispose(),{keypoints:p,score:r/d.length}}var tie=1,k8=16;function I8(e,t,{x:n,y:r},a){return e.some(({keypoints:s})=>{let i=s[a].position;return m8(r,n,i.y,i.x)<=t})}function nie(e,t,n){return n.reduce((a,{position:s,score:i},o)=>(I8(e,t,s,o)||(a+=i),a),0)/n.length}function N8(e,t,n,r,a,s,i){let o=[],l=p8(i,tie,e),c=a^2;for(;o.length<s&&!l.empty();){let u=l.dequeue(),h=T0(u.part,k8,t);if(I8(o,c,h,u.part.id))continue;let d=_8(u,e,t,k8,n,r),p=nie(o,c,d);p>i&&o.push({keypoints:d,score:Math.round(100*p)/100})}return o}async function S8(e){return Promise.all(e.map(t=>t.buffer()))}function 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r=T8(t,[this.inputSize,this.inputSize]),a=this.baseModel.predict(r,n),s=n.body.maxDetections<2?await sie(t,a,n,this.inputSize):await aie(t,a,n,this.inputSize);return a.heatmapScores.dispose(),a.offsets.dispose(),a.displacementFwd.dispose(),a.displacementBwd.dispose(),r.dispose(),s}dispose(){this.baseModel.dispose()}};async function cg(e){let t=await ct(e.body.modelPath),n=new Q2(t);return e.debug&&Ne(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`),new ug(n)}var mg={};Jn(mg,{HandPose:()=>yg,load:()=>gg});function E0(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function Hc(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function E8(e,t,n){let r=t.shape[1],a=t.shape[2],s=[[e.startPoint[1]/r,e.startPoint[0]/a,e.endPoint[1]/r,e.endPoint[0]/a]];return ze.cropAndResize(t,s,[0],n)}function C8(e,t){let 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g=A.dataSync()[0];if(A.dispose(),g>=n.hand.minConfidence){let b=H(y,[-1,3]),w=b.arraySync();y.dispose(),b.dispose();let _=this.transformRawCoords(w,p,l,d),x=this.getBoxForHandLandmarks(_);this.storedBoxes[i]=x;let N={landmarks:_,confidence:g,box:{topLeft:x.startPoint,bottomRight:x.endPoint}};s.push(N)}else this.storedBoxes[i]=null;y.dispose()}else{let l=C0(R0(o),$8),c={confidence:o.confidence,box:{topLeft:l.startPoint,bottomRight:l.endPoint}};s.push(c)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s}}};var 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P8=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],L8=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var hr;async function bg(e){return hr||(hr=await ct(e.body.modelPath),hr.width=parseInt(hr.signature.inputs["input_1:0"].tensorShape.dim[2].size),hr.height=parseInt(hr.signature.inputs["input_1:0"].tensorShape.dim[1].size),e.debug&&Ne(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`)),hr}async function wg(e,t){if(!hr||!t.body.enabled)return null;let n={width:e.shape[2],height:e.shape[1]},r=ze.resizeBilinear(e,[hr.width,hr.height],!1),a=me(r,[255]);r.dispose();let s;if(t.profile){let u=await an(()=>hr.predict(a));s=u.result.find(h=>h.size===195||h.size===155).dataSync(),u.result.forEach(h=>h.dispose()),fn("blazepose",u)}else{let u=await hr.predict(a);s=u.find(h=>h.size===195||h.size===155).dataSync(),u.forEach(h=>h.dispose())}a.dispose();let i=[],o=s.length===195?P8:L8,l=5;for(let 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s=Math.abs(r.annotations.leftEyeIris[3][0]-r.annotations.leftEyeIris[1][0])/2,i=Math.abs(r.annotations.leftEyeIris[4][1]-r.annotations.leftEyeIris[2][1])/2;n.ellipse(r.annotations.leftEyeIris[0][0],r.annotations.leftEyeIris[0][1],s,i,0,0,2*Math.PI),n.stroke(),ie.fillPolygons&&(n.fillStyle=ie.useDepth?"rgba(255, 255, 200, 0.3)":ie.color,n.fill())}if(r.annotations&&r.annotations.rightEyeIris){n.strokeStyle=ie.useDepth?"rgba(255, 200, 255, 0.3)":ie.color,n.beginPath();let s=Math.abs(r.annotations.rightEyeIris[3][0]-r.annotations.rightEyeIris[1][0])/2,i=Math.abs(r.annotations.rightEyeIris[4][1]-r.annotations.rightEyeIris[2][1])/2;n.ellipse(r.annotations.rightEyeIris[0][0],r.annotations.rightEyeIris[0][1],s,i,0,0,2*Math.PI),n.stroke(),ie.fillPolygons&&(n.fillStyle=ie.useDepth?"rgba(255, 255, 200, 0.3)":ie.color,n.fill())}}}}}var Qa=[];async function p4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round";for(let r=0;r<t.length;r++){if(!Qa[r]&&ie.bufferedOutput&&(Qa[r]={...t[r]}),n.strokeStyle=ie.color,n.lineWidth=ie.lineWidth,ie.drawPoints)for(let a=0;a<t[r].keypoints.length;a++)n.fillStyle=ie.useDepth&&t[r].keypoints[a].position.z?`rgba(${127.5+2*t[r].keypoints[a].position.z}, ${127.5-2*t[r].keypoints[a].position.z}, 255, 0.5)`:ie.color,ie.bufferedOutput?(Qa[r].keypoints[a][0]=(Qa[r].keypoints[a][0]+t[r].keypoints[a].position.x)/2,Qa[r].keypoints[a][1]=(Qa[r].keypoints[a][1]+t[r].keypoints[a].position.y)/2,z0(n,Qa[r].keypoints[a][0],Qa[r].keypoints[a][1])):z0(n,t[r].keypoints[a].position.x,t[r].keypoints[a].position.y);if(ie.drawLabels&&(n.font=ie.font,t[r].keypoints))for(let a of t[r].keypoints)n.fillStyle=ie.useDepth&&a.position.z?`rgba(${127.5+2*a.position.z}, ${127.5-2*a.position.z}, 255, 0.5)`:ie.color,n.fillText(`${a.part}`,a.position.x+4,a.position.y+4);if(ie.drawPolygons&&t[r].keypoints){let a,s=[];s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),qc(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),s.length===4&&Ig(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftKnee"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftAnkle"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHeel"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftFoot"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),qc(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightKnee"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightAnkle"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHeel"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightFoot"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),qc(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftElbow"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftWrist"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftPalm"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),qc(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightElbow"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightWrist"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightPalm"),a&&a.score>ht.body.scoreThreshold&&s.push([a.position.x,a.position.y]),qc(n,s)}}}}async function f4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=ie.font;for(let r of t){if(ie.drawBoxes&&(n.strokeStyle=ie.color,n.fillStyle=ie.color,ie.useRawBoxes?Yl(n,e.width*r.boxRaw[0],e.height*r.boxRaw[1],e.width*r.boxRaw[2],e.height*r.boxRaw[3]):Yl(n,r.box[0],r.box[1],r.box[2],r.box[3]),ie.drawLabels&&(ie.shadowColor&&ie.shadowColor!==""&&(n.fillStyle=ie.shadowColor,n.fillText("hand",r.box[0]+3,1+r.box[1]+ie.lineHeight,r.box[2])),n.fillStyle=ie.labelColor,n.fillText("hand",r.box[0]+2,0+r.box[1]+ie.lineHeight,r.box[2])),n.stroke()),ie.drawPoints&&r.landmarks&&r.landmarks.length>0)for(let a of r.landmarks)n.fillStyle=ie.useDepth?`rgba(${127.5+2*a[2]}, ${127.5-2*a[2]}, 255, 0.5)`:ie.color,z0(n,a[0],a[1]);if(ie.drawPolygons){let a=s=>{if(!!s)for(let i=0;i<s.length;i++)n.lineWidth=ie.lineWidth,n.beginPath(),n.strokeStyle=ie.useDepth?`rgba(${127.5+2*s[i][2]}, ${127.5-2*s[i][2]}, 255, 0.5)`:ie.color,n.moveTo(s[i>0?i-1:0][0],s[i>0?i-1:0][1]),n.lineTo(s[i][0],s[i][1]),n.stroke()};a(r.annotations.indexFinger),a(r.annotations.middleFinger),a(r.annotations.ringFinger),a(r.annotations.pinky),a(r.annotations.thumb)}}}}async function m4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=ie.font;for(let r of t)if(ie.drawBoxes){if(n.strokeStyle=ie.color,n.fillStyle=ie.color,ie.useRawBoxes?Yl(n,e.width*r.boxRaw[0],e.height*r.boxRaw[1],e.width*r.boxRaw[2],e.height*r.boxRaw[3]):Yl(n,r.box[0],r.box[1],r.box[2],r.box[3]),ie.drawLabels){let a=`${Math.round(100*r.score)}% ${r.label}`;ie.shadowColor&&ie.shadowColor!==""&&(n.fillStyle=ie.shadowColor,n.fillText(a,r.box[0]+3,1+r.box[1]+ie.lineHeight,r.box[2])),n.fillStyle=ie.labelColor,n.fillText(a,r.box[0]+2,0+r.box[1]+ie.lineHeight,r.box[2])}n.stroke()}}}async function Dae(e,t){if(!e||!t||!(e instanceof HTMLCanvasElement)||!(t instanceof HTMLCanvasElement))return;let n=e.getContext("2d");n==null||n.drawImage(e,0,0)}async function Oae(e,t){!t||!e||e instanceof HTMLCanvasElement&&(d4(e,t.face),p4(e,t.body),f4(e,t.hand),h4(e,t.gesture),m4(e,t.object))}var P0=`
+`),h.brightness=function(_){let x=(_||0)+1;h.colorMatrix([x,0,0,0,0,0,x,0,0,0,0,0,x,0,0,0,0,0,1,0])},h.saturation=function(_){let x=(_||0)*2/3+1,N=(x-1)*-.5;h.colorMatrix([x,N,N,0,0,N,x,N,0,0,N,N,x,0,0,0,0,0,1,0])},h.desaturate=function(){h.saturation(-1)},h.contrast=function(_){let x=(_||0)+1,N=-128*(x-1);h.colorMatrix([x,0,0,0,N,0,x,0,0,N,0,0,x,0,N,0,0,0,1,0])},h.negative=function(){h.contrast(-2)},h.hue=function(_){_=(_||0)/180*Math.PI;let x=Math.cos(_),N=Math.sin(_),T=.213,E=.715,F=.072;h.colorMatrix([T+x*(1-T)+N*-T,E+x*-E+N*-E,F+x*-F+N*(1-F),0,0,T+x*-T+N*.143,E+x*(1-E)+N*.14,F+x*-F+N*-.283,0,0,T+x*-T+N*-(1-T),E+x*-E+N*E,F+x*(1-F)+N*F,0,0,0,0,0,1,0])},h.desaturateLuminance=function(){h.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},h.sepia=function(){h.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},h.brownie=function(){h.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},h.vintagePinhole=function(){h.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},h.kodachrome=function(){h.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])},h.technicolor=function(){h.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])},h.polaroid=function(){h.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},h.shiftToBGR=function(){h.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},h.convolution=function(_){let x=new Float32Array(_),N=1/o,T=1/l,E=w(h.convolution.SHADER);m.uniform1fv(E.uniform.m,x),m.uniform2f(E.uniform.px,N,T),b()},h.convolution.SHADER=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","uniform vec2 px;","uniform float m[9];","void main(void) {","vec4 c11 = texture2D(texture, vUv - px);","vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));","vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));","vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );","vec4 c22 = texture2D(texture, vUv);","vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );","vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );","vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );","vec4 c33 = texture2D(texture, vUv + px );","gl_FragColor = ","c11 * m[0] + c12 * m[1] + c22 * m[2] +","c21 * m[3] + c22 * m[4] + c23 * m[5] +","c31 * m[6] + c32 * m[7] + c33 * m[8];","gl_FragColor.a = c22.a;","}"].join(`
+`),h.detectEdges=function(){h.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},h.sobelX=function(){h.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},h.sobelY=function(){h.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},h.sharpen=function(_){let x=_||1;h.convolution.call(this,[0,-1*x,0,-1*x,1+4*x,-1*x,0,-1*x,0])},h.emboss=function(_){let x=_||1;h.convolution.call(this,[-2*x,-1*x,0,-1*x,1,1*x,0,1*x,2*x])},h.blur=function(_){let x=_/7/o,N=_/7/l,T=w(h.blur.SHADER);m.uniform2f(T.uniform.px,0,N),b(f.INTERMEDIATE),m.uniform2f(T.uniform.px,x,0),b()},h.blur.SHADER=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","uniform vec2 px;","void main(void) {","gl_FragColor = vec4(0.0);","gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;","gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;","gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;","gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;","gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;","gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;","gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;","gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;","gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;","gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;","gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;","gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;","gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;","gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;","gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;","}"].join(`
+`),h.pixelate=function(_){let x=_/o,N=_/l,T=w(h.pixelate.SHADER);m.uniform2f(T.uniform.size,x,N),b()},h.pixelate.SHADER=["precision highp float;","varying vec2 vUv;","uniform vec2 size;","uniform sampler2D texture;","vec2 pixelate(vec2 coord, vec2 size) {","return floor( coord / size ) * size;","}","void main(void) {","gl_FragColor = vec4(0.0);","vec2 coord = pixelate(vUv, size);","gl_FragColor += texture2D(texture, coord);","}"].join(`
+`)}var O0=2048,Tt=null,Xt=null,Rt=null;function Tg(e,t){let n;if(!e)throw new Error("Human: Input is missing");if(!(e instanceof We)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(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("Human: Input type is not recognized");if(e instanceof We)n=Rr(e);else{let a=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,s=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0,i=a,o=s;if(i>O0&&(i=O0,o=i*s/a),o>O0&&(o=O0,i=o*a/s),t.filter.width>0?i=t.filter.width:t.filter.height>0&&(i=a*(t.filter.height/s)),t.filter.height>0?o=t.filter.height:t.filter.width>0&&(o=s*(t.filter.width/a)),!i||!o)throw new Error("Human: Input cannot determine dimension");(!Tt||Tt.width!==i||Tt.height!==o)&&(Tt=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(i,o):document.createElement("canvas"),Tt.width!==i&&(Tt.width=i),Tt.height!==o&&(Tt.height=o));let l=Tt.getContext("2d");if(e instanceof ImageData?l.putImageData(e,0,0):l.drawImage(e,0,0,a,s,0,0,Tt.width,Tt.height),t.filter.enabled){if((!Rt||!Xt||Tt.width!==Xt.width||Tt.height!==Xt.height)&&(Xt=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(Tt.width,Tt.height):document.createElement("canvas"),Xt.width!==Tt.width&&(Xt.width=Tt.width),Xt.height!==Tt.height&&(Xt.height=Tt.height),Rt=fr.flags.IS_BROWSER?new U8({canvas:Xt}):null),!Rt)return{tensor:null,canvas:Tt};Rt.reset(),Rt.addFilter("brightness",t.filter.brightness),t.filter.contrast!==0&&Rt.addFilter("contrast",t.filter.contrast),t.filter.sharpness!==0&&Rt.addFilter("sharpen",t.filter.sharpness),t.filter.blur!==0&&Rt.addFilter("blur",t.filter.blur),t.filter.saturation!==0&&Rt.addFilter("saturation",t.filter.saturation),t.filter.hue!==0&&Rt.addFilter("hue",t.filter.hue),t.filter.negative&&Rt.addFilter("negative"),t.filter.sepia&&Rt.addFilter("sepia"),t.filter.vintage&&Rt.addFilter("brownie"),t.filter.sepia&&Rt.addFilter("sepia"),t.filter.kodachrome&&Rt.addFilter("kodachrome"),t.filter.technicolor&&Rt.addFilter("technicolor"),t.filter.polaroid&&Rt.addFilter("polaroid"),t.filter.pixelate!==0&&Rt.addFilter("pixelate",t.filter.pixelate),Rt.apply(Tt)}else Xt=Tt,Rt&&(Rt=null);let c;if(Xt.data){let h=[Xt.height,Xt.width,3];c=hd(Xt.data,h,"int32")}else if(Xt instanceof ImageData)c=si.fromPixels(Xt);else if(t.backend==="webgl"||t.backend==="humangl"){let h=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(i,o):document.createElement("canvas");h.width=i,h.height=o;let d=h.getContext("2d");d==null||d.drawImage(Xt,0,0),c=si.fromPixels(h)}else{let h=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(i,o):document.createElement("canvas");h.width=i,h.height=o;let d=h.getContext("2d");d==null||d.drawImage(Xt,0,0);let p=d==null?void 0:d.getImageData(0,0,i,o);c=si.fromPixels(p)}let u=c.toFloat();n=u.expandDims(0),c.dispose(),u.dispose()}let r=t.filter.return?Xt:null;return{tensor:n,canvas:r}}var Eg={};Jn(Eg,{all:()=>Aie,body:()=>q8,canvas:()=>mie,drawOptions:()=>ie,face:()=>G8,gesture:()=>H8,hand:()=>X8,object:()=>K8});var ht={backend:"webgl",wasmPath:"../assets/",debug:!0,async:!0,profile:!1,deallocate:!1,scoped:!1,videoOptimized:!0,warmup:"face",filter:{enabled:!0,width:0,height:0,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:"../models/blazeface-back.json",rotation:!1,maxFaces:10,skipFrames:21,skipInitial:!1,minConfidence:.2,iouThreshold:.1,scoreThreshold:.2,return:!1},mesh:{enabled:!0,modelPath:"../models/facemesh.json"},iris:{enabled:!0,modelPath:"../models/iris.json"},description:{enabled:!0,modelPath:"../models/faceres.json",skipFrames:31},emotion:{enabled:!0,minConfidence:.1,skipFrames:32,modelPath:"../models/emotion.json"},age:{enabled:!1,modelPath:"../models/age.json",skipFrames:33},gender:{enabled:!1,minConfidence:.1,modelPath:"../models/gender.json",skipFrames:34},embedding:{enabled:!1,modelPath:"../models/mobileface.json"}},body:{enabled:!0,modelPath:"../models/posenet.json",maxDetections:10,scoreThreshold:.3,nmsRadius:20},hand:{enabled:!0,rotation:!1,skipFrames:12,skipInitial:!1,minConfidence:.1,iouThreshold:.1,scoreThreshold:.5,maxHands:1,landmarks:!0,detector:{modelPath:"../models/handdetect.json"},skeleton:{modelPath:"../models/handskeleton.json"}},object:{enabled:!1,modelPath:"../models/nanodet.json",minConfidence:.2,iouThreshold:.4,maxResults:10,skipFrames:41}};var 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backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&Ne("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let r=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&Ne(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),r||Ne("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&x6();try{await this.tf.setBackend(this.config.backend)}catch(r){Ne("error: cannot set backend:",this.config.backend,r)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"||this.tf.getBackend()==="humangl"){this.tf.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),this.tf.ENV.set("WEBGL_PACK_DEPTHWISECONV",!0),this.config.deallocate&&(Ne("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let r=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&Ne(`gl version:${r.getParameter(r.VERSION)} renderer:${r.getParameter(r.RENDERER)}`)}await this.tf.ready(),this.perf.backend=Math.trunc(Ye()-n)}});B0.set(this,async()=>{let t=(a,s="application/octet-stream")=>fetch(`data:${s};base64,${a}`).then(i=>i.blob()),n,r;switch(this.config.warmup){case"face":n=await t(P0);break;case"full":n=await t(L0);break;default:n=null}if(n){let a=await createImageBitmap(n);r=await this.detect(a,this.config),a.close()}return r});V0.set(this,async()=>new Promise(t=>{let n,r=0;switch(this.config.warmup){case"face":r=256,n="data:image/jpeg;base64,"+P0;break;case"full":case"body":r=1200,n="data:image/jpeg;base64,"+L0;break;default:n=null}let a=new Image;a.onload=async()=>{let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(r,r):document.createElement("canvas");s.width=a.naturalWidth,s.height=a.naturalHeight;let i=s.getContext("2d");i==null||i.drawImage(a,0,0);let o=await this.detect(s,this.config);t(o)},n?a.src=n:t(null)}));U0.set(this,async()=>{let t=i=>Buffer.from(i,"base64"),n=this.config.warmup==="face"?t(P0):t(L0),r=(void 0).decodeJpeg(n),a=r.expandDims(0);this.tf.dispose(r);let s=await this.detect(a,this.config);return this.tf.dispose(a),s});this.tf=wh,this.draw=kg,this.version=A4,this.config=Xi(ht,t),this.state="idle",rs(this,Jl,0),rs(this,Xc,!1),rs(this,Kc,!1),rs(this,Di,!0),this.perf={},this.models={face:null,posenet:null,blazepose:null,efficientpose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null,faceres:null},this.image=n=>vg(n,this.config),this.classes={facemesh:H2,age:_2,gender:k2,emotion:E2,faceres:D2,body:this.config.body.modelPath.includes("posenet")?rg:fg,hand:cg,nanodet:xg},this.faceTriangulation=R6,this.faceUVMap=M6,this.sysinfo=Lg()}profileData(){return this.config.profile?h0:{}}similarity(t,n){return this.config.face.description.enabled?z2(t,n):this.config.face.embedding.enabled?w6(t,n):0}enhance(t){return P2(t)}match(t,n,r=0){return b6(t,n,r)}async load(t={}){this.state="load";let n=Ye();t&&(this.config=Xi(this.config,t)),Qn(this,Di)&&(this.config.debug&&Ne(`version: ${this.version}`),this.config.debug&&Ne(`tfjs version: ${this.tf.version_core}`),this.config.debug&&Ne("platform:",this.sysinfo.platform),this.config.debug&&Ne("agent:",this.sysinfo.agent),await Qn(this,Zc).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&Ne("configuration:",this.config),this.config.debug&&Ne("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.efficientpose,this.models.nanodet,this.models.faceres]=await Promise.all([this.models.face||(this.config.face.enabled?q2(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?v2(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?T2(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?M2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?F2(this.config):null),this.models.handpose||(this.config.hand.enabled?pg(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?sg(this.config):null),this.models.blazepose||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?mg(this.config):null),this.models.efficientpose||(this.config.body.enabled&&this.config.body.modelPath.includes("efficientpose")?yg(this.config):null),this.models.nanodet||(this.config.object.enabled?bg(this.config):null),this.models.faceres||(this.config.face.enabled&&this.config.face.description.enabled?O2(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await q2(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await v2(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await T2(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await M2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await F2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await pg(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await sg(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await mg(this.config)),this.config.body.enabled&&!this.models.efficientpose&&this.config.body.modelPath.includes("efficientpose")&&(this.models.efficientpose=await yg(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await bg(this.config)),this.config.face.enabled&&this.config.face.description.enabled&&!this.models.faceres&&(this.models.faceres=await O2(this.config))),Qn(this,Di)&&(this.config.debug&&Ne("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),rs(this,Di,!1));let r=Math.trunc(Ye()-n);r>(this.perf.load||0)&&(this.perf.load=r)}async detect(t,n={}){return new Promise(async r=>{var m,A,y,g;this.state="config";let a;this.config=Xi(this.config,n),this.state="check";let s=Qn(this,W0).call(this,t);s&&(Ne(s,t),r({error:s}));let i=Ye();await Qn(this,Zc).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),this.analyze("Start Scope:"),a=Ye();let o=vg(t,this.config);if(!o||!o.tensor){Ne("could not convert input to tensor"),r({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(Ye()-a),this.analyze("Get Image:");let l,c,u,h,d;this.config.async?(u=this.config.face.enabled?L2(this,o.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",a=Ye(),u=this.config.face.enabled?await L2(this,o.tensor):[],d=Math.trunc(Ye()-a),d>0&&(this.perf.face=d)),this.analyze("Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?(m=this.models.posenet)==null?void 0:m.estimatePoses(o.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?l=this.config.body.enabled?Ag(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(l=this.config.body.enabled?gg(o.tensor,this.config):[]),this.perf.body&&delete this.perf.body):(this.state="run:body",a=Ye(),this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?await((A=this.models.posenet)==null?void 0:A.estimatePoses(o.tensor,this.config)):[]:this.config.body.modelPath.includes("blazepose")?l=this.config.body.enabled?await Ag(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(l=this.config.body.enabled?await gg(o.tensor,this.config):[]),d=Math.trunc(Ye()-a),d>0&&(this.perf.body=d)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(c=this.config.hand.enabled?(y=this.models.handpose)==null?void 0:y.estimateHands(o.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",a=Ye(),c=this.config.hand.enabled?await((g=this.models.handpose)==null?void 0:g.estimateHands(o.tensor,this.config)):[],d=Math.trunc(Ye()-a),d>0&&(this.perf.hand=d)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.config.async?(h=this.config.object.enabled?_g(o.tensor,this.config):[],this.perf.object&&delete this.perf.object):(this.state="run:object",a=Ye(),h=this.config.object.enabled?await _g(o.tensor,this.config):[],d=Math.trunc(Ye()-a),d>0&&(this.perf.object=d)),this.analyze("End Object:"),this.config.async&&([u,l,c,h]=await Promise.all([u,l,c,h])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),this.analyze("End Scope:");let p=[];this.config.gesture.enabled&&(a=Ye(),p=[...o4(u),...i4(l),...u4(c),...l4(u)],this.config.async?this.perf.gesture&&delete this.perf.gesture:this.perf.gesture=Math.trunc(Ye()-a)),this.perf.total=Math.trunc(Ye()-i),this.state="idle";let f={face:u,body:l,hand:c,gesture:p,object:h,performance:this.perf,canvas:o.canvas};r(f)})}async warmup(t={}){let n=Ye();t&&(this.config=Xi(this.config,t));let r=this.config.videoOptimized;this.config.videoOptimized=!1;let a;typeof createImageBitmap=="function"?a=await Qn(this,B0).call(this):typeof Image!="undefined"?a=await Qn(this,V0).call(this):a=await Qn(this,U0).call(this),this.config.videoOptimized=r;let s=Ye();return this.config.debug&&Ne("Warmup",this.config.warmup,Math.round(s-n),"ms",a),a}};Jl=new WeakMap,Xc=new WeakMap,Kc=new WeakMap,Di=new WeakMap,W0=new WeakMap,Zc=new WeakMap,B0=new WeakMap,V0=new WeakMap,U0=new WeakMap;return zae;})();
+2Q==`;var Z8="1.3.5";var Jl,Xc,Kc,$i,W0,Zc,B0,V0,j0,Y8=class{constructor(t={}){Jl.set(this,void 0);Xc.set(this,void 0);Kc.set(this,void 0);$i.set(this,void 0);this.analyze=(...t)=>{if(!Qn(this,Xc))return;let n=this.tf.engine().state.numTensors,r=Qn(this,Jl);rs(this,Jl,n);let a=n-r;a!==0&&Ne(...t,a)};W0.set(this,t=>{if(!Qn(this,Kc))return null;if(!t)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(t instanceof We))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});Zc.set(this,async(t=!1)=>{if(this.config.backend&&this.config.backend!==""&&t||this.tf.getBackend()!==this.config.backend){let n=Ye();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.tf.ENV.flags.IS_BROWSER&&this.config.backend==="tensorflow"&&(this.config.backend="webgl"),this.tf.ENV.flags.IS_NODE&&(this.config.backend==="webgl"||this.config.backend==="wasm")&&(this.config.backend="tensorflow"),this.config.debug&&Ne("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&Ne("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let r=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&Ne(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),r||Ne("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&Q4();try{await this.tf.setBackend(this.config.backend)}catch(r){Ne("error: cannot set backend:",this.config.backend,r)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"||this.tf.getBackend()==="humangl"){this.tf.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),this.tf.ENV.set("WEBGL_PACK_DEPTHWISECONV",!0),this.config.deallocate&&(Ne("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let r=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&Ne(`gl version:${r.getParameter(r.VERSION)} renderer:${r.getParameter(r.RENDERER)}`)}await this.tf.ready(),this.perf.backend=Math.trunc(Ye()-n)}});B0.set(this,async()=>{let t=(a,s="application/octet-stream")=>fetch(`data:${s};base64,${a}`).then(i=>i.blob()),n,r;switch(this.config.warmup){case"face":n=await t(P0);break;case"full":n=await t(L0);break;default:n=null}if(n){let a=await createImageBitmap(n);r=await this.detect(a,this.config),a.close()}return r});V0.set(this,async()=>new Promise(t=>{let n,r=0;switch(this.config.warmup){case"face":r=256,n="data:image/jpeg;base64,"+P0;break;case"full":case"body":r=1200,n="data:image/jpeg;base64,"+L0;break;default:n=null}let a=new Image;a.onload=async()=>{let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(r,r):document.createElement("canvas");s.width=a.naturalWidth,s.height=a.naturalHeight;let i=s.getContext("2d");i==null||i.drawImage(a,0,0);let o=await this.detect(s,this.config);t(o)},n?a.src=n:t(null)}));j0.set(this,async()=>{let t=i=>Buffer.from(i,"base64"),n=this.config.warmup==="face"?t(P0):t(L0),r=(void 0).decodeJpeg(n),a=r.expandDims(0);this.tf.dispose(r);let s=await this.detect(a,this.config);return this.tf.dispose(a),s});this.tf=bh,this.draw=Eg,this.version=Z8,this.config=Xi(ht,t),this.state="idle",rs(this,Jl,0),rs(this,Xc,!1),rs(this,Kc,!1),rs(this,$i,!0),this.perf={},this.models={face:null,posenet:null,blazepose:null,efficientpose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null,faceres:null},this.image=n=>Tg(n,this.config),this.classes={facemesh:Z2,age:S2,gender:E2,emotion:D2,faceres:W2,body:this.config.body.modelPath.includes("posenet")?lg:xg,hand:mg,nanodet:kg},this.faceTriangulation=h8,this.faceUVMap=d8,this.sysinfo=Ug()}profileData(){return this.config.profile?h0:{}}similarity(t,n){return this.config.face.description.enabled?V2(t,n):this.config.face.embedding.enabled?e8(t,n):0}enhance(t){return j2(t)}match(t,n,r=0){return t8(t,n,r)}async load(t={}){this.state="load";let n=Ye();t&&(this.config=Xi(this.config,t)),Qn(this,$i)&&(this.config.debug&&Ne(`version: ${this.version}`),this.config.debug&&Ne(`tfjs version: ${this.tf.version_core}`),this.config.debug&&Ne("platform:",this.sysinfo.platform),this.config.debug&&Ne("agent:",this.sysinfo.agent),await Qn(this,Zc).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&Ne("configuration:",this.config),this.config.debug&&Ne("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.efficientpose,this.models.nanodet,this.models.faceres]=await Promise.all([this.models.face||(this.config.face.enabled?J2(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?T2(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?F2(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?z2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?P2(this.config):null),this.models.handpose||(this.config.hand.enabled?gg(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?cg(this.config):null),this.models.blazepose||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?bg(this.config):null),this.models.efficientpose||(this.config.body.enabled&&this.config.body.modelPath.includes("efficientpose")?_g(this.config):null),this.models.nanodet||(this.config.object.enabled?Ng(this.config):null),this.models.faceres||(this.config.face.enabled&&this.config.face.description.enabled?B2(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await J2(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await T2(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await F2(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await z2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await P2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await gg(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await cg(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await bg(this.config)),this.config.body.enabled&&!this.models.efficientpose&&this.config.body.modelPath.includes("efficientpose")&&(this.models.efficientpose=await _g(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await Ng(this.config)),this.config.face.enabled&&this.config.face.description.enabled&&!this.models.faceres&&(this.models.faceres=await B2(this.config))),Qn(this,$i)&&(this.config.debug&&Ne("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),rs(this,$i,!1));let r=Math.trunc(Ye()-n);r>(this.perf.load||0)&&(this.perf.load=r)}async detect(t,n={}){return new Promise(async r=>{var m,A,y,g;this.state="config";let a;this.config=Xi(this.config,n),this.state="check";let s=Qn(this,W0).call(this,t);s&&(Ne(s,t),r({error:s}));let i=Ye();await Qn(this,Zc).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),this.analyze("Start Scope:"),a=Ye();let o=Tg(t,this.config);if(!o||!o.tensor){Ne("could not convert input to tensor"),r({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(Ye()-a),this.analyze("Get Image:");let l,c,u,h,d;this.config.async?(u=this.config.face.enabled?U2(this,o.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",a=Ye(),u=this.config.face.enabled?await U2(this,o.tensor):[],d=Math.trunc(Ye()-a),d>0&&(this.perf.face=d)),this.analyze("Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?(m=this.models.posenet)==null?void 0:m.estimatePoses(o.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?l=this.config.body.enabled?wg(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(l=this.config.body.enabled?vg(o.tensor,this.config):[]),this.perf.body&&delete this.perf.body):(this.state="run:body",a=Ye(),this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?await((A=this.models.posenet)==null?void 0:A.estimatePoses(o.tensor,this.config)):[]:this.config.body.modelPath.includes("blazepose")?l=this.config.body.enabled?await wg(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(l=this.config.body.enabled?await vg(o.tensor,this.config):[]),d=Math.trunc(Ye()-a),d>0&&(this.perf.body=d)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(c=this.config.hand.enabled?(y=this.models.handpose)==null?void 0:y.estimateHands(o.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",a=Ye(),c=this.config.hand.enabled?await((g=this.models.handpose)==null?void 0:g.estimateHands(o.tensor,this.config)):[],d=Math.trunc(Ye()-a),d>0&&(this.perf.hand=d)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.config.async?(h=this.config.object.enabled?Sg(o.tensor,this.config):[],this.perf.object&&delete this.perf.object):(this.state="run:object",a=Ye(),h=this.config.object.enabled?await Sg(o.tensor,this.config):[],d=Math.trunc(Ye()-a),d>0&&(this.perf.object=d)),this.analyze("End Object:"),this.config.async&&([u,l,c,h]=await Promise.all([u,l,c,h])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),this.analyze("End Scope:");let p=[];this.config.gesture.enabled&&(a=Ye(),p=[...B8(u),...W8(l),...j8(c),...V8(u)],this.config.async?this.perf.gesture&&delete this.perf.gesture:this.perf.gesture=Math.trunc(Ye()-a)),this.perf.total=Math.trunc(Ye()-i),this.state="idle";let f={face:u,body:l,hand:c,gesture:p,object:h,performance:this.perf,canvas:o.canvas};r(f)})}async warmup(t={}){let n=Ye();t&&(this.config=Xi(this.config,t));let r=this.config.videoOptimized;this.config.videoOptimized=!1;let a;typeof createImageBitmap=="function"?a=await Qn(this,B0).call(this):typeof Image!="undefined"?a=await Qn(this,V0).call(this):a=await Qn(this,j0).call(this),this.config.videoOptimized=r;let s=Ye();return this.config.debug&&Ne("Warmup",this.config.warmup,Math.round(s-n),"ms",a),a}};Jl=new WeakMap,Xc=new WeakMap,Kc=new WeakMap,$i=new WeakMap,W0=new WeakMap,Zc=new WeakMap,B0=new WeakMap,V0=new WeakMap,j0=new WeakMap;return yie;})();
 /**
  * @license
  * Copyright 2017 Google LLC. All Rights Reserved.
diff --git a/dist/human.js.map b/dist/human.js.map
index 72e3bb6d..51798850 100644
--- a/dist/human.js.map
+++ b/dist/human.js.map
@@ -1,7 +1,7 @@
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-  "sourcesContent": ["import { log, now, mergeDeep } from './helpers';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as faceall from './faceall';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as faceres from './faceres/faceres';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as efficientpose from './efficientpose/efficientpose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image/image';\nimport * as draw from './draw/draw';\nimport * as profile from './profile';\nimport { Config, defaults } from './config';\nimport { Result } from './result';\nimport * as sample from './sample';\nimport * as app from '../package.json';\n\n/** Generic Tensor object type */\nexport type Tensor = typeof tf.Tensor;\nexport type { Config } from './config';\nexport type { Result } from './result';\n/** Defines all possible input types for **Human** detection */\nexport type Input = Tensor | typeof Image | ImageData | ImageBitmap | HTMLImageElement | HTMLMediaElement | HTMLVideoElement | HTMLCanvasElement | OffscreenCanvas;\n\n/** Error message */\nexport type Error = { error: string };\n/** Instance of TensorFlow/JS */\nexport type TensorFlow = typeof tf;\n/** Generic Model object type, holds instance of individual models */\ntype Model = Object;\n\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 */\nexport class Human {\n  version: string;\n  config: Config;\n  state: string;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: TensorFlow;\n  draw: {\n    drawOptions?: typeof draw.drawOptions,\n    gesture: typeof draw.gesture,\n    face: typeof draw.face,\n    body: typeof draw.body,\n    hand: typeof draw.hand,\n    canvas: typeof draw.canvas,\n    all: typeof draw.all,\n  };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | Model | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    efficientpose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n    faceres: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n    faceres: typeof faceres;\n  };\n  faceTriangulation: typeof facemesh.triangulation;\n  faceUVMap: typeof facemesh.uvmap;\n  sysinfo: { platform: string, agent: string };\n  perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: boolean;\n  #checkSanity: boolean;\n  #firstRun: boolean;\n  // definition end\n\n  constructor(userConfig: Config | Object = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.version = app.version;\n    this.config = mergeDeep(defaults, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      efficientpose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n      faceres: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Input) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      faceres,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    this.faceTriangulation = facemesh.triangulation;\n    this.faceUVMap = facemesh.uvmap;\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | string => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_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  similarity(embedding1: Array<number>, embedding2: Array<number>): number {\n    if (this.config.face.description.enabled) return faceres.similarity(embedding1, embedding2);\n    if (this.config.face.embedding.enabled) return embedding.similarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return faceres.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<number>, db: Array<{ name: string, source: string, embedding: number[] }>, threshold = 0): { name: string, source: string, similarity: number, embedding: number[] } {\n    return faceres.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Config | Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        // @ts-ignore\n        this.models.handpose,\n        // @ts-ignore false warning with latest @typescript-eslint\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.efficientpose,\n        this.models.nanodet,\n        this.models.faceres,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? <Promise<handpose.HandPose>>handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.blazepose || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.efficientpose || (this.config.body.enabled && this.config.body.modelPath.includes('efficientpose') ? efficientpose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n        this.models.faceres || ((this.config.face.enabled && this.config.face.description.enabled) ? faceres.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.body.enabled && !this.models.efficientpose && this.config.body.modelPath.includes('efficientpose')) this.models.efficientpose = await efficientpose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n      if (this.config.face.enabled && this.config.face.description.enabled && !this.models.faceres) this.models.faceres = await faceres.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.perf.load || 0)) this.perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        // force browser vs node backend\n        if (this.tf.ENV.flags.IS_BROWSER && this.config.backend === 'tensorflow') this.config.backend = 'webgl';\n        if (this.tf.ENV.flags.IS_NODE && (this.config.backend === 'webgl' || this.config.backend === 'wasm')) this.config.backend = 'tensorflow';\n\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      // this.tf.enableDebugMode();\n      if (this.tf.getBackend() === 'webgl' || this.tf.getBackend() === 'humangl') {\n        this.tf.ENV.set('CHECK_COMPUTATION_FOR_ERRORS', false);\n        this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  // main detect function\n  async detect(input: Input, userConfig: Config | Object = {}): Promise<Result | Error> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.perf.image = Math.trunc(now() - timeStamp);\n      this.analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n      let current;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? faceall.detectFace(this, process.tensor) : [];\n        if (this.perf.face) delete this.perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await faceall.detectFace(this, process.tensor) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.face = current;\n      }\n\n      // run body: can be posenet or blazepose\n      this.analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('blazepose')) bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('efficientpose')) bodyRes = this.config.body.enabled ? efficientpose.predict(process.tensor, this.config) : [];\n        if (this.perf.body) delete this.perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('blazepose')) bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('efficientpose')) bodyRes = this.config.body.enabled ? await efficientpose.predict(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.body = current;\n      }\n      this.analyze('End Body:');\n\n      // run handpose\n      this.analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.perf.hand) delete this.perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.hand = current;\n      }\n      this.analyze('End Hand:');\n\n      // run nanodet\n      this.analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.perf.object) delete this.perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.object = current;\n      }\n      this.analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.perf.gesture) delete this.perf.gesture;\n      }\n\n      this.perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      const result = {\n        face: faceRes,\n        body: bodyRes,\n        hand: handRes,\n        gesture: gestureRes,\n        object: objectRes,\n        performance: this.perf,\n        canvas: process.canvas,\n      };\n      // log('Result:', result);\n      resolve(result);\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\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 this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.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    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Config | Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\n/**\n * Class Human is also available as default export\n */\nexport { Human as default };\n", "// helper function: wrapper around console output\nexport function log(...msg) {\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')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n\n// helper function: gets elapsed time on both browser and nodejs\nexport const now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nexport function mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n", "export function info(): { platform: string, agent: string } {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\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) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = 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) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\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\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) 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 + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\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\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModuleThreadedSimd) {\n  WasmBackendModuleThreadedSimd = WasmBackendModuleThreadedSimd || {};\n\nfunction GROWABLE_HEAP_I8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP8}function GROWABLE_HEAP_U8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU8}function GROWABLE_HEAP_I32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP32}function GROWABLE_HEAP_U32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU32}function GROWABLE_HEAP_F64(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPF64}var Module=typeof WasmBackendModuleThreadedSimd!==\"undefined\"?WasmBackendModuleThreadedSimd:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var ENVIRONMENT_IS_PTHREAD=Module[\"ENVIRONMENT_IS_PTHREAD\"]||false;if(ENVIRONMENT_IS_PTHREAD){buffer=Module[\"buffer\"]}var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process[\"on\"](\"unhandledRejection\",abort);quit_=function(status){process[\"exit\"](status)};Module[\"inspect\"]=function(){return\"[Emscripten Module object]\"};var nodeWorkerThreads;try{nodeWorkerThreads=require(\"worker_threads\")}catch(e){console.error('The \"worker_threads\" module is not supported in this node.js build - perhaps a newer version is needed?');throw e}global.Worker=nodeWorkerThreads.Worker}else if(ENVIRONMENT_IS_SHELL){if(typeof read!=\"undefined\"){read_=function shell_read(f){return read(f)}}readBinary=function readBinary(f){var data;if(typeof readbuffer===\"function\"){return new Uint8Array(readbuffer(f))}data=read(f,\"binary\");assert(typeof data===\"object\");return data};if(typeof scriptArgs!=\"undefined\"){arguments_=scriptArgs}else if(typeof arguments!=\"undefined\"){arguments_=arguments}if(typeof quit===\"function\"){quit_=function(status){quit(status)}}if(typeof print!==\"undefined\"){if(typeof console===\"undefined\")console={};console.log=print;console.warn=console.error=typeof printErr!==\"undefined\"?printErr:print}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href}else if(typeof document!==\"undefined\"&&document.currentScript){scriptDirectory=document.currentScript.src}if(typeof _scriptDir !== \"undefined\" && _scriptDir){scriptDirectory=_scriptDir}if(scriptDirectory.indexOf(\"blob:\")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf(\"/\")+1)}else{scriptDirectory=\"\"}if(ENVIRONMENT_IS_NODE){read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret}}else{read_=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}if(ENVIRONMENT_IS_NODE){if(typeof performance===\"undefined\"){global.performance=require(\"perf_hooks\").performance}}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var Atomics_load=Atomics.load;var Atomics_store=Atomics.store;var Atomics_compareExchange=Atomics.compareExchange;var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var wasmModule;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module[\"wasmMemory\"];buffer=Module[\"buffer\"]}else{if(Module[\"wasmMemory\"]){wasmMemory=Module[\"wasmMemory\"]}else{wasmMemory=new WebAssembly.Memory({\"initial\":INITIAL_MEMORY/65536,\"maximum\":2147483648/65536,\"shared\":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){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\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];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)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={\"e\":___assert_fail,\"r\":___call_main,\"x\":__emscripten_notify_thread_queue,\"b\":_abort,\"y\":_emscripten_asm_const_int,\"j\":_emscripten_conditional_set_current_thread_status,\"c\":_emscripten_futex_wait,\"d\":_emscripten_futex_wake,\"f\":_emscripten_get_now,\"p\":_emscripten_memcpy_big,\"z\":_emscripten_num_logical_cores,\"u\":_emscripten_receive_on_main_thread_js,\"q\":_emscripten_resize_heap,\"v\":_emscripten_set_canvas_element_size,\"i\":_emscripten_set_current_thread_status,\"t\":_emscripten_set_thread_name,\"w\":_emscripten_webgl_create_context,\"m\":_fd_close,\"n\":_fd_seek,\"g\":_fd_write,\"o\":initPthreadsJS,\"a\":wasmMemory||Module[\"wasmMemory\"],\"k\":_pthread_cleanup_pop,\"l\":_pthread_cleanup_push,\"h\":_pthread_create,\"s\":_sysconf};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var _ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"X\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"Y\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"Z\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"_\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"$\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"aa\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"ba\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"ca\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"da\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"ea\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"fa\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"ga\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"ha\"]).apply(null,arguments)};var 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exit(status,implicit){if(implicit&&noExitRuntime&&status===0){return}if(!implicit){if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exitProcess\",\"returnCode\":status});throw new ExitStatus(status)}else{}}if(noExitRuntime){}else{PThread.terminateAllThreads();EXITSTATUS=status;exitRuntime();if(Module[\"onExit\"])Module[\"onExit\"](status);ABORT=true}quit_(status,new ExitStatus(status))}if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}if(ENVIRONMENT_IS_PTHREAD){noExitRuntime=false;PThread.initWorker()}run();\n\n\n  return WasmBackendModuleThreadedSimd.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModuleThreadedSimd;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModuleThreadedSimd; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModuleThreadedSimd\"] = WasmBackendModuleThreadedSimd;\n", "\nvar WasmBackendModule = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModule) {\n  WasmBackendModule = WasmBackendModule || {};\n\nvar Module=typeof WasmBackendModule!==\"undefined\"?WasmBackendModule:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var 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\"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var 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Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function 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fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmMemory=Module[\"asm\"][\"g\"];updateGlobalBufferAndViews(wasmMemory.buffer);wasmTable=Module[\"asm\"][\"m\"];removeRunDependency(\"wasm-instantiate\")}addRunDependency(\"wasm-instantiate\");function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _abort(){abort()}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num)}function _emscripten_get_heap_size(){return HEAPU8.length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=HEAP32[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){}function _fd_write(fd,iov,iovcnt,pnum){var num=0;for(var i=0;i<iovcnt;i++){var ptr=HEAP32[iov+i*8>>2];var len=HEAP32[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,HEAPU8[ptr+j])}num+=len}HEAP32[pnum>>2]=num;return 0}var asmLibraryArg={\"a\":_abort,\"d\":_emscripten_memcpy_big,\"e\":_emscripten_resize_heap,\"f\":_fd_close,\"c\":_fd_seek,\"b\":_fd_write};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"h\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"i\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"j\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"k\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"l\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"n\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"o\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"p\"]).apply(null,arguments)};var _ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"q\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"r\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"s\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"t\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"u\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"v\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"w\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"x\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"y\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"z\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"F\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _Log=Module[\"_Log\"]=function(){return(_Log=Module[\"_Log\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _LogicalAnd=Module[\"_LogicalAnd\"]=function(){return(_LogicalAnd=Module[\"_LogicalAnd\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _Max=Module[\"_Max\"]=function(){return(_Max=Module[\"_Max\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _MaxPool=Module[\"_MaxPool\"]=function(){return(_MaxPool=Module[\"_MaxPool\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Maximum=Module[\"_Maximum\"]=function(){return(_Maximum=Module[\"_Maximum\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Mean=Module[\"_Mean\"]=function(){return(_Mean=Module[\"_Mean\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var _Min=Module[\"_Min\"]=function(){return(_Min=Module[\"_Min\"]=Module[\"asm\"][\"X\"]).apply(null,arguments)};var _Minimum=Module[\"_Minimum\"]=function(){return(_Minimum=Module[\"_Minimum\"]=Module[\"asm\"][\"Y\"]).apply(null,arguments)};var _Multiply=Module[\"_Multiply\"]=function(){return(_Multiply=Module[\"_Multiply\"]=Module[\"asm\"][\"Z\"]).apply(null,arguments)};var _Neg=Module[\"_Neg\"]=function(){return(_Neg=Module[\"_Neg\"]=Module[\"asm\"][\"_\"]).apply(null,arguments)};var _NonMaxSuppressionV3=Module[\"_NonMaxSuppressionV3\"]=function(){return(_NonMaxSuppressionV3=Module[\"_NonMaxSuppressionV3\"]=Module[\"asm\"][\"$\"]).apply(null,arguments)};var _NonMaxSuppressionV4=Module[\"_NonMaxSuppressionV4\"]=function(){return(_NonMaxSuppressionV4=Module[\"_NonMaxSuppressionV4\"]=Module[\"asm\"][\"aa\"]).apply(null,arguments)};var _NonMaxSuppressionV5=Module[\"_NonMaxSuppressionV5\"]=function(){return(_NonMaxSuppressionV5=Module[\"_NonMaxSuppressionV5\"]=Module[\"asm\"][\"ba\"]).apply(null,arguments)};var _NotEqual=Module[\"_NotEqual\"]=function(){return(_NotEqual=Module[\"_NotEqual\"]=Module[\"asm\"][\"ca\"]).apply(null,arguments)};var _OneHot=Module[\"_OneHot\"]=function(){return(_OneHot=Module[\"_OneHot\"]=Module[\"asm\"][\"da\"]).apply(null,arguments)};var _PadV2=Module[\"_PadV2\"]=function(){return(_PadV2=Module[\"_PadV2\"]=Module[\"asm\"][\"ea\"]).apply(null,arguments)};var _Pow=Module[\"_Pow\"]=function(){return(_Pow=Module[\"_Pow\"]=Module[\"asm\"][\"fa\"]).apply(null,arguments)};var _Prelu=Module[\"_Prelu\"]=function(){return(_Prelu=Module[\"_Prelu\"]=Module[\"asm\"][\"ga\"]).apply(null,arguments)};var _Prod=Module[\"_Prod\"]=function(){return(_Prod=Module[\"_Prod\"]=Module[\"asm\"][\"ha\"]).apply(null,arguments)};var _RealDiv=Module[\"_RealDiv\"]=function(){return(_RealDiv=Module[\"_RealDiv\"]=Module[\"asm\"][\"ia\"]).apply(null,arguments)};var _Relu=Module[\"_Relu\"]=function(){return(_Relu=Module[\"_Relu\"]=Module[\"asm\"][\"ja\"]).apply(null,arguments)};var _Relu6=Module[\"_Relu6\"]=function(){return(_Relu6=Module[\"_Relu6\"]=Module[\"asm\"][\"ka\"]).apply(null,arguments)};var _ResizeBilinear=Module[\"_ResizeBilinear\"]=function(){return(_ResizeBilinear=Module[\"_ResizeBilinear\"]=Module[\"asm\"][\"la\"]).apply(null,arguments)};var _Reverse=Module[\"_Reverse\"]=function(){return(_Reverse=Module[\"_Reverse\"]=Module[\"asm\"][\"ma\"]).apply(null,arguments)};var _RotateWithOffset=Module[\"_RotateWithOffset\"]=function(){return(_RotateWithOffset=Module[\"_RotateWithOffset\"]=Module[\"asm\"][\"na\"]).apply(null,arguments)};var _Round=Module[\"_Round\"]=function(){return(_Round=Module[\"_Round\"]=Module[\"asm\"][\"oa\"]).apply(null,arguments)};var _Rsqrt=Module[\"_Rsqrt\"]=function(){return(_Rsqrt=Module[\"_Rsqrt\"]=Module[\"asm\"][\"pa\"]).apply(null,arguments)};var _ScatterNd=Module[\"_ScatterNd\"]=function(){return(_ScatterNd=Module[\"_ScatterNd\"]=Module[\"asm\"][\"qa\"]).apply(null,arguments)};var _SelectV2=Module[\"_SelectV2\"]=function(){return(_SelectV2=Module[\"_SelectV2\"]=Module[\"asm\"][\"ra\"]).apply(null,arguments)};var _Sigmoid=Module[\"_Sigmoid\"]=function(){return(_Sigmoid=Module[\"_Sigmoid\"]=Module[\"asm\"][\"sa\"]).apply(null,arguments)};var _Sin=Module[\"_Sin\"]=function(){return(_Sin=Module[\"_Sin\"]=Module[\"asm\"][\"ta\"]).apply(null,arguments)};var _Softmax=Module[\"_Softmax\"]=function(){return(_Softmax=Module[\"_Softmax\"]=Module[\"asm\"][\"ua\"]).apply(null,arguments)};var _Sqrt=Module[\"_Sqrt\"]=function(){return(_Sqrt=Module[\"_Sqrt\"]=Module[\"asm\"][\"va\"]).apply(null,arguments)};var _Square=Module[\"_Square\"]=function(){return(_Square=Module[\"_Square\"]=Module[\"asm\"][\"wa\"]).apply(null,arguments)};var _SquaredDifference=Module[\"_SquaredDifference\"]=function(){return(_SquaredDifference=Module[\"_SquaredDifference\"]=Module[\"asm\"][\"xa\"]).apply(null,arguments)};var _Step=Module[\"_Step\"]=function(){return(_Step=Module[\"_Step\"]=Module[\"asm\"][\"ya\"]).apply(null,arguments)};var _StridedSlice=Module[\"_StridedSlice\"]=function(){return(_StridedSlice=Module[\"_StridedSlice\"]=Module[\"asm\"][\"za\"]).apply(null,arguments)};var _Sub=Module[\"_Sub\"]=function(){return(_Sub=Module[\"_Sub\"]=Module[\"asm\"][\"Aa\"]).apply(null,arguments)};var _Sum=Module[\"_Sum\"]=function(){return(_Sum=Module[\"_Sum\"]=Module[\"asm\"][\"Ba\"]).apply(null,arguments)};var _Tanh=Module[\"_Tanh\"]=function(){return(_Tanh=Module[\"_Tanh\"]=Module[\"asm\"][\"Ca\"]).apply(null,arguments)};var _Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\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) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = 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) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\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\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) 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 + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\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\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");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;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(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;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}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);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}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);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var nodeFS=require(\"fs\");var nodeRead=function(filename){return nodeFS.readFileSync(filename,\"utf8\")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance===\"undefined\"){performance={now:function(){return Date.now()}}}}';", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }\n\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export versions\nexport const version = {\n  tfjs: packageBundle.version,\n  'tfjs-core': packageCore.version,\n  'tfjs-data': packageData.version,\n  'tfjs-layers': packageLayers.version,\n  'tfjs-converter': packageConverter.version,\n  'tfjs-backend-cpu': version_cpu,\n  'tfjs-backend-webgl': version_webgl,\n  'tfjs-backend-wasm': version_wasm,\n};\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\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\nexport function register(): void {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 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    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './helpers';\n\nexport const data = {};\n\nexport function run(modelName: string, profileData: any): void {\n  if (!profileData || !profileData.kernels) return;\n  const maxResults = 5;\n  const time = profileData.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = profileData.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = profileData.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  data[modelName] = {\n    model: modelName,\n    newBytes: profileData.newBytes,\n    newTensors: profileData.newTensors,\n    peakBytes: profileData.peakBytes,\n    numKernelOps: profileData.kernels.length,\n    timeKernelOps: time,\n    slowestKernelOps: slowest,\n    largestKernelOps: largest,\n  };\n  log('profiler', modelName, data[modelName]);\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(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 = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      if (!Array.isArray(genderT)) {\n        const data = genderT.dataSync();\n        if (alternative) {\n          // returns two values 0..1, bigger one is prediction\n          if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n            obj.gender = data[0] > data[1] ? 'female' : 'male';\n            obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n          }\n        } else {\n          // returns one value 0..1, .5 is prediction threshold\n          const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n          if (confidence > config.face.gender.minConfidence) {\n            obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n            obj.confidence = Math.min(0.99, confidence);\n          }\n        }\n        genderT.dispose();\n      } else {\n        const gender = genderT[0].dataSync();\n        const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n        /*\n        let age = genderT[1].argMax(1).dataSync()[0];\n        const all = genderT[1].dataSync();\n        age = Math.round(all[age - 1] > all[age + 1] ? 10 * age - 100 * all[age - 1] : 10 * age + 100 * all[age + 1]) / 10;\n        const descriptor = genderT[1].dataSync();\n        */\n        genderT.forEach((t) => tf.dispose(t));\n      }\n    }\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\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\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\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    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = typeof tf.Tensor;\ntype DB = Array<{ name: string, source: string, embedding: number[] }>;\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function similarity(embedding1, embedding2, order = 2): number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<number>, db: DB, threshold = 0) {\n  let best = { similarity: 0, name: '', source: '', embedding: [] as number[] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = similarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.similarity) best = { ...f, similarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = 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    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\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    // 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    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\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\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([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: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\ntype Tensor = typeof tf.Tensor;\ntype DB = Array<{ name: string, source: string, embedding: number[] }>;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.description.modelPath);\n    if (config.debug) log(`load model: ${config.face.description.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function similarity(embedding1, embedding2, order = 2): number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = 4.0 * embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(0, 100 - distance) / 100.0;\n  return res;\n}\n\nexport function match(embedding: Array<number>, db: DB, threshold = 0) {\n  let best = { similarity: 0, name: '', source: '', embedding: [] as number[] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = similarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.similarity) best = { ...f, similarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    const tensor = input.image || input.tensor || input;\n    if (!(tensor instanceof tf.Tensor)) return null;\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    // const crop = tf.image.resizeBilinear(tensor, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\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    /*\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\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n    /*\n    // normalize brightness from 0..1\n    const darken = crop.sub(crop.min());\n    const lighten = darken.div(darken.max());\n    */\n    const norm = crop.mul(255);\n\n    return norm;\n  });\n  return image;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.description.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    // const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    // const enhanced = tf.mul(resize, [255.0]);\n    // tf.dispose(resize);\n    const enhanced = enhance(image);\n\n    let resT;\n    const obj = {\n      age: <number>0,\n      gender: <string>'unknown',\n      genderConfidence: <number>0,\n      descriptor: <number[]>[] };\n\n    if (!config.profile) {\n      if (config.face.description.enabled) resT = await model.predict(enhanced);\n    } else {\n      const profileDesc = config.face.description.enabled ? await tf.profile(() => model.predict(enhanced)) : {};\n      resT = profileDesc.result;\n      profile.run('faceres', profileDesc);\n    }\n    tf.dispose(enhanced);\n\n    if (resT) {\n      tf.tidy(() => {\n        const gender = resT.find((t) => t.shape[1] === 1).dataSync();\n        const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n          obj.genderConfidence = Math.min(0.99, confidence);\n        }\n        const age = resT.find((t) => t.shape[1] === 100).argMax(1).dataSync()[0];\n        const all = resT.find((t) => t.shape[1] === 100).dataSync();\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]);\n        // const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n        obj.descriptor = [...desc.dataSync()];\n      });\n      resT.forEach((t) => tf.dispose(t));\n    }\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log, now } from './helpers';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as faceres from './faceres/faceres';\n\ntype Tensor = typeof tf.Tensor;\n\nconst calculateFaceAngle = (face, image_size): { angle: { pitch: number, yaw: number, roll: number }, matrix: [number, number, number, number, number, number, number, number, number] } => {\n  // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n  const degrees = (theta) => (theta * 180) / Math.PI;\n  // const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n  const normalize = (v) => { // 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, b) => { // 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, b) => { // 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) => {\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; let thetaY; let thetaZ;\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    return { pitch: 2 * -thetaX, yaw: 2 * -thetaY, roll: 2 * -thetaZ };\n  };\n  // simple Euler angle calculation based existing 3D mesh\n  // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n  const meshToEulerAngle = (mesh) => {\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // pitch is face move up/down\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\n      // yaw is face turn left/right\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\n      // roll is face lean 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\n    };\n    return angle;\n  };\n\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] };\n\n  const size = Math.max(face.boxRaw[2] * image_size[0], face.boxRaw[3] * image_size[1]) / 1.5;\n  // top, bottom, left, right\n  const pts = [mesh[10], mesh[152], mesh[234], mesh[454]].map((pt) => [\n    // make the xyz coordinates proportional, independent of the image/box size\n    pt[0] * image_size[0] / size,\n    pt[1] * image_size[1] / size,\n    pt[2],\n  ]);\n\n  const y_axis = normalize(subVectors(pts[1], pts[0]));\n  let x_axis = normalize(subVectors(pts[3], pts[2]));\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  return { angle, matrix };\n};\n\nexport const detectFace = async (parent, input): Promise<any> => {\n  // run facemesh, includes blazeface and iris\n  // eslint-disable-next-line no-async-promise-executor\n  let timeStamp;\n  let ageRes;\n  let genderRes;\n  let emotionRes;\n  let embeddingRes;\n  let descRes;\n  const faceRes: Array<{\n      confidence: number,\n      boxConfidence: number,\n      faceConfidence: number,\n      box: [number, number, number, number],\n      mesh: Array<[number, number, number]>\n      meshRaw: Array<[number, number, number]>\n      boxRaw: [number, number, number, number],\n      annotations: Array<{ part: string, points: Array<[number, number, number]>[] }>,\n      age: number,\n      gender: string,\n      genderConfidence: number,\n      emotion: string,\n      embedding: number[],\n      iris: number,\n      rotation: {\n        angle: { pitch: number, yaw: number, roll: number },\n        matrix: [number, number, number, number, number, number, number, number, number]\n      },\n      tensor: Tensor,\n    }> = [];\n  parent.state = 'run:face';\n  timeStamp = now();\n  const faces = await parent.models.face?.estimateFaces(input, parent.config);\n  parent.perf.face = Math.trunc(now() - timeStamp);\n  if (!faces) return [];\n  for (const face of faces) {\n    parent.analyze('Get Face');\n\n    // is something went wrong, skip the face\n    if (!face.image || face.image.isDisposedInternal) {\n      log('Face object is disposed:', face.image);\n      continue;\n    }\n\n    const rotation = calculateFaceAngle(face, [input.shape[2], input.shape[1]]);\n\n    // run age, inherits face from blazeface\n    parent.analyze('Start Age:');\n    if (parent.config.async) {\n      ageRes = parent.config.face.age.enabled ? age.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:age';\n      timeStamp = now();\n      ageRes = parent.config.face.age.enabled ? await age.predict(face.image, parent.config) : {};\n      parent.perf.age = Math.trunc(now() - timeStamp);\n    }\n\n    // run gender, inherits face from blazeface\n    parent.analyze('Start Gender:');\n    if (parent.config.async) {\n      genderRes = parent.config.face.gender.enabled ? gender.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:gender';\n      timeStamp = now();\n      genderRes = parent.config.face.gender.enabled ? await gender.predict(face.image, parent.config) : {};\n      parent.perf.gender = Math.trunc(now() - timeStamp);\n    }\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Emotion:');\n    if (parent.config.async) {\n      emotionRes = parent.config.face.emotion.enabled ? emotion.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:emotion';\n      timeStamp = now();\n      emotionRes = parent.config.face.emotion.enabled ? await emotion.predict(face.image, parent.config) : {};\n      parent.perf.emotion = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Emotion:');\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Embedding:');\n    if (parent.config.async) {\n      embeddingRes = parent.config.face.embedding.enabled ? embedding.predict(face, parent.config) : [];\n    } else {\n      parent.state = 'run:embedding';\n      timeStamp = now();\n      embeddingRes = parent.config.face.embedding.enabled ? await embedding.predict(face, parent.config) : [];\n      parent.perf.embedding = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Embedding:');\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Description:');\n    if (parent.config.async) {\n      descRes = parent.config.face.description.enabled ? faceres.predict(face, parent.config) : [];\n    } else {\n      parent.state = 'run:description';\n      timeStamp = now();\n      descRes = parent.config.face.description.enabled ? await faceres.predict(face.image, parent.config) : [];\n      parent.perf.embedding = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Description:');\n\n    // if async wait for results\n    if (parent.config.async) {\n      [ageRes, genderRes, emotionRes, embeddingRes, descRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes, descRes]);\n    }\n\n    parent.analyze('Finish Face:');\n\n    // calculate iris distance\n    // iris: array[ center, left, top, right, bottom]\n    if (!parent.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n      delete face.annotations.leftEyeIris;\n      delete face.annotations.rightEyeIris;\n    }\n    const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n    /* average human iris size is 11.7mm */\n      ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n      : 0;\n\n    // combine results\n    faceRes.push({\n      ...face,\n      age: descRes.age || ageRes.age,\n      gender: descRes.gender || genderRes.gender,\n      genderConfidence: descRes.genderConfidence || genderRes.confidence,\n      embedding: descRes.descriptor || embeddingRes,\n      emotion: emotionRes,\n      iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n      rotation,\n      tensor: parent.config.face.detector.return ? face.image?.squeeze() : null,\n    });\n    // dispose original face tensor\n    face.image?.dispose();\n\n    parent.analyze('End Face');\n  }\n  parent.analyze('End FaceMesh:');\n  if (parent.config.async) {\n    if (parent.perf.face) delete parent.perf.face;\n    if (parent.perf.age) delete parent.perf.age;\n    if (parent.perf.gender) delete parent.perf.gender;\n    if (parent.perf.emotion) delete parent.perf.emotion;\n  }\n  return faceRes;\n};\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[2], prediction.box.endPoint[0]) - Math.max(0, prediction.box.startPoint[0]),\n        Math.min(input.shape[1], prediction.box.endPoint[1]) - Math.max(0, prediction.box.startPoint[1]),\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        prediction.box.startPoint[0] / input.shape[2],\n        prediction.box.startPoint[1] / input.shape[1],\n        (prediction.box.endPoint[0] - prediction.box.startPoint[0]) / input.shape[2],\n        (prediction.box.endPoint[1] - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: Math.round(100 * prediction.faceConfidence || 100 * prediction.boxConfidence || 0) / 100,\n        boxConfidence: Math.round(100 * prediction.boxConfidence) / 100,\n        faceConfidence: Math.round(100 * prediction.faceConfidence) / 100,\n        box,\n        boxRaw,\n        mesh,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config): Promise<MediaPipeFaceMesh> {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexport const triangulation = coords.TRI468;\nexport const uvmap = coords.UV468;\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\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++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\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 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]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\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];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\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 function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\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\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\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],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\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 MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\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 = [\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 = [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 = [\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 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\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 = [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 = [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", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\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], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  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.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\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.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\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 / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * 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.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${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\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (!config.videoOptimized || (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces)))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(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\n          // 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          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && (config.face.description.enabled || config.face.embedding.enabled) && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\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, landmarks };\n  }\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\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() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\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    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", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, 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(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.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 < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "export 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 NUM_KEYPOINTS = 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 const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\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", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\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 sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, 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 sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !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    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score: Math.round(100 * score) / 100 });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.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\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return 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: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, boxRaw: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - Math.max(0, prediction.box.topLeft[0]),\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - Math.max(0, prediction.box.topLeft[1]),\n      ] : [];\n      const boxRaw = [\n        (prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.topLeft[1]) / input.shape[1],\n        (prediction.box.bottomRight[0] - prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.bottomRight[1] - prediction.box.topLeft[1]) / input.shape[1],\n      ];\n      hands.push({ confidence: Math.round(100 * prediction.confidence) / 100, box, boxRaw, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config): Promise<HandPose> {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\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]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\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]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\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];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\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]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "export 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", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\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 box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.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 = [...box.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      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) 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.maxHands) || !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<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\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[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? 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 = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\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", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.984375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.984375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    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   x_center: 0.5625,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  const score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n  return [{ score, keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet keypoints: Array<any> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst bodyParts = ['head', 'neck', 'rightShoulder', 'rightElbow', 'rightWrist', 'chest', 'leftShoulder', 'leftElbow', 'leftWrist', 'pelvis', 'rightHip', 'rightKnee', 'rightAnkle', 'leftHip', 'leftKnee', 'leftAnkle'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\n// performs argmax and max functions on a 2d tensor\nfunction max2d(inputs, minScore) {\n  const [width, height] = inputs.shape;\n  return tf.tidy(() => {\n    // modulus op implemented in tf\n    const mod = (a, b) => tf.sub(a, tf.mul(tf.div(a, tf.scalar(b, 'int32')), tf.scalar(b, 'int32')));\n    // combine all data\n    const reshaped = tf.reshape(inputs, [height * width]);\n    // get highest score\n    const score = tf.max(reshaped, 0).dataSync()[0];\n    if (score > minScore) {\n      // skip coordinate calculation is score is too low\n      const coords = tf.argMax(reshaped, 0);\n      const x = mod(coords, width).dataSync()[0];\n      const y = tf.div(coords, tf.scalar(width, 'int32')).dataSync()[0];\n      return [x, y, score];\n    }\n    return [0, 0, score];\n  });\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.body.skipFrames) && config.videoOptimized && Object.keys(keypoints).length > 0) {\n    skipped++;\n    return keypoints;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const tensor = tf.tidy(() => {\n      const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n      const enhance = tf.mul(resize, 2);\n      const norm = enhance.sub(1);\n      return norm;\n    });\n\n    let resT;\n\n    if (!config.profile) {\n      if (config.body.enabled) resT = await model.predict(tensor);\n    } else {\n      const profileT = config.body.enabled ? await tf.profile(() => model.predict(tensor)) : {};\n      resT = profileT.result.clone();\n      profileT.result.dispose();\n      profile.run('body', profileT);\n    }\n    tensor.dispose();\n\n    if (resT) {\n      const parts: Array<{ id, score, part, position: { x, y }, positionRaw: { xRaw, yRaw} }> = [];\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, score] = max2d(stack[id], config.body.scoreThreshold);\n        if (score > config.body.scoreThreshold) {\n          parts.push({\n            id,\n            score: Math.round(100 * score) / 100,\n            part: bodyParts[id],\n            positionRaw: {\n              xRaw: x / model.inputs[0].shape[2], // x normalized to 0..1\n              yRaw: y / model.inputs[0].shape[1], // y normalized to 0..1\n            },\n            position: {\n              x: Math.round(image.shape[2] * x / model.inputs[0].shape[2]), // x normalized to input image size\n              y: Math.round(image.shape[1] * y / model.inputs[0].shape[1]), // y normalized to input image size\n            },\n          });\n        }\n      }\n      stack.forEach((s) => tf.dispose(s));\n      keypoints = parts;\n    }\n    const score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n    resolve([{ score, keypoints }]);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport { labels } from './labels';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let id = 0;\n  let results: Array<{ score: number, strideSize: number, class: number, label: string, center: number[], centerRaw: number[], box: number[], boxRaw: number[] }> = [];\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(() => { // 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 = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === labels.length))?.squeeze();\n      const featuresT = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] < labels.length))?.squeeze();\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 = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      const scores = scoresT.arraySync(); // 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 && 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) => 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 = [x, y, w, h]; // results normalized to range 0..1\n            boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // 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,\n              center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n              centerRaw: [cx, cy],\n              box: box.map((a) => Math.trunc(a)),\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);\n  const nmsScores = results.map((a) => a.score);\n  let nmsIdx: any[] = [];\n  if (nmsBoxes && nmsBoxes.length > 0) {\n    const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n    nmsIdx = nms.dataSync();\n    tf.dispose(nms);\n  }\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n    resize.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result;\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export 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", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\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.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) 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) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\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];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (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\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), 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, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\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  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\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  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\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    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\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    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\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;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\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)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\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  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\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  ].join('\\n');\n\n  _filter.brightness = function (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  _filter.saturation = function (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  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\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  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (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\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  _filter.desaturateLuminance = function () {\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  _filter.sepia = function () {\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  _filter.brownie = function () {\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  _filter.vintagePinhole = function () {\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  _filter.kodachrome = function () {\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  _filter.technicolor = function () {\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  _filter.polaroid = function () {\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  _filter.shiftToBGR = function () {\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  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\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  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\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  _filter.emboss = function (size) {\n    const s = size || 1;\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  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\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  _filter.blur.SHADER = [\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  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\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  ].join('\\n');\n}\n", "// @ts-nocheck\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\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 function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (!input) throw new Error('Human: Input is missing');\n  if (\n    !(input instanceof tf.Tensor)\n    && !(typeof Image !== 'undefined' && input instanceof Image)\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('Human: Input type is not recognized');\n  }\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\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    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) throw new Error('Human: Input cannot determine dimension');\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) { // if we have data, just convert to tensor\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if (outCanvas instanceof ImageData) { // if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else if (config.backend === 'webgl' || config.backend === 'humangl') { // tf kernel-optimized method to get imagedata\n      // we can use canvas as-is as it already has a context, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      pixels = tf.browser.fromPixels(tempCanvas);\n    } else { // cpu and wasm kernel does not implement efficient fromPixels method\n      // we can use canvas as-is as it already has a context, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "import { defaults } from '../config';\nimport { TRI468 as triangulation } from '../blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n  useRawBoxes: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n      else rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.rotation && f.rotation.angle && f.rotation.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.rotation.angle.roll) / 100} yaw:${Math.trunc(100 * f.rotation.angle.yaw) / 100} pitch:${Math.trunc(100 * f.rotation.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.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 (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.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 (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      if (result[i].keypoints) {\n        for (const pt of result[i].keypoints) {\n          ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n          ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons && result[i].keypoints) {\n      let part;\n      const points: any[] = [];\n      // shoulder line\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // torso main\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 4) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas: HTMLCanvasElement, outCanvas: HTMLCanvasElement) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas: HTMLCanvasElement, result:any) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\n/**\n * Configuration interface definition for **Human** library\n *\n * Contains all configurable parameters\n */\nexport interface Config {\n  backend: string,\n  wasmPath: string,\n  debug: boolean,\n  async: boolean,\n  profile: boolean,\n  deallocate: boolean,\n  scoped: boolean,\n  videoOptimized: boolean,\n  warmup: string,\n  filter: {\n    enabled: boolean,\n    width: number,\n    height: number,\n    return: boolean,\n    brightness: number,\n    contrast: number,\n    sharpness: number,\n    blur: number\n    saturation: number,\n    hue: number,\n    negative: boolean,\n    sepia: boolean,\n    vintage: boolean,\n    kodachrome: boolean,\n    technicolor: boolean,\n    polaroid: boolean,\n    pixelate: number,\n  },\n  gesture: {\n    enabled: boolean,\n  },\n  face: {\n    enabled: boolean,\n    detector: {\n      modelPath: string,\n      rotation: boolean,\n      maxFaces: number,\n      skipFrames: number,\n      skipInitial: boolean,\n      minConfidence: number,\n      iouThreshold: number,\n      scoreThreshold: number,\n      return: boolean,\n    },\n    mesh: {\n      enabled: boolean,\n      modelPath: string,\n    },\n    iris: {\n      enabled: boolean,\n      modelPath: string,\n    },\n    description: {\n      enabled: boolean,\n      modelPath: string,\n      skipFrames: number,\n    },\n    age: {\n      enabled: boolean,\n      modelPath: string,\n      skipFrames: number,\n    },\n    gender: {\n      enabled: boolean,\n      minConfidence: number,\n      modelPath: string,\n      skipFrames: number,\n    },\n    emotion: {\n      enabled: boolean,\n      minConfidence: number,\n      skipFrames: number,\n      modelPath: string,\n    },\n    embedding: {\n      enabled: boolean,\n      modelPath: string,\n    },\n  },\n  body: {\n    enabled: boolean,\n    modelPath: string,\n    maxDetections: number,\n    scoreThreshold: number,\n    nmsRadius: number,\n  },\n  hand: {\n    enabled: boolean,\n    rotation: boolean,\n    skipFrames: number,\n    skipInitial: boolean,\n    minConfidence: number,\n    iouThreshold: number,\n    scoreThreshold: number,\n    maxHands: number,\n    landmarks: boolean,\n    detector: {\n      modelPath: string,\n    },\n    skeleton: {\n      modelPath: string,\n    },\n  },\n  object: {\n    enabled: boolean,\n    modelPath: string,\n    minConfidence: number,\n    iouThreshold: number,\n    maxResults: number,\n    skipFrames: number,\n  },\n}\n\nconst config: Config = {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // 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    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    description: {\n      enabled: true,         // to improve accuracy of face description extraction it is\n                             // recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/faceres.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 32,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    age: {\n      enabled: false,        // obsolete, replaced by description module\n      modelPath: '../models/age.json',\n      skipFrames: 33,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: false,        // obsolete, replaced by description module\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 34,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    embedding: {\n      enabled: false,        // obsolete, replaced by description module\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet', 'blazepose' or 'efficientpose'\n                             // 'blazepose' and 'efficientpose' are experimental\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n                             // 'nanodet' is experimental\n    minConfidence: 0.20,     // threshold for discarding a prediction\n    iouThreshold: 0.40,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 41,          // how many frames to go without re-running the detector\n  },\n};\nexport { config as defaults };\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"../src/blazeface/blazeface.ts", "../src/blazeface/box.ts", "../src/blazeface/util.ts", "../src/blazeface/coords.ts", "../src/blazeface/facepipeline.ts", "../src/posenet/posenet.ts", "../src/posenet/modelBase.ts", "../src/posenet/heapSort.ts", "../src/posenet/buildParts.ts", "../src/posenet/keypoints.ts", "../src/posenet/vectors.ts", "../src/posenet/decoders.ts", "../src/posenet/decodePose.ts", "../src/posenet/decodeMultiple.ts", "../src/posenet/util.ts", "../src/handpose/handpose.ts", "../src/handpose/box.ts", "../src/handpose/handdetector.ts", "../src/handpose/util.ts", "../src/handpose/handpipeline.ts", "../src/handpose/anchors.ts", "../src/blazepose/blazepose.ts", "../src/blazepose/annotations.ts", "../src/efficientpose/efficientpose.ts", "../src/nanodet/nanodet.ts", "../src/nanodet/labels.ts", "../src/gesture/gesture.ts", "../src/image/imagefx.js", "../src/image/image.ts", "../src/draw/draw.ts", "../src/config.ts", "../src/sample.ts"],
+  "sourcesContent": ["import { log, now, mergeDeep } from './helpers';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as faceall from './faceall';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as faceres from './faceres/faceres';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as efficientpose from './efficientpose/efficientpose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image/image';\nimport * as draw from './draw/draw';\nimport * as profile from './profile';\nimport { Config, defaults } from './config';\nimport { Result } from './result';\nimport * as sample from './sample';\nimport * as app from '../package.json';\n\n/** Generic Tensor object type */\nexport type Tensor = typeof tf.Tensor;\nexport type { Config } from './config';\nexport type { Result } from './result';\n/** Defines all possible input types for **Human** detection */\nexport type Input = Tensor | typeof Image | ImageData | ImageBitmap | HTMLImageElement | HTMLMediaElement | HTMLVideoElement | HTMLCanvasElement | OffscreenCanvas;\n\n/** Error message */\nexport type Error = { error: string };\n/** Instance of TensorFlow/JS */\nexport type TensorFlow = typeof tf;\n/** Generic Model object type, holds instance of individual models */\ntype Model = Object;\n\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 */\nexport class Human {\n  version: string;\n  config: Config;\n  state: string;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: TensorFlow;\n  draw: {\n    drawOptions?: typeof draw.drawOptions,\n    gesture: typeof draw.gesture,\n    face: typeof draw.face,\n    body: typeof draw.body,\n    hand: typeof draw.hand,\n    canvas: typeof draw.canvas,\n    all: typeof draw.all,\n  };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | Model | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    efficientpose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n    faceres: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n    faceres: typeof faceres;\n  };\n  faceTriangulation: typeof facemesh.triangulation;\n  faceUVMap: typeof facemesh.uvmap;\n  sysinfo: { platform: string, agent: string };\n  perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: boolean;\n  #checkSanity: boolean;\n  #firstRun: boolean;\n  // definition end\n\n  constructor(userConfig: Config | Object = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.version = app.version;\n    this.config = mergeDeep(defaults, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      efficientpose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n      faceres: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Input) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      faceres,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    this.faceTriangulation = facemesh.triangulation;\n    this.faceUVMap = facemesh.uvmap;\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | string => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_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  similarity(embedding1: Array<number>, embedding2: Array<number>): number {\n    if (this.config.face.description.enabled) return faceres.similarity(embedding1, embedding2);\n    if (this.config.face.embedding.enabled) return embedding.similarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return faceres.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<number>, db: Array<{ name: string, source: string, embedding: number[] }>, threshold = 0): { name: string, source: string, similarity: number, embedding: number[] } {\n    return faceres.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Config | Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        // @ts-ignore\n        this.models.handpose,\n        // @ts-ignore false warning with latest @typescript-eslint\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.efficientpose,\n        this.models.nanodet,\n        this.models.faceres,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? <Promise<handpose.HandPose>>handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.blazepose || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.efficientpose || (this.config.body.enabled && this.config.body.modelPath.includes('efficientpose') ? efficientpose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n        this.models.faceres || ((this.config.face.enabled && this.config.face.description.enabled) ? faceres.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.body.enabled && !this.models.efficientpose && this.config.body.modelPath.includes('efficientpose')) this.models.efficientpose = await efficientpose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n      if (this.config.face.enabled && this.config.face.description.enabled && !this.models.faceres) this.models.faceres = await faceres.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.perf.load || 0)) this.perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        // force browser vs node backend\n        if (this.tf.ENV.flags.IS_BROWSER && this.config.backend === 'tensorflow') this.config.backend = 'webgl';\n        if (this.tf.ENV.flags.IS_NODE && (this.config.backend === 'webgl' || this.config.backend === 'wasm')) this.config.backend = 'tensorflow';\n\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      // this.tf.enableDebugMode();\n      if (this.tf.getBackend() === 'webgl' || this.tf.getBackend() === 'humangl') {\n        this.tf.ENV.set('CHECK_COMPUTATION_FOR_ERRORS', false);\n        this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  // main detect function\n  async detect(input: Input, userConfig: Config | Object = {}): Promise<Result | Error> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.perf.image = Math.trunc(now() - timeStamp);\n      this.analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n      let current;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? faceall.detectFace(this, process.tensor) : [];\n        if (this.perf.face) delete this.perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await faceall.detectFace(this, process.tensor) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.face = current;\n      }\n\n      // run body: can be posenet or blazepose\n      this.analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('blazepose')) bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('efficientpose')) bodyRes = this.config.body.enabled ? efficientpose.predict(process.tensor, this.config) : [];\n        if (this.perf.body) delete this.perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('blazepose')) bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        else if (this.config.body.modelPath.includes('efficientpose')) bodyRes = this.config.body.enabled ? await efficientpose.predict(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.body = current;\n      }\n      this.analyze('End Body:');\n\n      // run handpose\n      this.analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.perf.hand) delete this.perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.hand = current;\n      }\n      this.analyze('End Hand:');\n\n      // run nanodet\n      this.analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.perf.object) delete this.perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        current = Math.trunc(now() - timeStamp);\n        if (current > 0) this.perf.object = current;\n      }\n      this.analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.perf.gesture) delete this.perf.gesture;\n      }\n\n      this.perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      const result = {\n        face: faceRes,\n        body: bodyRes,\n        hand: handRes,\n        gesture: gestureRes,\n        object: objectRes,\n        performance: this.perf,\n        canvas: process.canvas,\n      };\n      // log('Result:', result);\n      resolve(result);\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\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 this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.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    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Config | Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\n/**\n * Class Human is also available as default export\n */\nexport { Human as default };\n", "// helper function: wrapper around console output\nexport function log(...msg) {\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')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n\n// helper function: gets elapsed time on both browser and nodejs\nexport const now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nexport function mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n", "export function info(): { platform: string, agent: string } {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\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) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = 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) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\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\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) 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 + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\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\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 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xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}if(ENVIRONMENT_IS_NODE){if(typeof performance===\"undefined\"){global.performance=require(\"perf_hooks\").performance}}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var Atomics_load=Atomics.load;var Atomics_store=Atomics.store;var Atomics_compareExchange=Atomics.compareExchange;var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var wasmModule;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module[\"wasmMemory\"];buffer=Module[\"buffer\"]}else{if(Module[\"wasmMemory\"]){wasmMemory=Module[\"wasmMemory\"]}else{wasmMemory=new WebAssembly.Memory({\"initial\":INITIAL_MEMORY/65536,\"maximum\":2147483648/65536,\"shared\":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){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\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];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)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var 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print!==\"undefined\"){if(typeof console===\"undefined\")console={};console.log=print;console.warn=console.error=typeof printErr!==\"undefined\"?printErr:print}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href}else if(typeof document!==\"undefined\"&&document.currentScript){scriptDirectory=document.currentScript.src}if(_scriptDir){scriptDirectory=_scriptDir}if(scriptDirectory.indexOf(\"blob:\")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf(\"/\")+1)}else{scriptDirectory=\"\"}{read_=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,HEAPU8,outPtr,maxBytesToWrite)}function writeArrayToMemory(array,buffer){HEAP8.set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;__ATINIT__.push({func:function(){___wasm_call_ctors()}});function preRun(){if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmMemory=Module[\"asm\"][\"g\"];updateGlobalBufferAndViews(wasmMemory.buffer);wasmTable=Module[\"asm\"][\"m\"];removeRunDependency(\"wasm-instantiate\")}addRunDependency(\"wasm-instantiate\");function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _abort(){abort()}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num)}function _emscripten_get_heap_size(){return HEAPU8.length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=HEAP32[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){}function _fd_write(fd,iov,iovcnt,pnum){var num=0;for(var i=0;i<iovcnt;i++){var ptr=HEAP32[iov+i*8>>2];var len=HEAP32[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,HEAPU8[ptr+j])}num+=len}HEAP32[pnum>>2]=num;return 0}var asmLibraryArg={\"a\":_abort,\"d\":_emscripten_memcpy_big,\"e\":_emscripten_resize_heap,\"f\":_fd_close,\"c\":_fd_seek,\"b\":_fd_write};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"h\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"i\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"j\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"k\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"l\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"n\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"o\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"p\"]).apply(null,arguments)};var _ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"q\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"r\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"s\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"t\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"u\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"v\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"w\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"x\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"y\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"z\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"F\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _Log=Module[\"_Log\"]=function(){return(_Log=Module[\"_Log\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _LogicalAnd=Module[\"_LogicalAnd\"]=function(){return(_LogicalAnd=Module[\"_LogicalAnd\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _Max=Module[\"_Max\"]=function(){return(_Max=Module[\"_Max\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _MaxPool=Module[\"_MaxPool\"]=function(){return(_MaxPool=Module[\"_MaxPool\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Maximum=Module[\"_Maximum\"]=function(){return(_Maximum=Module[\"_Maximum\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Mean=Module[\"_Mean\"]=function(){return(_Mean=Module[\"_Mean\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var _Min=Module[\"_Min\"]=function(){return(_Min=Module[\"_Min\"]=Module[\"asm\"][\"X\"]).apply(null,arguments)};var _Minimum=Module[\"_Minimum\"]=function(){return(_Minimum=Module[\"_Minimum\"]=Module[\"asm\"][\"Y\"]).apply(null,arguments)};var _Multiply=Module[\"_Multiply\"]=function(){return(_Multiply=Module[\"_Multiply\"]=Module[\"asm\"][\"Z\"]).apply(null,arguments)};var _Neg=Module[\"_Neg\"]=function(){return(_Neg=Module[\"_Neg\"]=Module[\"asm\"][\"_\"]).apply(null,arguments)};var _NonMaxSuppressionV3=Module[\"_NonMaxSuppressionV3\"]=function(){return(_NonMaxSuppressionV3=Module[\"_NonMaxSuppressionV3\"]=Module[\"asm\"][\"$\"]).apply(null,arguments)};var _NonMaxSuppressionV4=Module[\"_NonMaxSuppressionV4\"]=function(){return(_NonMaxSuppressionV4=Module[\"_NonMaxSuppressionV4\"]=Module[\"asm\"][\"aa\"]).apply(null,arguments)};var 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_RealDiv=Module[\"_RealDiv\"]=function(){return(_RealDiv=Module[\"_RealDiv\"]=Module[\"asm\"][\"ia\"]).apply(null,arguments)};var _Relu=Module[\"_Relu\"]=function(){return(_Relu=Module[\"_Relu\"]=Module[\"asm\"][\"ja\"]).apply(null,arguments)};var _Relu6=Module[\"_Relu6\"]=function(){return(_Relu6=Module[\"_Relu6\"]=Module[\"asm\"][\"ka\"]).apply(null,arguments)};var _ResizeBilinear=Module[\"_ResizeBilinear\"]=function(){return(_ResizeBilinear=Module[\"_ResizeBilinear\"]=Module[\"asm\"][\"la\"]).apply(null,arguments)};var _Reverse=Module[\"_Reverse\"]=function(){return(_Reverse=Module[\"_Reverse\"]=Module[\"asm\"][\"ma\"]).apply(null,arguments)};var _RotateWithOffset=Module[\"_RotateWithOffset\"]=function(){return(_RotateWithOffset=Module[\"_RotateWithOffset\"]=Module[\"asm\"][\"na\"]).apply(null,arguments)};var _Round=Module[\"_Round\"]=function(){return(_Round=Module[\"_Round\"]=Module[\"asm\"][\"oa\"]).apply(null,arguments)};var 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_Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\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) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = 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) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\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\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) 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 + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\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\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");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;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(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;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}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);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}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);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var nodeFS=require(\"fs\");var nodeRead=function(filename){return nodeFS.readFileSync(filename,\"utf8\")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance===\"undefined\"){performance={now:function(){return Date.now()}}}}';", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1250, moduleBytes: 4013323, imports: 7, importBytes: 2255, outputBytes: 2991826, outputFiles: 'dist/tfjs.esm.js' }\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1253, moduleBytes: 4029357, imports: 7, importBytes: 2285, outputBytes: 2998298, outputFiles: 'dist/tfjs.esm.js' }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all - compiled\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all - sources\n/*\nexport * from '@tensorflow/tfjs-core/src/index';\nexport * from '@tensorflow/tfjs-layers/src/index';\nexport * from '@tensorflow/tfjs-converter/src/index';\nexport * as data from '@tensorflow/tfjs-data/src/index';\nexport * from '@tensorflow/tfjs-backend-cpu/src/index';\nexport * from '@tensorflow/tfjs-backend-webgl/src/index';\nexport * from '@tensorflow/tfjs-backend-wasm/src/index';\n*/\n\n// export versions\nexport const version = {\n  tfjs: packageBundle?.version || undefined,\n  'tfjs-core': packageCore?.version || undefined,\n  'tfjs-data': packageData?.version || undefined,\n  'tfjs-layers': packageLayers?.version || undefined,\n  'tfjs-converter': packageConverter?.version || undefined,\n  'tfjs-backend-cpu': version_cpu || undefined,\n  'tfjs-backend-webgl': version_webgl || undefined,\n  'tfjs-backend-wasm': version_wasm || undefined,\n};\n// export const version = {};\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\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\nexport function register(): void {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 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    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './helpers';\n\nexport const data = {};\n\nexport function run(modelName: string, profileData: any): void {\n  if (!profileData || !profileData.kernels) return;\n  const maxResults = 5;\n  const time = profileData.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = profileData.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = profileData.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  data[modelName] = {\n    model: modelName,\n    newBytes: profileData.newBytes,\n    newTensors: profileData.newTensors,\n    peakBytes: profileData.peakBytes,\n    numKernelOps: profileData.kernels.length,\n    timeKernelOps: time,\n    slowestKernelOps: slowest,\n    largestKernelOps: largest,\n  };\n  log('profiler', modelName, data[modelName]);\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(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 = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      if (!Array.isArray(genderT)) {\n        const data = genderT.dataSync();\n        if (alternative) {\n          // returns two values 0..1, bigger one is prediction\n          if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n            obj.gender = data[0] > data[1] ? 'female' : 'male';\n            obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n          }\n        } else {\n          // returns one value 0..1, .5 is prediction threshold\n          const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n          if (confidence > config.face.gender.minConfidence) {\n            obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n            obj.confidence = Math.min(0.99, confidence);\n          }\n        }\n        genderT.dispose();\n      } else {\n        const gender = genderT[0].dataSync();\n        const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n        /*\n        let age = genderT[1].argMax(1).dataSync()[0];\n        const all = genderT[1].dataSync();\n        age = Math.round(all[age - 1] > all[age + 1] ? 10 * age - 100 * all[age - 1] : 10 * age + 100 * all[age + 1]) / 10;\n        const descriptor = genderT[1].dataSync();\n        */\n        genderT.forEach((t) => tf.dispose(t));\n      }\n    }\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\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\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\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    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = typeof tf.Tensor;\ntype DB = Array<{ name: string, source: string, embedding: number[] }>;\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function similarity(embedding1, embedding2, order = 2): number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<number>, db: DB, threshold = 0) {\n  let best = { similarity: 0, name: '', source: '', embedding: [] as number[] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = similarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.similarity) best = { ...f, similarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = 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    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\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    // 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    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\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\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([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: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\ntype Tensor = typeof tf.Tensor;\ntype DB = Array<{ name: string, source: string, embedding: number[] }>;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.description.modelPath);\n    if (config.debug) log(`load model: ${config.face.description.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function similarity(embedding1, embedding2, order = 2): number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = 4.0 * embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(0, 100 - distance) / 100.0;\n  return res;\n}\n\nexport function match(embedding: Array<number>, db: DB, threshold = 0) {\n  let best = { similarity: 0, name: '', source: '', embedding: [] as number[] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = similarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.similarity) best = { ...f, similarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    const tensor = input.image || input.tensor || input;\n    if (!(tensor instanceof tf.Tensor)) return null;\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    // const crop = tf.image.resizeBilinear(tensor, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\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    /*\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\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n    /*\n    // normalize brightness from 0..1\n    const darken = crop.sub(crop.min());\n    const lighten = darken.div(darken.max());\n    */\n    const norm = crop.mul(255);\n\n    return norm;\n  });\n  return image;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.description.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    // const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    // const enhanced = tf.mul(resize, [255.0]);\n    // tf.dispose(resize);\n    const enhanced = enhance(image);\n\n    let resT;\n    const obj = {\n      age: <number>0,\n      gender: <string>'unknown',\n      genderConfidence: <number>0,\n      descriptor: <number[]>[] };\n\n    if (!config.profile) {\n      if (config.face.description.enabled) resT = await model.predict(enhanced);\n    } else {\n      const profileDesc = config.face.description.enabled ? await tf.profile(() => model.predict(enhanced)) : {};\n      resT = profileDesc.result;\n      profile.run('faceres', profileDesc);\n    }\n    tf.dispose(enhanced);\n\n    if (resT) {\n      tf.tidy(() => {\n        const gender = resT.find((t) => t.shape[1] === 1).dataSync();\n        const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n          obj.genderConfidence = Math.min(0.99, confidence);\n        }\n        const age = resT.find((t) => t.shape[1] === 100).argMax(1).dataSync()[0];\n        const all = resT.find((t) => t.shape[1] === 100).dataSync();\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]);\n        // const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n        obj.descriptor = [...desc.dataSync()];\n      });\n      resT.forEach((t) => tf.dispose(t));\n    }\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log, now } from './helpers';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as faceres from './faceres/faceres';\n\ntype Tensor = typeof tf.Tensor;\n\nconst calculateFaceAngle = (face, image_size): { angle: { pitch: number, yaw: number, roll: number }, matrix: [number, number, number, number, number, number, number, number, number] } => {\n  // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n  const degrees = (theta) => (theta * 180) / Math.PI;\n  // const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n  const normalize = (v) => { // 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, b) => { // 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, b) => { // 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) => {\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; let thetaY; let thetaZ;\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    return { pitch: 2 * -thetaX, yaw: 2 * -thetaY, roll: 2 * -thetaZ };\n  };\n  // simple Euler angle calculation based existing 3D mesh\n  // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n  const meshToEulerAngle = (mesh) => {\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // pitch is face move up/down\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\n      // yaw is face turn left/right\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\n      // roll is face lean 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\n    };\n    return angle;\n  };\n\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] };\n\n  const size = Math.max(face.boxRaw[2] * image_size[0], face.boxRaw[3] * image_size[1]) / 1.5;\n  // top, bottom, left, right\n  const pts = [mesh[10], mesh[152], mesh[234], mesh[454]].map((pt) => [\n    // make the xyz coordinates proportional, independent of the image/box size\n    pt[0] * image_size[0] / size,\n    pt[1] * image_size[1] / size,\n    pt[2],\n  ]);\n\n  const y_axis = normalize(subVectors(pts[1], pts[0]));\n  let x_axis = normalize(subVectors(pts[3], pts[2]));\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  return { angle, matrix };\n};\n\nexport const detectFace = async (parent, input): Promise<any> => {\n  // run facemesh, includes blazeface and iris\n  // eslint-disable-next-line no-async-promise-executor\n  let timeStamp;\n  let ageRes;\n  let genderRes;\n  let emotionRes;\n  let embeddingRes;\n  let descRes;\n  const faceRes: Array<{\n      confidence: number,\n      boxConfidence: number,\n      faceConfidence: number,\n      box: [number, number, number, number],\n      mesh: Array<[number, number, number]>\n      meshRaw: Array<[number, number, number]>\n      boxRaw: [number, number, number, number],\n      annotations: Array<{ part: string, points: Array<[number, number, number]>[] }>,\n      age: number,\n      gender: string,\n      genderConfidence: number,\n      emotion: string,\n      embedding: number[],\n      iris: number,\n      rotation: {\n        angle: { pitch: number, yaw: number, roll: number },\n        matrix: [number, number, number, number, number, number, number, number, number]\n      },\n      tensor: Tensor,\n    }> = [];\n  parent.state = 'run:face';\n  timeStamp = now();\n  const faces = await parent.models.face?.estimateFaces(input, parent.config);\n  parent.perf.face = Math.trunc(now() - timeStamp);\n  if (!faces) return [];\n  for (const face of faces) {\n    parent.analyze('Get Face');\n\n    // is something went wrong, skip the face\n    if (!face.image || face.image.isDisposedInternal) {\n      log('Face object is disposed:', face.image);\n      continue;\n    }\n\n    const rotation = calculateFaceAngle(face, [input.shape[2], input.shape[1]]);\n\n    // run age, inherits face from blazeface\n    parent.analyze('Start Age:');\n    if (parent.config.async) {\n      ageRes = parent.config.face.age.enabled ? age.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:age';\n      timeStamp = now();\n      ageRes = parent.config.face.age.enabled ? await age.predict(face.image, parent.config) : {};\n      parent.perf.age = Math.trunc(now() - timeStamp);\n    }\n\n    // run gender, inherits face from blazeface\n    parent.analyze('Start Gender:');\n    if (parent.config.async) {\n      genderRes = parent.config.face.gender.enabled ? gender.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:gender';\n      timeStamp = now();\n      genderRes = parent.config.face.gender.enabled ? await gender.predict(face.image, parent.config) : {};\n      parent.perf.gender = Math.trunc(now() - timeStamp);\n    }\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Emotion:');\n    if (parent.config.async) {\n      emotionRes = parent.config.face.emotion.enabled ? emotion.predict(face.image, parent.config) : {};\n    } else {\n      parent.state = 'run:emotion';\n      timeStamp = now();\n      emotionRes = parent.config.face.emotion.enabled ? await emotion.predict(face.image, parent.config) : {};\n      parent.perf.emotion = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Emotion:');\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Embedding:');\n    if (parent.config.async) {\n      embeddingRes = parent.config.face.embedding.enabled ? embedding.predict(face, parent.config) : [];\n    } else {\n      parent.state = 'run:embedding';\n      timeStamp = now();\n      embeddingRes = parent.config.face.embedding.enabled ? await embedding.predict(face, parent.config) : [];\n      parent.perf.embedding = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Embedding:');\n\n    // run emotion, inherits face from blazeface\n    parent.analyze('Start Description:');\n    if (parent.config.async) {\n      descRes = parent.config.face.description.enabled ? faceres.predict(face, parent.config) : [];\n    } else {\n      parent.state = 'run:description';\n      timeStamp = now();\n      descRes = parent.config.face.description.enabled ? await faceres.predict(face.image, parent.config) : [];\n      parent.perf.embedding = Math.trunc(now() - timeStamp);\n    }\n    parent.analyze('End Description:');\n\n    // if async wait for results\n    if (parent.config.async) {\n      [ageRes, genderRes, emotionRes, embeddingRes, descRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes, descRes]);\n    }\n\n    parent.analyze('Finish Face:');\n\n    // calculate iris distance\n    // iris: array[ center, left, top, right, bottom]\n    if (!parent.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n      delete face.annotations.leftEyeIris;\n      delete face.annotations.rightEyeIris;\n    }\n    const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n    /* average human iris size is 11.7mm */\n      ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n      : 0;\n\n    // combine results\n    faceRes.push({\n      ...face,\n      age: descRes.age || ageRes.age,\n      gender: descRes.gender || genderRes.gender,\n      genderConfidence: descRes.genderConfidence || genderRes.confidence,\n      embedding: descRes.descriptor || embeddingRes,\n      emotion: emotionRes,\n      iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n      rotation,\n      tensor: parent.config.face.detector.return ? face.image?.squeeze() : null,\n    });\n    // dispose original face tensor\n    face.image?.dispose();\n\n    parent.analyze('End Face');\n  }\n  parent.analyze('End FaceMesh:');\n  if (parent.config.async) {\n    if (parent.perf.face) delete parent.perf.face;\n    if (parent.perf.age) delete parent.perf.age;\n    if (parent.perf.gender) delete parent.perf.gender;\n    if (parent.perf.emotion) delete parent.perf.emotion;\n  }\n  return faceRes;\n};\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[2], prediction.box.endPoint[0]) - Math.max(0, prediction.box.startPoint[0]),\n        Math.min(input.shape[1], prediction.box.endPoint[1]) - Math.max(0, prediction.box.startPoint[1]),\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        prediction.box.startPoint[0] / input.shape[2],\n        prediction.box.startPoint[1] / input.shape[1],\n        (prediction.box.endPoint[0] - prediction.box.startPoint[0]) / input.shape[2],\n        (prediction.box.endPoint[1] - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: Math.round(100 * prediction.faceConfidence || 100 * prediction.boxConfidence || 0) / 100,\n        boxConfidence: Math.round(100 * prediction.boxConfidence) / 100,\n        faceConfidence: Math.round(100 * prediction.faceConfidence) / 100,\n        box,\n        boxRaw,\n        mesh,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config): Promise<MediaPipeFaceMesh> {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexport const triangulation = coords.TRI468;\nexport const uvmap = coords.UV468;\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\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++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\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 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]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\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];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\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 function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\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\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\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],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\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 MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\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, 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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 = [\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 = [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 = [\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 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\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 = [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 = [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", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\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], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  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.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\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.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\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 / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * 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.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${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\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (!config.videoOptimized || (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces)))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(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\n          // 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          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && (config.face.description.enabled || config.face.embedding.enabled) && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\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, landmarks };\n  }\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\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() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\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    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", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, 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(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.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 < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "export 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 NUM_KEYPOINTS = 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 const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\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", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\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 sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, 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 sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !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    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score: Math.round(100 * score) / 100 });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.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\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return 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: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, boxRaw: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - Math.max(0, prediction.box.topLeft[0]),\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - Math.max(0, prediction.box.topLeft[1]),\n      ] : [];\n      const boxRaw = [\n        (prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.topLeft[1]) / input.shape[1],\n        (prediction.box.bottomRight[0] - prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.bottomRight[1] - prediction.box.topLeft[1]) / input.shape[1],\n      ];\n      hands.push({ confidence: Math.round(100 * prediction.confidence) / 100, box, boxRaw, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config): Promise<HandPose> {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\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]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\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]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\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];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\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]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "export 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", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\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 box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.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 = [...box.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      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) 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.maxHands) || !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<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\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[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? 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 = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\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", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    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y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.3125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.4375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.4375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.4375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.4375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.4375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.4375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.5625,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.5625,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.5625,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.5625,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.5625,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.5625,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  const score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n  return [{ score, keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet keypoints: Array<any> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst bodyParts = ['head', 'neck', 'rightShoulder', 'rightElbow', 'rightWrist', 'chest', 'leftShoulder', 'leftElbow', 'leftWrist', 'pelvis', 'rightHip', 'rightKnee', 'rightAnkle', 'leftHip', 'leftKnee', 'leftAnkle'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\n// performs argmax and max functions on a 2d tensor\nfunction max2d(inputs, minScore) {\n  const [width, height] = inputs.shape;\n  return tf.tidy(() => {\n    // modulus op implemented in tf\n    const mod = (a, b) => tf.sub(a, tf.mul(tf.div(a, tf.scalar(b, 'int32')), tf.scalar(b, 'int32')));\n    // combine all data\n    const reshaped = tf.reshape(inputs, [height * width]);\n    // get highest score\n    const score = tf.max(reshaped, 0).dataSync()[0];\n    if (score > minScore) {\n      // skip coordinate calculation is score is too low\n      const coords = tf.argMax(reshaped, 0);\n      const x = mod(coords, width).dataSync()[0];\n      const y = tf.div(coords, tf.scalar(width, 'int32')).dataSync()[0];\n      return [x, y, score];\n    }\n    return [0, 0, score];\n  });\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.body.skipFrames) && config.videoOptimized && Object.keys(keypoints).length > 0) {\n    skipped++;\n    return keypoints;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const tensor = tf.tidy(() => {\n      const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n      const enhance = tf.mul(resize, 2);\n      const norm = enhance.sub(1);\n      return norm;\n    });\n\n    let resT;\n\n    if (!config.profile) {\n      if (config.body.enabled) resT = await model.predict(tensor);\n    } else {\n      const profileT = config.body.enabled ? await tf.profile(() => model.predict(tensor)) : {};\n      resT = profileT.result.clone();\n      profileT.result.dispose();\n      profile.run('body', profileT);\n    }\n    tensor.dispose();\n\n    if (resT) {\n      const parts: Array<{ id, score, part, position: { x, y }, positionRaw: { xRaw, yRaw} }> = [];\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, score] = max2d(stack[id], config.body.scoreThreshold);\n        if (score > config.body.scoreThreshold) {\n          parts.push({\n            id,\n            score: Math.round(100 * score) / 100,\n            part: bodyParts[id],\n            positionRaw: {\n              xRaw: x / model.inputs[0].shape[2], // x normalized to 0..1\n              yRaw: y / model.inputs[0].shape[1], // y normalized to 0..1\n            },\n            position: {\n              x: Math.round(image.shape[2] * x / model.inputs[0].shape[2]), // x normalized to input image size\n              y: Math.round(image.shape[1] * y / model.inputs[0].shape[1]), // y normalized to input image size\n            },\n          });\n        }\n      }\n      stack.forEach((s) => tf.dispose(s));\n      keypoints = parts;\n    }\n    const score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n    resolve([{ score, keypoints }]);\n  });\n}\n", "import { log } from '../helpers';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport { labels } from './labels';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let id = 0;\n  let results: Array<{ score: number, strideSize: number, class: number, label: string, center: number[], centerRaw: number[], box: number[], boxRaw: number[] }> = [];\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(() => { // 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 = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === labels.length))?.squeeze();\n      const featuresT = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] < labels.length))?.squeeze();\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 = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      const scores = scoresT.arraySync(); // 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 && 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) => 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 = [x, y, w, h]; // results normalized to range 0..1\n            boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // 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,\n              center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n              centerRaw: [cx, cy],\n              box: box.map((a) => Math.trunc(a)),\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);\n  const nmsScores = results.map((a) => a.score);\n  let nmsIdx: any[] = [];\n  if (nmsBoxes && nmsBoxes.length > 0) {\n    const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n    nmsIdx = nms.dataSync();\n    tf.dispose(nms);\n  }\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n    resize.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result;\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export 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", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\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.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) 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) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\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];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (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\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), 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, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\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  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\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  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\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    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\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    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\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;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\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)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\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  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\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  ].join('\\n');\n\n  _filter.brightness = function (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  _filter.saturation = function (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  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\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  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (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\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  _filter.desaturateLuminance = function () {\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  _filter.sepia = function () {\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  _filter.brownie = function () {\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  _filter.vintagePinhole = function () {\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  _filter.kodachrome = function () {\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  _filter.technicolor = function () {\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  _filter.polaroid = function () {\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  _filter.shiftToBGR = function () {\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  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\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  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\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  _filter.emboss = function (size) {\n    const s = size || 1;\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  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\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  _filter.blur.SHADER = [\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  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\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  ].join('\\n');\n}\n", "// @ts-nocheck\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\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 function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (!input) throw new Error('Human: Input is missing');\n  if (\n    !(input instanceof tf.Tensor)\n    && !(typeof Image !== 'undefined' && input instanceof Image)\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('Human: Input type is not recognized');\n  }\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\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    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) throw new Error('Human: Input cannot determine dimension');\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) { // if we have data, just convert to tensor\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if (outCanvas instanceof ImageData) { // if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else if (config.backend === 'webgl' || config.backend === 'humangl') { // tf kernel-optimized method to get imagedata\n      // we can use canvas as-is as it already has a context, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      pixels = tf.browser.fromPixels(tempCanvas);\n    } else { // cpu and wasm kernel does not implement efficient fromPixels method\n      // we can use canvas as-is as it already has a context, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "import { defaults } from '../config';\nimport { TRI468 as triangulation } from '../blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n  useRawBoxes: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n      else rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.rotation && f.rotation.angle && f.rotation.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.rotation.angle.roll) / 100} yaw:${Math.trunc(100 * f.rotation.angle.yaw) / 100} pitch:${Math.trunc(100 * f.rotation.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.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 (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.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 (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      if (result[i].keypoints) {\n        for (const pt of result[i].keypoints) {\n          ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n          ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons && result[i].keypoints) {\n      let part;\n      const points: any[] = [];\n      // shoulder line\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // torso main\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 4) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > defaults.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas: HTMLCanvasElement, result: Array<any>) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas: HTMLCanvasElement, outCanvas: HTMLCanvasElement) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas: HTMLCanvasElement, result:any) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\n/**\n * Configuration interface definition for **Human** library\n *\n * Contains all configurable parameters\n */\nexport interface Config {\n  backend: string,\n  wasmPath: string,\n  debug: boolean,\n  async: boolean,\n  profile: boolean,\n  deallocate: boolean,\n  scoped: boolean,\n  videoOptimized: boolean,\n  warmup: string,\n  filter: {\n    enabled: boolean,\n    width: number,\n    height: number,\n    return: boolean,\n    brightness: number,\n    contrast: number,\n    sharpness: number,\n    blur: number\n    saturation: number,\n    hue: number,\n    negative: boolean,\n    sepia: boolean,\n    vintage: boolean,\n    kodachrome: boolean,\n    technicolor: boolean,\n    polaroid: boolean,\n    pixelate: number,\n  },\n  gesture: {\n    enabled: boolean,\n  },\n  face: {\n    enabled: boolean,\n    detector: {\n      modelPath: string,\n      rotation: boolean,\n      maxFaces: number,\n      skipFrames: number,\n      skipInitial: boolean,\n      minConfidence: number,\n      iouThreshold: number,\n      scoreThreshold: number,\n      return: boolean,\n    },\n    mesh: {\n      enabled: boolean,\n      modelPath: string,\n    },\n    iris: {\n      enabled: boolean,\n      modelPath: string,\n    },\n    description: {\n      enabled: boolean,\n      modelPath: string,\n      skipFrames: number,\n    },\n    age: {\n      enabled: boolean,\n      modelPath: string,\n      skipFrames: number,\n    },\n    gender: {\n      enabled: boolean,\n      minConfidence: number,\n      modelPath: string,\n      skipFrames: number,\n    },\n    emotion: {\n      enabled: boolean,\n      minConfidence: number,\n      skipFrames: number,\n      modelPath: string,\n    },\n    embedding: {\n      enabled: boolean,\n      modelPath: string,\n    },\n  },\n  body: {\n    enabled: boolean,\n    modelPath: string,\n    maxDetections: number,\n    scoreThreshold: number,\n    nmsRadius: number,\n  },\n  hand: {\n    enabled: boolean,\n    rotation: boolean,\n    skipFrames: number,\n    skipInitial: boolean,\n    minConfidence: number,\n    iouThreshold: number,\n    scoreThreshold: number,\n    maxHands: number,\n    landmarks: boolean,\n    detector: {\n      modelPath: string,\n    },\n    skeleton: {\n      modelPath: string,\n    },\n  },\n  object: {\n    enabled: boolean,\n    modelPath: string,\n    minConfidence: number,\n    iouThreshold: number,\n    maxResults: number,\n    skipFrames: number,\n  },\n}\n\nconst config: Config = {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // 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    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    description: {\n      enabled: true,         // to improve accuracy of face description extraction it is\n                             // recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/faceres.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 32,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    age: {\n      enabled: false,        // obsolete, replaced by description module\n      modelPath: '../models/age.json',\n      skipFrames: 33,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: false,        // obsolete, replaced by description module\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 34,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    embedding: {\n      enabled: false,        // obsolete, replaced by description module\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet', 'blazepose' or 'efficientpose'\n                             // 'blazepose' and 'efficientpose' are experimental\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n                             // 'nanodet' is experimental\n    minConfidence: 0.20,     // threshold for discarding a prediction\n    iouThreshold: 0.40,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 41,          // how many frames to go without re-running the detector\n  },\n};\nexport { config as defaults };\n", "// data:image/jpeg;base64,\nexport const face = 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diff --git a/dist/human.node-gpu.js b/dist/human.node-gpu.js
index 41f686ac..dba8f689 100644
--- a/dist/human.node-gpu.js
+++ b/dist/human.node-gpu.js
@@ -731,5 +731,5 @@ AAAAAAJAAAAAAAAAAAAAABAJEAAAAAAAAAAAAAAAIEoBKAAAAAAAAAAAAAAABAlAAAAAAAIAAAAA
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this.detect(_,this.config);t(o)},n?r.src=n:t(null)}));mt.set(this,async()=>{let t=A=>Buffer.from(A,"base64"),n=this.config.warmup==="face"?t(yt):t(wt),c=E1.node.decodeJpeg(n),r=c.expandDims(0);this.tf.dispose(c);let _=await this.detect(r,this.config);return this.tf.dispose(r),_});this.tf=E1,this.draw=M1,this.version=Z0,this.config=pe(j,t),this.state="idle",le(this,ze,0),le(this,Oe,!1),le(this,ke,!1),le(this,me,!0),this.perf={},this.models={face:null,posenet:null,blazepose:null,efficientpose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null,faceres:null},this.image=n=>v1(n,this.config),this.classes={facemesh:Bt,age:gt,gender:Pt,emotion:Rt,faceres:kt,body:this.config.body.modelPath.includes("posenet")?c1:d1,hand:a1,nanodet:b1},this.faceTriangulation=U1,this.faceUVMap=D1,this.sysinfo=N1()}profileData(){return this.config.profile?Ve:{}}similarity(t,n){return 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Promise.all([this.models.face||(this.config.face.enabled?Kt(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?Tt(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?Et(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?Wt(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?Nt(this.config):null),this.models.handpose||(this.config.hand.enabled?l1(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?_1(this.config):null),this.models.blazepose||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?f1(this.config):null),this.models.efficientpose||(this.config.body.enabled&&this.config.body.modelPath.includes("efficientpose")?p1(this.config):null),this.models.nanodet||(this.config.object.enabled?T1(this.config):null),this.models.faceres||(this.config.face.enabled&&this.config.face.description.enabled?It(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await Kt(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await Tt(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await Et(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await Wt(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await Nt(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await l1(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await _1(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await f1(this.config)),this.config.body.enabled&&!this.models.efficientpose&&this.config.body.modelPath.includes("efficientpose")&&(this.models.efficientpose=await p1(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await T1(this.config)),this.config.face.enabled&&this.config.face.description.enabled&&!this.models.faceres&&(this.models.faceres=await It(this.config))),D(this,me)&&(this.config.debug&&g("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),le(this,me,!1));let c=Math.trunc(z()-n);c>(this.perf.load||0)&&(this.perf.load=c)}async detect(t,n={}){return new Promise(async c=>{var x,d,f,T;this.state="config";let r;this.config=pe(this.config,n),this.state="check";let _=D(this,lt).call(this,t);_&&(g(_,t),c({error:_}));let A=z();await D(this,Ie).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),this.analyze("Start Scope:"),r=z();let o=v1(t,this.config);if(!o||!o.tensor){g("could not convert input to tensor"),c({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(z()-r),this.analyze("Get Image:");let s,i,a,h,y;this.config.async?(a=this.config.face.enabled?Vt(this,o.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",r=z(),a=this.config.face.enabled?await Vt(this,o.tensor):[],y=Math.trunc(z()-r),y>0&&(this.perf.face=y)),this.analyze("Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?s=this.config.body.enabled?(x=this.models.posenet)==null?void 0:x.estimatePoses(o.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?s=this.config.body.enabled?m1(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(s=this.config.body.enabled?u1(o.tensor,this.config):[]),this.perf.body&&delete this.perf.body):(this.state="run:body",r=z(),this.config.body.modelPath.includes("posenet")?s=this.config.body.enabled?await((d=this.models.posenet)==null?void 0:d.estimatePoses(o.tensor,this.config)):[]:this.config.body.modelPath.includes("blazepose")?s=this.config.body.enabled?await m1(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(s=this.config.body.enabled?await u1(o.tensor,this.config):[]),y=Math.trunc(z()-r),y>0&&(this.perf.body=y)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(i=this.config.hand.enabled?(f=this.models.handpose)==null?void 0:f.estimateHands(o.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",r=z(),i=this.config.hand.enabled?await((T=this.models.handpose)==null?void 0:T.estimateHands(o.tensor,this.config)):[],y=Math.trunc(z()-r),y>0&&(this.perf.hand=y)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.config.async?(h=this.config.object.enabled?P1(o.tensor,this.config):[],this.perf.object&&delete this.perf.object):(this.state="run:object",r=z(),h=this.config.object.enabled?await P1(o.tensor,this.config):[],y=Math.trunc(z()-r),y>0&&(this.perf.object=y)),this.analyze("End Object:"),this.config.async&&([a,s,i,h]=await Promise.all([a,s,i,h])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),this.analyze("End Scope:");let m=[];this.config.gesture.enabled&&(r=z(),m=[...E0(a),...z0(s),...S0(i),...R0(a)],this.config.async?this.perf.gesture&&delete this.perf.gesture:this.perf.gesture=Math.trunc(z()-r)),this.perf.total=Math.trunc(z()-A),this.state="idle";let p={face:a,body:s,hand:i,gesture:m,object:h,performance:this.perf,canvas:o.canvas};c(p)})}async warmup(t={}){let n=z();t&&(this.config=pe(this.config,t));let c=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await D(this,dt).call(this):typeof Image!="undefined"?r=await D(this,ft).call(this):r=await D(this,mt).call(this),this.config.videoOptimized=c;let _=z();return this.config.debug&&g("Warmup",this.config.warmup,Math.round(_-n),"ms",r),r}};ze=new WeakMap,Oe=new WeakMap,ke=new WeakMap,me=new WeakMap,lt=new WeakMap,Ie=new WeakMap,dt=new WeakMap,ft=new WeakMap,mt=new WeakMap;0&&(module.exports={Human});
+2Q==`;var Z0="1.3.5";var ze,Oe,ke,me,lt,Ie,dt,ft,mt,L0=class{constructor(t={}){ze.set(this,void 0);Oe.set(this,void 0);ke.set(this,void 0);me.set(this,void 0);this.analyze=(...t)=>{if(!D(this,Oe))return;let n=this.tf.engine().state.numTensors,c=D(this,ze);le(this,ze,n);let r=n-c;r!==0&&g(...t,r)};lt.set(this,t=>{if(!D(this,ke))return null;if(!t)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(t instanceof E1.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});Ie.set(this,async(t=!1)=>{if(this.config.backend&&this.config.backend!==""&&t||this.tf.getBackend()!==this.config.backend){let n=z();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.tf.ENV.flags.IS_BROWSER&&this.config.backend==="tensorflow"&&(this.config.backend="webgl"),this.tf.ENV.flags.IS_NODE&&(this.config.backend==="webgl"||this.config.backend==="wasm")&&(this.config.backend="tensorflow"),this.config.debug&&g("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&g("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let c=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),r=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&g(`wasm execution: ${c?"SIMD":"no SIMD"} ${r?"multithreaded":"singlethreaded"}`),c||g("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&I1();try{await this.tf.setBackend(this.config.backend)}catch(c){g("error: cannot set backend:",this.config.backend,c)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"||this.tf.getBackend()==="humangl"){this.tf.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),this.tf.ENV.set("WEBGL_PACK_DEPTHWISECONV",!0),this.config.deallocate&&(g("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let c=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&g(`gl version:${c.getParameter(c.VERSION)} renderer:${c.getParameter(c.RENDERER)}`)}await this.tf.ready(),this.perf.backend=Math.trunc(z()-n)}});dt.set(this,async()=>{let t=(r,_="application/octet-stream")=>fetch(`data:${_};base64,${r}`).then(A=>A.blob()),n,c;switch(this.config.warmup){case"face":n=await t(yt);break;case"full":n=await t(wt);break;default:n=null}if(n){let r=await createImageBitmap(n);c=await this.detect(r,this.config),r.close()}return c});ft.set(this,async()=>new Promise(t=>{let n,c=0;switch(this.config.warmup){case"face":c=256,n="data:image/jpeg;base64,"+yt;break;case"full":case"body":c=1200,n="data:image/jpeg;base64,"+wt;break;default:n=null}let r=new Image;r.onload=async()=>{let _=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(c,c):document.createElement("canvas");_.width=r.naturalWidth,_.height=r.naturalHeight;let A=_.getContext("2d");A==null||A.drawImage(r,0,0);let o=await this.detect(_,this.config);t(o)},n?r.src=n:t(null)}));mt.set(this,async()=>{let t=A=>Buffer.from(A,"base64"),n=this.config.warmup==="face"?t(yt):t(wt),c=E1.node.decodeJpeg(n),r=c.expandDims(0);this.tf.dispose(c);let _=await this.detect(r,this.config);return this.tf.dispose(r),_});this.tf=E1,this.draw=M1,this.version=Z0,this.config=pe(j,t),this.state="idle",le(this,ze,0),le(this,Oe,!1),le(this,ke,!1),le(this,me,!0),this.perf={},this.models={face:null,posenet:null,blazepose:null,efficientpose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null,faceres:null},this.image=n=>v1(n,this.config),this.classes={facemesh:Bt,age:gt,gender:Pt,emotion:Rt,faceres:kt,body:this.config.body.modelPath.includes("posenet")?c1:d1,hand:a1,nanodet:b1},this.faceTriangulation=U1,this.faceUVMap=D1,this.sysinfo=N1()}profileData(){return this.config.profile?Ve:{}}similarity(t,n){return this.config.face.description.enabled?Zt(t,n):this.config.face.embedding.enabled?Z1(t,n):0}enhance(t){return Lt(t)}match(t,n,c=0){return L1(t,n,c)}async load(t={}){this.state="load";let n=z();t&&(this.config=pe(this.config,t)),D(this,me)&&(this.config.debug&&g(`version: ${this.version}`),this.config.debug&&g(`tfjs version: ${this.tf.version_core}`),this.config.debug&&g("platform:",this.sysinfo.platform),this.config.debug&&g("agent:",this.sysinfo.agent),await D(this,Ie).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&g("configuration:",this.config),this.config.debug&&g("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.efficientpose,this.models.nanodet,this.models.faceres]=await Promise.all([this.models.face||(this.config.face.enabled?Kt(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?Tt(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?Et(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?Wt(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?Nt(this.config):null),this.models.handpose||(this.config.hand.enabled?l1(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?_1(this.config):null),this.models.blazepose||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?f1(this.config):null),this.models.efficientpose||(this.config.body.enabled&&this.config.body.modelPath.includes("efficientpose")?p1(this.config):null),this.models.nanodet||(this.config.object.enabled?T1(this.config):null),this.models.faceres||(this.config.face.enabled&&this.config.face.description.enabled?It(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await Kt(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await Tt(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await Et(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await Wt(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await Nt(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await l1(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await _1(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await f1(this.config)),this.config.body.enabled&&!this.models.efficientpose&&this.config.body.modelPath.includes("efficientpose")&&(this.models.efficientpose=await p1(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await T1(this.config)),this.config.face.enabled&&this.config.face.description.enabled&&!this.models.faceres&&(this.models.faceres=await It(this.config))),D(this,me)&&(this.config.debug&&g("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),le(this,me,!1));let c=Math.trunc(z()-n);c>(this.perf.load||0)&&(this.perf.load=c)}async detect(t,n={}){return new Promise(async c=>{var x,d,f,T;this.state="config";let r;this.config=pe(this.config,n),this.state="check";let _=D(this,lt).call(this,t);_&&(g(_,t),c({error:_}));let A=z();await D(this,Ie).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),this.analyze("Start Scope:"),r=z();let o=v1(t,this.config);if(!o||!o.tensor){g("could not convert input to tensor"),c({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(z()-r),this.analyze("Get Image:");let s,i,a,h,y;this.config.async?(a=this.config.face.enabled?Vt(this,o.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",r=z(),a=this.config.face.enabled?await Vt(this,o.tensor):[],y=Math.trunc(z()-r),y>0&&(this.perf.face=y)),this.analyze("Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?s=this.config.body.enabled?(x=this.models.posenet)==null?void 0:x.estimatePoses(o.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?s=this.config.body.enabled?m1(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(s=this.config.body.enabled?u1(o.tensor,this.config):[]),this.perf.body&&delete this.perf.body):(this.state="run:body",r=z(),this.config.body.modelPath.includes("posenet")?s=this.config.body.enabled?await((d=this.models.posenet)==null?void 0:d.estimatePoses(o.tensor,this.config)):[]:this.config.body.modelPath.includes("blazepose")?s=this.config.body.enabled?await m1(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(s=this.config.body.enabled?await u1(o.tensor,this.config):[]),y=Math.trunc(z()-r),y>0&&(this.perf.body=y)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(i=this.config.hand.enabled?(f=this.models.handpose)==null?void 0:f.estimateHands(o.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",r=z(),i=this.config.hand.enabled?await((T=this.models.handpose)==null?void 0:T.estimateHands(o.tensor,this.config)):[],y=Math.trunc(z()-r),y>0&&(this.perf.hand=y)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.config.async?(h=this.config.object.enabled?P1(o.tensor,this.config):[],this.perf.object&&delete this.perf.object):(this.state="run:object",r=z(),h=this.config.object.enabled?await P1(o.tensor,this.config):[],y=Math.trunc(z()-r),y>0&&(this.perf.object=y)),this.analyze("End Object:"),this.config.async&&([a,s,i,h]=await Promise.all([a,s,i,h])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),this.analyze("End Scope:");let m=[];this.config.gesture.enabled&&(r=z(),m=[...E0(a),...z0(s),...S0(i),...R0(a)],this.config.async?this.perf.gesture&&delete this.perf.gesture:this.perf.gesture=Math.trunc(z()-r)),this.perf.total=Math.trunc(z()-A),this.state="idle";let p={face:a,body:s,hand:i,gesture:m,object:h,performance:this.perf,canvas:o.canvas};c(p)})}async warmup(t={}){let n=z();t&&(this.config=pe(this.config,t));let c=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await D(this,dt).call(this):typeof Image!="undefined"?r=await D(this,ft).call(this):r=await D(this,mt).call(this),this.config.videoOptimized=c;let _=z();return this.config.debug&&g("Warmup",this.config.warmup,Math.round(_-n),"ms",r),r}};ze=new WeakMap,Oe=new WeakMap,ke=new WeakMap,me=new WeakMap,lt=new WeakMap,Ie=new WeakMap,dt=new WeakMap,ft=new WeakMap,mt=new WeakMap;0&&(module.exports={Human});
 //# sourceMappingURL=human.node-gpu.js.map
diff --git a/dist/human.node.js b/dist/human.node.js
index 763ff8a4..9a7d6bb2 100644
--- a/dist/human.node.js
+++ b/dist/human.node.js
@@ -731,5 +731,5 @@ AAAAAAJAAAAAAAAAAAAAABAJEAAAAAAAAAAAAAAAIEoBKAAAAAAAAAAAAAAABAlAAAAAAAIAAAAA
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-2Q==`;var Z0="1.3.4";var ze,Oe,ke,me,lt,Ie,dt,ft,mt,L0=class{constructor(t={}){ze.set(this,void 0);Oe.set(this,void 0);ke.set(this,void 0);me.set(this,void 0);this.analyze=(...t)=>{if(!D(this,Oe))return;let n=this.tf.engine().state.numTensors,c=D(this,ze);le(this,ze,n);let r=n-c;r!==0&&g(...t,r)};lt.set(this,t=>{if(!D(this,ke))return null;if(!t)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(t instanceof E1.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});Ie.set(this,async(t=!1)=>{if(this.config.backend&&this.config.backend!==""&&t||this.tf.getBackend()!==this.config.backend){let n=z();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.tf.ENV.flags.IS_BROWSER&&this.config.backend==="tensorflow"&&(this.config.backend="webgl"),this.tf.ENV.flags.IS_NODE&&(this.config.backend==="webgl"||this.config.backend==="wasm")&&(this.config.backend="tensorflow"),this.config.debug&&g("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&g("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let c=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),r=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&g(`wasm execution: ${c?"SIMD":"no SIMD"} ${r?"multithreaded":"singlethreaded"}`),c||g("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&I1();try{await this.tf.setBackend(this.config.backend)}catch(c){g("error: cannot set backend:",this.config.backend,c)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"||this.tf.getBackend()==="humangl"){this.tf.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),this.tf.ENV.set("WEBGL_PACK_DEPTHWISECONV",!0),this.config.deallocate&&(g("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let c=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&g(`gl version:${c.getParameter(c.VERSION)} renderer:${c.getParameter(c.RENDERER)}`)}await this.tf.ready(),this.perf.backend=Math.trunc(z()-n)}});dt.set(this,async()=>{let t=(r,_="application/octet-stream")=>fetch(`data:${_};base64,${r}`).then(A=>A.blob()),n,c;switch(this.config.warmup){case"face":n=await t(yt);break;case"full":n=await t(wt);break;default:n=null}if(n){let r=await createImageBitmap(n);c=await this.detect(r,this.config),r.close()}return c});ft.set(this,async()=>new Promise(t=>{let n,c=0;switch(this.config.warmup){case"face":c=256,n="data:image/jpeg;base64,"+yt;break;case"full":case"body":c=1200,n="data:image/jpeg;base64,"+wt;break;default:n=null}let r=new Image;r.onload=async()=>{let _=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(c,c):document.createElement("canvas");_.width=r.naturalWidth,_.height=r.naturalHeight;let A=_.getContext("2d");A==null||A.drawImage(r,0,0);let o=await this.detect(_,this.config);t(o)},n?r.src=n:t(null)}));mt.set(this,async()=>{let t=A=>Buffer.from(A,"base64"),n=this.config.warmup==="face"?t(yt):t(wt),c=E1.node.decodeJpeg(n),r=c.expandDims(0);this.tf.dispose(c);let _=await this.detect(r,this.config);return this.tf.dispose(r),_});this.tf=E1,this.draw=M1,this.version=Z0,this.config=pe(j,t),this.state="idle",le(this,ze,0),le(this,Oe,!1),le(this,ke,!1),le(this,me,!0),this.perf={},this.models={face:null,posenet:null,blazepose:null,efficientpose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null,faceres:null},this.image=n=>v1(n,this.config),this.classes={facemesh:Bt,age:gt,gender:Pt,emotion:Rt,faceres:kt,body:this.config.body.modelPath.includes("posenet")?c1:d1,hand:a1,nanodet:b1},this.faceTriangulation=U1,this.faceUVMap=D1,this.sysinfo=N1()}profileData(){return this.config.profile?Ve:{}}similarity(t,n){return this.config.face.description.enabled?Zt(t,n):this.config.face.embedding.enabled?Z1(t,n):0}enhance(t){return Lt(t)}match(t,n,c=0){return L1(t,n,c)}async load(t={}){this.state="load";let n=z();t&&(this.config=pe(this.config,t)),D(this,me)&&(this.config.debug&&g(`version: ${this.version}`),this.config.debug&&g(`tfjs version: ${this.tf.version_core}`),this.config.debug&&g("platform:",this.sysinfo.platform),this.config.debug&&g("agent:",this.sysinfo.agent),await D(this,Ie).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&g("configuration:",this.config),this.config.debug&&g("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.efficientpose,this.models.nanodet,this.models.faceres]=await Promise.all([this.models.face||(this.config.face.enabled?Kt(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?Tt(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?Et(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?Wt(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?Nt(this.config):null),this.models.handpose||(this.config.hand.enabled?l1(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?_1(this.config):null),this.models.blazepose||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?f1(this.config):null),this.models.efficientpose||(this.config.body.enabled&&this.config.body.modelPath.includes("efficientpose")?p1(this.config):null),this.models.nanodet||(this.config.object.enabled?T1(this.config):null),this.models.faceres||(this.config.face.enabled&&this.config.face.description.enabled?It(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await Kt(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await Tt(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await Et(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await Wt(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await Nt(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await l1(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await _1(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await f1(this.config)),this.config.body.enabled&&!this.models.efficientpose&&this.config.body.modelPath.includes("efficientpose")&&(this.models.efficientpose=await p1(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await T1(this.config)),this.config.face.enabled&&this.config.face.description.enabled&&!this.models.faceres&&(this.models.faceres=await It(this.config))),D(this,me)&&(this.config.debug&&g("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),le(this,me,!1));let c=Math.trunc(z()-n);c>(this.perf.load||0)&&(this.perf.load=c)}async detect(t,n={}){return new Promise(async c=>{var x,d,f,T;this.state="config";let r;this.config=pe(this.config,n),this.state="check";let _=D(this,lt).call(this,t);_&&(g(_,t),c({error:_}));let A=z();await D(this,Ie).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),this.analyze("Start Scope:"),r=z();let o=v1(t,this.config);if(!o||!o.tensor){g("could not convert input to tensor"),c({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(z()-r),this.analyze("Get Image:");let s,i,a,h,y;this.config.async?(a=this.config.face.enabled?Vt(this,o.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",r=z(),a=this.config.face.enabled?await Vt(this,o.tensor):[],y=Math.trunc(z()-r),y>0&&(this.perf.face=y)),this.analyze("Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?s=this.config.body.enabled?(x=this.models.posenet)==null?void 0:x.estimatePoses(o.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?s=this.config.body.enabled?m1(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(s=this.config.body.enabled?u1(o.tensor,this.config):[]),this.perf.body&&delete this.perf.body):(this.state="run:body",r=z(),this.config.body.modelPath.includes("posenet")?s=this.config.body.enabled?await((d=this.models.posenet)==null?void 0:d.estimatePoses(o.tensor,this.config)):[]:this.config.body.modelPath.includes("blazepose")?s=this.config.body.enabled?await m1(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(s=this.config.body.enabled?await u1(o.tensor,this.config):[]),y=Math.trunc(z()-r),y>0&&(this.perf.body=y)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(i=this.config.hand.enabled?(f=this.models.handpose)==null?void 0:f.estimateHands(o.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",r=z(),i=this.config.hand.enabled?await((T=this.models.handpose)==null?void 0:T.estimateHands(o.tensor,this.config)):[],y=Math.trunc(z()-r),y>0&&(this.perf.hand=y)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.config.async?(h=this.config.object.enabled?P1(o.tensor,this.config):[],this.perf.object&&delete this.perf.object):(this.state="run:object",r=z(),h=this.config.object.enabled?await P1(o.tensor,this.config):[],y=Math.trunc(z()-r),y>0&&(this.perf.object=y)),this.analyze("End Object:"),this.config.async&&([a,s,i,h]=await Promise.all([a,s,i,h])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),this.analyze("End Scope:");let m=[];this.config.gesture.enabled&&(r=z(),m=[...E0(a),...z0(s),...S0(i),...R0(a)],this.config.async?this.perf.gesture&&delete this.perf.gesture:this.perf.gesture=Math.trunc(z()-r)),this.perf.total=Math.trunc(z()-A),this.state="idle";let p={face:a,body:s,hand:i,gesture:m,object:h,performance:this.perf,canvas:o.canvas};c(p)})}async warmup(t={}){let n=z();t&&(this.config=pe(this.config,t));let c=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await D(this,dt).call(this):typeof Image!="undefined"?r=await D(this,ft).call(this):r=await D(this,mt).call(this),this.config.videoOptimized=c;let _=z();return this.config.debug&&g("Warmup",this.config.warmup,Math.round(_-n),"ms",r),r}};ze=new WeakMap,Oe=new WeakMap,ke=new WeakMap,me=new WeakMap,lt=new WeakMap,Ie=new WeakMap,dt=new WeakMap,ft=new WeakMap,mt=new WeakMap;0&&(module.exports={Human});
+2Q==`;var Z0="1.3.5";var ze,Oe,ke,me,lt,Ie,dt,ft,mt,L0=class{constructor(t={}){ze.set(this,void 0);Oe.set(this,void 0);ke.set(this,void 0);me.set(this,void 0);this.analyze=(...t)=>{if(!D(this,Oe))return;let n=this.tf.engine().state.numTensors,c=D(this,ze);le(this,ze,n);let r=n-c;r!==0&&g(...t,r)};lt.set(this,t=>{if(!D(this,ke))return null;if(!t)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(t instanceof E1.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});Ie.set(this,async(t=!1)=>{if(this.config.backend&&this.config.backend!==""&&t||this.tf.getBackend()!==this.config.backend){let n=z();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.tf.ENV.flags.IS_BROWSER&&this.config.backend==="tensorflow"&&(this.config.backend="webgl"),this.tf.ENV.flags.IS_NODE&&(this.config.backend==="webgl"||this.config.backend==="wasm")&&(this.config.backend="tensorflow"),this.config.debug&&g("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&g("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let c=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),r=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&g(`wasm execution: ${c?"SIMD":"no SIMD"} ${r?"multithreaded":"singlethreaded"}`),c||g("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&I1();try{await this.tf.setBackend(this.config.backend)}catch(c){g("error: cannot set backend:",this.config.backend,c)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"||this.tf.getBackend()==="humangl"){this.tf.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),this.tf.ENV.set("WEBGL_PACK_DEPTHWISECONV",!0),this.config.deallocate&&(g("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let c=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&g(`gl version:${c.getParameter(c.VERSION)} renderer:${c.getParameter(c.RENDERER)}`)}await this.tf.ready(),this.perf.backend=Math.trunc(z()-n)}});dt.set(this,async()=>{let t=(r,_="application/octet-stream")=>fetch(`data:${_};base64,${r}`).then(A=>A.blob()),n,c;switch(this.config.warmup){case"face":n=await t(yt);break;case"full":n=await t(wt);break;default:n=null}if(n){let r=await createImageBitmap(n);c=await this.detect(r,this.config),r.close()}return c});ft.set(this,async()=>new Promise(t=>{let n,c=0;switch(this.config.warmup){case"face":c=256,n="data:image/jpeg;base64,"+yt;break;case"full":case"body":c=1200,n="data:image/jpeg;base64,"+wt;break;default:n=null}let r=new Image;r.onload=async()=>{let _=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(c,c):document.createElement("canvas");_.width=r.naturalWidth,_.height=r.naturalHeight;let A=_.getContext("2d");A==null||A.drawImage(r,0,0);let o=await this.detect(_,this.config);t(o)},n?r.src=n:t(null)}));mt.set(this,async()=>{let t=A=>Buffer.from(A,"base64"),n=this.config.warmup==="face"?t(yt):t(wt),c=E1.node.decodeJpeg(n),r=c.expandDims(0);this.tf.dispose(c);let _=await this.detect(r,this.config);return this.tf.dispose(r),_});this.tf=E1,this.draw=M1,this.version=Z0,this.config=pe(j,t),this.state="idle",le(this,ze,0),le(this,Oe,!1),le(this,ke,!1),le(this,me,!0),this.perf={},this.models={face:null,posenet:null,blazepose:null,efficientpose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null,faceres:null},this.image=n=>v1(n,this.config),this.classes={facemesh:Bt,age:gt,gender:Pt,emotion:Rt,faceres:kt,body:this.config.body.modelPath.includes("posenet")?c1:d1,hand:a1,nanodet:b1},this.faceTriangulation=U1,this.faceUVMap=D1,this.sysinfo=N1()}profileData(){return this.config.profile?Ve:{}}similarity(t,n){return this.config.face.description.enabled?Zt(t,n):this.config.face.embedding.enabled?Z1(t,n):0}enhance(t){return Lt(t)}match(t,n,c=0){return L1(t,n,c)}async load(t={}){this.state="load";let n=z();t&&(this.config=pe(this.config,t)),D(this,me)&&(this.config.debug&&g(`version: ${this.version}`),this.config.debug&&g(`tfjs version: ${this.tf.version_core}`),this.config.debug&&g("platform:",this.sysinfo.platform),this.config.debug&&g("agent:",this.sysinfo.agent),await D(this,Ie).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&g("configuration:",this.config),this.config.debug&&g("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.efficientpose,this.models.nanodet,this.models.faceres]=await Promise.all([this.models.face||(this.config.face.enabled?Kt(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?Tt(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?Et(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?Wt(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?Nt(this.config):null),this.models.handpose||(this.config.hand.enabled?l1(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?_1(this.config):null),this.models.blazepose||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?f1(this.config):null),this.models.efficientpose||(this.config.body.enabled&&this.config.body.modelPath.includes("efficientpose")?p1(this.config):null),this.models.nanodet||(this.config.object.enabled?T1(this.config):null),this.models.faceres||(this.config.face.enabled&&this.config.face.description.enabled?It(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await Kt(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await Tt(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await Et(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await Wt(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await Nt(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await l1(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await _1(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await f1(this.config)),this.config.body.enabled&&!this.models.efficientpose&&this.config.body.modelPath.includes("efficientpose")&&(this.models.efficientpose=await p1(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await T1(this.config)),this.config.face.enabled&&this.config.face.description.enabled&&!this.models.faceres&&(this.models.faceres=await It(this.config))),D(this,me)&&(this.config.debug&&g("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),le(this,me,!1));let c=Math.trunc(z()-n);c>(this.perf.load||0)&&(this.perf.load=c)}async detect(t,n={}){return new Promise(async c=>{var x,d,f,T;this.state="config";let r;this.config=pe(this.config,n),this.state="check";let _=D(this,lt).call(this,t);_&&(g(_,t),c({error:_}));let A=z();await D(this,Ie).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),this.analyze("Start Scope:"),r=z();let o=v1(t,this.config);if(!o||!o.tensor){g("could not convert input to tensor"),c({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(z()-r),this.analyze("Get Image:");let s,i,a,h,y;this.config.async?(a=this.config.face.enabled?Vt(this,o.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",r=z(),a=this.config.face.enabled?await Vt(this,o.tensor):[],y=Math.trunc(z()-r),y>0&&(this.perf.face=y)),this.analyze("Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?s=this.config.body.enabled?(x=this.models.posenet)==null?void 0:x.estimatePoses(o.tensor,this.config):[]:this.config.body.modelPath.includes("blazepose")?s=this.config.body.enabled?m1(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(s=this.config.body.enabled?u1(o.tensor,this.config):[]),this.perf.body&&delete this.perf.body):(this.state="run:body",r=z(),this.config.body.modelPath.includes("posenet")?s=this.config.body.enabled?await((d=this.models.posenet)==null?void 0:d.estimatePoses(o.tensor,this.config)):[]:this.config.body.modelPath.includes("blazepose")?s=this.config.body.enabled?await m1(o.tensor,this.config):[]:this.config.body.modelPath.includes("efficientpose")&&(s=this.config.body.enabled?await u1(o.tensor,this.config):[]),y=Math.trunc(z()-r),y>0&&(this.perf.body=y)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(i=this.config.hand.enabled?(f=this.models.handpose)==null?void 0:f.estimateHands(o.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",r=z(),i=this.config.hand.enabled?await((T=this.models.handpose)==null?void 0:T.estimateHands(o.tensor,this.config)):[],y=Math.trunc(z()-r),y>0&&(this.perf.hand=y)),this.analyze("End Hand:"),this.analyze("Start 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diff --git a/dist/tfjs.esm.js b/dist/tfjs.esm.js
index 99a9548a..e87be879 100644
--- a/dist/tfjs.esm.js
+++ b/dist/tfjs.esm.js
@@ -5,31 +5,31 @@
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   */
 
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this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(f=this.profiler.profileKernel(u,c,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(f),t=f.outputs)}),n&&this.addTapeNode(u,c,t,m,o,p),this.state.profiling&&this.state.activeProfile.kernels.push({name:u,bytesAdded:this.state.numBytes-s,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-a,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(c).map(d=>c[d]!=null?c[d].shape:null),outputShapes:t.map(d=>d.shape),kernelTimeMs:f.timeMs,extraInfo:f.extraInfo}),Array.isArray(l)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(o=>this.keep(this.clone(o)))}getTensorsForGradient(e,t,o){let n=Vb(e);if(n!=null){let s=n.inputsToSave||[],a=n.outputsToSave||[],i;n.saveAllInputs?(A(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(u=>t[u])):i=s.map(u=>t[u]);let 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o=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(o=e.size*Wh(e.dtype)),this.state.numBytes+=o,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:o})),e instanceof nl||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 o=e.size*Wh(e.dtype);this.state.numBytes-=o}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,o=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(n=>n.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-o;for(let n of this.state.activeProfile.kernels)n.kernelTimeMs=await n.kernelTimeMs,n.extraInfo=await n.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(e,t,o,n,s,a){let i={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:o,saved:s},l=Vb(e);l!=null&&(n=l.gradFunc),n!=null&&(i.gradient=u=>(u=u.map((c,p)=>{if(c==null){let m=o[p],f=uc(m.size,m.dtype);return this.makeTensor(f,m.shape,m.dtype)}return c}),n(u.length>1?u:u[0],s,a))),this.state.activeTape.push(i)}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=Im(e),o=new Set(t.map(s=>s.id));for(let s=0;s<this.state.activeScope.track.length;s++){let a=this.state.activeScope.track[s];!a.kept&&!o.has(a.id)&&a.dispose()}let n=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(s=>{!s.kept&&s.scopeId===n.id&&this.track(s)})}gradients(e,t,o,n=!1){if(A(t.length>0,()=>"gradients() received an empty list of xs."),o!=null&&o.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${o.dtype}'`);let s=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));A(s instanceof Ve,()=>"The result y returned by f() must be a tensor.");let a=oS(this.state.activeTape,t,s);if(!n&&a.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. 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The output of every math call will be downloaded to CPU and checked for NaNs. 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Got an object with ${e.length} keys.`);let t=e[0],o=r[t];t.endsWith("_")&&(t=t.substring(0,t.length-1)),t=t+bG;let n=(...s)=>{E.startScope(t);try{let a=o(...s);return hm(a)&&console.error("Cannot return a Promise inside of tidy."),E.endScope(a),a}catch(a){throw E.endScope(null),a}};return Object.defineProperty(n,"name",{value:t,configurable:!0}),n}function wG(r,e){let t=v(r,"real","complex"),o=v(e,"imag","complex");vt(t.shape,o.shape,`real and imag shapes, ${t.shape} and ${o.shape}, must match in call to tf.complex().`);let n={real:t,imag:o};return E.runKernel(hc,n)}var Co=S({complex_:wG});function qr(r,e,t,o){if(o==null&&(o=ac(r)),o==="complex64")throw new Error("Cannot construct a complex64 tensor directly. 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s=n,a=!1;n.rank===3&&(a=!0,s=L(n,[1,n.shape[0],n.shape[1],n.shape[2]]));let[]=e,i={images:s},l={alignCorners:t,halfPixelCenters:o,size:e},u=E.runKernel(Ka,i,l);return a?L(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var gg=S({resizeNearestNeighbor_:T4});function A4(r,e,t="nearest",o="constant",n=0,s){let a=v(r,"image","transform","float32"),i=v(e,"transforms","transform","float32");A(a.rank===4,()=>`Error in transform: image must be rank 4,but got rank ${a.rank}.`),A(i.rank===2&&(i.shape[0]===a.shape[0]||i.shape[0]===1)&&i.shape[1]===8,()=>"Error in transform: Input transform should be batch x 8 or 1 x 8"),A(s==null||s.length===2,()=>`Error in transform: outputShape must be [height, width] or null, but got ${s}.`);let l={image:a,transforms:i},u={interpolation:t,fillMode:o,fillValue:n,outputShape:s};return E.runKernel($c,l,u)}var bS=S({transform_:A4});function E4(r,e,t){A(e%1==0,()=>`bandPart(): numLower must be an integer, got ${e}.`),A(t%1==0,()=>`bandPart(): numUpper must be an integer, 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Labels / logits was rank ${e.rank} and dim was ${t}`);return io((n,s,a)=>{let l=Qh(s,[t],!0),u=ce(ne(s,"float32"),l);a([n,u]);let c=Ue(P(u,n));return{value:ge(c,[t]),gradFunc:(f,d)=>{let[h,g]=d,x=Xo(f.shape,[t]);return[P(L(f,x),ce(ne(h,"float32"),Zt(g))),P(L(f,x),ce(Zt(g),ne(h,"float32")))]}}})(r,e)}function W4(r,e,t,o=0,n=qt.SUM_BY_NONZERO_WEIGHTS){let s=v(r,"onehotLabels","softmaxCrossEntropy"),a=v(e,"logits","softmaxCrossEntropy"),i=null;if(t!=null&&(i=v(t,"weights","softmaxCrossEntropy")),vt(s.shape,a.shape,"Error in softmaxCrossEntropy: "),o>0){let u=le(o),c=le(1),p=le(s.shape[1]);s=ee(P(s,ce(c,u)),me(u,p))}let l=G4(s,a);return Tr(l,i,n)}var DS=S({softmaxCrossEntropy_:W4});var wDe={fft:da,ifft:Ys,rfft:ha,irfft:iu},_De={hammingWindow:iS,hannWindow:cg,frame:pg,stft:aS},Js={flipLeftRight:uS,resizeNearestNeighbor:gg,resizeBilinear:hg,rotateWithOffset:cS,cropAndResize:lS,nonMaxSuppression:pS,nonMaxSuppressionAsync:dS,nonMaxSuppressionWithScore:hS,nonMaxSuppressionWithScoreAsync:gS,nonMaxSuppressionPadded:xS,nonMaxSuppressionPaddedAsync:yS,transform:bS},$S={bandPart:wS,gramSchmidt:_S,qr:vS},kDe={absoluteDifference:CS,computeWeightedLoss:Tr,cosineDistance:IS,hingeLoss:NS,huberLoss:SS,logLoss:TS,meanSquaredError:AS,sigmoidCrossEntropy:ES,softmaxCrossEntropy:DS};var Pr=class extends Xh{minimize(e,t=!1,o){let{value:n,grads:s}=this.computeGradients(e,o);if(o!=null){let a=o.map(i=>({name:i.name,tensor:s[i.name]}));this.applyGradients(a)}else this.applyGradients(s);return Ae(s),t?n:(n.dispose(),null)}get iterations(){return this.iterations_==null&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return 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Pr{constructor(e,t,o,n=null){super();this.learningRate=e,this.beta1=t,this.beta2=o,this.epsilon=n,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],V(()=>{this.accBeta1=le(t).variable(),this.accBeta2=le(o).variable()}),n==null&&(this.epsilon=E.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(o=>o.name):Object.keys(e);V(()=>{let o=ce(1,this.accBeta1),n=ce(1,this.accBeta2);t.forEach((s,a)=>{let i=E.registeredVariables[s],l=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${s}/m`,variable:V(()=>Ce(i).variable(l))}),this.accumulatedSecondMoment[a]==null&&(this.accumulatedSecondMoment[a]={originalName:`${s}/v`,variable:V(()=>Ce(i).variable(l))});let u=Array.isArray(e)?e[a].tensor:e[s];if(u==null)return;let c=this.accumulatedFirstMoment[a].variable,p=this.accumulatedSecondMoment[a].variable,m=ee(P(c,this.beta1),P(u,1-this.beta1)),f=ee(P(p,this.beta2),P(Oe(u),1-this.beta2)),d=me(m,o),h=me(f,n);c.assign(m),p.assign(f);let 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t=e.length/2,o=!1;this.accumulatedFirstMoment=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(o)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(o)}))}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)}};Zm.className="Adam";no(Zm);var Jm=class extends Pr{constructor(e,t,o,n=null,s=0){super();this.learningRate=e,this.beta1=t,this.beta2=o,this.epsilon=n,this.decay=s,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],V(()=>{this.iteration=le(0).variable(),this.accBeta1=le(t).variable()}),n==null&&(this.epsilon=E.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(o=>o.name):Object.keys(e);V(()=>{let o=ce(1,this.accBeta1),n=me(-this.learningRate,ee(P(this.iteration,this.decay),1));t.forEach((s,a)=>{let i=E.registeredVariables[s],l=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${s}/m`,variable:Ce(i).variable(l)}),this.accumulatedWeightedInfNorm[a]==null&&(this.accumulatedWeightedInfNorm[a]={originalName:`${s}/v`,variable:Ce(i).variable(l)});let u=Array.isArray(e)?e[a].tensor:e[s];if(u==null)return;let c=this.accumulatedFirstMoment[a].variable,p=this.accumulatedWeightedInfNorm[a].variable,m=ee(P(c,this.beta1),P(u,1-this.beta1)),f=P(p,this.beta2),d=It(u),h=Kr(f,d);c.assign(m),p.assign(h);let g=ee(P(me(n,o),me(m,ee(h,this.epsilon))),i);i.assign(g)}),this.iteration.assign(ee(this.iteration,1)),this.accBeta1.assign(P(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&Ae(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&Ae(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)}};Jm.className="Adamax";no(Jm);var fu=class extends Pr{constructor(e){super();this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let s=Array.isArray(e)?e[n].tensor:e[o];if(s==null)return;let a=E.registeredVariables[o];V(()=>{let i=ee(P(this.c,s),a);a.assign(i)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Et(le(-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 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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(o=>({originalName:o.name,variable:o.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)}};Qm.className="Momentum";no(Qm);var ef=class extends Pr{constructor(e,t=.9,o=0,n=null,s=!1){super();if(this.learningRate=e,this.decay=t,this.momentum=o,this.epsilon=n,this.accumulatedMeanSquares=[],this.accumulatedMoments=[],this.accumulatedMeanGrads=[],this.centered=s,n==null&&(this.epsilon=E.backend.epsilon()),e==null)throw new Error("learningRate for RMSPropOptimizer must be defined.")}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let s=E.registeredVariables[o],a=!1;this.accumulatedMeanSquares[n]==null&&(this.accumulatedMeanSquares[n]={originalName:`${o}/rms`,variable:V(()=>Ce(s).variable(a))}),this.accumulatedMoments[n]==null&&(this.accumulatedMoments[n]={originalName:`${o}/momentum`,variable:V(()=>Ce(s).variable(a))}),this.accumulatedMeanGrads[n]==null&&this.centered&&(this.accumulatedMeanGrads[n]={originalName:`${o}/mg`,variable:V(()=>Ce(s).variable(a))});let i=Array.isArray(e)?e[n].tensor:e[o];if(i==null)return;let l=this.accumulatedMeanSquares[n].variable,u=this.accumulatedMoments[n].variable;V(()=>{let c=ee(P(l,this.decay),P(Oe(i),1-this.decay));if(this.centered){let p=this.accumulatedMeanGrads[n].variable,m=ee(P(p,this.decay),P(i,1-this.decay)),f=me(P(i,this.learningRate),gt(ce(c,ee(Oe(m),this.epsilon)))),d=ee(P(u,this.momentum),f);l.assign(c),p.assign(m),u.assign(d);let h=ce(s,d);s.assign(h)}else{let 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t=this.centered?e.length/3:e.length/2,o=!1;this.accumulatedMeanSquares=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(o)})),this.accumulatedMoments=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(o)})),this.centered&&(this.accumulatedMeanGrads=e.slice(t*2,t*3).map(n=>({originalName:n.name,variable:n.tensor.variable(o)})))}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)}};ef.className="RMSProp";no(ef);var ga=class{static sgd(e){return new fu(e)}static momentum(e,t,o=!1){return new Qm(e,t,o)}static rmsprop(e,t=.9,o=0,n=null,s=!1){return new ef(e,t,o,n,s)}static adam(e=.001,t=.9,o=.999,n=null){return new Zm(e,t,o,n)}static adadelta(e=.001,t=.95,o=null){return new Xm(e,t,o)}static adamax(e=.002,t=.9,o=.999,n=null,s=0){return new Jm(e,t,o,n,s)}static 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Labels / logits was rank ${e.rank} and dim was ${t}`);return po((n,s,a)=>{let l=ug(s,[t],!0),u=ce(ne(s,"float32"),l);a([n,u]);let c=He(P(u,n));return{value:ge(c,[t]),gradFunc:(f,d)=>{let[h,g]=d,x=en(f.shape,[t]);return[P(L(f,x),ce(ne(h,"float32"),Zt(g))),P(L(f,x),ce(Zt(g),ne(h,"float32")))]}}})(r,e)}function TH(r,e,t,o=0,n=qt.SUM_BY_NONZERO_WEIGHTS){let s=v(r,"onehotLabels","softmaxCrossEntropy"),a=v(e,"logits","softmaxCrossEntropy"),i=null;if(t!=null&&(i=v(t,"weights","softmaxCrossEntropy")),vt(s.shape,a.shape,"Error in softmaxCrossEntropy: "),o>0){let u=le(o),c=le(1),p=le(s.shape[1]);s=ee(P(s,ce(c,u)),me(u,p))}let l=SH(s,a);return Ar(l,i,n)}var p1=S({softmaxCrossEntropy_:TH});var X$e={fft:ba,ifft:ti,rfft:wa,irfft:pu},Y$e={hammingWindow:BT,hannWindow:wg,frame:_g,stft:VT},oi={flipLeftRight:WT,resizeNearestNeighbor:Ng,resizeBilinear:Ig,rotateWithOffset:jT,cropAndResize:GT,nonMaxSuppression:UT,nonMaxSuppressionAsync:KT,nonMaxSuppressionWithScore:XT,nonMaxSuppressionWithScoreAsync:YT,nonMaxSuppressionPadded:ZT,nonMaxSuppressionPaddedAsync:JT,transform:QT},m1={bandPart:e1,gramSchmidt:t1,qr:o1},Z$e={absoluteDifference:n1,computeWeightedLoss:Ar,cosineDistance:s1,hingeLoss:i1,huberLoss:a1,logLoss:l1,meanSquaredError:u1,sigmoidCrossEntropy:c1,softmaxCrossEntropy:p1};var zr=class extends sg{minimize(e,t=!1,o){let{value:n,grads:s}=this.computeGradients(e,o);if(o!=null){let a=o.map(i=>({name:i.name,tensor:s[i.name]}));this.applyGradients(a)}else this.applyGradients(s);return Ae(s),t?n:(n.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&&Ae(this.iterations_)}async saveIterations(){return this.iterations_==null&&(this.iterations_=0),{name:"iter",tensor:le(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 ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(zr,Symbol.hasInstance,{value:r=>r.minimize!=null&&r.computeGradients!=null&&r.applyGradients!=null});var sf=class extends zr{constructor(e,t,o=null){super();this.learningRate=e,this.rho=t,this.epsilon=o,this.accumulatedGrads=[],this.accumulatedUpdates=[],o==null&&(this.epsilon=E.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let 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setWeights(e){e=await this.extractIterations(e);let t=e.length/2,o=!1;this.accumulatedGrads=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(o)})),this.accumulatedUpdates=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(o)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}};sf.className="Adadelta";uo(sf);var af=class extends zr{constructor(e,t=.1){super();this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let s=E.registeredVariables[o];if(this.accumulatedGrads[n]==null){let l=!1;this.accumulatedGrads[n]={originalName:`${o}/accumulator`,variable:V(()=>ma(s.shape,this.initialAccumulatorValue).variable(l))}}let a=Array.isArray(e)?e[n].tensor:e[o];if(a==null)return;let i=this.accumulatedGrads[n].variable;V(()=>{let l=ee(i,Oe(a));i.assign(l);let u=ee(P(me(a,gt(ee(l,E.backend.epsilon()))),-this.learningRate),s);s.assign(u)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&Ae(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(o=>({originalName:o.name,variable:o.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}};af.className="Adagrad";uo(af);var lf=class extends zr{constructor(e,t,o,n=null){super();this.learningRate=e,this.beta1=t,this.beta2=o,this.epsilon=n,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],V(()=>{this.accBeta1=le(t).variable(),this.accBeta2=le(o).variable()}),n==null&&(this.epsilon=E.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(o=>o.name):Object.keys(e);V(()=>{let o=ce(1,this.accBeta1),n=ce(1,this.accBeta2);t.forEach((s,a)=>{let i=E.registeredVariables[s],l=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${s}/m`,variable:V(()=>Ce(i).variable(l))}),this.accumulatedSecondMoment[a]==null&&(this.accumulatedSecondMoment[a]={originalName:`${s}/v`,variable:V(()=>Ce(i).variable(l))});let u=Array.isArray(e)?e[a].tensor:e[s];if(u==null)return;let c=this.accumulatedFirstMoment[a].variable,p=this.accumulatedSecondMoment[a].variable,m=ee(P(c,this.beta1),P(u,1-this.beta1)),f=ee(P(p,this.beta2),P(Oe(u),1-this.beta2)),d=me(m,o),h=me(f,n);c.assign(m),p.assign(f);let g=ee(P(me(d,ee(gt(h),this.epsilon)),-this.learningRate),i);i.assign(g)}),this.accBeta1.assign(P(this.accBeta1,this.beta1)),this.accBeta2.assign(P(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&Ae(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&Ae(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),V(()=>{this.accBeta1.assign(Lr(this.beta1,this.iterations_+1)),this.accBeta2.assign(Lr(this.beta2,this.iterations_+1))});let t=e.length/2,o=!1;this.accumulatedFirstMoment=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(o)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(o)}))}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)}};lf.className="Adam";uo(lf);var uf=class extends zr{constructor(e,t,o,n=null,s=0){super();this.learningRate=e,this.beta1=t,this.beta2=o,this.epsilon=n,this.decay=s,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],V(()=>{this.iteration=le(0).variable(),this.accBeta1=le(t).variable()}),n==null&&(this.epsilon=E.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(o=>o.name):Object.keys(e);V(()=>{let o=ce(1,this.accBeta1),n=me(-this.learningRate,ee(P(this.iteration,this.decay),1));t.forEach((s,a)=>{let i=E.registeredVariables[s],l=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${s}/m`,variable:Ce(i).variable(l)}),this.accumulatedWeightedInfNorm[a]==null&&(this.accumulatedWeightedInfNorm[a]={originalName:`${s}/v`,variable:Ce(i).variable(l)});let u=Array.isArray(e)?e[a].tensor:e[s];if(u==null)return;let c=this.accumulatedFirstMoment[a].variable,p=this.accumulatedWeightedInfNorm[a].variable,m=ee(P(c,this.beta1),P(u,1-this.beta1)),f=P(p,this.beta2),d=It(u),h=Zr(f,d);c.assign(m),p.assign(h);let g=ee(P(me(n,o),me(m,ee(h,this.epsilon))),i);i.assign(g)}),this.iteration.assign(ee(this.iteration,1)),this.accBeta1.assign(P(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&Ae(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&Ae(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)}};uf.className="Adamax";uo(uf);var yu=class extends zr{constructor(e){super();this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let s=Array.isArray(e)?e[n].tensor:e[o];if(s==null)return;let a=E.registeredVariables[o];V(()=>{let i=ee(P(this.c,s),a);a.assign(i)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Et(le(-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 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c=N.computePool3DInfo(s.shape,a,i,1,l,u),p=c.strideDepth,m=c.strideHeight,f=c.strideWidth,d=c.filterDepth,h=c.filterHeight,g=c.filterWidth,x=c.dilationDepth,b=c.dilationHeight,w=c.dilationWidth,_=c.effectiveFilterDepth,k=c.effectiveFilterHeight,D=c.effectiveFilterWidth,T=_-1-c.padInfo.front,R=D-1-c.padInfo.left,O=k-1-c.padInfo.top,M=ve(s.shape,"float32"),G=1/(d*h*g),j=t.bufferSync(n);for(let U=0;U<c.batchSize;++U)for(let H=0;H<c.inChannels;++H)for(let q=0;q<c.inDepth;++q)for(let X=0;X<c.inHeight;++X)for(let oe=0;oe<c.inWidth;++oe){let Y=q-T,re=X-O,J=oe-R,ie=0;for(let ue=0;ue<_;ue+=x){let ae=(Y+ue)/p;if(!(ae<0||ae>=c.outDepth||Math.floor(ae)!==ae))for(let fe=0;fe<k;fe+=b){let de=(re+fe)/m;if(!(de<0||de>=c.outHeight||Math.floor(de)!==de))for(let xe=0;xe<D;xe+=w){let we=(J+xe)/f;if(we<0||we>=c.outWidth||Math.floor(we)!==we)continue;ie+=j.get(U,ae,de,we,H)}}}M.set(ie*G,U,q,X,oe,H)}return t.makeTensorInfo(M.shape,M.dtype,M.values)}var NT={kernelName:lc,backendName:"cpu",kernelFunc:oH};function nH(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s;te([n,s],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=o,c=N.computePool2DInfo(a.shape,i,l,1,u),p=c.strideHeight,m=c.strideWidth,f=c.filterHeight,d=c.filterWidth,h=c.dilationHeight,g=c.dilationWidth,x=c.effectiveFilterHeight,b=c.effectiveFilterWidth,w=b-1-c.padInfo.left,_=x-1-c.padInfo.top,k=ve(a.shape,"float32"),D=1/(f*d),T=t.data.get(n.dataId).values,R=ve(n.shape,"float32",T);for(let O=0;O<c.batchSize;++O)for(let M=0;M<c.inChannels;++M)for(let G=0;G<c.inHeight;++G)for(let j=0;j<c.inWidth;++j){let U=G-_,H=j-w,q=0;for(let X=0;X<x;X+=h){let oe=(U+X)/p;if(!(oe<0||oe>=c.outHeight||Math.floor(oe)!==oe))for(let Y=0;Y<b;Y+=g){let re=(H+Y)/m;if(re<0||re>=c.outWidth||Math.floor(re)!==re)continue;q+=R.get(O,oe,re,M)}}k.set(q*D,O,G,j,M)}return t.makeTensorInfo(k.shape,k.dtype,k.values)}var ST={kernelName:ac,backendName:"cpu",kernelFunc:nH};function 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t.makeTensorInfo(n.shape,n.dtype,h)}var TT={kernelName:Dn,backendName:"cpu",kernelFunc:sH};function iH(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockShape:s,crops:a}=o;te([n],"batchToSpaceND");let i=s.reduce((x,b)=>x*b),l=N.getReshaped(n.shape,s,i),u=N.getPermuted(l.length,s.length),c=N.getReshapedPermuted(n.shape,s,i),p=N.getSliceBeginCoords(a,s.length),m=N.getSliceSize(c,a,s.length),f=Qe({inputs:{x:n},backend:t,attrs:{shape:l}}),d=or({inputs:{x:f},backend:t,attrs:{perm:u}}),h=Qe({inputs:{x:d},backend:t,attrs:{shape:c}}),g=on({inputs:{x:h},backend:t,attrs:{begin:p,size:m}});return t.disposeIntermediateTensorInfo(f),t.disposeIntermediateTensorInfo(d),t.disposeIntermediateTensorInfo(h),g}var AT={kernelName:za,backendName:"cpu",kernelFunc:iH};function aH(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a}=o,i=t.data.get(n.dataId).values,l=t.data.get(s.dataId).values,u=rp(i,l,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,u)}var ET={kernelName:uc,backendName:"cpu",kernelFunc:aH};var lH=$e(Go,(r,e)=>{let t=e;return r>t.clipValueMax?t.clipValueMax:r<t.clipValueMin?t.clipValueMin:r}),DT={kernelName:Go,backendName:"cpu",kernelFunc:lH};var uH=r=>{let{x:e}=r.inputs,t=r.backend,o=new Float32Array(y.sizeFromShape(e.shape)),n=t.data.get(e.dataId),s=n.complexTensorInfos.real,a=n.complexTensorInfos.imag,i=t.data.get(s.dataId).values,l=t.data.get(a.dataId).values;for(let u=0;u<i.length;u++){let c=i[u],p=l[u];o[u]=Math.hypot(c,p)}return t.makeOutput(o,e.shape,"float32")},$T={kernelName:Ba,backendName:"cpu",kernelFunc:uH};function Qs(r){let{inputs:e,backend:t}=r,{input:o}=e,n=t.data.get(o.dataId).complexTensorInfos.imag,s=t.data.get(n.dataId).values;return t.makeTensorInfo(n.shape,n.dtype,s)}var RT={kernelName:_c,backendName:"cpu",kernelFunc:Qs};function il(r){let{inputs:e,backend:t,attrs:o}=r,{axis:n}=o,s=y.parseAxisParam(n,e[0].shape)[0],a=N.computeOutShape(e.map(h=>h.shape),s);if(y.sizeFromShape(a)===0)return 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u.forEach(h=>t.disposeIntermediateTensorInfo(h)),d}var FT={kernelName:Ds,backendName:"cpu",kernelFunc:il};function b_(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=o;te([n,s],"conv2d");let p=N.convertConv2DDataFormat(l),m=N.computeConv2DInfo(n.shape,s.shape,a,u,i,c,!1,p),f=m.filterHeight,d=m.filterWidth,h=m.dilationHeight,g=m.dilationWidth,x=m.padInfo.left,b=m.padInfo.top,w=m.dataFormat==="channelsLast",_=new lt(m.outShape,n.dtype),k=y.computeStrides(n.shape),D=y.computeStrides(s.shape),T=k[0],R=w?k[1]:k[2],O=w?k[2]:1,M=w?1:k[1],G=_.strides[0],j=w?_.strides[1]:_.strides[2],U=w?_.strides[2]:1,H=w?1:_.strides[1],q=t.data.get(n.dataId).values,X=t.data.get(s.dataId).values,oe=_.values;for(let Y=0;Y<m.batchSize;++Y){let re=Y*T,J=Y*G;for(let ie=0;ie<m.outHeight;++ie){let ue=J+ie*j,ae=ie*m.strideHeight-b;for(let fe=0;fe<f;++fe){let de=ae+fe*h;if(de<0||de>=m.inHeight)continue;let xe=fe*D[0],we=re+de*R;for(let 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MT={kernelName:vn,backendName:"cpu",kernelFunc:pH};function mH(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:l}=o;te([n,s],"conv3d");let u=N.computeConv3DInfo(n.shape,s.shape,a,l,i),{filterDepth:c,filterHeight:p,filterWidth:m,dilationDepth:f,dilationHeight:d,dilationWidth:h,padInfo:g}=u,x=g.front,b=g.left,w=g.top,_=new lt(u.outShape,n.dtype),k=t.data.get(n.dataId).values,D=t.data.get(s.dataId).values,T=_.values,R=y.computeStrides(n.shape),O=y.computeStrides(s.shape);for(let M=0;M<u.batchSize;++M){let G=M*R[0],j=M*_.strides[0];for(let U=0;U<u.outDepth;++U){let H=j+U*_.strides[1],q=U*u.strideDepth-x;for(let X=0;X<c;++X){let oe=q+X*f;if(oe<0||oe>=u.inDepth)continue;let Y=X*O[0],re=G+oe*R[1];for(let J=0;J<u.outHeight;++J){let ie=H+J*_.strides[2],ue=J*u.strideHeight-w;for(let ae=0;ae<p;++ae){let fe=ue+ae*d;if(fe<0||fe>=u.inHeight)continue;let de=Y+ae*O[1],xe=re+fe*R[2];for(let we=0;we<u.outWidth;++we){let 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WT={kernelName:_i,backendName:"cpu",kernelFunc:xH};function yH(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,exclusive:a,reverse:i}=o;te(n,"cumsum");let l=N.getAxesPermutation([s],n.shape.length),u=n;l!=null&&(u=or({inputs:{x:n},backend:t,attrs:{perm:l}}));let c=N.getInnerMostAxes(1,n.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=ir(u.dtype,"int32"),m=y.makeZerosTypedArray(y.sizeFromShape(u.shape),p),f=t.data.get(u.dataId).values,d=u.shape[u.shape.length-1],h=i?(x,b)=>x+d-b-1:(x,b)=>x+b;for(let x=0;x<f.length;x+=d)for(let b=0;b<d;b++){let w=h(x,b);if(b===0)m[w]=a?0:f[w];else{let _=h(x,b-1);m[w]=a?f[_]+m[_]:f[w]+m[_]}}let g=t.makeTensorInfo(u.shape,p,m);if(l!=null){let x=N.getUndoAxesPermutation(l),b=or({inputs:{x:g},backend:t,attrs:{perm:x}});return t.disposeIntermediateTensorInfo(g),t.disposeIntermediateTensorInfo(u),b}return g}var jT={kernelName:In,backendName:"cpu",kernelFunc:yH};function bH(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a,binaryOutput:i}=o;if(n.shape.length===1){let l=t.data.get(n.dataId).values,u=t.data.get(s.dataId).values,c=rp(l,u,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,c)}else if(n.shape.length===2){let l=t.bufferSync(n),u=t.bufferSync(s),c=yg(l,u,a,i);return t.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${n.shape.length}.`)}var UT={kernelName:dc,backendName:"cpu",kernelFunc:bH};function wH(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockSize:s,dataFormat:a}=o;y.assert(a==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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c=N.computePool3DInfo(s.shape,a,i,1,l,u),p=c.strideDepth,m=c.strideHeight,f=c.strideWidth,d=c.filterDepth,h=c.filterHeight,g=c.filterWidth,x=c.dilationDepth,b=c.dilationHeight,w=c.dilationWidth,_=c.effectiveFilterDepth,k=c.effectiveFilterHeight,D=c.effectiveFilterWidth,T=_-1-c.padInfo.front,R=D-1-c.padInfo.left,O=k-1-c.padInfo.top,M=ve(s.shape,"float32"),G=1/(d*h*g),j=t.bufferSync(n);for(let U=0;U<c.batchSize;++U)for(let H=0;H<c.inChannels;++H)for(let q=0;q<c.inDepth;++q)for(let X=0;X<c.inHeight;++X)for(let oe=0;oe<c.inWidth;++oe){let Y=q-T,re=X-O,J=oe-R,ie=0;for(let ue=0;ue<_;ue+=x){let ae=(Y+ue)/p;if(!(ae<0||ae>=c.outDepth||Math.floor(ae)!==ae))for(let fe=0;fe<k;fe+=b){let de=(re+fe)/m;if(!(de<0||de>=c.outHeight||Math.floor(de)!==de))for(let xe=0;xe<D;xe+=w){let we=(J+xe)/f;if(we<0||we>=c.outWidth||Math.floor(we)!==we)continue;ie+=j.get(U,ae,de,we,H)}}}M.set(ie*G,U,q,X,oe,H)}return t.makeTensorInfo(M.shape,M.dtype,M.values)}var iA={kernelName:fc,backendName:"cpu",kernelFunc:Gq};function Wq(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s;te([n,s],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=o,c=N.computePool2DInfo(a.shape,i,l,1,u),p=c.strideHeight,m=c.strideWidth,f=c.filterHeight,d=c.filterWidth,h=c.dilationHeight,g=c.dilationWidth,x=c.effectiveFilterHeight,b=c.effectiveFilterWidth,w=b-1-c.padInfo.left,_=x-1-c.padInfo.top,k=ve(a.shape,"float32"),D=1/(f*d),T=t.data.get(n.dataId).values,R=ve(n.shape,"float32",T);for(let O=0;O<c.batchSize;++O)for(let M=0;M<c.inChannels;++M)for(let G=0;G<c.inHeight;++G)for(let j=0;j<c.inWidth;++j){let U=G-_,H=j-w,q=0;for(let X=0;X<x;X+=h){let oe=(U+X)/p;if(!(oe<0||oe>=c.outHeight||Math.floor(oe)!==oe))for(let Y=0;Y<b;Y+=g){let re=(H+Y)/m;if(re<0||re>=c.outWidth||Math.floor(re)!==re)continue;q+=R.get(O,oe,re,M)}}k.set(q*D,O,G,j,M)}return t.makeTensorInfo(k.shape,k.dtype,k.values)}var aA={kernelName:mc,backendName:"cpu",kernelFunc:Wq};function 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t.makeTensorInfo(n.shape,n.dtype,h)}var lA={kernelName:Pn,backendName:"cpu",kernelFunc:jq};function Uq(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockShape:s,crops:a}=o;te([n],"batchToSpaceND");let i=s.reduce((x,b)=>x*b),l=N.getReshaped(n.shape,s,i),u=N.getPermuted(l.length,s.length),c=N.getReshapedPermuted(n.shape,s,i),p=N.getSliceBeginCoords(a,s.length),m=N.getSliceSize(c,a,s.length),f=Qe({inputs:{x:n},backend:t,attrs:{shape:l}}),d=or({inputs:{x:f},backend:t,attrs:{perm:u}}),h=Qe({inputs:{x:d},backend:t,attrs:{shape:c}}),g=un({inputs:{x:h},backend:t,attrs:{begin:p,size:m}});return t.disposeIntermediateTensorInfo(f),t.disposeIntermediateTensorInfo(d),t.disposeIntermediateTensorInfo(h),g}var uA={kernelName:ja,backendName:"cpu",kernelFunc:Uq};function Hq(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a}=o,i=t.data.get(n.dataId).values,l=t.data.get(s.dataId).values,u=ap(i,l,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,u)}var cA={kernelName:dc,backendName:"cpu",kernelFunc:Hq};var qq=$e(qo,(r,e)=>{let t=e;return r>t.clipValueMax?t.clipValueMax:r<t.clipValueMin?t.clipValueMin:r}),pA={kernelName:qo,backendName:"cpu",kernelFunc:qq};var Kq=r=>{let{x:e}=r.inputs,t=r.backend,o=new Float32Array(y.sizeFromShape(e.shape)),n=t.data.get(e.dataId),s=n.complexTensorInfos.real,a=n.complexTensorInfos.imag,i=t.data.get(s.dataId).values,l=t.data.get(a.dataId).values;for(let u=0;u<i.length;u++){let c=i[u],p=l[u];o[u]=Math.hypot(c,p)}return t.makeOutput(o,e.shape,"float32")},mA={kernelName:Ua,backendName:"cpu",kernelFunc:Kq};function ni(r){let{inputs:e,backend:t}=r,{input:o}=e,n=t.data.get(o.dataId).complexTensorInfos.imag,s=t.data.get(n.dataId).values;return t.makeTensorInfo(n.shape,n.dtype,s)}var fA={kernelName:Nc,backendName:"cpu",kernelFunc:ni};function pl(r){let{inputs:e,backend:t,attrs:o}=r,{axis:n}=o,s=y.parseAxisParam(n,e[0].shape)[0],a=N.computeOutShape(e.map(h=>h.shape),s);if(y.sizeFromShape(a)===0)return 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u.forEach(h=>t.disposeIntermediateTensorInfo(h)),d}var dA={kernelName:Ps,backendName:"cpu",kernelFunc:pl};function A_(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=o;te([n,s],"conv2d");let p=N.convertConv2DDataFormat(l),m=N.computeConv2DInfo(n.shape,s.shape,a,u,i,c,!1,p),f=m.filterHeight,d=m.filterWidth,h=m.dilationHeight,g=m.dilationWidth,x=m.padInfo.left,b=m.padInfo.top,w=m.dataFormat==="channelsLast",_=new lt(m.outShape,n.dtype),k=y.computeStrides(n.shape),D=y.computeStrides(s.shape),T=k[0],R=w?k[1]:k[2],O=w?k[2]:1,M=w?1:k[1],G=_.strides[0],j=w?_.strides[1]:_.strides[2],U=w?_.strides[2]:1,H=w?1:_.strides[1],q=t.data.get(n.dataId).values,X=t.data.get(s.dataId).values,oe=_.values;for(let Y=0;Y<m.batchSize;++Y){let re=Y*T,J=Y*G;for(let ie=0;ie<m.outHeight;++ie){let ue=J+ie*j,ae=ie*m.strideHeight-b;for(let fe=0;fe<f;++fe){let de=ae+fe*h;if(de<0||de>=m.inHeight)continue;let xe=fe*D[0],we=re+de*R;for(let 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xA={kernelName:Tn,backendName:"cpu",kernelFunc:Yq};function Zq(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:l}=o;te([n,s],"conv3d");let u=N.computeConv3DInfo(n.shape,s.shape,a,l,i),{filterDepth:c,filterHeight:p,filterWidth:m,dilationDepth:f,dilationHeight:d,dilationWidth:h,padInfo:g}=u,x=g.front,b=g.left,w=g.top,_=new lt(u.outShape,n.dtype),k=t.data.get(n.dataId).values,D=t.data.get(s.dataId).values,T=_.values,R=y.computeStrides(n.shape),O=y.computeStrides(s.shape);for(let M=0;M<u.batchSize;++M){let G=M*R[0],j=M*_.strides[0];for(let U=0;U<u.outDepth;++U){let H=j+U*_.strides[1],q=U*u.strideDepth-x;for(let X=0;X<c;++X){let oe=q+X*f;if(oe<0||oe>=u.inDepth)continue;let Y=X*O[0],re=G+oe*R[1];for(let J=0;J<u.outHeight;++J){let ie=H+J*_.strides[2],ue=J*u.strideHeight-w;for(let ae=0;ae<p;++ae){let fe=ue+ae*d;if(fe<0||fe>=u.inHeight)continue;let de=Y+ae*O[1],xe=re+fe*R[2];for(let we=0;we<u.outWidth;++we){let 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vA={kernelName:Ni,backendName:"cpu",kernelFunc:rK};function oK(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,exclusive:a,reverse:i}=o;te(n,"cumsum");let l=N.getAxesPermutation([s],n.shape.length),u=n;l!=null&&(u=or({inputs:{x:n},backend:t,attrs:{perm:l}}));let c=N.getInnerMostAxes(1,n.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=ir(u.dtype,"int32"),m=y.makeZerosTypedArray(y.sizeFromShape(u.shape),p),f=t.data.get(u.dataId).values,d=u.shape[u.shape.length-1],h=i?(x,b)=>x+d-b-1:(x,b)=>x+b;for(let x=0;x<f.length;x+=d)for(let b=0;b<d;b++){let w=h(x,b);if(b===0)m[w]=a?0:f[w];else{let _=h(x,b-1);m[w]=a?f[_]+m[_]:f[w]+m[_]}}let g=t.makeTensorInfo(u.shape,p,m);if(l!=null){let x=N.getUndoAxesPermutation(l),b=or({inputs:{x:g},backend:t,attrs:{perm:x}});return t.disposeIntermediateTensorInfo(g),t.disposeIntermediateTensorInfo(u),b}return g}var CA={kernelName:En,backendName:"cpu",kernelFunc:oK};function nK(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a,binaryOutput:i}=o;if(n.shape.length===1){let l=t.data.get(n.dataId).values,u=t.data.get(s.dataId).values,c=ap(l,u,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,c)}else if(n.shape.length===2){let l=t.bufferSync(n),u=t.bufferSync(s),c=Tg(l,u,a,i);return t.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${n.shape.length}.`)}var IA={kernelName:bc,backendName:"cpu",kernelFunc:nK};function sK(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockSize:s,dataFormat:a}=o;y.assert(a==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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TA={kernelName:wc,backendName:"cpu",kernelFunc:iK};function aK(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{strides:a,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=o;te([n,s],"depthwiseConv2DNativeBackpropInput");let p=y.computeStrides(n.shape),m=y.computeStrides(s.shape),f=N.computeConv2DInfo(c,s.shape,a,i,l,u,!0),d=new lt(f.inShape,"float32"),h=d.values,[g,x,b]=d.strides,w=t.data.get(n.dataId).values,[_,k,D]=p,T=t.data.get(s.dataId).values,[R,O,M]=m,{batchSize:G,filterHeight:j,filterWidth:U,inChannels:H,inHeight:q,inWidth:X,outChannels:oe,outHeight:Y,outWidth:re,strideHeight:J,strideWidth:ie}=f,ue=j-1-f.padInfo.top,ae=U-1-f.padInfo.left,fe=oe/H;for(let de=0;de<G;++de)for(let xe=0;xe<H;++xe)for(let we=0;we<q;++we){let De=we-ue,Ne=Math.max(0,Math.ceil(De/J)),ze=Math.min(Y,(j+De)/J);for(let qe=0;qe<X;++qe){let it=qe-ae,St=Math.max(0,Math.ceil(it/ie)),Tt=Math.min(re,(U+it)/ie),Ue=0;for(let ut=Ne;ut<ze;++ut){let mt=ut*J-De;for(let Pt=St;Pt<Tt;++Pt){let 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r=Pe.getNumber("WEBGL_VERSION");return r===0?0:W_(r)});Pe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Pe.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!Ll.isMobile());Pe.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>U_(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",()=>H_(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_FENCE_API_ENABLED",()=>q_(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,r=>{if(r<0&&r!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${r}.`)});Pe.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>Ll.isMobile()&&Pe.getBool("IS_CHROME")?1:-1,r=>{if(r<0&&r!==-1)throw new 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+`))}function B_(r){return va(r,()=>r.createProgram(),"Unable to create WebGLProgram.")}function V_(r,e){if(Ie(r,()=>r.linkProgram(e)),r.getProgramParameter(e,r.LINK_STATUS)===!1)throw console.log(r.getProgramInfoLog(e)),new Error("Failed to link vertex and fragment shaders.")}function kf(r,e){if(Ie(r,()=>r.validateProgram(e)),r.getProgramParameter(e,r.VALIDATE_STATUS)===!1)throw console.log(r.getProgramInfoLog(e)),new Error("Shader program validation failed.")}function G_(r,e){let t=va(r,()=>r.createBuffer(),"Unable to create WebGLBuffer");return Ie(r,()=>r.bindBuffer(r.ARRAY_BUFFER,t)),Ie(r,()=>r.bufferData(r.ARRAY_BUFFER,e,r.STATIC_DRAW)),t}function W_(r,e){let t=va(r,()=>r.createBuffer(),"Unable to create WebGLBuffer");return Ie(r,()=>r.bindBuffer(r.ELEMENT_ARRAY_BUFFER,t)),Ie(r,()=>r.bufferData(r.ELEMENT_ARRAY_BUFFER,e,r.STATIC_DRAW)),t}function a5(){return W().getNumber("WEBGL_VERSION")===2?1:4}function j_(r){return va(r,()=>r.createTexture(),"Unable to create 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r.getUniformLocation(e,t)}function X_(r,e,t,o){Ie(r,()=>d2(r,e,o)),Ie(r,()=>r.uniform1i(t,o))}function u5(r){Ie(r,()=>r.bindFramebuffer(r.FRAMEBUFFER,null)),Ie(r,()=>r.viewport(0,0,r.canvas.width,r.canvas.height)),Ie(r,()=>r.scissor(0,0,r.canvas.width,r.canvas.height))}function vf(r,e,t){Ie(r,()=>r.bindFramebuffer(r.FRAMEBUFFER,t)),Ie(r,()=>r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,e,0))}function Gg(r,e){Ie(r,()=>r.bindFramebuffer(r.FRAMEBUFFER,e)),Ie(r,()=>r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,null,0))}function fp(r){let e=r.checkFramebufferStatus(r.FRAMEBUFFER);if(e!==r.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+h2(r,e))}function h2(r,e){switch(e){case r.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_ATTACHMENT";case r.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT";case r.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case r.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${e}`}}function va(r,e,t){let o=Ie(r,()=>e());if(o==null)throw new Error(t);return o}function f2(r,e){let t=r.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,o=e+r.TEXTURE0;if(o<r.TEXTURE0||o>t){let n=`[gl.TEXTURE0, gl.TEXTURE${t}]`;throw new Error(`textureUnit must be in ${n}.`)}}function Ca(r,e=2){return y.sizeFromShape(r.slice(0,r.length-e))}function Ia(r){if(r.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[r.length>1?r[r.length-2]:1,r[r.length-1]]}function Cf(r){let e=[1,1,1];return r.length===0||r.length===1&&r[0]===1||(e=[Ca(r),...Ia(r)]),e}function Y_(r,e=!1){let t=W().getNumber("WEBGL_MAX_TEXTURE_SIZE");e&&(t=t*2,r=r.map((n,s)=>s>=r.length-2?y.nearestLargerEven(r[s]):r[s]),r.length===1&&(r=[2,r[0]])),r.length!==2&&(r=y.squeezeShape(r).newShape);let o=y.sizeFromShape(r);if(r.length<=1&&o<=t)return[1,o];if(r.length===2&&r[0]<=t&&r[1]<=t)return r;if(r.length===3&&r[0]*r[1]<=t&&r[2]<=t)return[r[0]*r[1],r[2]];if(r.length===3&&r[0]<=t&&r[1]*r[2]<=t)return[r[0],r[1]*r[2]];if(r.length===4&&r[0]*r[1]*r[2]<=t&&r[3]<=t)return[r[0]*r[1]*r[2],r[3]];if(r.length===4&&r[0]<=t&&r[1]*r[2]*r[3]<=t)return[r[0],r[1]*r[2]*r[3]];if(e){let n=Ca(r),s=2,a=2;return r.length&&([s,a]=Ia(r)),o=n*(s/2)*(a/2),y.sizeToSquarishShape(o).map(i=>i*2)}return y.sizeToSquarishShape(o)}function Wg(r){return r%2==0}function dl(r,e){if(r=r.slice(-2),e=e.slice(-2),y.arraysEqual(r,e)||!r.length||!e.length||r[0]===0||r[1]===0||e[0]===0||e[1]===0)return!0;if(r.length!==e.length){let t=r.slice(-1)[0],o=e.slice(-1)[0];if(t===o||Wg(t)&&Wg(o)&&(r[0]===1||e[0]===1))return!0}return r[1]===e[1]&&Wg(r[0])&&Wg(e[0])}var jg,Ug;function Z_(r){if(jg==null){let e=Bo(r);jg=e.getParameter(e.MAX_TEXTURE_SIZE)}return jg}function c5(){jg=null}function p5(){Ug=null}function J_(r){if(Ug==null){let e=Bo(r);Ug=e.getParameter(e.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,Ug)}function Q_(r){if(r===0)return 0;let e,t=Bo(r);return So(t,"EXT_disjoint_timer_query_webgl2")&&r===2?e=2:So(t,"EXT_disjoint_timer_query")?e=1:e=0,e}function So(r,e){return r.getExtension(e)!=null}function Hg(r){try{if(Bo(r)!=null)return!0}catch(e){return console.log("Error when getting WebGL context: ",e),!1}return!1}function tk(r){if(r===0)return!1;let e=Bo(r);if(r===1){if(!So(e,"OES_texture_float"))return!1}else if(!So(e,"EXT_color_buffer_float"))return!1;return ek(e)}function rk(r){if(r===0)return!1;let e=Bo(r);if(r===1){if(!So(e,"OES_texture_float")||!So(e,"WEBGL_color_buffer_float"))return!1}else{if(So(e,"EXT_color_buffer_float"))return ek(e);let o="EXT_color_buffer_half_float";if(So(e,o)){let n=e.getExtension(o);return m5(e,n)}return!1}return ek(e)}function ek(r){let e=_f(r),t=r.createTexture();r.bindTexture(r.TEXTURE_2D,t);let o=1,n=1;r.texImage2D(r.TEXTURE_2D,0,e.internalFormatFloat,o,n,0,e.textureFormatFloat,e.textureTypeFloat,null);let s=r.createFramebuffer();r.bindFramebuffer(r.FRAMEBUFFER,s),r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,t,0);let a=r.checkFramebufferStatus(r.FRAMEBUFFER)===r.FRAMEBUFFER_COMPLETE;return r.bindTexture(r.TEXTURE_2D,null),r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteTexture(t),r.deleteFramebuffer(s),a}function m5(r,e){let t=_f(r,e),o=r.createTexture();r.bindTexture(r.TEXTURE_2D,o);let n=1,s=1;r.texImage2D(r.TEXTURE_2D,0,t.internalFormatHalfFloat,n,s,0,t.textureFormatFloat,t.textureTypeHalfFloat,null);let a=r.createFramebuffer();r.bindFramebuffer(r.FRAMEBUFFER,a),r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,o,0);let i=r.checkFramebufferStatus(r.FRAMEBUFFER)===r.FRAMEBUFFER_COMPLETE;return r.bindTexture(r.TEXTURE_2D,null),r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteTexture(o),r.deleteFramebuffer(a),i}function ok(r){return r!==2?!1:Bo(r).fenceSync!=null}function _s(r,e){Array.isArray(r)||(r=[r]),r.forEach(t=>{t!=null&&y.assert(t.dtype!=="complex64",()=>`${e} does not support complex64 tensors in the WebGL backend.`)})}var Pe=W();Pe.registerFlag("HAS_WEBGL",()=>Pe.getNumber("WEBGL_VERSION")>0);Pe.registerFlag("WEBGL_VERSION",()=>Hg(2)?2:Hg(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",()=>!1);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",()=>Z_(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>J_(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let r=Pe.getNumber("WEBGL_VERSION");return r===0?0:Q_(r)});Pe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Pe.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!Wl.isMobile());Pe.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>tk(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",()=>rk(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_FENCE_API_ENABLED",()=>ok(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,r=>{if(r<0&&r!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${r}.`)});Pe.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>Wl.isMobile()&&Pe.getBool("IS_CHROME")?1:-1,r=>{if(r<0&&r!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${r}.`)});function Rt(){let r,e,t,o,n,s,a,i,l,u;return W().getNumber("WEBGL_VERSION")===2?(r="#version 300 es",e="in",t="out",o="in",n="texture",s="outputColor",a="out vec4 outputColor;",i=`
       bool isnan_custom(float val) {
         return (val > 0.0 || val < 0.0) ? false : val != 0.0;
       }
@@ -74,11 +74,11 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       ivec4 round(vec4 value) {
         return ivec4(floor(value + vec4(0.5)));
       }
-    `),{version:r,attribute:e,varyingVs:t,varyingFs:o,texture2D:n,output:s,defineOutput:a,defineSpecialNaN:i,defineSpecialInf:l,defineRound:u}}function xs(r,e,t="index"){let o=y.computeStrides(e);return o.map((n,s)=>{let a=`int ${r[s]} = ${t} / ${n}`,i=s===o.length-1?`int ${r[s+1]} = ${t} - ${r[s]} * ${n}`:`index -= ${r[s]} * ${n}`;return`${a}; ${i};`}).join("")}function up(r){let e=y.computeStrides(r).map(t=>t.toString());return`
+    `),{version:r,attribute:e,varyingVs:t,varyingFs:o,texture2D:n,output:s,defineOutput:a,defineSpecialNaN:i,defineSpecialInf:l,defineRound:u}}function ks(r,e,t="index"){let o=y.computeStrides(e);return o.map((n,s)=>{let a=`int ${r[s]} = ${t} / ${n}`,i=s===o.length-1?`int ${r[s+1]} = ${t} - ${r[s]} * ${n}`:`index -= ${r[s]} * ${n}`;return`${a}; ${i};`}).join("")}function dp(r){let e=y.computeStrides(r).map(t=>t.toString());return`
   int getFlatIndex(ivec3 coords) {
     return coords.x * ${e[0]} + coords.y * ${e[1]} + coords.z;
   }
-`}var Mg=`
+`}var qg=`
   const float FLOAT_MAX = 1.70141184e38;
   const float FLOAT_MIN = 1.17549435e-38;
 
@@ -117,9 +117,9 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
     return c / 255.0;
   }
-`;var K_=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=al.DENSE;let t=ll(e),o=Rt();this.outputShape=e,this.userCode=`
+`;var nk=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=ml.DENSE;let t=fl(e),o=Rt();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
-        ${xs(["r","c","d"],e)}
+        ${ks(["r","c","d"],e)}
         return ivec3(r, c, d);
       }
 
@@ -138,9 +138,9 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${o.output} = result;
       }
-    `}};var X_=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=al.DENSE;let t=ll(e),o=Rt();this.outputShape=e,this.userCode=`
+    `}};var sk=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=ml.DENSE;let t=fl(e),o=Rt();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
-        ${xs(["r","c","d"],e)}
+        ${ks(["r","c","d"],e)}
         return ivec3(r, c, d);
       }
 
@@ -159,23 +159,23 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${o.output} = result;
       }
-    `}};var Y_=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Dr.DOWNLOAD;let t=Rt();this.outputShape=e,this.userCode=`
-      ${Mg}
+    `}};var ik=class{constructor(e){this.variableNames=["A"],this.outTexUsage=$r.DOWNLOAD;let t=Rt();this.outputShape=e,this.userCode=`
+      ${qg}
 
       void main() {
         float x = getAAtOutCoords();
         ${t.output} = encode_float(x);
       }
-    `}};var Z_=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Dr.DOWNLOAD;let t=Rt();this.outputShape=e,this.userCode=`
-      ${Mg}
+    `}};var ak=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=$r.DOWNLOAD;let t=Rt();this.outputShape=e,this.userCode=`
+      ${qg}
 
       void main() {
         ivec3 coords = getOutputCoords();
         float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
         ${t.output} = encode_float(x);
       }
-    `}};var J_=class{constructor(e,t,o=!1){this.variableNames=["A"];let n=Rt(),[s,a]=t;this.outputShape=e;let i="result";o&&(i="floor(result * 255. + 0.5)"),this.userCode=`
-      ${up(e)}
+    `}};var lk=class{constructor(e,t,o=!1){this.variableNames=["A"];let n=Rt(),[s,a]=t;this.outputShape=e;let i="result";o&&(i="floor(result * 255. + 0.5)"),this.userCode=`
+      ${dp(e)}
 
       void main() {
         ivec3 coords = getOutputCoords();
@@ -204,7 +204,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${n.output} = vec4(${i}, 0., 0., 0.);
       }
-    `}};var Q_=class{constructor(e,t,o=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let n=Rt(),[s,a]=t;this.outputShape=e;let i="",l="result";o&&(l="floor(result * 255. + 0.5)");for(let u=0;u<=1;u++)for(let c=0;c<=1;c++){let p=u*2+c;i+=`
+    `}};var uk=class{constructor(e,t,o=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let n=Rt(),[s,a]=t;this.outputShape=e;let i="",l="result";o&&(l="floor(result * 255. + 0.5)");for(let u=0;u<=1;u++)for(let c=0;c<=1;c++){let p=u*2+c;i+=`
           localCoords = coords;
           if(localCoords[2] + ${c} < ${e[2]}) {
             localCoords[2] += ${c};
@@ -233,7 +233,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
             }
           }
         `}this.userCode=`
-      ${up(e)}
+      ${dp(e)}
 
       void main() {
         ivec3 coords = getOutputCoords();
@@ -248,7 +248,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${n.output} = ${l};
       }
-    `}};var TK={};Ke(TK,{bindVertexProgramAttributeStreams:()=>lk,createBufferFromOutputTexture:()=>pk,createFloat16MatrixTexture:()=>nk,createFloat16PackedMatrixTexture:()=>ak,createFloat32MatrixTexture:()=>ok,createIndexBuffer:()=>rk,createPackedMatrixTexture:()=>ik,createUnsignedBytesMatrixTexture:()=>sk,createVertexBuffer:()=>tk,createVertexShader:()=>ek,downloadByteEncodedFloatMatrixFromOutputTexture:()=>fk,downloadFloat32MatrixFromBuffer:()=>mk,downloadMatrixFromPackedOutputTexture:()=>hk,downloadPackedMatrixFromBuffer:()=>dk,getInternalFormatForFloat16MatrixTexture:()=>zg,getInternalFormatForFloat16PackedMatrixTexture:()=>Gg,getInternalFormatForFloat32MatrixTexture:()=>Lg,getInternalFormatForPackedMatrixTexture:()=>Vg,getInternalFormatForUnsignedBytesMatrixTexture:()=>Bg,uploadDenseMatrixToTexture:()=>uk,uploadPixelDataToTexture:()=>ck});function ek(r){let e=Rt(),t=`${e.version}
+    `}};var f5={};Ge(f5,{bindVertexProgramAttributeStreams:()=>yk,createBufferFromOutputTexture:()=>_k,createFloat16MatrixTexture:()=>dk,createFloat16PackedMatrixTexture:()=>xk,createFloat32MatrixTexture:()=>fk,createIndexBuffer:()=>mk,createPackedMatrixTexture:()=>gk,createUnsignedBytesMatrixTexture:()=>hk,createVertexBuffer:()=>pk,createVertexShader:()=>ck,downloadByteEncodedFloatMatrixFromOutputTexture:()=>vk,downloadFloat32MatrixFromBuffer:()=>kk,downloadMatrixFromPackedOutputTexture:()=>Ik,downloadPackedMatrixFromBuffer:()=>Ck,getInternalFormatForFloat16MatrixTexture:()=>Xg,getInternalFormatForFloat16PackedMatrixTexture:()=>Jg,getInternalFormatForFloat32MatrixTexture:()=>Kg,getInternalFormatForPackedMatrixTexture:()=>Zg,getInternalFormatForUnsignedBytesMatrixTexture:()=>Yg,uploadDenseMatrixToTexture:()=>bk,uploadPixelDataToTexture:()=>wk});function ck(r){let e=Rt(),t=`${e.version}
     precision highp float;
     ${e.attribute} vec3 clipSpacePos;
     ${e.attribute} vec2 uv;
@@ -257,22 +257,22 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
     void main() {
       gl_Position = vec4(clipSpacePos, 1);
       resultUV = uv;
-    }`;return T_(r,t)}function tk(r){let e=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return $_(r,e)}function rk(r){let e=new Uint16Array([0,1,2,2,1,3]);return R_(r,e)}function hf(r,e,t,o,n,s){O_(e,t);let a=F_(r),i=r.TEXTURE_2D;return Ie(r,()=>r.bindTexture(i,a)),Ie(r,()=>r.texParameteri(i,r.TEXTURE_WRAP_S,r.CLAMP_TO_EDGE)),Ie(r,()=>r.texParameteri(i,r.TEXTURE_WRAP_T,r.CLAMP_TO_EDGE)),Ie(r,()=>r.texParameteri(i,r.TEXTURE_MIN_FILTER,r.NEAREST)),Ie(r,()=>r.texParameteri(i,r.TEXTURE_MAG_FILTER,r.NEAREST)),Ie(r,()=>r.texImage2D(i,0,o,e,t,0,n,s,null)),Ie(r,()=>r.bindTexture(r.TEXTURE_2D,null)),a}function Lg(r){return r.internalFormatFloat}function ok(r,e,t,o){let[n,s]=wu(e,t);return hf(r,n,s,Lg(o),o.textureFormatFloat,r.FLOAT)}function zg(r){return r.internalFormatHalfFloat}function nk(r,e,t,o){let[n,s]=wu(e,t);return hf(r,n,s,zg(o),o.textureFormatFloat,o.textureTypeHalfFloat)}function Bg(r){return r.downloadTextureFormat}function sk(r,e,t,o){let[n,s]=wu(e,t);return hf(r,n,s,Bg(o),r.RGBA,r.UNSIGNED_BYTE)}function Vg(r){return r.internalFormatPackedFloat}function ik(r,e,t,o){let[n,s]=ei(e,t);return hf(r,n,s,Vg(o),r.RGBA,r.FLOAT)}function Gg(r){return r.internalFormatPackedHalfFloat}function ak(r,e,t,o){let[n,s]=ei(e,t);return hf(r,n,s,Gg(o),r.RGBA,o.textureTypeHalfFloat)}function lk(r,e,t){let o=0,n=3*4,s=3*4+2*4;return Ie(r,()=>r.bindBuffer(r.ARRAY_BUFFER,t)),Dg(r,e,"clipSpacePos",t,3,s,o)&&Dg(r,e,"uv",t,2,s,n)}function uk(r,e,t,o,n,s){Ie(r,()=>r.bindTexture(r.TEXTURE_2D,e));let a,i,l;n instanceof Uint8Array?(a=new Uint8Array(t*o*4),i=r.UNSIGNED_BYTE,l=r.RGBA):(a=new Float32Array(t*o*4),i=r.FLOAT,l=s.internalFormatPackedFloat),a.set(n),Ie(r,()=>r.texImage2D(r.TEXTURE_2D,0,l,t,o,0,r.RGBA,i,a)),Ie(r,()=>r.bindTexture(r.TEXTURE_2D,null))}function ck(r,e,t){Ie(r,()=>r.bindTexture(r.TEXTURE_2D,e)),t.data instanceof Uint8Array?Ie(r,()=>r.texImage2D(r.TEXTURE_2D,0,r.RGBA,t.width,t.height,0,r.RGBA,r.UNSIGNED_BYTE,t.data)):Ie(r,()=>r.texImage2D(r.TEXTURE_2D,0,r.RGBA,r.RGBA,r.UNSIGNED_BYTE,t)),Ie(r,()=>r.bindTexture(r.TEXTURE_2D,null))}function pk(r,e,t,o){let n=r.createBuffer();Ie(r,()=>r.bindBuffer(r.PIXEL_PACK_BUFFER,n));let i=4*4*e*t;return Ie(r,()=>r.bufferData(r.PIXEL_PACK_BUFFER,i,r.STREAM_READ)),Ie(r,()=>r.readPixels(0,0,t,e,r.RGBA,r.FLOAT,0)),Ie(r,()=>r.bindBuffer(r.PIXEL_PACK_BUFFER,null)),n}function mk(r,e,t){let o=r,n=new Float32Array(t);return o.bindBuffer(o.PIXEL_PACK_BUFFER,e),o.getBufferSubData(o.PIXEL_PACK_BUFFER,0,n),o.bindBuffer(o.PIXEL_PACK_BUFFER,null),n}function fk(r,e,t,o){let[n,s]=wu(e,t),a=4,i=new Uint8Array(EA(e*t,a));return Ie(r,()=>r.readPixels(0,0,n,s,o.downloadTextureFormat,r.UNSIGNED_BYTE,i)),new Float32Array(i.buffer)}function dk(r,e,t,o,n,s,a,i){let l=r,u=new Float32Array(DA(s,a));return l.bindBuffer(l.PIXEL_PACK_BUFFER,e),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,u),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),u}function hk(r,e,t){let o=new Float32Array(e*t*4);return Ie(r,()=>r.readPixels(0,0,t,e,r.RGBA,r.FLOAT,o)),o}var gk=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=W().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,AA(t,e)):this.gl=Oo(t);let o="WEBGL_color_buffer_float",n="EXT_color_buffer_half_float";if(W().getNumber("WEBGL_VERSION")===1){let s="OES_texture_float",a="OES_texture_half_float";if(this.textureFloatExtension=ap(this.gl,s),ko(this.gl,a))this.textureHalfFloatExtension=ap(this.gl,a);else if(W().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(o),ko(this.gl,n))this.colorBufferHalfFloatExtension=ap(this.gl,n);else if(W().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(o="EXT_color_buffer_float",ko(this.gl,o))this.colorBufferFloatExtension=this.gl.getExtension(o);else if(ko(this.gl,n))this.colorBufferHalfFloatExtension=this.gl.getExtension(n);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=tk(this.gl),this.indexBuffer=rk(this.gl),this.framebuffer=P_(this.gl),this.textureConfig=pf(this.gl,this.textureHalfFloatExtension)}get debug(){return W().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. 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n=this.gl;ff(n,e,this.framebuffer),this.debug&&lp(n),this.outputTexture=e,Ie(n,()=>n.viewport(0,0,t,o)),Ie(n,()=>n.scissor(0,0,t,o))}setOutputMatrixWriteRegionDriver(e,t,o,n){this.throwIfDisposed(),Ie(this.gl,()=>this.gl.scissor(e,t,o,n))}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 AK(r){let e=0;for(;e<r.length&&r[e]();++e);return e-1}var{getBroadcastDims:PA}=N;function MA(r,e,t,o){let n=[];r.forEach(d=>{let h=y.sizeFromShape(d.shapeInfo.logicalShape);d.shapeInfo.isUniform?n.push(`uniform float ${d.name}${h>1?`[${h}]`:""};`):(n.push(`uniform sampler2D ${d.name};`),n.push(`uniform int offset${d.name};`))});let s=n.join(`
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-`),i=e.texShape,l=Rt(),u=RK(l),c,p,m=PK(l);return e.isPacked?(c=DK(e.logicalShape,i),p=OK(l)):(c=$K(e.logicalShape,i),p=FK(l)),o&&(m+=MK),[m,u,p,s,c,a,t].join(`
-`)}function cp(r){let e=r.shapeInfo.logicalShape;switch(e.length){case 0:return LK(r);case 1:return zK(r);case 2:return BK(r);case 3:return VK(r);case 4:return GK(r);case 5:return WK(r);case 6:return jK(r);default:throw new Error(`${e.length}-D input sampling is not yet supported`)}}function LA(r){switch(r.shapeInfo.logicalShape.length){case 0:return UK(r);case 1:return HK(r);case 2:return qK(r);case 3:return KK(r);default:return XK(r)}}function EK(r,e,t=!1){let o="";t?o+=LA(r):o+=cp(r);let n=r.shapeInfo.logicalShape,s=e.logicalShape;return n.length<=s.length&&(t?o+=YK(r,e):o+=ZK(r,e)),o}function DK(r,e){switch(r.length){case 0:return zA();case 1:return JK(r,e);case 2:return t6(r,e);case 3:return QK(r,e);default:return e6(r,e)}}function $K(r,e){switch(r.length){case 0:return zA();case 1:return r6(r,e);case 2:return a6(r,e);case 3:return o6(r,e);case 4:return n6(r,e);case 5:return s6(r,e);case 6:return i6(r,e);default:throw new Error(`${r.length}-D output sampling is not yet supported`)}}function RK(r){return`
+    }`;return L_(r,t)}function pk(r){let e=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return G_(r,e)}function mk(r){let e=new Uint16Array([0,1,2,2,1,3]);return W_(r,e)}function If(r,e,t,o,n,s){U_(e,t);let a=j_(r),i=r.TEXTURE_2D;return Ie(r,()=>r.bindTexture(i,a)),Ie(r,()=>r.texParameteri(i,r.TEXTURE_WRAP_S,r.CLAMP_TO_EDGE)),Ie(r,()=>r.texParameteri(i,r.TEXTURE_WRAP_T,r.CLAMP_TO_EDGE)),Ie(r,()=>r.texParameteri(i,r.TEXTURE_MIN_FILTER,r.NEAREST)),Ie(r,()=>r.texParameteri(i,r.TEXTURE_MAG_FILTER,r.NEAREST)),Ie(r,()=>r.texImage2D(i,0,o,e,t,0,n,s,null)),Ie(r,()=>r.bindTexture(r.TEXTURE_2D,null)),a}function Kg(r){return r.internalFormatFloat}function fk(r,e,t,o){let[n,s]=Iu(e,t);return If(r,n,s,Kg(o),o.textureFormatFloat,r.FLOAT)}function Xg(r){return r.internalFormatHalfFloat}function dk(r,e,t,o){let[n,s]=Iu(e,t);return If(r,n,s,Xg(o),o.textureFormatFloat,o.textureTypeHalfFloat)}function Yg(r){return r.downloadTextureFormat}function hk(r,e,t,o){let[n,s]=Iu(e,t);return If(r,n,s,Yg(o),r.RGBA,r.UNSIGNED_BYTE)}function Zg(r){return r.internalFormatPackedFloat}function gk(r,e,t,o){let[n,s]=si(e,t);return If(r,n,s,Zg(o),r.RGBA,r.FLOAT)}function Jg(r){return r.internalFormatPackedHalfFloat}function xk(r,e,t,o){let[n,s]=si(e,t);return If(r,n,s,Jg(o),r.RGBA,o.textureTypeHalfFloat)}function yk(r,e,t){let o=0,n=3*4,s=3*4+2*4;return Ie(r,()=>r.bindBuffer(r.ARRAY_BUFFER,t)),Vg(r,e,"clipSpacePos",t,3,s,o)&&Vg(r,e,"uv",t,2,s,n)}function bk(r,e,t,o,n,s){Ie(r,()=>r.bindTexture(r.TEXTURE_2D,e));let a,i,l;n instanceof Uint8Array?(a=new Uint8Array(t*o*4),i=r.UNSIGNED_BYTE,l=r.RGBA):(a=new Float32Array(t*o*4),i=r.FLOAT,l=s.internalFormatPackedFloat),a.set(n),Ie(r,()=>r.texImage2D(r.TEXTURE_2D,0,l,t,o,0,r.RGBA,i,a)),Ie(r,()=>r.bindTexture(r.TEXTURE_2D,null))}function wk(r,e,t){Ie(r,()=>r.bindTexture(r.TEXTURE_2D,e)),t.data instanceof Uint8Array?Ie(r,()=>r.texImage2D(r.TEXTURE_2D,0,r.RGBA,t.width,t.height,0,r.RGBA,r.UNSIGNED_BYTE,t.data)):Ie(r,()=>r.texImage2D(r.TEXTURE_2D,0,r.RGBA,r.RGBA,r.UNSIGNED_BYTE,t)),Ie(r,()=>r.bindTexture(r.TEXTURE_2D,null))}function _k(r,e,t,o){let n=r.createBuffer();Ie(r,()=>r.bindBuffer(r.PIXEL_PACK_BUFFER,n));let i=4*4*e*t;return Ie(r,()=>r.bufferData(r.PIXEL_PACK_BUFFER,i,r.STREAM_READ)),Ie(r,()=>r.readPixels(0,0,t,e,r.RGBA,r.FLOAT,0)),Ie(r,()=>r.bindBuffer(r.PIXEL_PACK_BUFFER,null)),n}function kk(r,e,t){let o=r,n=new Float32Array(t);return o.bindBuffer(o.PIXEL_PACK_BUFFER,e),o.getBufferSubData(o.PIXEL_PACK_BUFFER,0,n),o.bindBuffer(o.PIXEL_PACK_BUFFER,null),n}function vk(r,e,t,o){let[n,s]=Iu(e,t),a=4,i=new Uint8Array(c2(e*t,a));return Ie(r,()=>r.readPixels(0,0,n,s,o.downloadTextureFormat,r.UNSIGNED_BYTE,i)),new Float32Array(i.buffer)}function Ck(r,e,t,o,n,s,a,i){let l=r,u=new Float32Array(p2(s,a));return l.bindBuffer(l.PIXEL_PACK_BUFFER,e),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,u),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),u}function Ik(r,e,t){let o=new Float32Array(e*t*4);return Ie(r,()=>r.readPixels(0,0,t,e,r.RGBA,r.FLOAT,o)),o}var Nk=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=W().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,u2(t,e)):this.gl=Bo(t);let o="WEBGL_color_buffer_float",n="EXT_color_buffer_half_float";if(W().getNumber("WEBGL_VERSION")===1){let s="OES_texture_float",a="OES_texture_half_float";if(this.textureFloatExtension=mp(this.gl,s),So(this.gl,a))this.textureHalfFloatExtension=mp(this.gl,a);else if(W().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(o),So(this.gl,n))this.colorBufferHalfFloatExtension=mp(this.gl,n);else if(W().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(o="EXT_color_buffer_float",So(this.gl,o))this.colorBufferFloatExtension=this.gl.getExtension(o);else if(So(this.gl,n))this.colorBufferHalfFloatExtension=this.gl.getExtension(n);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=pk(this.gl),this.indexBuffer=mk(this.gl),this.framebuffer=H_(this.gl),this.textureConfig=_f(this.gl,this.textureHalfFloatExtension)}get debug(){return W().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(),fk(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),dk(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),hk(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),wk(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,o,n){this.throwIfDisposed(),bk(this.gl,e,t,o,n,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),xk(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),gk(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(Gg(this.gl,this.framebuffer),this.outputTexture=null),Ie(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,o){return this.downloadMatrixDriver(e,()=>vk(this.gl,t,o,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,o,n,s,a){return Ck(this.gl,e,t,o,n,s,a,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return kk(this.gl,e,t)}createBufferFromTexture(e,t,o){this.bindTextureToFrameBuffer(e);let n=_k(this.gl,t,o,this.textureConfig);return this.unbindTextureToFrameBuffer(),n}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,o;if(W().getBool("WEBGL_FENCE_API_ENABLED")){let n=e,s=n.fenceSync(n.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),o=()=>{let a=n.clientWaitSync(s,0,0);return a===n.ALREADY_SIGNALED||a===n.CONDITION_SATISFIED},t=s}else W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),o=()=>this.isQueryAvailable(t,W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):o=()=>!0;return{query:t,isFencePassed:o}}downloadMatrixFromPackedTexture(e,t,o){return this.downloadMatrixDriver(e,()=>Ik(this.gl,t,o))}createProgram(e){this.throwIfDisposed();let t=this.gl,o=z_(t,e),n=ck(t),s=B_(t);return Ie(t,()=>t.attachShader(s,n)),Ie(t,()=>t.attachShader(s,o)),V_(t,s),this.debug&&kf(t,s),this.vertexAttrsAreBound||(this.setProgram(s),this.vertexAttrsAreBound=yk(t,this.program,this.vertexBuffer)),s}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&&kf(this.gl,this.program),Ie(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,o=!0){return this.throwIfDisposed(),o?q_(this.gl,e,t):K_(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,o){this.throwIfDisposed(),this.throwIfNoProgram(),X_(this.gl,e,t,o)}setOutputMatrixTexture(e,t,o){this.setOutputMatrixTextureDriver(e,o,t)}setOutputPackedMatrixTexture(e,t,o){this.throwIfDisposed();let[n,s]=si(t,o);this.setOutputMatrixTextureDriver(e,n,s)}setOutputMatrixWriteRegion(e,t,o,n){this.setOutputMatrixWriteRegionDriver(o,e,n,t)}setOutputPackedMatrixWriteRegion(e,t,o,n){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&kf(this.gl,this.program),fp(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=mp(this.gl,W().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(W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let o=this.gl,n=this.getQueryTimerExtensionWebGL2(),s=o.createQuery();return o.beginQuery(n.TIME_ELAPSED_EXT,s),s}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,o=this.getQueryTimerExtensionWebGL2();t.endQuery(o.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await y.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let o=this.gl;return o.getQueryParameter(e,o.QUERY_RESULT)/1e6}else{let o=this.getQueryTimerExtensionWebGL1();return o.getQueryObjectEXT(e,o.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let o=this.gl,n=this.getQueryTimerExtensionWebGL2(),s=o.getQueryParameter(e,o.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),s&&!this.disjoint}else{let o=this.getQueryTimerExtensionWebGL1(),n=o.getQueryObjectEXT(e,o.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(o.GPU_DISJOINT_EXT)),n&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=d5(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:o}=this.itemsToPoll[t];o()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),!(this.itemsToPoll.length>1)&&y.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(e){this.throwIfDisposed(),vf(this.gl,e,this.framebuffer),this.debug&&fp(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(vf(this.gl,this.outputTexture,this.framebuffer),this.debug&&fp(this.gl)):Gg(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let o=t();return this.unbindTextureToFrameBuffer(),o}setOutputMatrixTextureDriver(e,t,o){this.throwIfDisposed();let n=this.gl;vf(n,e,this.framebuffer),this.debug&&fp(n),this.outputTexture=e,Ie(n,()=>n.viewport(0,0,t,o)),Ie(n,()=>n.scissor(0,0,t,o))}setOutputMatrixWriteRegionDriver(e,t,o,n){this.throwIfDisposed(),Ie(this.gl,()=>this.gl.scissor(e,t,o,n))}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 d5(r){let e=0;for(;e<r.length&&r[e]();++e);return e-1}var{getBroadcastDims:g2}=N;function x2(r,e,t,o){let n=[];r.forEach(d=>{let h=y.sizeFromShape(d.shapeInfo.logicalShape);d.shapeInfo.isUniform?n.push(`uniform float ${d.name}${h>1?`[${h}]`:""};`):(n.push(`uniform sampler2D ${d.name};`),n.push(`uniform int offset${d.name};`))});let s=n.join(`
+`),a=r.map(d=>h5(d,e,o)).join(`
+`),i=e.texShape,l=Rt(),u=y5(l),c,p,m=_5(l);return e.isPacked?(c=g5(e.logicalShape,i),p=w5(l)):(c=x5(e.logicalShape,i),p=b5(l)),o&&(m+=k5),[m,u,p,s,c,a,t].join(`
+`)}function hp(r){let e=r.shapeInfo.logicalShape;switch(e.length){case 0:return v5(r);case 1:return C5(r);case 2:return I5(r);case 3:return N5(r);case 4:return S5(r);case 5:return T5(r);case 6:return A5(r);default:throw new Error(`${e.length}-D input sampling is not yet supported`)}}function y2(r){switch(r.shapeInfo.logicalShape.length){case 0:return E5(r);case 1:return D5(r);case 2:return $5(r);case 3:return R5(r);default:return F5(r)}}function h5(r,e,t=!1){let o="";t?o+=y2(r):o+=hp(r);let n=r.shapeInfo.logicalShape,s=e.logicalShape;return n.length<=s.length&&(t?o+=O5(r,e):o+=P5(r,e)),o}function g5(r,e){switch(r.length){case 0:return b2();case 1:return M5(r,e);case 2:return B5(r,e);case 3:return L5(r,e);default:return z5(r,e)}}function x5(r,e){switch(r.length){case 0:return b2();case 1:return V5(r,e);case 2:return H5(r,e);case 3:return G5(r,e);case 4:return W5(r,e);case 5:return j5(r,e);case 6:return U5(r,e);default:throw new Error(`${r.length}-D output sampling is not yet supported`)}}function y5(r){return`
     float sampleTexture(sampler2D textureSampler, vec2 uv) {
       return ${r.texture2D}(textureSampler, uv).r;
     }
-  `}function FK(r){return`
+  `}function b5(r){return`
     void setOutput(float val) {
       ${r.output} = vec4(val, 0, 0, 0);
     }
-  `}function OK(r){return`
+  `}function w5(r){return`
     void setOutput(vec4 val) {
       ${r.output} = val;
     }
-  `}function PK(r){return`${r.version}
+  `}function _5(r){return`${r.version}
     precision highp float;
     precision highp int;
     precision highp sampler2D;
@@ -327,10 +327,10 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       return fract((p3.x + p3.y) * p3.z);
     }
 
-    ${l6}
-    ${u6}
-    ${c6}
-  `}var l6=`
+    ${q5}
+    ${K5}
+    ${X5}
+  `}var q5=`
 vec2 uvFromFlat(int texNumR, int texNumC, int index) {
   int texR = index / texNumC;
   int texC = index - texR * texNumC;
@@ -342,7 +342,7 @@ vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,u6=`
+`,K5=`
 vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texNumC, int row, int col) {
   int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
@@ -350,7 +350,7 @@ vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,c6=`
+`,X5=`
 vec2 packedUVfrom3D(int texNumR, int texNumC,
     int texelsInBatch, int texelsInLogicalRow, int b,
     int row, int col) {
@@ -359,7 +359,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   int texC = index - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,MK=`
+`,k5=`
   float getChannel(vec4 frag, vec2 innerDims) {
     vec2 modCoord = mod(innerDims, 2.);
     return modCoord.x == 0. ?
@@ -370,11 +370,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     float modCoord = mod(float(dim), 2.);
     return modCoord == 0. ? frag.r : frag.g;
   }
-`;function zA(){return`
+`;function b2(){return`
     int getOutputCoords() {
       return 0;
     }
-  `}function JK(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];return t[0]===1?`
+  `}function M5(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];return t[0]===1?`
       int getOutputCoords() {
         return 2 * int(resultUV.x * ${t[1]}.0);
       }
@@ -388,7 +388,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${t[0]}, ${t[1]}));
       return 2 * (resTexRC.x * ${t[1]} + resTexRC.y);
     }
-  `}function r6(r,e){return e[0]===1?`
+  `}function V5(r,e){return e[0]===1?`
       int getOutputCoords() {
         return int(resultUV.x * ${e[1]}.0);
       }
@@ -402,7 +402,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${e[0]}, ${e[1]}));
       return resTexRC.x * ${e[1]} + resTexRC.y;
     }
-  `}function QK(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],o=Math.ceil(r[2]/2),n=o*Math.ceil(r[1]/2);return`
+  `}function L5(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],o=Math.ceil(r[2]/2),n=o*Math.ceil(r[1]/2);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${t[0]}, ${t[1]}));
@@ -416,7 +416,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec3(b, r, c);
     }
-  `}function o6(r,e){let t=xs(["r","c","d"],r);return`
+  `}function G5(r,e){let t=ks(["r","c","d"],r);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${e[0]}, ${e[1]}));
@@ -424,7 +424,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${t}
       return ivec3(r, c, d);
     }
-  `}function e6(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],o=Math.ceil(r[r.length-1]/2),n=o*Math.ceil(r[r.length-2]/2),s=n,a="",i="b, r, c";for(let l=2;l<r.length-1;l++)s*=r[r.length-l-1],a=`
+  `}function z5(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],o=Math.ceil(r[r.length-1]/2),n=o*Math.ceil(r[r.length-2]/2),s=n,a="",i="b, r, c";for(let l=2;l<r.length-1;l++)s*=r[r.length-l-1],a=`
       int b${l} = index / ${s};
       index -= b${l} * ${s};
     `+a,i=`b${l}, `+i;return`
@@ -443,7 +443,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec${r.length}(${i});
     }
-  `}function n6(r,e){let t=xs(["r","c","d","d2"],r);return`
+  `}function W5(r,e){let t=ks(["r","c","d","d2"],r);return`
     ivec4 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${e[0]}, ${e[1]}));
@@ -451,7 +451,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${t}
       return ivec4(r, c, d, d2);
     }
-  `}function s6(r,e){let t=xs(["r","c","d","d2","d3"],r);return`
+  `}function j5(r,e){let t=ks(["r","c","d","d2","d3"],r);return`
     ivec5 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx * vec2(${e[0]},
                              ${e[1]}));
@@ -463,7 +463,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec5 outShape = ivec5(r, c, d, d2, d3);
       return outShape;
     }
-  `}function i6(r,e){let t=xs(["r","c","d","d2","d3","d4"],r);return`
+  `}function U5(r,e){let t=ks(["r","c","d","d2","d3","d4"],r);return`
     ivec6 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${e[0]}, ${e[1]}));
@@ -474,7 +474,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec6 result = ivec6(r, c, d, d2, d3, d4);
       return result;
     }
-  `}function t6(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(y.arraysEqual(r,e))return`
+  `}function B5(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(y.arraysEqual(r,e))return`
       ivec2 getOutputCoords() {
         return 2 * ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
       }
@@ -489,7 +489,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec2(r, c);
     }
-  `}function a6(r,e){return y.arraysEqual(r,e)?`
+  `}function H5(r,e){return y.arraysEqual(r,e)?`
       ivec2 getOutputCoords() {
         return ivec2(resultUV.yx * vec2(${e[0]}, ${e[1]}));
       }
@@ -516,34 +516,34 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       int c = index - r * ${r[1]};
       return ivec2(r, c);
     }
-  `}function _u(r){return`offset${r}`}function UK(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1),o=Rt();return`
+  `}function Nu(r){return`offset${r}`}function E5(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1),o=Rt();return`
     vec4 ${t}() {
       return ${o.texture2D}(${e}, halfCR);
     }
-  `}function LK(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`float ${t}() {return ${e};}`;let[o,n]=r.shapeInfo.texShape;if(o===1&&n===1)return`
+  `}function v5(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`float ${t}() {return ${e};}`;let[o,n]=r.shapeInfo.texShape;if(o===1&&n===1)return`
       float ${t}() {
         return sampleTexture(${e}, halfCR);
       }
-    `;let[s,a]=r.shapeInfo.texShape,i=_u(e);return`
+    `;let[s,a]=r.shapeInfo.texShape,i=Nu(e);return`
     float ${t}() {
       vec2 uv = uvFromFlat(${s}, ${a}, ${i});
       return sampleTexture(${e}, uv);
     }
-  `}function HK(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1),o=r.shapeInfo.texShape,n=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],s=Rt();return`
+  `}function D5(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1),o=r.shapeInfo.texShape,n=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],s=Rt();return`
     vec4 ${t}(int index) {
       vec2 uv = packedUVfrom1D(
         ${n[0]}, ${n[1]}, index);
       return ${s.texture2D}(${e}, uv);
     }
-  `}function zK(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`
+  `}function C5(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`
       float ${t}(int index) {
-        ${pp(r)}
+        ${gp(r)}
       }
     `;let o=r.shapeInfo.texShape,n=o[0],s=o[1];if(s===1&&n===1)return`
       float ${t}(int index) {
         return sampleTexture(${e}, halfCR);
       }
-    `;let a=_u(e);return s===1?`
+    `;let a=Nu(e);return s===1?`
       float ${t}(int index) {
         vec2 uv = vec2(0.5, (float(index + ${a}) + 0.5) / ${n}.0);
         return sampleTexture(${e}, uv);
@@ -558,7 +558,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${n}, ${s}, index + ${a});
       return sampleTexture(${e}, uv);
     }
-  `}function qK(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=r.shapeInfo.texShape,s=n[0],a=n[1],i=Rt();if(n!=null&&y.arraysEqual(e,n))return`
+  `}function $5(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=r.shapeInfo.texShape,s=n[0],a=n[1],i=Rt();if(n!=null&&y.arraysEqual(e,n))return`
       vec4 ${o}(int row, int col) {
         vec2 uv = (vec2(col, row) + halfCR) / vec2(${a}.0, ${s}.0);
 
@@ -569,22 +569,22 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = packedUVfrom2D(${u}, ${l[0]}, ${l[1]}, row, col);
       return ${i.texture2D}(${t}, uv);
     }
-  `}function BK(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=r.shapeInfo.texShape;if(n!=null&&y.arraysEqual(e,n)){let p=n[0],m=n[1];return`
+  `}function I5(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=r.shapeInfo.texShape;if(n!=null&&y.arraysEqual(e,n)){let p=n[0],m=n[1];return`
     float ${o}(int row, int col) {
       vec2 uv = (vec2(col, row) + halfCR) / vec2(${m}.0, ${p}.0);
       return sampleTexture(${t}, uv);
     }
-  `}let{newShape:s,keptDims:a}=y.squeezeShape(e),i=s;if(i.length<e.length){let p=mp(r,i),m=["row","col"];return`
-      ${cp(p)}
+  `}let{newShape:s,keptDims:a}=y.squeezeShape(e),i=s;if(i.length<e.length){let p=xp(r,i),m=["row","col"];return`
+      ${hp(p)}
       float ${o}(int row, int col) {
-        return ${o}(${fp(m,a)});
+        return ${o}(${yp(m,a)});
       }
     `}if(r.shapeInfo.isUniform)return`
       float ${o}(int row, int col) {
         int index = round(dot(vec2(row, col), vec2(${e[1]}, 1)));
-        ${pp(r)}
+        ${gp(r)}
       }
-    `;let l=n[0],u=n[1],c=_u(t);return u===1?`
+    `;let l=n[0],u=n[1],c=Nu(t);return u===1?`
     float ${o}(int row, int col) {
       float index = dot(vec3(row, col, ${c}), vec3(${e[1]}, 1, 1));
       vec2 uv = vec2(0.5, (index + 0.5) / ${l}.0);
@@ -603,10 +603,10 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     vec2 uv = uvFromFlat(${l}, ${u}, index);
     return sampleTexture(${t}, uv);
   }
-`}function KK(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=r.shapeInfo.texShape,s=[Math.ceil(n[0]/2),Math.ceil(n[1]/2)];if(e[0]===1){let p=e.slice(1),m=[1,2],f=mp(r,p),d=["b","row","col"];return`
-        ${LA(f)}
+`}function R5(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=r.shapeInfo.texShape,s=[Math.ceil(n[0]/2),Math.ceil(n[1]/2)];if(e[0]===1){let p=e.slice(1),m=[1,2],f=xp(r,p),d=["b","row","col"];return`
+        ${y2(f)}
         vec4 ${o}(int b, int row, int col) {
-          return ${o}(${fp(d,m)});
+          return ${o}(${yp(d,m)});
         }
       `}let a=s[0],i=s[1],l=Math.ceil(e[2]/2),u=l*Math.ceil(e[1]/2),c=Rt();return`
     vec4 ${o}(int b, int row, int col) {
@@ -614,16 +614,16 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         ${a}, ${i}, ${u}, ${l}, b, row, col);
       return ${c.texture2D}(${t}, uv);
     }
-  `}function VK(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=e[1]*e[2],s=e[2],{newShape:a,keptDims:i}=y.squeezeShape(e),l=a;if(l.length<e.length){let d=mp(r,l),h=["row","col","depth"];return`
-        ${cp(d)}
+  `}function N5(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=e[1]*e[2],s=e[2],{newShape:a,keptDims:i}=y.squeezeShape(e),l=a;if(l.length<e.length){let d=xp(r,l),h=["row","col","depth"];return`
+        ${hp(d)}
         float ${o}(int row, int col, int depth) {
-          return ${o}(${fp(h,i)});
+          return ${o}(${yp(h,i)});
         }
       `}if(r.shapeInfo.isUniform)return`
       float ${o}(int row, int col, int depth) {
         int index = round(dot(vec3(row, col, depth),
                           vec3(${n}, ${s}, 1)));
-        ${pp(r)}
+        ${gp(r)}
       }
     `;let u=r.shapeInfo.texShape,c=u[0],p=u[1],m=r.shapeInfo.flatOffset;if(p===n&&m==null)return`
         float ${o}(int row, int col, int depth) {
@@ -640,14 +640,14 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${p}.0, ${c}.0);
       return sampleTexture(${t}, uv);
     }
-  `;let f=_u(t);return`
+  `;let f=Nu(t);return`
       float ${o}(int row, int col, int depth) {
         // Explicitly use integer operations as dot() only works on floats.
         int index = row * ${n} + col * ${s} + depth + ${f};
         vec2 uv = uvFromFlat(${c}, ${p}, index);
         return sampleTexture(${t}, uv);
       }
-  `}function XK(r){let e=r.shapeInfo.logicalShape,t=e.length,o=r.name,n="get"+o.charAt(0).toUpperCase()+o.slice(1),s=r.shapeInfo.texShape,a=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],i=a[0],l=a[1],u=Math.ceil(e[t-1]/2),c=u*Math.ceil(e[t-2]/2),p="int b, int row, int col",m=`b * ${c} + (row / 2) * ${u} + (col / 2)`;for(let d=2;d<t-1;d++)p=`int b${d}, `+p,c*=e[t-d-1],m=`b${d} * ${c} + `+m;let f=Rt();return`
+  `}function F5(r){let e=r.shapeInfo.logicalShape,t=e.length,o=r.name,n="get"+o.charAt(0).toUpperCase()+o.slice(1),s=r.shapeInfo.texShape,a=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],i=a[0],l=a[1],u=Math.ceil(e[t-1]/2),c=u*Math.ceil(e[t-2]/2),p="int b, int row, int col",m=`b * ${c} + (row / 2) * ${u} + (col / 2)`;for(let d=2;d<t-1;d++)p=`int b${d}, `+p,c*=e[t-d-1],m=`b${d} * ${c} + `+m;let f=Rt();return`
     vec4 ${n}(${p}) {
       int index = ${m};
       int texR = index / ${l};
@@ -655,16 +655,16 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${l}, ${i});
       return ${f.texture2D}(${o}, uv);
     }
-  `}function GK(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=e[3],s=e[2]*n,a=e[1]*s,{newShape:i,keptDims:l}=y.squeezeShape(e);if(i.length<e.length){let d=mp(r,i),h=["row","col","depth","depth2"];return`
-      ${cp(d)}
+  `}function S5(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=e[3],s=e[2]*n,a=e[1]*s,{newShape:i,keptDims:l}=y.squeezeShape(e);if(i.length<e.length){let d=xp(r,i),h=["row","col","depth","depth2"];return`
+      ${hp(d)}
       float ${o}(int row, int col, int depth, int depth2) {
-        return ${o}(${fp(h,l)});
+        return ${o}(${yp(h,l)});
       }
     `}if(r.shapeInfo.isUniform)return`
       float ${o}(int row, int col, int depth, int depth2) {
         int index = round(dot(vec4(row, col, depth, depth2),
                           vec4(${a}, ${s}, ${n}, 1)));
-        ${pp(r)}
+        ${gp(r)}
       }
     `;let u=r.shapeInfo.flatOffset,c=r.shapeInfo.texShape,p=c[0],m=c[1];if(m===a&&u==null)return`
       float ${o}(int row, int col, int depth, int depth2) {
@@ -685,7 +685,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${m}.0, ${p}.0);
         return sampleTexture(${t}, uv);
       }
-    `;let f=_u(t);return`
+    `;let f=Nu(t);return`
     float ${o}(int row, int col, int depth, int depth2) {
       // Explicitly use integer operations as dot() only works on floats.
       int index = row * ${a} + col * ${s} +
@@ -693,10 +693,10 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${p}, ${m}, index + ${f});
       return sampleTexture(${t}, uv);
     }
-  `}function WK(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=e[4],s=e[3]*n,a=e[2]*s,i=e[1]*a,{newShape:l,keptDims:u}=y.squeezeShape(e);if(l.length<e.length){let h=mp(r,l),g=["row","col","depth","depth2","depth3"];return`
-      ${cp(h)}
+  `}function T5(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=e[4],s=e[3]*n,a=e[2]*s,i=e[1]*a,{newShape:l,keptDims:u}=y.squeezeShape(e);if(l.length<e.length){let h=xp(r,l),g=["row","col","depth","depth2","depth3"];return`
+      ${hp(h)}
       float ${o}(int row, int col, int depth, int depth2, int depth3) {
-        return ${o}(${fp(g,u)});
+        return ${o}(${yp(g,u)});
       }
     `}if(r.shapeInfo.isUniform)return`
       float ${o}(int row, int col, int depth, int depth2, int depth3) {
@@ -704,7 +704,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           vec4(row, col, depth, depth2),
           vec4(${i}, ${a}, ${s}, ${n})) +
           depth3;
-        ${pp(r)}
+        ${gp(r)}
       }
     `;let c=r.shapeInfo.flatOffset,p=r.shapeInfo.texShape,m=p[0],f=p[1];if(f===i&&c==null)return`
       float ${o}(int row, int col, int depth, int depth2, int depth3) {
@@ -726,7 +726,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${f}.0, ${m}.0);
         return sampleTexture(${t}, uv);
       }
-    `;let d=_u(t);return`
+    `;let d=Nu(t);return`
     float ${o}(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 * ${a} + depth * ${s} +
@@ -734,11 +734,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${m}, ${f}, index);
       return sampleTexture(${t}, uv);
     }
-  `}function jK(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),{newShape:n,keptDims:s}=y.squeezeShape(e);if(n.length<e.length){let g=mp(r,n),x=["row","col","depth","depth2","depth3","depth4"];return`
-      ${cp(g)}
+  `}function A5(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),{newShape:n,keptDims:s}=y.squeezeShape(e);if(n.length<e.length){let g=xp(r,n),x=["row","col","depth","depth2","depth3","depth4"];return`
+      ${hp(g)}
       float ${o}(int row, int col, int depth,
                     int depth2, int depth3, int depth4) {
-        return ${o}(${fp(x,s)});
+        return ${o}(${yp(x,s)});
       }
     `}let a=e[5],i=e[4]*a,l=e[3]*i,u=e[2]*l,c=e[1]*u;if(r.shapeInfo.isUniform)return`
       float ${o}(int row, int col, int depth,
@@ -749,7 +749,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           dot(
             vec2(depth3, depth4),
             vec2(${a}, 1)));
-        ${pp(r)}
+        ${gp(r)}
       }
     `;let p=r.shapeInfo.flatOffset,m=r.shapeInfo.texShape,f=m[0],d=m[1];if(d===c&&p==null)return`
       float ${o}(int row, int col, int depth,
@@ -775,7 +775,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${d}.0, ${f}.0);
         return sampleTexture(${t}, uv);
       }
-    `;let h=_u(t);return`
+    `;let h=Nu(t);return`
     float ${o}(int row, int col, int depth,
                   int depth2, int depth3, int depth4) {
       // Explicitly use integer operations as dot() only works on floats.
@@ -784,13 +784,13 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${f}, ${d}, index);
       return sampleTexture(${t}, uv);
     }
-  `}function pp(r){let e=r.name,t=y.sizeFromShape(r.shapeInfo.logicalShape);return t<2?`return ${e};`:`
+  `}function gp(r){let e=r.name,t=y.sizeFromShape(r.shapeInfo.logicalShape);return t<2?`return ${e};`:`
     for (int i = 0; i < ${t}; i++) {
       if (i == index) {
         return ${e}[i];
       }
     }
-  `}function YK(r,e){let t=r.name,o=t.charAt(0).toUpperCase()+t.slice(1),n="get"+o+"AtOutCoords",s=r.shapeInfo.logicalShape.length,a=e.logicalShape.length,i=PA(r.shapeInfo.logicalShape,e.logicalShape),l=Le(a),u=a-s,c,p=["x","y","z","w","u","v"];s===0?c="":a<2&&i.length>=1?c="coords = 0;":c=i.map(b=>`coords.${p[b+u]} = 0;`).join(`
+  `}function O5(r,e){let t=r.name,o=t.charAt(0).toUpperCase()+t.slice(1),n="get"+o+"AtOutCoords",s=r.shapeInfo.logicalShape.length,a=e.logicalShape.length,i=g2(r.shapeInfo.logicalShape,e.logicalShape),l=Le(a),u=a-s,c,p=["x","y","z","w","u","v"];s===0?c="":a<2&&i.length>=1?c="coords = 0;":c=i.map(b=>`coords.${p[b+u]} = 0;`).join(`
 `);let m="";a<2&&s>0?m="coords":m=r.shapeInfo.logicalShape.map((b,w)=>`coords.${p[w+u]}`).join(", ");let f="return outputValue;",h=y.sizeFromShape(r.shapeInfo.logicalShape)===1,x=y.sizeFromShape(e.logicalShape)===1;if(s===1&&!h&&!x)f=`
       return vec4(outputValue.xy, outputValue.xy);
     `;else if(h&&!x)a===1?f=`
@@ -804,22 +804,22 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec4 outputValue = get${o}(${m});
       ${f}
     }
-  `}function ZK(r,e){let t=r.name,o=t.charAt(0).toUpperCase()+t.slice(1),n="get"+o+"AtOutCoords",s=e.texShape,a=r.shapeInfo.texShape,i=r.shapeInfo.logicalShape.length,l=e.logicalShape.length;if(!r.shapeInfo.isUniform&&i===l&&r.shapeInfo.flatOffset==null&&y.arraysEqual(a,s))return`
+  `}function P5(r,e){let t=r.name,o=t.charAt(0).toUpperCase()+t.slice(1),n="get"+o+"AtOutCoords",s=e.texShape,a=r.shapeInfo.texShape,i=r.shapeInfo.logicalShape.length,l=e.logicalShape.length;if(!r.shapeInfo.isUniform&&i===l&&r.shapeInfo.flatOffset==null&&y.arraysEqual(a,s))return`
       float ${n}() {
         return sampleTexture(${t}, resultUV);
       }
-    `;let u=Le(l),c=PA(r.shapeInfo.logicalShape,e.logicalShape),p=l-i,m,f=["x","y","z","w","u","v"];i===0?m="":l<2&&c.length>=1?m="coords = 0;":m=c.map(h=>`coords.${f[h+p]} = 0;`).join(`
+    `;let u=Le(l),c=g2(r.shapeInfo.logicalShape,e.logicalShape),p=l-i,m,f=["x","y","z","w","u","v"];i===0?m="":l<2&&c.length>=1?m="coords = 0;":m=c.map(h=>`coords.${f[h+p]} = 0;`).join(`
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       ${m}
       return get${o}(${d});
     }
-  `}function Le(r){if(r<=1)return"int";if(r===2)return"ivec2";if(r===3)return"ivec3";if(r===4)return"ivec4";if(r===5)return"ivec5";if(r===6)return"ivec6";throw Error(`GPU for rank ${r} is not yet supported`)}function mp(r,e){let t=JSON.parse(JSON.stringify(r));return t.shapeInfo.logicalShape=e,t}function fp(r,e){return e.map(t=>r[t]).join(", ")}function BA(r,e,t,o){let n=e.userCode,s=t.map((f,d)=>{let h={logicalShape:f.shape,texShape:f.isUniform?null:f.texData.texShape,isUniform:f.isUniform,isPacked:f.isUniform?!1:f.texData.isPacked,flatOffset:null};return f.texData!=null&&f.texData.slice!=null&&f.texData.slice.flatOffset>0&&(h.flatOffset=f.texData.slice.flatOffset),{name:e.variableNames[d],shapeInfo:h}}),a=s.map(f=>f.shapeInfo),i={logicalShape:o.shape,texShape:o.texData.texShape,isUniform:!1,isPacked:o.texData.isPacked,flatOffset:null},l=MA(s,i,n,e.packedInputs),u=r.createProgram(l),c=null,p=r.getUniformLocation(u,"NAN",!1);W().getNumber("WEBGL_VERSION")===1&&(c=r.getUniformLocation(u,"INFINITY",!1));let m={};for(let f=0;f<e.variableNames.length;f++){let d=e.variableNames[f],h=!1;m[d]=r.getUniformLocation(u,d,h),m[`offset${d}`]=r.getUniformLocation(u,`offset${d}`,h)}return{program:e,source:l,webGLProgram:u,uniformLocations:m,inShapeInfos:a,outShapeInfo:i,infLoc:c,nanLoc:p}}function VA(r,e){if(r.length!==e.length)throw Error(`Binary was compiled with ${r.length} inputs, but was executed with ${e.length} inputs`);r.forEach((t,o)=>{let n=t.logicalShape,s=e[o],a=s.shape;if(!y.arraysEqual(n,a))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${n} and ${a} must match`);if(t.isUniform&&s.isUniform)return;let i=t.texShape,l=s.isUniform?null:s.texData.texShape;if(!y.arraysEqual(i,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${i} and ${l} must match`)})}function GA(r,e,t,o,n){VA(e.inShapeInfos,t),VA([e.outShapeInfo],[o]);let s=o.texData.texture,a=o.texData.texShape;o.texData.isPacked?r.setOutputPackedMatrixTexture(s,a[0],a[1]):r.setOutputMatrixTexture(s,a[0],a[1]),r.setProgram(e.webGLProgram),W().getNumber("WEBGL_VERSION")===1&&e.infLoc!==null&&r.gl.uniform1f(e.infLoc,Infinity),e.nanLoc!==null&&r.gl.uniform1f(e.nanLoc,NaN),t.forEach((i,l)=>{let u=e.program.variableNames[l],c=e.uniformLocations[u],p=e.uniformLocations[`offset${u}`];if(c!=null){if(i.isUniform){if(y.sizeFromShape(i.shape)<2)r.gl.uniform1f(c,i.uniformValues[0]);else{let m=i.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),r.gl.uniform1fv(c,m)}return}i.texData.slice!=null&&p!=null&&r.gl.uniform1i(p,i.texData.slice.flatOffset),r.setInputMatrixTexture(i.texData.texture,c,l)}}),n!=null&&n(r,e.webGLProgram),r.executeProgram()}function WA(r,e,t){let o="";e.concat(t).forEach(a=>{let i=a.texData!=null&&a.texData.slice!=null&&a.texData.slice.flatOffset>0,l=a.isUniform?"uniform":a.texData.texShape;o+=`${a.shape}_${l}_${i}`});let n=r.userCode,s=r.constructor.name;return s+="_"+o+"_"+n,s}var{addImpl:jA,bincountImpl:Wg,bincountReduceImpl:UA,ceilImpl:HA,concatImpl:qA,expImpl:KA,expm1Impl:XA,floorImpl:YA,gatherV2Impl:ZA,greaterImpl:JA,lessImpl:QA,linSpaceImpl:eE,logImpl:tE,maxImpl:rE,maximumImpl:oE,minimumImpl:nE,multiplyImpl:sE,negImpl:iE,prodImpl:aE,rangeImpl:lE,rsqrtImpl:uE,simpleAbsImpl:jg,sliceImpl:cE,stridedSliceImpl:pE,subImpl:mE,tileImpl:fE,topKImpl:dE,transposeImpl:ku,uniqueImpl:hE}=p_;function xk(r,e){return["x","y","z","w","u","v"].slice(0,e).map(t=>`${r}.${t}`)}function Gt(r,e){return e===1?[r]:xk(r,e)}function gE(r,e){if(r===1)return"rc";let t="";for(let o=0;o<r;o++)t+=e[o],o<r-1&&(t+=",");return t}var yk=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
+  `}function Le(r){if(r<=1)return"int";if(r===2)return"ivec2";if(r===3)return"ivec3";if(r===4)return"ivec4";if(r===5)return"ivec5";if(r===6)return"ivec6";throw Error(`GPU for rank ${r} is not yet supported`)}function xp(r,e){let t=JSON.parse(JSON.stringify(r));return t.shapeInfo.logicalShape=e,t}function yp(r,e){return e.map(t=>r[t]).join(", ")}function w2(r,e,t,o){let n=e.userCode,s=t.map((f,d)=>{let h={logicalShape:f.shape,texShape:f.isUniform?null:f.texData.texShape,isUniform:f.isUniform,isPacked:f.isUniform?!1:f.texData.isPacked,flatOffset:null};return f.texData!=null&&f.texData.slice!=null&&f.texData.slice.flatOffset>0&&(h.flatOffset=f.texData.slice.flatOffset),{name:e.variableNames[d],shapeInfo:h}}),a=s.map(f=>f.shapeInfo),i={logicalShape:o.shape,texShape:o.texData.texShape,isUniform:!1,isPacked:o.texData.isPacked,flatOffset:null},l=x2(s,i,n,e.packedInputs),u=r.createProgram(l),c=null,p=r.getUniformLocation(u,"NAN",!1);W().getNumber("WEBGL_VERSION")===1&&(c=r.getUniformLocation(u,"INFINITY",!1));let m={};for(let f=0;f<e.variableNames.length;f++){let d=e.variableNames[f],h=!1;m[d]=r.getUniformLocation(u,d,h),m[`offset${d}`]=r.getUniformLocation(u,`offset${d}`,h)}return{program:e,source:l,webGLProgram:u,uniformLocations:m,inShapeInfos:a,outShapeInfo:i,infLoc:c,nanLoc:p}}function _2(r,e){if(r.length!==e.length)throw Error(`Binary was compiled with ${r.length} inputs, but was executed with ${e.length} inputs`);r.forEach((t,o)=>{let n=t.logicalShape,s=e[o],a=s.shape;if(!y.arraysEqual(n,a))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${n} and ${a} must match`);if(t.isUniform&&s.isUniform)return;let i=t.texShape,l=s.isUniform?null:s.texData.texShape;if(!y.arraysEqual(i,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${i} and ${l} must match`)})}function k2(r,e,t,o,n){_2(e.inShapeInfos,t),_2([e.outShapeInfo],[o]);let s=o.texData.texture,a=o.texData.texShape;o.texData.isPacked?r.setOutputPackedMatrixTexture(s,a[0],a[1]):r.setOutputMatrixTexture(s,a[0],a[1]),r.setProgram(e.webGLProgram),W().getNumber("WEBGL_VERSION")===1&&e.infLoc!==null&&r.gl.uniform1f(e.infLoc,Infinity),e.nanLoc!==null&&r.gl.uniform1f(e.nanLoc,NaN),t.forEach((i,l)=>{let u=e.program.variableNames[l],c=e.uniformLocations[u],p=e.uniformLocations[`offset${u}`];if(c!=null){if(i.isUniform){if(y.sizeFromShape(i.shape)<2)r.gl.uniform1f(c,i.uniformValues[0]);else{let m=i.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),r.gl.uniform1fv(c,m)}return}i.texData.slice!=null&&p!=null&&r.gl.uniform1i(p,i.texData.slice.flatOffset),r.setInputMatrixTexture(i.texData.texture,c,l)}}),n!=null&&n(r,e.webGLProgram),r.executeProgram()}function v2(r,e,t){let o="";e.concat(t).forEach(a=>{let i=a.texData!=null&&a.texData.slice!=null&&a.texData.slice.flatOffset>0,l=a.isUniform?"uniform":a.texData.texShape;o+=`${a.shape}_${l}_${i}`});let n=r.userCode,s=r.constructor.name;return s+="_"+o+"_"+n,s}var{addImpl:C2,bincountImpl:Qg,bincountReduceImpl:I2,ceilImpl:N2,concatImpl:S2,expImpl:T2,expm1Impl:A2,floorImpl:E2,gatherV2Impl:D2,greaterImpl:$2,lessImpl:R2,linSpaceImpl:F2,logImpl:O2,maxImpl:P2,maximumImpl:M2,minimumImpl:L2,multiplyImpl:z2,negImpl:B2,prodImpl:V2,rangeImpl:G2,rsqrtImpl:W2,simpleAbsImpl:ex,sliceImpl:j2,stridedSliceImpl:U2,subImpl:H2,tileImpl:q2,topKImpl:K2,transposeImpl:Su,uniqueImpl:X2}=__;function Sk(r,e){return["x","y","z","w","u","v"].slice(0,e).map(t=>`${r}.${t}`)}function Gt(r,e){return e===1?[r]:Sk(r,e)}function Y2(r,e){if(r===1)return"rc";let t="";for(let o=0;o<r;o++)t+=e[o],o<r-1&&(t+=",");return t}var Tk=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
         void main() {
           setOutput(vec4(getA(), 0., 0., 0.));
         }
-      `;else{let o=Gt("rc",t),n=Le(t),s=p6(t,e,o),a=m6(t,e[e.length-1],e[e.length-2],o),i=f6(e,o);this.userCode=`
+      `;else{let o=Gt("rc",t),n=Le(t),s=Y5(t,e,o),a=Z5(t,e[e.length-1],e[e.length-2],o),i=J5(e,o);this.userCode=`
         void main() {
           ${n} rc = getOutputCoords();
 
@@ -831,7 +831,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             setOutput(vec4(${i}));
           }
         }
-      `}}};function d6(r,e){let t=[];for(let o=0;o<=1;o++)for(let n=0;n<=1;n++){let s=`${o===0?"r":"rp1"}, ${n===0?"c":"cp1"}`;for(let a=2;a<r;a++)s=`${e[e.length-1-a]},`+s;t.push(s)}return t}function p6(r,e,t){if(r===1)return`rc > ${e[0]}`;let o="";for(let n=r-2;n<r;n++)o+=`${t[n]} >= ${e[n]}`,n<r-1&&(o+="||");return o}function m6(r,e,t,o){if(r===1)return"";let n=o.slice(-2);return`
+      `}}};function Q5(r,e){let t=[];for(let o=0;o<=1;o++)for(let n=0;n<=1;n++){let s=`${o===0?"r":"rp1"}, ${n===0?"c":"cp1"}`;for(let a=2;a<r;a++)s=`${e[e.length-1-a]},`+s;t.push(s)}return t}function Y5(r,e,t){if(r===1)return`rc > ${e[0]}`;let o="";for(let n=r-2;n<r;n++)o+=`${t[n]} >= ${e[n]}`,n<r-1&&(o+="||");return o}function Z5(r,e,t,o){if(r===1)return"";let n=o.slice(-2);return`
     int r = ${n[0]};
     int c = ${n[1]};
     int rp1 = r + 1;
@@ -839,12 +839,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
     bool cEdge = cp1 >= ${e};
     bool rEdge = rp1 >= ${t};
-  `}function f6(r,e){let t=r.length,o=d6(t,e);return t===1?`getA(rc),
+  `}function J5(r,e){let t=r.length,o=Q5(t,e);return t===1?`getA(rc),
             rc + 1 >= ${r[0]} ? 0. : getA(rc + 1),
             0, 0`:`getA(${o[0]}),
           cEdge ? 0. : getA(${o[1]}),
           rEdge ? 0. : getA(${o[2]}),
-          rEdge || cEdge ? 0. : getA(${o[3]})`}var gf=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let o="";for(let n=0;n<4;n++){let s="thisRC = rc;";n%2==1&&(s+="thisRC.z += 1;"),n>1&&(s+="thisRC.y += 1;"),o+=`
+          rEdge || cEdge ? 0. : getA(${o[3]})`}var Nf=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let o="";for(let n=0;n<4;n++){let s="thisRC = rc;";n%2==1&&(s+="thisRC.z += 1;"),n>1&&(s+="thisRC.y += 1;"),o+=`
         ${s}
         ${n>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
           int flatIndex = getFlatIndex(thisRC);
@@ -856,8 +856,8 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
         ${n>0?"}":""}
       `}this.userCode=`
-      ${h6(t)}
-      ${up(e)}
+      ${eX(t)}
+      ${dp(e)}
 
       void main() {
         ivec3 rc = getOutputCoords();
@@ -872,12 +872,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function h6(r){return`
+    `}};function eX(r){return`
     ivec3 inputCoordsFromReshapedOutCoords(int index) {
-      ${xs(["r","c","d"],r)}
+      ${ks(["r","c","d"],r)}
       return ivec3(r, c, d);
     }
-  `}var bk=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,o){let n=yE(t,o),s=bE(e,n,o);s in this.freeTextures||(this.freeTextures[s]=[]),s in this.usedTextures||(this.usedTextures[s]=[]);let a=xE(e,n,this.gpgpu.gl,this.gpgpu.textureConfig,o);if(this.freeTextures[s].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=a,this.log();let l=this.freeTextures[s].shift();return this.usedTextures[s].push(l),l}let i;return n===kr.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):n===kr.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):n===kr.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):n===kr.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):n===kr.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[s].push(i),this.numUsedTextures++,this._numBytesAllocated+=a,this.log(),i}releaseTexture(e,t,o,n){if(this.freeTextures==null)return;let s=yE(o,n),a=bE(t,s,n);a in this.freeTextures||(this.freeTextures[a]=[]);let i=xE(t,s,this.gpgpu.gl,this.gpgpu.textureConfig,n),l=W().get("WEBGL_DELETE_TEXTURE_THRESHOLD");l!==-1&&this._numBytesAllocated>l?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[a].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let u=this.usedTextures[a],c=u.indexOf(e);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");u.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${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)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function g6(r,e){let t=r;if(e===t.R32F)return 4;if(e===t.R16F)return 2;if(e===t.RGBA32F)return 16;if(e===r.RGBA)return 16;if(e===t.RGBA16F)return 8;throw new Error(`Unknown internal format ${e}`)}function xE(r,e,t,o,n){let s=x6(e,o),a;if(n){let[l,u]=ei(r[0],r[1]);a=l*u}else{let[l,u]=wu(r[0],r[1]);a=l*u}let i=g6(t,s);return a*i}function x6(r,e){switch(r){case kr.PACKED_2X2_FLOAT32:return Vg(e);case kr.PACKED_2X2_FLOAT16:return Gg(e);case kr.UNPACKED_FLOAT32:return Lg(e);case kr.UNPACKED_FLOAT16:return zg(e);case kr.PACKED_4X1_UNSIGNED_BYTE:return Bg(e);default:throw new Error(`Unknown physical texture type ${r}`)}}function y6(r){return W().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?r?kr.PACKED_2X2_FLOAT32:kr.UNPACKED_FLOAT32:r?kr.PACKED_2X2_FLOAT16:kr.UNPACKED_FLOAT16}function yE(r,e){if(r===Dr.UPLOAD)return kr.PACKED_2X2_FLOAT32;if(r===Dr.RENDER||r==null)return y6(e);if(r===Dr.DOWNLOAD||r===Dr.PIXELS)return kr.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${r}`)}function bE(r,e,t){return`${r[0]}_${r[1]}_${e}_${t}`}var ao=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+  `}var Ak=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,o){let n=J2(t,o),s=Q2(e,n,o);s in this.freeTextures||(this.freeTextures[s]=[]),s in this.usedTextures||(this.usedTextures[s]=[]);let a=Z2(e,n,this.gpgpu.gl,this.gpgpu.textureConfig,o);if(this.freeTextures[s].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=a,this.log();let l=this.freeTextures[s].shift();return this.usedTextures[s].push(l),l}let i;return n===vr.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):n===vr.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):n===vr.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):n===vr.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):n===vr.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[s].push(i),this.numUsedTextures++,this._numBytesAllocated+=a,this.log(),i}releaseTexture(e,t,o,n){if(this.freeTextures==null)return;let s=J2(o,n),a=Q2(t,s,n);a in this.freeTextures||(this.freeTextures[a]=[]);let i=Z2(t,s,this.gpgpu.gl,this.gpgpu.textureConfig,n),l=W().get("WEBGL_DELETE_TEXTURE_THRESHOLD");l!==-1&&this._numBytesAllocated>l?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[a].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let u=this.usedTextures[a],c=u.indexOf(e);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");u.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${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)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function tX(r,e){let t=r;if(e===t.R32F)return 4;if(e===t.R16F)return 2;if(e===t.RGBA32F)return 16;if(e===r.RGBA)return 16;if(e===t.RGBA16F)return 8;throw new Error(`Unknown internal format ${e}`)}function Z2(r,e,t,o,n){let s=rX(e,o),a;if(n){let[l,u]=si(r[0],r[1]);a=l*u}else{let[l,u]=Iu(r[0],r[1]);a=l*u}let i=tX(t,s);return a*i}function rX(r,e){switch(r){case vr.PACKED_2X2_FLOAT32:return Zg(e);case vr.PACKED_2X2_FLOAT16:return Jg(e);case vr.UNPACKED_FLOAT32:return Kg(e);case vr.UNPACKED_FLOAT16:return Xg(e);case vr.PACKED_4X1_UNSIGNED_BYTE:return Yg(e);default:throw new Error(`Unknown physical texture type ${r}`)}}function oX(r){return W().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?r?vr.PACKED_2X2_FLOAT32:vr.UNPACKED_FLOAT32:r?vr.PACKED_2X2_FLOAT16:vr.UNPACKED_FLOAT16}function J2(r,e){if(r===$r.UPLOAD)return vr.PACKED_2X2_FLOAT32;if(r===$r.RENDER||r==null)return oX(e);if(r===$r.DOWNLOAD||r===$r.PIXELS)return vr.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${r}`)}function Q2(r,e,t){return`${r[0]}_${r[1]}_${e}_${t}`}var mo=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       float unaryOperation(float x) {
         ${t}
       }
@@ -888,11 +888,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}},gr="if (isnan(x)) return x;",wE="return x;",wk="return abs(x);";var _E="return (x >= 0.0) ? x : (exp(x) - 1.0);",kE=gr+`
+    `}},gr="if (isnan(x)) return x;",eD="return x;",Ek="return abs(x);";var tD="return (x >= 0.0) ? x : (exp(x) - 1.0);",rD=gr+`
   return (x < 0.0) ? 0.0 : x;
-`,vE=gr+`
+`,oD=gr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,xf="return x;";var CE="return x;",IE=`
+`,Sf="return x;";var nD="return x;",sD=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -901,7 +901,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,NE=`
+`,iD=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -911,7 +911,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,SE=`
+`,aD=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -921,7 +921,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,ys=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
+`,vs=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
       vec4 unaryOperation(vec4 x) {
         ${t}
       }
@@ -932,17 +932,17 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}};var _k=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,o=Gt("rc",t),n=Le(t),s=gE(t,o),a=o.slice(-2),i=t<=1?"rc":`vec2(${a.join(",")})`;this.userCode=`
+    `}};var Dk=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,o=Gt("rc",t),n=Le(t),s=Y2(t,o),a=o.slice(-2),i=t<=1?"rc":`vec2(${a.join(",")})`;this.userCode=`
       void main() {
         ${n} rc = getOutputCoords();
         vec4 packedInput = getA(${s});
 
         setOutput(getChannel(packedInput, ${i}));
       }
-    `}};var b6=Ar.whereImpl,w6=1e-7,_6=1e-4,Ug={};function k6(r){return r in Ug||(Ug[r]={}),Ug[r]}var v6=128,C6=600;function I6(){return W().global.screen==null?1024:W().global.screen.height*W().global.screen.width*window.devicePixelRatio*C6/1024/1024}var dp=class extends Ss{constructor(e){super();if(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.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!W().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Oo(W().getNumber("WEBGL_VERSION"));this.binaryCache=k6(W().getNumber("WEBGL_VERSION")),this.gpgpu=new gk(t),this.canvas=t.canvas,this.gpgpuCreatedLocally=!0}else this.gpgpu=e,this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=e.gl.canvas;this.textureManager=new bk(this.gpgpu),this.numMBBeforeWarning=I6(),this.texData=new Pa(this,Ho())}nextDataId(){return dp.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,o){if((W().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||W().getBool("DEBUG"))&&this.checkNumericalProblems(e),o==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let n={id:this.nextDataId()};return this.texData.set(n,{shape:t,dtype:o,values:e,usage:Dr.UPLOAD,refCount:1}),n}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,o,n,s){if(W().getBool("DEBUG")&&this.checkNumericalProblems(t),n==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:o,dtype:n,values:t,usage:Dr.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:o,dtype:n,complexTensorInfos:s,slice:a,shape:i,isPacked:l}=t;if(a!=null){let m;l?m=new ys(i,xf):m=new ao(i,xf);let f=this.runWebGLProgram(m,[{dataId:e,shape:i,dtype:n}],n),d=this.readSync(f.dataId);return this.disposeIntermediateTensorInfo(f),d}if(o!=null)return this.convertAndCacheOnCPU(e);if(n==="string")return o;let u=this.activeTimers!=null,c;u&&(c=y.now());let p;if(n==="complex64"){let m=this.readSync(s.real.dataId),f=this.readSync(s.imag.dataId);p=N.mergeRealAndImagArrays(m,f)}else p=this.getValuesFromTexture(e);return u&&(this.downloadWaitMs+=y.now()-c),this.convertAndCacheOnCPU(e,p)}async read(e){if(this.pendingRead.has(e)){let d=this.pendingRead.get(e);return new Promise(h=>d.push(h))}let t=this.texData.get(e),{values:o,shape:n,slice:s,dtype:a,complexTensorInfos:i,isPacked:l}=t;if(s!=null){let d;l?d=new ys(n,xf):d=new ao(n,xf);let h=this.runWebGLProgram(d,[{dataId:e,shape:n,dtype:a}],a),g=this.read(h.dataId);return this.disposeIntermediateTensorInfo(h),g}if(o!=null)return this.convertAndCacheOnCPU(e);if(!W().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&W().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let u=null,c;if(a!=="complex64"&&W().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let d=this.texData.get(c.dataId);u=this.gpgpu.createBufferFromTexture(d.texture,...ll(n))}this.pendingRead.set(e,[]),a!=="complex64"&&await this.gpgpu.createAndWaitForFence();let p;if(a==="complex64"){let d=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),h=d[0],g=d[1];p=N.mergeRealAndImagArrays(h,g)}else if(u==null)p=this.getValuesFromTexture(e);else{let d=y.sizeFromShape(n);p=this.gpgpu.downloadFloat32MatrixFromBuffer(u,d)}c!=null&&this.disposeIntermediateTensorInfo(c);let m=this.convertAndCacheOnCPU(e,p),f=this.pendingRead.get(e);return this.pendingRead.delete(e),f.forEach(d=>d(m)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&Ho().removeDataId(e,this),this.pendingDeletes--),m}bufferSync(e){let t=this.readSync(e.dataId),o=t;if(e.dtype==="string")try{o=t.map(n=>y.decodeString(n))}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return ve(e.shape,e.dtype,o)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let o=e[t];if(!S_(o))throw W().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${o} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${o} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:o,isPacked:n}=this.texData.get(e),s=y.sizeFromShape(t);if(W().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let m=this.decode(e),f=this.texData.get(m.dataId),d=this.gpgpu.downloadMatrixFromPackedTexture(f.texture,...ll(t)).subarray(0,s);return this.disposeIntermediateTensorInfo(m),d}let a=W().getBool("WEBGL_PACK")&&n===!0,i=a?df(t):t,l=a?new Z_(i):new Y_(i),u=this.runWebGLProgram(l,[{shape:i,dtype:o,dataId:e}],"float32"),c=this.texData.get(u.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture,c.texShape[0],c.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(u),p}timerAvailable(){return W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,o=[],n=!1;this.programTimersStack==null?(this.programTimersStack=o,n=!0):this.activeTimers.push(o),this.activeTimers=o,e();let s=y.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),a=y.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=t,n&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let l=await Promise.all(s);i.kernelMs=y.sum(l),i.getExtraProfileInfo=()=>l.map((u,c)=>({name:a[c],ms:u})).map(u=>`${u.name}: ${u.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:y.now(),endMs:null}}endTimer(e){return W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=y.now(),e)}async getQueryTime(e){if(W().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:o}=this.texData.get(e);return o!=null&&(this.disposeData(o.real.dataId,t),this.disposeData(o.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:o,texShape:n,usage:s,isPacked:a,slice:i}=this.texData.get(e),l=i&&i.origDataId||e,u=this.dataRefCount.get(l);u>1?this.dataRefCount.set(l,u-1):(this.dataRefCount.delete(l),t!=null&&(this.numBytesInGPU-=this.computeBytes(n,o),this.textureManager.releaseTexture(t,n,s,a)));let c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return W().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Ho().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=v6){let o=this.getCPUBackend();return!W().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&o==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),o!=null&&e.every(n=>this.texData.get(n.dataId).texture==null&&y.sizeFromShape(n.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){N.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return b6(e.shape,t)}packedUnaryOp(e,t,o){let n=new ys(e.shape,t),s=this.compileAndRun(n,[e],o);return Ho().makeTensorFromDataId(s.dataId,s.shape,s.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let n=jg(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,n)}if(W().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,wk,e.dtype);let t=new ao(e.shape,wk),o=this.compileAndRun(t,[e]);return Ho().makeTensorFromDataId(o.dataId,o.shape,o.dtype)}makeTensorInfo(e,t,o){let n;if(t==="string"&&o!=null&&o.length>0&&y.isString(o[0])){let s=o.map(a=>y.encodeString(a));n=this.write(s,e,t)}else n=this.write(o,e,t);return this.texData.get(n).usage=null,{dataId:n,shape:e,dtype:t}}makeOutput(e,t,o){let{dataId:n}=this.makeTensorInfo(e,t,o);return Ho().makeTensorFromDataId(n,e,t,this)}unpackTensor(e){let t=new _k(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new yk(e.shape),o=!0;return this.runWebGLProgram(t,[e],e.dtype,null,o)}packedReshape(e,t){let o=[ba(e.shape),...wa(e.shape)],n={dtype:e.dtype,shape:o,dataId:e.dataId},s=[ba(t),...wa(t)],a=new gf(s,o),i=!0,l=this.runWebGLProgram(a,[n],e.dtype,null,i);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e){let t=this.texData.get(e),{isPacked:o,shape:n,dtype:s}=t,a=df(n),i;o?i=new X_(a):i=new K_(a);let l=!0,u=this.runWebGLProgram(i,[{shape:a,dtype:s,dataId:e}],s,null,l);return{dtype:s,shape:n,dataId:u.dataId}}runWebGLProgram(e,t,o,n,s=!1){let a=this.makeTensorInfo(e.outputShape,o),i=this.texData.get(a.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===al.DENSE){let g=ll(e.outputShape);i.texShape=g.map(x=>x*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),y.sizeFromShape(a.shape)===0)return i.values=y.getTypedArrayFromDType(a.dtype,0),a;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 x=this.texData.get(g.dataId);if(x.texture==null){if(!e.packedInputs&&y.sizeFromShape(g.shape)<=W().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:g.shape,texData:null,isUniform:!0,uniformValues:x.values};e.packedInputs&&(x.isPacked=!0,x.shape=g.shape)}else if(!!x.isPacked!=!!e.packedInputs)g=x.isPacked?this.unpackTensor(g):this.packTensor(g),l.push(g),x=this.texData.get(g.dataId);else if(x.isPacked&&!ul(x.shape,g.shape)){let b=g,w=g.shape;g.shape=x.shape,g=this.packedReshape(g,w),l.push(g),x=this.texData.get(g.dataId),b.shape=w}return this.uploadToGPU(g.dataId),{shape:g.shape,texData:x,isUniform:!1}});this.uploadToGPU(a.dataId);let c={shape:a.shape,texData:i,isUniform:!1},p=WA(e,u,c),m=this.getAndSaveBinary(p,()=>BA(this.gpgpu,e,u,c)),f=this.activeTimers!=null,d;f&&(d=this.startTimer()),GA(this.gpgpu,m,u,c,n),l.forEach(g=>this.disposeIntermediateTensorInfo(g)),f&&(d=this.endTimer(d),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(d)}));let h=W().get("WEBGL_FLUSH_THRESHOLD");if(h>0){let g=y.now();g-this.lastGlFlushTime>h&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!W().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&s===!1){let g=this.unpackTensor(a);return this.disposeIntermediateTensorInfo(a),g}return a}compileAndRun(e,t,o,n,s=!1){return o=o||t[0].dtype,this.runWebGLProgram(e,t,o,n,s)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(W().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=V(()=>{if(!W().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=W().getBool("DEBUG");W().set("DEBUG",!1);let t=this.abs(le(1e-8)).dataSync()[0];if(W().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?w6:_6}uploadToGPU(e){let t=this.texData.get(e),{shape:o,dtype:n,values:s,texture:a,usage:i,isPacked:l}=t;if(a!=null)return;let u=this.activeTimers!=null,c;u&&(c=y.now());let p=t.texShape;if(p==null&&(p=B_(o,l),t.texShape=p),s!=null){let m=df(o),f,d=p[1],h=p[0],g=s instanceof Uint8Array;l?([d,h]=ei(p[0],p[1]),f=new Q_(m,[h,d],g)):f=new J_(m,[h,d],g);let x=this.makeTensorInfo([h,d],n);g?this.texData.get(x.dataId).usage=Dr.PIXELS:this.texData.get(x.dataId).usage=Dr.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(x.dataId),d,h,s);let b=!0,w=this.runWebGLProgram(f,[x],n,null,b),_=this.texData.get(w.dataId);t.texture=_.texture,t.texShape=_.texShape,t.isPacked=_.isPacked,t.usage=_.usage,this.disposeIntermediateTensorInfo(x),this.texData.delete(w.dataId),t.values=null,u&&(this.uploadWaitMs+=y.now()-c)}else{let m=this.acquireTexture(p,i,n,l);t.texture=m}}convertAndCacheOnCPU(e,t){let o=this.texData.get(e),{dtype:n}=o;return this.releaseGPUData(e),t!=null&&(o.values=N6(t,n)),o.values}acquireTexture(e,t,o,n){if(this.numBytesInGPU+=this.computeBytes(e,o),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let s=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${s} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,n)}computeBytes(e,t){return e[0]*e[1]*y.bytesPerElement(t)}};dp.nextDataId=0;function N6(r,e){if(e==="float32"||e==="complex64")return r;if(e==="int32"||e==="bool"){let t=e==="int32"?new Int32Array(r.length):new Uint8Array(r.length);for(let o=0;o<t.length;++o)t[o]=Math.round(r[o]);return t}else throw new Error(`Unknown dtype ${e}`)}var kk="3.3.0";function TE(){W().set("WEBGL_FORCE_F16_TEXTURES",!0)}Ll.isBrowser()&&Gc("webgl",()=>new dp,2);var s6e={forceHalfFloat:TE};var Hg=`
+    `}};var nX=Er.whereImpl,sX=1e-7,iX=1e-4,tx={};function aX(r){return r in tx||(tx[r]={}),tx[r]}var lX=128,uX=600;function cX(){return W().global.screen==null?1024:W().global.screen.height*W().global.screen.width*window.devicePixelRatio*uX/1024/1024}var bp=class extends $s{constructor(e){super();if(this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!W().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Bo(W().getNumber("WEBGL_VERSION"));this.binaryCache=aX(W().getNumber("WEBGL_VERSION")),this.gpgpu=new Nk(t),this.canvas=t.canvas,this.gpgpuCreatedLocally=!0}else this.gpgpu=e,this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=e.gl.canvas;this.textureManager=new Ak(this.gpgpu),this.numMBBeforeWarning=cX(),this.texData=new Va(this,Zo())}nextDataId(){return bp.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,o){if((W().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||W().getBool("DEBUG"))&&this.checkNumericalProblems(e),o==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let n={id:this.nextDataId()};return this.texData.set(n,{shape:t,dtype:o,values:e,usage:$r.UPLOAD,refCount:1}),n}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,o,n,s){if(W().getBool("DEBUG")&&this.checkNumericalProblems(t),n==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:o,dtype:n,values:t,usage:$r.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:o,dtype:n,complexTensorInfos:s,slice:a,shape:i,isPacked:l}=t;if(a!=null){let m;l?m=new vs(i,Sf):m=new mo(i,Sf);let f=this.runWebGLProgram(m,[{dataId:e,shape:i,dtype:n}],n),d=this.readSync(f.dataId);return this.disposeIntermediateTensorInfo(f),d}if(o!=null)return this.convertAndCacheOnCPU(e);if(n==="string")return o;let u=this.activeTimers!=null,c;u&&(c=y.now());let p;if(n==="complex64"){let m=this.readSync(s.real.dataId),f=this.readSync(s.imag.dataId);p=N.mergeRealAndImagArrays(m,f)}else p=this.getValuesFromTexture(e);return u&&(this.downloadWaitMs+=y.now()-c),this.convertAndCacheOnCPU(e,p)}async read(e){if(this.pendingRead.has(e)){let d=this.pendingRead.get(e);return new Promise(h=>d.push(h))}let t=this.texData.get(e),{values:o,shape:n,slice:s,dtype:a,complexTensorInfos:i,isPacked:l}=t;if(s!=null){let d;l?d=new vs(n,Sf):d=new mo(n,Sf);let h=this.runWebGLProgram(d,[{dataId:e,shape:n,dtype:a}],a),g=this.read(h.dataId);return this.disposeIntermediateTensorInfo(h),g}if(o!=null)return this.convertAndCacheOnCPU(e);if(!W().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&W().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let u=null,c;if(a!=="complex64"&&W().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let d=this.texData.get(c.dataId);u=this.gpgpu.createBufferFromTexture(d.texture,...fl(n))}this.pendingRead.set(e,[]),a!=="complex64"&&await this.gpgpu.createAndWaitForFence();let p;if(a==="complex64"){let d=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),h=d[0],g=d[1];p=N.mergeRealAndImagArrays(h,g)}else if(u==null)p=this.getValuesFromTexture(e);else{let d=y.sizeFromShape(n);p=this.gpgpu.downloadFloat32MatrixFromBuffer(u,d)}c!=null&&this.disposeIntermediateTensorInfo(c);let m=this.convertAndCacheOnCPU(e,p),f=this.pendingRead.get(e);return this.pendingRead.delete(e),f.forEach(d=>d(m)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&Zo().removeDataId(e,this),this.pendingDeletes--),m}bufferSync(e){let t=this.readSync(e.dataId),o=t;if(e.dtype==="string")try{o=t.map(n=>y.decodeString(n))}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return ve(e.shape,e.dtype,o)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let o=e[t];if(!M_(o))throw W().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${o} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${o} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:o,isPacked:n}=this.texData.get(e),s=y.sizeFromShape(t);if(W().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let m=this.decode(e),f=this.texData.get(m.dataId),d=this.gpgpu.downloadMatrixFromPackedTexture(f.texture,...fl(t)).subarray(0,s);return this.disposeIntermediateTensorInfo(m),d}let a=W().getBool("WEBGL_PACK")&&n===!0,i=a?Cf(t):t,l=a?new ak(i):new ik(i),u=this.runWebGLProgram(l,[{shape:i,dtype:o,dataId:e}],"float32"),c=this.texData.get(u.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture,c.texShape[0],c.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(u),p}timerAvailable(){return W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,o=[],n=!1;this.programTimersStack==null?(this.programTimersStack=o,n=!0):this.activeTimers.push(o),this.activeTimers=o,e();let s=y.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),a=y.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=t,n&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let l=await Promise.all(s);i.kernelMs=y.sum(l),i.getExtraProfileInfo=()=>l.map((u,c)=>({name:a[c],ms:u})).map(u=>`${u.name}: ${u.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:y.now(),endMs:null}}endTimer(e){return W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=y.now(),e)}async getQueryTime(e){if(W().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:o}=this.texData.get(e);return o!=null&&(this.disposeData(o.real.dataId,t),this.disposeData(o.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:o,texShape:n,usage:s,isPacked:a,slice:i}=this.texData.get(e),l=i&&i.origDataId||e,u=this.dataRefCount.get(l);u>1?this.dataRefCount.set(l,u-1):(this.dataRefCount.delete(l),t!=null&&(this.numBytesInGPU-=this.computeBytes(n,o),this.textureManager.releaseTexture(t,n,s,a)));let c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return W().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Zo().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=lX){let o=this.getCPUBackend();return!W().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&o==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),o!=null&&e.every(n=>this.texData.get(n.dataId).texture==null&&y.sizeFromShape(n.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){N.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return nX(e.shape,t)}packedUnaryOp(e,t,o){let n=new vs(e.shape,t),s=this.compileAndRun(n,[e],o);return Zo().makeTensorFromDataId(s.dataId,s.shape,s.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let n=ex(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,n)}if(W().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,Ek,e.dtype);let t=new mo(e.shape,Ek),o=this.compileAndRun(t,[e]);return Zo().makeTensorFromDataId(o.dataId,o.shape,o.dtype)}makeTensorInfo(e,t,o){let n;if(t==="string"&&o!=null&&o.length>0&&y.isString(o[0])){let s=o.map(a=>y.encodeString(a));n=this.write(s,e,t)}else n=this.write(o,e,t);return this.texData.get(n).usage=null,{dataId:n,shape:e,dtype:t}}makeOutput(e,t,o){let{dataId:n}=this.makeTensorInfo(e,t,o);return Zo().makeTensorFromDataId(n,e,t,this)}unpackTensor(e){let t=new Dk(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new Tk(e.shape),o=!0;return this.runWebGLProgram(t,[e],e.dtype,null,o)}packedReshape(e,t){let o=[Ca(e.shape),...Ia(e.shape)],n={dtype:e.dtype,shape:o,dataId:e.dataId},s=[Ca(t),...Ia(t)],a=new Nf(s,o),i=!0,l=this.runWebGLProgram(a,[n],e.dtype,null,i);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e){let t=this.texData.get(e),{isPacked:o,shape:n,dtype:s}=t,a=Cf(n),i;o?i=new sk(a):i=new nk(a);let l=!0,u=this.runWebGLProgram(i,[{shape:a,dtype:s,dataId:e}],s,null,l);return{dtype:s,shape:n,dataId:u.dataId}}runWebGLProgram(e,t,o,n,s=!1){let a=this.makeTensorInfo(e.outputShape,o),i=this.texData.get(a.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===ml.DENSE){let g=fl(e.outputShape);i.texShape=g.map(x=>x*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),y.sizeFromShape(a.shape)===0)return i.values=y.getTypedArrayFromDType(a.dtype,0),a;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 x=this.texData.get(g.dataId);if(x.texture==null){if(!e.packedInputs&&y.sizeFromShape(g.shape)<=W().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:g.shape,texData:null,isUniform:!0,uniformValues:x.values};e.packedInputs&&(x.isPacked=!0,x.shape=g.shape)}else if(!!x.isPacked!=!!e.packedInputs)g=x.isPacked?this.unpackTensor(g):this.packTensor(g),l.push(g),x=this.texData.get(g.dataId);else if(x.isPacked&&!dl(x.shape,g.shape)){let b=g,w=g.shape;g.shape=x.shape,g=this.packedReshape(g,w),l.push(g),x=this.texData.get(g.dataId),b.shape=w}return this.uploadToGPU(g.dataId),{shape:g.shape,texData:x,isUniform:!1}});this.uploadToGPU(a.dataId);let c={shape:a.shape,texData:i,isUniform:!1},p=v2(e,u,c),m=this.getAndSaveBinary(p,()=>w2(this.gpgpu,e,u,c)),f=this.activeTimers!=null,d;f&&(d=this.startTimer()),k2(this.gpgpu,m,u,c,n),l.forEach(g=>this.disposeIntermediateTensorInfo(g)),f&&(d=this.endTimer(d),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(d)}));let h=W().get("WEBGL_FLUSH_THRESHOLD");if(h>0){let g=y.now();g-this.lastGlFlushTime>h&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!W().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&s===!1){let g=this.unpackTensor(a);return this.disposeIntermediateTensorInfo(a),g}return a}compileAndRun(e,t,o,n,s=!1){return o=o||t[0].dtype,this.runWebGLProgram(e,t,o,n,s)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(W().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=V(()=>{if(!W().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=W().getBool("DEBUG");W().set("DEBUG",!1);let t=this.abs(le(1e-8)).dataSync()[0];if(W().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?sX:iX}uploadToGPU(e){let t=this.texData.get(e),{shape:o,dtype:n,values:s,texture:a,usage:i,isPacked:l}=t;if(a!=null)return;let u=this.activeTimers!=null,c;u&&(c=y.now());let p=t.texShape;if(p==null&&(p=Y_(o,l),t.texShape=p),s!=null){let m=Cf(o),f,d=p[1],h=p[0],g=s instanceof Uint8Array;l?([d,h]=si(p[0],p[1]),f=new uk(m,[h,d],g)):f=new lk(m,[h,d],g);let x=this.makeTensorInfo([h,d],n);g?this.texData.get(x.dataId).usage=$r.PIXELS:this.texData.get(x.dataId).usage=$r.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(x.dataId),d,h,s);let b=!0,w=this.runWebGLProgram(f,[x],n,null,b),_=this.texData.get(w.dataId);t.texture=_.texture,t.texShape=_.texShape,t.isPacked=_.isPacked,t.usage=_.usage,this.disposeIntermediateTensorInfo(x),this.texData.delete(w.dataId),t.values=null,u&&(this.uploadWaitMs+=y.now()-c)}else{let m=this.acquireTexture(p,i,n,l);t.texture=m}}convertAndCacheOnCPU(e,t){let o=this.texData.get(e),{dtype:n}=o;return this.releaseGPUData(e),t!=null&&(o.values=pX(t,n)),o.values}acquireTexture(e,t,o,n){if(this.numBytesInGPU+=this.computeBytes(e,o),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let s=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${s} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,n)}computeBytes(e,t){return e[0]*e[1]*y.bytesPerElement(t)}};bp.nextDataId=0;function pX(r,e){if(e==="float32"||e==="complex64")return r;if(e==="int32"||e==="bool"){let t=e==="int32"?new Int32Array(r.length):new Uint8Array(r.length);for(let o=0;o<t.length;++o)t[o]=Math.round(r[o]);return t}else throw new Error(`Unknown dtype ${e}`)}var $k="3.3.0";function lD(){W().set("WEBGL_FORCE_F16_TEXTURES",!0)}Wl.isBrowser()&&qc("webgl",()=>new bp,2);var F5e={forceHalfFloat:lD};var rx=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
-`;var nn=class{constructor(e,t,o){this.variableNames=["A","B"],this.outputShape=N.assertAndGetBroadcastShape(t,o),this.userCode=`
+`;var cn=class{constructor(e,t,o){this.variableNames=["A","B"],this.outputShape=N.assertAndGetBroadcastShape(t,o),this.userCode=`
       float binaryOperation(float a, float b) {
         ${e}
       }
@@ -952,12 +952,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float b = getBAtOutCoords();
         setOutput(binaryOperation(a, b));
       }
-    `}};var cl=`
+    `}};var hl=`
   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;
-`;var bs=class{constructor(e,t,o,n=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=N.assertAndGetBroadcastShape(t,o);let s=this.outputShape.length,a="";if(n)if(s===0||y.sizeFromShape(this.outputShape)===1)a=`
+`;var Cs=class{constructor(e,t,o,n=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=N.assertAndGetBroadcastShape(t,o);let s=this.outputShape.length,a="";if(n)if(s===0||y.sizeFromShape(this.outputShape)===1)a=`
           result.y = 0.;
           result.z = 0.;
           result.w = 0.;
@@ -989,21 +989,21 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function Wt(r){let{inputs:e,backend:t}=r,{x:o}=e;return t.incRef(o.dataId),{dataId:o.dataId,shape:o.shape,dtype:o.dtype}}var AE={kernelName:Wo,backendName:"webgl",kernelFunc:Wt};function lo(r){let{inputs:e,backend:t}=r,{real:o,imag:n}=e,s=t.makeTensorInfo(o.shape,"complex64"),a=t.texData.get(s.dataId),i=Wt({inputs:{x:o},backend:t}),l=Wt({inputs:{x:n},backend:t});return a.complexTensorInfos={real:i,imag:l},s}var EE={kernelName:cc,backendName:"webgl",kernelFunc:lo};var vk="return (a < 0.) ? b * a : a;",Ck=`
+    `}};function Wt(r){let{inputs:e,backend:t}=r,{x:o}=e;return t.incRef(o.dataId),{dataId:o.dataId,shape:o.shape,dtype:o.dtype}}var uD={kernelName:Ko,backendName:"webgl",kernelFunc:Wt};function fo(r){let{inputs:e,backend:t}=r,{real:o,imag:n}=e,s=t.makeTensorInfo(o.shape,"complex64"),a=t.texData.get(s.dataId),i=Wt({inputs:{x:o},backend:t}),l=Wt({inputs:{x:n},backend:t});return a.complexTensorInfos={real:i,imag:l},s}var cD={kernelName:hc,backendName:"webgl",kernelFunc:fo};var Rk="return (a < 0.) ? b * a : a;",Fk=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function S6(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{alpha:s}=o,a=t.makeTensorInfo([],"float32",y.createScalarValue(s,"float32")),i=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new bs(Ck,n.shape,a.shape):new nn(vk,n.shape,a.shape),l=t.runWebGLProgram(i,[n,a],n.dtype);return t.disposeIntermediateTensorInfo(a),l}var DE={kernelName:Rn,backendName:"webgl",kernelFunc:S6};var Ik="return (a < 0.) ? b * a : a;",Nk=`
+`;function mX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{alpha:s}=o,a=t.makeTensorInfo([],"float32",y.createScalarValue(s,"float32")),i=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Cs(Fk,n.shape,a.shape):new cn(Rk,n.shape,a.shape),l=t.runWebGLProgram(i,[n,a],n.dtype);return t.disposeIntermediateTensorInfo(a),l}var pD={kernelName:Ln,backendName:"webgl",kernelFunc:mX};var Ok="return (a < 0.) ? b * a : a;",Pk=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function T6(r){let{inputs:e,backend:t}=r,{x:o,alpha:n}=e,s=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new bs(Nk,o.shape,n.shape):new nn(Ik,o.shape,n.shape);return t.runWebGLProgram(s,[o,n],o.dtype)}var $E={kernelName:Un,backendName:"webgl",kernelFunc:T6};var qg="if (isnan(x)) return x;",RE=`
+`;function fX(r){let{inputs:e,backend:t}=r,{x:o,alpha:n}=e,s=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Cs(Pk,o.shape,n.shape):new cn(Ok,o.shape,n.shape);return t.runWebGLProgram(s,[o,n],o.dtype)}var mD={kernelName:Yn,backendName:"webgl",kernelFunc:fX};var ox="if (isnan(x)) return x;",fD=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
-`,FE=`
+`,dD=`
   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;
-`;function _e({opSnippet:r,packedOpSnippet:e,cpuKernelImpl:t,dtype:o}){return({inputs:n,backend:s})=>{let{x:a}=n,i=s,l=o||a.dtype;if(i.shouldExecuteOnCPU([a])&&t!=null){let p=i.texData.get(a.dataId),m=t(p.values,l);return i.makeTensorInfo(a.shape,l,m)}let u=W().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&e!=null,c;return u?c=new ys(a.shape,e):c=new ao(a.shape,r),i.runWebGLProgram(c,[a],l)}}function nt({opSnippet:r,packedOpSnippet:e,checkOutOfBounds:t=!1,supportsComplex:o=!1,cpuKernelImpl:n,dtype:s}){return({inputs:a,backend:i})=>{let{a:l,b:u}=a,c=i;if(o&&l.dtype==="complex64"){let d=c.texData.get(l.dataId),h=c.texData.get(u.dataId),[g,x]=[[d.complexTensorInfos.real,h.complexTensorInfos.real],[d.complexTensorInfos.imag,h.complexTensorInfos.imag]].map(w=>{let[_,k]=w,D={dataId:_.dataId,dtype:_.dtype,shape:l.shape},T={dataId:k.dataId,dtype:k.dtype,shape:u.shape},R=new nn(r,l.shape,u.shape);return c.runWebGLProgram(R,[D,T],ir(_.dtype,k.dtype))}),b=lo({inputs:{real:g,imag:x},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(x),b}let p=s||ir(l.dtype,u.dtype);if(c.shouldExecuteOnCPU([l,u])&&n!=null){let d=c.texData.get(l.dataId),h=c.texData.get(u.dataId),[g,x]=n(l.shape,u.shape,d.values,h.values,p),b=c.makeTensorInfo(x,p),w=c.texData.get(b.dataId);return w.values=g,b}let m=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&e!=null,f;return m?f=new bs(e,l.shape,u.shape,t):f=new nn(r,l.shape,u.shape),c.runWebGLProgram(f,[l,u],p)}}function pl(r,e=!1){if(r==="linear")return e?CE:wE;if(r==="relu")return e?NE:kE;if(r==="elu")return e?IE:_E;if(r==="relu6")return e?SE:vE;if(r==="prelu")return e?Nk:Ik;if(r==="leakyrelu")return e?Ck:vk;throw new Error(`Activation ${r} has not been implemented for the WebGL backend.`)}var yf=class{constructor(e,t,o,n=!1,s=!1,a=!1,i=null,l=!1,u=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=o;let c=n?e[1]:e[2],p=Math.ceil(c/2),m=n?"i * 2, rc.y":"rc.y, i * 2",f=s?"rc.z, i * 2":"i * 2, rc.z",d=n?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],h=s?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],g="",x="";i&&(l?g=`vec4 activation(vec4 a) {
+`;function _e({opSnippet:r,packedOpSnippet:e,cpuKernelImpl:t,dtype:o}){return({inputs:n,backend:s})=>{let{x:a}=n,i=s,l=o||a.dtype;if(i.shouldExecuteOnCPU([a])&&t!=null){let p=i.texData.get(a.dataId),m=t(p.values,l);return i.makeTensorInfo(a.shape,l,m)}let u=W().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&e!=null,c;return u?c=new vs(a.shape,e):c=new mo(a.shape,r),i.runWebGLProgram(c,[a],l)}}function nt({opSnippet:r,packedOpSnippet:e,checkOutOfBounds:t=!1,supportsComplex:o=!1,cpuKernelImpl:n,dtype:s}){return({inputs:a,backend:i})=>{let{a:l,b:u}=a,c=i;if(o&&l.dtype==="complex64"){let d=c.texData.get(l.dataId),h=c.texData.get(u.dataId),[g,x]=[[d.complexTensorInfos.real,h.complexTensorInfos.real],[d.complexTensorInfos.imag,h.complexTensorInfos.imag]].map(w=>{let[_,k]=w,D={dataId:_.dataId,dtype:_.dtype,shape:l.shape},T={dataId:k.dataId,dtype:k.dtype,shape:u.shape},R=new cn(r,l.shape,u.shape);return c.runWebGLProgram(R,[D,T],ir(_.dtype,k.dtype))}),b=fo({inputs:{real:g,imag:x},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(x),b}let p=s||ir(l.dtype,u.dtype);if(c.shouldExecuteOnCPU([l,u])&&n!=null){let d=c.texData.get(l.dataId),h=c.texData.get(u.dataId),[g,x]=n(l.shape,u.shape,d.values,h.values,p),b=c.makeTensorInfo(x,p),w=c.texData.get(b.dataId);return w.values=g,b}let m=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&e!=null,f;return m?f=new Cs(e,l.shape,u.shape,t):f=new cn(r,l.shape,u.shape),c.runWebGLProgram(f,[l,u],p)}}function gl(r,e=!1){if(r==="linear")return e?nD:eD;if(r==="relu")return e?iD:rD;if(r==="elu")return e?sD:tD;if(r==="relu6")return e?aD:oD;if(r==="prelu")return e?Pk:Ok;if(r==="leakyrelu")return e?Fk:Rk;throw new Error(`Activation ${r} has not been implemented for the WebGL backend.`)}var Tf=class{constructor(e,t,o,n=!1,s=!1,a=!1,i=null,l=!1,u=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=o;let c=n?e[1]:e[2],p=Math.ceil(c/2),m=n?"i * 2, rc.y":"rc.y, i * 2",f=s?"rc.z, i * 2":"i * 2, rc.z",d=n?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],h=s?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],g="",x="";i&&(l?g=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${i}
         }`:u?g=`vec4 activation(vec4 a) {
@@ -1042,7 +1042,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};var Sk={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},Kg=class{constructor(e,t,o){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=N.assertAndGetBroadcastShape(t,o),this.userCode=`
+    `}};var Mk={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},nx=class{constructor(e,t,o){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=N.assertAndGetBroadcastShape(t,o),this.userCode=`
       float binaryOpComplex(
           float areal, float aimag, float breal, float bimag) {
         ${e}
@@ -1055,7 +1055,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float bimag = getBImagAtOutCoords();
         setOutput(binaryOpComplex(areal, aimag, breal, bimag));
       }
-    `}};var OE="return a * b;";function Tk(r){let{inputs:e,backend:t}=r,{a:o,b:n}=e,s=N.upcastType(o.dtype,n.dtype);if(o.dtype==="complex64"){let i=t.texData.get(o.dataId),l=t.texData.get(n.dataId),u=new Kg(Sk.REAL,o.shape,n.shape),c=new Kg(Sk.IMAG,o.shape,n.shape),p=[{dataId:i.complexTensorInfos.real.dataId,dtype:i.complexTensorInfos.real.dtype,shape:o.shape},{dataId:i.complexTensorInfos.imag.dataId,dtype:i.complexTensorInfos.imag.dtype,shape:o.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:n.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:n.shape}],m=t.runWebGLProgram(u,p,"float32"),f=t.runWebGLProgram(c,p,"float32"),d=lo({inputs:{real:m,imag:f},backend:t});return t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(f),d}if(t.shouldExecuteOnCPU([o,n])){let i=t.texData.get(o.dataId),l=t.texData.get(n.dataId),[u,c]=sE(o.shape,n.shape,i.values,l.values,s),p=t.makeTensorInfo(c,s),m=t.texData.get(p.dataId);return m.values=u,p}let a;return W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?a=new bs(OE,o.shape,n.shape):a=new nn(OE,o.shape,n.shape),t.runWebGLProgram(a,[o,n],s)}var PE={kernelName:Vn,backendName:"webgl",kernelFunc:Tk};function ME(r,e,t){let o=[ba(r.shape),...wa(r.shape)],n={dtype:r.dtype,shape:o,dataId:r.dataId},s=[ba(e),...wa(e)],a=new gf(s,o),i=!0,l=t.runWebGLProgram(a,[n],r.dtype,null,i);return{dataId:l.dataId,shape:e,dtype:l.dtype}}function pe(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{shape:s}=o,a=t,i=y.sizeFromShape(n.shape),l=y.inferFromImplicitShape(s,i),u=y.sizeFromShape(l);y.assert(i===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${n.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`);let c=a.texData.get(n.dataId);return c.isPacked&&!ul(n.shape,l)&&!(c.texture!==null&&ul(c.shape,l))?ME(n,l,a):(a.incRef(n.dataId),{dataId:n.dataId,shape:l,dtype:n.dtype})}var LE={kernelName:Ms,backendName:"webgl",kernelFunc:pe};var Xg=class{constructor(e,t){this.variableNames=["x"];let{windowSize:o,batchSize:n,inSize:s,outSize:a}=e;this.outputShape=[n,a];let i=Math.floor(o/4)*4,l=o%4,u="sumValue += dot(values, ones);";if(t!=null){let p=1/t;u=`sumValue += dot(values * ${y.isInt(p)?p.toPrecision(2):p}, ones);`}let c="";s%o>0&&(c=`
+    `}};var hD="return a * b;";function Lk(r){let{inputs:e,backend:t}=r,{a:o,b:n}=e,s=N.upcastType(o.dtype,n.dtype);if(o.dtype==="complex64"){let i=t.texData.get(o.dataId),l=t.texData.get(n.dataId),u=new nx(Mk.REAL,o.shape,n.shape),c=new nx(Mk.IMAG,o.shape,n.shape),p=[{dataId:i.complexTensorInfos.real.dataId,dtype:i.complexTensorInfos.real.dtype,shape:o.shape},{dataId:i.complexTensorInfos.imag.dataId,dtype:i.complexTensorInfos.imag.dtype,shape:o.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:n.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:n.shape}],m=t.runWebGLProgram(u,p,"float32"),f=t.runWebGLProgram(c,p,"float32"),d=fo({inputs:{real:m,imag:f},backend:t});return t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(f),d}if(t.shouldExecuteOnCPU([o,n])){let i=t.texData.get(o.dataId),l=t.texData.get(n.dataId),[u,c]=z2(o.shape,n.shape,i.values,l.values,s),p=t.makeTensorInfo(c,s),m=t.texData.get(p.dataId);return m.values=u,p}let a;return W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?a=new Cs(hD,o.shape,n.shape):a=new cn(hD,o.shape,n.shape),t.runWebGLProgram(a,[o,n],s)}var gD={kernelName:Hn,backendName:"webgl",kernelFunc:Lk};function xD(r,e,t){let o=[Ca(r.shape),...Ia(r.shape)],n={dtype:r.dtype,shape:o,dataId:r.dataId},s=[Ca(e),...Ia(e)],a=new Nf(s,o),i=!0,l=t.runWebGLProgram(a,[n],r.dtype,null,i);return{dataId:l.dataId,shape:e,dtype:l.dtype}}function pe(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{shape:s}=o,a=t,i=y.sizeFromShape(n.shape),l=y.inferFromImplicitShape(s,i),u=y.sizeFromShape(l);y.assert(i===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${n.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`);let c=a.texData.get(n.dataId);return c.isPacked&&!dl(n.shape,l)&&!(c.texture!==null&&dl(c.shape,l))?xD(n,l,a):(a.incRef(n.dataId),{dataId:n.dataId,shape:l,dtype:n.dtype})}var yD={kernelName:Gs,backendName:"webgl",kernelFunc:pe};var sx=class{constructor(e,t){this.variableNames=["x"];let{windowSize:o,batchSize:n,inSize:s,outSize:a}=e;this.outputShape=[n,a];let i=Math.floor(o/4)*4,l=o%4,u="sumValue += dot(values, ones);";if(t!=null){let p=1/t;u=`sumValue += dot(values * ${y.isInt(p)?p.toPrecision(2):p}, ones);`}let c="";s%o>0&&(c=`
         if (inIdx < 0 || inIdx >= ${s}) {
           return 0.0;
         }
@@ -1108,7 +1108,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(sumValue);
       }
-    `}};var Ak=class{constructor(e,t){this.variableNames=["x"];let{windowSize:o,batchSize:n,inSize:s,outSize:a}=e;this.outputShape=[n,a];let i="0.0",l="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",l="min"):t==="max"&&(i="-1.0 / 1e-20",l="max");let u=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?u="sumValue":t==="prod"?u="prodValue":t==="all"?u="allValue":t==="any"&&(u="anyValue");let c=Math.floor(o/4)*4,p=o%4,m=`
+    `}};var zk=class{constructor(e,t){this.variableNames=["x"];let{windowSize:o,batchSize:n,inSize:s,outSize:a}=e;this.outputShape=[n,a];let i="0.0",l="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",l="min"):t==="max"&&(i="-1.0 / 1e-20",l="max");let u=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?u="sumValue":t==="prod"?u="prodValue":t==="all"?u="allValue":t==="any"&&(u="anyValue");let c=Math.floor(o/4)*4,p=o%4,m=`
       if (${t==="sum"}) {
         sumValue += dot(values, ones);
       } else if (${t==="prod"}) {
@@ -1193,12 +1193,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(${u});
       }
-    `}};function A6(r){let e=[];for(;e.length===0||e[e.length-1].outSize!==1;){let t=e.length?e[e.length-1].outSize:r[1],o=N.computeOptimalWindowSize(t);e.push({inSize:t,windowSize:o,outSize:Math.ceil(t/o)})}return e}function vo(r,e,t,o){let n=A6(r.shape),s=r;for(let a=0;a<n.length;a++){let{inSize:i,windowSize:l,outSize:u}=n[a],c,p;t==="mean"?c=a===0?new Xg({windowSize:l,inSize:i,batchSize:r.shape[0],outSize:u},i):new Xg({windowSize:l,inSize:i,batchSize:r.shape[0],outSize:u}):c=new Ak({windowSize:l,inSize:i,batchSize:r.shape[0],outSize:u},t),p=s,s=o.runWebGLProgram(c,[s],e),p.dataId!==r.dataId&&o.disposeIntermediateTensorInfo(p)}return s}var Ek=class{constructor(e,t){this.variableNames=["A"];let o=new Array(e.length);for(let a=0;a<o.length;a++)o[a]=e[t[a]];this.outputShape=o,this.rank=o.length;let n=Le(this.rank),s=E6(t);this.userCode=`
+    `}};function dX(r){let e=[];for(;e.length===0||e[e.length-1].outSize!==1;){let t=e.length?e[e.length-1].outSize:r[1],o=N.computeOptimalWindowSize(t);e.push({inSize:t,windowSize:o,outSize:Math.ceil(t/o)})}return e}function To(r,e,t,o){let n=dX(r.shape),s=r;for(let a=0;a<n.length;a++){let{inSize:i,windowSize:l,outSize:u}=n[a],c,p;t==="mean"?c=a===0?new sx({windowSize:l,inSize:i,batchSize:r.shape[0],outSize:u},i):new sx({windowSize:l,inSize:i,batchSize:r.shape[0],outSize:u}):c=new zk({windowSize:l,inSize:i,batchSize:r.shape[0],outSize:u},t),p=s,s=o.runWebGLProgram(c,[s],e),p.dataId!==r.dataId&&o.disposeIntermediateTensorInfo(p)}return s}var Bk=class{constructor(e,t){this.variableNames=["A"];let o=new Array(e.length);for(let a=0;a<o.length;a++)o[a]=e[t[a]];this.outputShape=o,this.rank=o.length;let n=Le(this.rank),s=hX(t);this.userCode=`
     void main() {
       ${n} resRC = getOutputCoords();
       setOutput(getA(${s}));
     }
-    `}};function E6(r){let e=r.length;if(e>6)throw Error(`Transpose for rank ${e} is not yet supported`);let t=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],o=new Array(e);for(let n=0;n<r.length;n++)o[r[n]]=t[n];return o.join()}var Dk=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let o=new Array(e.length);for(let c=0;c<o.length;c++)o[c]=e[t[c]];if(this.outputShape=o,this.rank=o.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let n=Le(this.rank),s=xk("rc",this.rank),a=new Array(this.rank);for(let c=0;c<t.length;c++)a[t[c]]=s[c];let i=`vec2(${a.slice(-2).join()})`,l=`++${s[this.rank-1]} < ${o[this.rank-1]}`,u=`getChannel(getA(${a.join()}), ${i})`;this.userCode=`
+    `}};function hX(r){let e=r.length;if(e>6)throw Error(`Transpose for rank ${e} is not yet supported`);let t=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],o=new Array(e);for(let n=0;n<r.length;n++)o[r[n]]=t[n];return o.join()}var Vk=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let o=new Array(e.length);for(let c=0;c<o.length;c++)o[c]=e[t[c]];if(this.outputShape=o,this.rank=o.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let n=Le(this.rank),s=Sk("rc",this.rank),a=new Array(this.rank);for(let c=0;c<t.length;c++)a[t[c]]=s[c];let i=`vec2(${a.slice(-2).join()})`,l=`++${s[this.rank-1]} < ${o[this.rank-1]}`,u=`getChannel(getA(${a.join()}), ${i})`;this.userCode=`
     void main() {
       ${n} rc = getOutputCoords();
       vec4 result = vec4(0.);
@@ -1215,14 +1215,14 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       }
       setOutput(result);
     }
-    `}};function ml(r,e,t){let o=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Dk(r.shape,e):new Ek(r.shape,e);return t.runWebGLProgram(o,[r],r.dtype)}function zE(r,e,t,o){let n=e,s=r.shape.length,a=y.parseAxisParam(n,r.shape),i=a,l=N.getAxesPermutation(i,s),u=l!=null,c=r;u&&(c=ml(r,l,o),i=N.getInnerMostAxes(i.length,s)),N.assertAxesAreInnerMostDims("sum",i,s);let[p,m]=N.computeOutAndReduceShapes(c.shape,i),f=p;t&&(f=N.expandShapeToKeepDim(p,a));let d=y.sizeFromShape(m),g=y.sizeFromShape(r.shape)/d,x=pe({inputs:{x:c},attrs:{shape:[g,d]},backend:o}),b=Pl(r.dtype),w=vo(x,b,"sum",o),_=pe({inputs:{x:w},attrs:{shape:f},backend:o});return o.disposeIntermediateTensorInfo(x),o.disposeIntermediateTensorInfo(w),u&&o.disposeIntermediateTensorInfo(c),_}function bf(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o;return zE(n,s,a,t)}var BE={kernelName:ts,backendName:"webgl",kernelFunc:bf};function Mt(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{perm:s}=o,a=t,i=n.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=n.shape[s[c]];let u;if(a.shouldExecuteOnCPU([n])){let p=a.texData.get(n.dataId).values,m=ku(p,n.shape,n.dtype,s,l);u=a.makeTensorInfo(l,n.dtype);let f=a.texData.get(u.dataId);f.values=m}else u=ml(n,s,a);return u}var VE={kernelName:is,backendName:"webgl",kernelFunc:Mt};var $k=1e3;function vu({a:r,b:e,transposeA:t,transposeB:o,backend:n,bias:s=null,preluActivationWeights:a=null,leakyreluAlpha:i=0,activation:l=null}){let u=r.shape.length,c=e.shape.length,p=t?r.shape[u-2]:r.shape[u-1],m=o?e.shape[c-1]:e.shape[c-2],f=t?r.shape[u-1]:r.shape[u-2],d=o?e.shape[c-2]:e.shape[c-1],h=r.shape.slice(0,-2),g=e.shape.slice(0,-2),x=y.sizeFromShape(h),b=y.sizeFromShape(g),w=x===b||x===1||b===1;y.assert(u>=2&&c>=2&&w,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${h}) and (${g}).`);let k=(x>b?r.shape.slice(0,-2):e.shape.slice(0,-2)).concat([f,d]);y.assert(p===m,()=>`Error in matMul: inner shapes (${p}) and (${m}) of Tensors with shapes ${r.shape} and ${e.shape} and transposeA=${t} and transposeB=${o} must match.`);let D=t?[x,p,f]:[x,f,p],T=o?[b,d,m]:[b,m,d],R=pe({inputs:{x:r},backend:n,attrs:{shape:D}}),O=pe({inputs:{x:e},backend:n,attrs:{shape:T}}),M=[R,O],G=Math.max(x,b),j=t?R.shape[1]:R.shape[2],U=s!=null,H=a!=null,q=l==="leakyrelu",X=l!=null?pl(l,!0):null,oe=U||H||q||X!=null,Y;if((f===1||d===1)&&j>$k&&oe===!1){let J=R,ie=O;t&&(J=Mt({inputs:{x:R},backend:n,attrs:{perm:[0,2,1]}}),M.push(J)),o&&(ie=Mt({inputs:{x:O},backend:n,attrs:{perm:[0,2,1]}}),M.push(ie));let ue=d!==1,ae=d===1,fe=J;ue&&(fe=pe({inputs:{x:J},backend:n,attrs:{shape:[G,j,1]}}),M.push(fe));let de=d===1?2:1,xe=ie;ae&&(xe=pe({inputs:{x:ie},backend:n,attrs:{shape:[G,1,j]}}),M.push(xe));let we=Tk({inputs:{a:fe,b:xe},backend:n});Y=bf({inputs:{x:we},backend:n,attrs:{axis:de,keepDims:!0}}),M.push(we)}else{let J=ir(r.dtype,e.dtype),ie=new yf(D,T,[G,f,d],t,o,U,X,H,q),ue=[R,O];if(s!=null&&ue.push(s),H&&ue.push(a),q){let ae=n.makeTensorInfo([],"float32",y.createScalarValue(i,"float32"));ue.push(ae),M.push(ae)}Y=n.runWebGLProgram(ie,ue,J)}let re=pe({inputs:{x:Y},backend:n,attrs:{shape:k}});M.push(Y);for(let J of M)n.disposeIntermediateTensorInfo(J);return re}function D6(r){let{inputs:e,backend:t,attrs:o}=r,{a:n,b:s,bias:a,preluActivationWeights:i}=e,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=o;return vu({a:n,b:s,transposeA:l,transposeB:u,backend:t,bias:a,preluActivationWeights:i,leakyreluAlpha:p,activation:c})}var GE={kernelName:Ws,backendName:"webgl",kernelFunc:D6};var WE="return abs(x);";function $6(r){let{inputs:e,backend:t}=r,{x:o}=e;if(t.shouldExecuteOnCPU([o])&&o.dtype!=="complex64"){let s=t.texData.get(o.dataId),a=jg(s.values);return t.makeTensorInfo(o.shape,o.dtype,a)}let n;return W().getBool("WEBGL_PACK_UNARY_OPERATIONS")?n=new ys(o.shape,WE):n=new ao(o.shape,WE),t.runWebGLProgram(n,[o],o.dtype)}var jE={kernelName:Es,backendName:"webgl",kernelFunc:$6};var R6=gr+`
+    `}};function xl(r,e,t){let o=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Vk(r.shape,e):new Bk(r.shape,e);return t.runWebGLProgram(o,[r],r.dtype)}function bD(r,e,t,o){let n=e,s=r.shape.length,a=y.parseAxisParam(n,r.shape),i=a,l=N.getAxesPermutation(i,s),u=l!=null,c=r;u&&(c=xl(r,l,o),i=N.getInnerMostAxes(i.length,s)),N.assertAxesAreInnerMostDims("sum",i,s);let[p,m]=N.computeOutAndReduceShapes(c.shape,i),f=p;t&&(f=N.expandShapeToKeepDim(p,a));let d=y.sizeFromShape(m),g=y.sizeFromShape(r.shape)/d,x=pe({inputs:{x:c},attrs:{shape:[g,d]},backend:o}),b=Vl(r.dtype),w=To(x,b,"sum",o),_=pe({inputs:{x:w},attrs:{shape:f},backend:o});return o.disposeIntermediateTensorInfo(x),o.disposeIntermediateTensorInfo(w),u&&o.disposeIntermediateTensorInfo(c),_}function Af(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o;return bD(n,s,a,t)}var wD={kernelName:is,backendName:"webgl",kernelFunc:Af};function Mt(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{perm:s}=o,a=t,i=n.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=n.shape[s[c]];let u;if(a.shouldExecuteOnCPU([n])){let p=a.texData.get(n.dataId).values,m=Su(p,n.shape,n.dtype,s,l);u=a.makeTensorInfo(l,n.dtype);let f=a.texData.get(u.dataId);f.values=m}else u=xl(n,s,a);return u}var _D={kernelName:ps,backendName:"webgl",kernelFunc:Mt};var Gk=1e3;function Tu({a:r,b:e,transposeA:t,transposeB:o,backend:n,bias:s=null,preluActivationWeights:a=null,leakyreluAlpha:i=0,activation:l=null}){let u=r.shape.length,c=e.shape.length,p=t?r.shape[u-2]:r.shape[u-1],m=o?e.shape[c-1]:e.shape[c-2],f=t?r.shape[u-1]:r.shape[u-2],d=o?e.shape[c-2]:e.shape[c-1],h=r.shape.slice(0,-2),g=e.shape.slice(0,-2),x=y.sizeFromShape(h),b=y.sizeFromShape(g),w=x===b||x===1||b===1;y.assert(u>=2&&c>=2&&w,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${h}) and (${g}).`);let k=(x>b?r.shape.slice(0,-2):e.shape.slice(0,-2)).concat([f,d]);y.assert(p===m,()=>`Error in matMul: inner shapes (${p}) and (${m}) of Tensors with shapes ${r.shape} and ${e.shape} and transposeA=${t} and transposeB=${o} must match.`);let D=t?[x,p,f]:[x,f,p],T=o?[b,d,m]:[b,m,d],R=pe({inputs:{x:r},backend:n,attrs:{shape:D}}),O=pe({inputs:{x:e},backend:n,attrs:{shape:T}}),M=[R,O],G=Math.max(x,b),j=t?R.shape[1]:R.shape[2],U=s!=null,H=a!=null,q=l==="leakyrelu",X=l!=null?gl(l,!0):null,oe=U||H||q||X!=null,Y;if((f===1||d===1)&&j>Gk&&oe===!1){let J=R,ie=O;t&&(J=Mt({inputs:{x:R},backend:n,attrs:{perm:[0,2,1]}}),M.push(J)),o&&(ie=Mt({inputs:{x:O},backend:n,attrs:{perm:[0,2,1]}}),M.push(ie));let ue=d!==1,ae=d===1,fe=J;ue&&(fe=pe({inputs:{x:J},backend:n,attrs:{shape:[G,j,1]}}),M.push(fe));let de=d===1?2:1,xe=ie;ae&&(xe=pe({inputs:{x:ie},backend:n,attrs:{shape:[G,1,j]}}),M.push(xe));let we=Lk({inputs:{a:fe,b:xe},backend:n});Y=Af({inputs:{x:we},backend:n,attrs:{axis:de,keepDims:!0}}),M.push(we)}else{let J=ir(r.dtype,e.dtype),ie=new Tf(D,T,[G,f,d],t,o,U,X,H,q),ue=[R,O];if(s!=null&&ue.push(s),H&&ue.push(a),q){let ae=n.makeTensorInfo([],"float32",y.createScalarValue(i,"float32"));ue.push(ae),M.push(ae)}Y=n.runWebGLProgram(ie,ue,J)}let re=pe({inputs:{x:Y},backend:n,attrs:{shape:k}});M.push(Y);for(let J of M)n.disposeIntermediateTensorInfo(J);return re}function gX(r){let{inputs:e,backend:t,attrs:o}=r,{a:n,b:s,bias:a,preluActivationWeights:i}=e,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=o;return Tu({a:n,b:s,transposeA:l,transposeB:u,backend:t,bias:a,preluActivationWeights:i,leakyreluAlpha:p,activation:c})}var kD={kernelName:Ks,backendName:"webgl",kernelFunc:gX};var vD="return abs(x);";function xX(r){let{inputs:e,backend:t}=r,{x:o}=e;if(t.shouldExecuteOnCPU([o])&&o.dtype!=="complex64"){let s=t.texData.get(o.dataId),a=ex(s.values);return t.makeTensorInfo(o.shape,o.dtype,a)}let n;return W().getBool("WEBGL_PACK_UNARY_OPERATIONS")?n=new vs(o.shape,vD):n=new mo(o.shape,vD),t.runWebGLProgram(n,[o],o.dtype)}var CD={kernelName:Os,backendName:"webgl",kernelFunc:xX};var yX=gr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return acos(x);
-`,F6=_e({opSnippet:R6}),UE={kernelName:fi,backendName:"webgl",kernelFunc:F6};var O6=gr+`
+`,bX=_e({opSnippet:yX}),ID={kernelName:yi,backendName:"webgl",kernelFunc:bX};var wX=gr+`
   if (x < 1.0) return NAN;
-return log(x + sqrt(x * x - 1.0));`,P6=_e({opSnippet:O6}),HE={kernelName:di,backendName:"webgl",kernelFunc:P6};var qE="return a + b;",M6=nt({opSnippet:qE,packedOpSnippet:qE,supportsComplex:!0,cpuKernelImpl:jA}),KE={kernelName:Ao,backendName:"webgl",kernelFunc:M6};var Rk=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((s,a)=>`T${a}`);let o=[];this.variableNames.forEach(s=>{o.push(`float v${s} = get${s}AtOutCoords();`)});let n=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
+return log(x + sqrt(x * x - 1.0));`,_X=_e({opSnippet:wX}),ND={kernelName:bi,backendName:"webgl",kernelFunc:_X};var SD="return a + b;",kX=nt({opSnippet:SD,packedOpSnippet:SD,supportsComplex:!0,cpuKernelImpl:C2}),TD={kernelName:Fo,backendName:"webgl",kernelFunc:kX};var Wk=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((s,a)=>`T${a}`);let o=[];this.variableNames.forEach(s=>{o.push(`float v${s} = get${s}AtOutCoords();`)});let n=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
       void main() {
         ${o.join(`
         `)}
@@ -1230,7 +1230,7 @@ return log(x + sqrt(x * x - 1.0));`,P6=_e({opSnippet:O6}),HE={kernelName:di,back
         float result = ${n};
         setOutput(result);
       }
-    `}};var Fk=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((s,a)=>`T${a}`);let o=[];this.variableNames.forEach(s=>{o.push(`vec4 v${s} = get${s}AtOutCoords();`)});let n=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
+    `}};var jk=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((s,a)=>`T${a}`);let o=[];this.variableNames.forEach(s=>{o.push(`vec4 v${s} = get${s}AtOutCoords();`)});let n=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
       void main() {
         ${o.join(`
         `)}
@@ -1238,7 +1238,7 @@ return log(x + sqrt(x * x - 1.0));`,P6=_e({opSnippet:O6}),HE={kernelName:di,back
         vec4 result = ${n};
         setOutput(result);
       }
-    `}};function Yg(r){let{inputs:e,backend:t}=r,o=e;if(o.length===1)return Wt({inputs:{x:o[0]},backend:t});if(o.length>W().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let l=Math.floor(o.length/2),u=Yg({inputs:o.slice(0,l),backend:t}),c=Yg({inputs:o.slice(l),backend:t});return Yg({inputs:[u,c],backend:t})}let n=o.map(l=>l.dtype).reduce((l,u)=>ir(l,u)),s=o.map(l=>l.shape),i=W().getBool("WEBGL_PACK")?new Fk(o[0].shape,s):new Rk(o[0].shape,s);return t.runWebGLProgram(i,o,n)}var XE={kernelName:xn,backendName:"webgl",kernelFunc:Yg};function L6(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,l=y.parseAxisParam(s,n.shape),u=l,c=N.getAxesPermutation(u,i),p=n;c!=null&&(p=Mt({inputs:{x:n},backend:t,attrs:{perm:c}}),u=N.getInnerMostAxes(u.length,i)),N.assertAxesAreInnerMostDims("all",u,i);let[m,f]=N.computeOutAndReduceShapes(p.shape,u),d=y.sizeFromShape(f),h=pe({inputs:{x:p},backend:t,attrs:{shape:[-1,d]}}),g=vo(h,h.dtype,"all",t),x;if(a){let b=N.expandShapeToKeepDim(m,l);x=pe({inputs:{x:g},backend:t,attrs:{shape:b}})}else x=pe({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(p),x}var YE={kernelName:sc,backendName:"webgl",kernelFunc:L6};function z6(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,l=y.parseAxisParam(s,n.shape),u=l,c=N.getAxesPermutation(u,i),p=n;c!=null&&(p=Mt({inputs:{x:n},backend:t,attrs:{perm:c}}),u=N.getInnerMostAxes(u.length,i)),N.assertAxesAreInnerMostDims("any",u,i);let[m,f]=N.computeOutAndReduceShapes(p.shape,u),d=y.sizeFromShape(f),h=pe({inputs:{x:p},backend:t,attrs:{shape:[-1,d]}}),g=vo(h,h.dtype,"any",t),x;if(a){let b=N.expandShapeToKeepDim(m,l);x=pe({inputs:{x:g},backend:t,attrs:{shape:b}})}else x=pe({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(p),x}var ZE={kernelName:ic,backendName:"webgl",kernelFunc:z6};var Ok=class{constructor(e,t,o){this.variableNames=["A"];let{windowSize:n,batchSize:s,outSize:a}=e;o||this.variableNames.push("bestIndicesA"),this.outputShape=[s,a];let i=t==="max"?">":"<",l=o?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
+    `}};function ix(r){let{inputs:e,backend:t}=r,o=e;if(o.length===1)return Wt({inputs:{x:o[0]},backend:t});if(o.length>W().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let l=Math.floor(o.length/2),u=ix({inputs:o.slice(0,l),backend:t}),c=ix({inputs:o.slice(l),backend:t});return ix({inputs:[u,c],backend:t})}let n=o.map(l=>l.dtype).reduce((l,u)=>ir(l,u)),s=o.map(l=>l.shape),i=W().getBool("WEBGL_PACK")?new jk(o[0].shape,s):new Wk(o[0].shape,s);return t.runWebGLProgram(i,o,n)}var AD={kernelName:kn,backendName:"webgl",kernelFunc:ix};function vX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,l=y.parseAxisParam(s,n.shape),u=l,c=N.getAxesPermutation(u,i),p=n;c!=null&&(p=Mt({inputs:{x:n},backend:t,attrs:{perm:c}}),u=N.getInnerMostAxes(u.length,i)),N.assertAxesAreInnerMostDims("all",u,i);let[m,f]=N.computeOutAndReduceShapes(p.shape,u),d=y.sizeFromShape(f),h=pe({inputs:{x:p},backend:t,attrs:{shape:[-1,d]}}),g=To(h,h.dtype,"all",t),x;if(a){let b=N.expandShapeToKeepDim(m,l);x=pe({inputs:{x:g},backend:t,attrs:{shape:b}})}else x=pe({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(p),x}var ED={kernelName:cc,backendName:"webgl",kernelFunc:vX};function CX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,l=y.parseAxisParam(s,n.shape),u=l,c=N.getAxesPermutation(u,i),p=n;c!=null&&(p=Mt({inputs:{x:n},backend:t,attrs:{perm:c}}),u=N.getInnerMostAxes(u.length,i)),N.assertAxesAreInnerMostDims("any",u,i);let[m,f]=N.computeOutAndReduceShapes(p.shape,u),d=y.sizeFromShape(f),h=pe({inputs:{x:p},backend:t,attrs:{shape:[-1,d]}}),g=To(h,h.dtype,"any",t),x;if(a){let b=N.expandShapeToKeepDim(m,l);x=pe({inputs:{x:g},backend:t,attrs:{shape:b}})}else x=pe({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(p),x}var DD={kernelName:pc,backendName:"webgl",kernelFunc:CX};var Uk=class{constructor(e,t,o){this.variableNames=["A"];let{windowSize:n,batchSize:s,outSize:a}=e;o||this.variableNames.push("bestIndicesA"),this.outputShape=[s,a];let i=t==="max"?">":"<",l=o?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
@@ -1258,7 +1258,7 @@ return log(x + sqrt(x * x - 1.0));`,P6=_e({opSnippet:O6}),HE={kernelName:di,back
         }
         setOutput(float(bestIndex));
       }
-    `}};var Pk=class{constructor(e,t,o,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,y.assert(e.length>2,()=>`Packed arg${o.charAt(0).toUpperCase()+o.slice(1)} supports only inputs with rank above 2.`);let s=e[e.length-1],a=Math.ceil(s/t);this.outputShape=e.slice(0,-1),a>1&&this.outputShape.push(a),n||this.variableNames.push("bestIndicesA");let i=this.outputShape,l=i.length,u=Le(l),c=Gt("coords",l),p,m;if(a===1){m=l+1;let R=Le(m);p=`
+    `}};var Hk=class{constructor(e,t,o,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,y.assert(e.length>2,()=>`Packed arg${o.charAt(0).toUpperCase()+o.slice(1)} supports only inputs with rank above 2.`);let s=e[e.length-1],a=Math.ceil(s/t);this.outputShape=e.slice(0,-1),a>1&&this.outputShape.push(a),n||this.variableNames.push("bestIndicesA");let i=this.outputShape,l=i.length,u=Le(l),c=Gt("coords",l),p,m;if(a===1){m=l+1;let R=Le(m);p=`
         ${R} sourceLocR = ${R}(${c.join()}, 0);
         ++${c[l-1]};
         ${R} sourceLocG = ${R}(${c.join()}, 0);
@@ -1320,23 +1320,23 @@ return log(x + sqrt(x * x - 1.0));`,P6=_e({opSnippet:O6}),HE={kernelName:di,back
         }
         setOutput(bestIndex);
       }
-    `}};function JE(r,e,t,o=null){let n=e.shape[0],s=e.shape[1];o!=null&&(n=o.shape[0],s=o.shape[1]);let a=N.computeOptimalWindowSize(s),i={windowSize:a,inSize:s,batchSize:n,outSize:Math.ceil(s/a)},l=new Ok(i,t,o==null),u=[e];o!=null&&u.push(o);let c=r.runWebGLProgram(l,u,"int32");if(c.shape[1]===1)return c;let p=JE(r,e,t,c);return r.disposeIntermediateTensorInfo(c),p}function QE(r,e,t,o=null){let n=o!=null?o.shape:e.shape,s=n[n.length-1],a=N.computeOptimalWindowSize(s),i=new Pk(n,a,t,o==null),l=o==null?[e]:[e,o],u=r.runWebGLProgram(i,l,"int32");if(u.shape.length===e.shape.length){let c=QE(r,e,t,u);return r.disposeIntermediateTensorInfo(u),c}return u}function Zg(r,e,t,o){let n=[t];if(N.assertAxesAreInnerMostDims("arg"+o.charAt(0).toUpperCase()+o.slice(1),n,e.shape.length),!W().getBool("WEBGL_PACK_REDUCE")||e.shape.length<=2){let s=[],[a,i]=N.computeOutAndReduceShapes(e.shape,n),l=y.sizeFromShape(i),u=pe({inputs:{x:e},backend:r,attrs:{shape:[-1,l]}});s.push(u);let c=JE(r,u,o);s.push(c);let p=pe({inputs:{x:c},backend:r,attrs:{shape:a}});return s.forEach(m=>r.disposeIntermediateTensorInfo(m)),p}return QE(r,e,o)}function B6(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s}=o,a=y.parseAxisParam(s,n.shape),i=N.getAxesPermutation(a,n.shape.length),l=n,u=[];i!=null&&(l=Mt({inputs:{x:n},backend:t,attrs:{perm:i}}),u.push(l),a=N.getInnerMostAxes(a.length,l.shape.length)),N.assertAxesAreInnerMostDims("argMax",[a[0]],l.shape.length);let c=Zg(t,l,a[0],"max");return u.forEach(p=>t.disposeIntermediateTensorInfo(p)),c}var e2={kernelName:yn,backendName:"webgl",kernelFunc:B6};function V6(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s}=o,a=y.parseAxisParam(s,n.shape),i=N.getAxesPermutation(a,n.shape.length),l=n,u=[];i!=null&&(l=Mt({inputs:{x:n},backend:t,attrs:{perm:i}}),u.push(l),a=N.getInnerMostAxes(a.length,l.shape.length)),N.assertAxesAreInnerMostDims("argMin",[a[0]],l.shape.length);let c=Zg(t,l,a[0],"min");return u.forEach(p=>t.disposeIntermediateTensorInfo(p)),c}var t2={kernelName:Ma,backendName:"webgl",kernelFunc:V6};var G6=gr+`
+    `}};function $D(r,e,t,o=null){let n=e.shape[0],s=e.shape[1];o!=null&&(n=o.shape[0],s=o.shape[1]);let a=N.computeOptimalWindowSize(s),i={windowSize:a,inSize:s,batchSize:n,outSize:Math.ceil(s/a)},l=new Uk(i,t,o==null),u=[e];o!=null&&u.push(o);let c=r.runWebGLProgram(l,u,"int32");if(c.shape[1]===1)return c;let p=$D(r,e,t,c);return r.disposeIntermediateTensorInfo(c),p}function RD(r,e,t,o=null){let n=o!=null?o.shape:e.shape,s=n[n.length-1],a=N.computeOptimalWindowSize(s),i=new Hk(n,a,t,o==null),l=o==null?[e]:[e,o],u=r.runWebGLProgram(i,l,"int32");if(u.shape.length===e.shape.length){let c=RD(r,e,t,u);return r.disposeIntermediateTensorInfo(u),c}return u}function ax(r,e,t,o){let n=[t];if(N.assertAxesAreInnerMostDims("arg"+o.charAt(0).toUpperCase()+o.slice(1),n,e.shape.length),!W().getBool("WEBGL_PACK_REDUCE")||e.shape.length<=2){let s=[],[a,i]=N.computeOutAndReduceShapes(e.shape,n),l=y.sizeFromShape(i),u=pe({inputs:{x:e},backend:r,attrs:{shape:[-1,l]}});s.push(u);let c=$D(r,u,o);s.push(c);let p=pe({inputs:{x:c},backend:r,attrs:{shape:a}});return s.forEach(m=>r.disposeIntermediateTensorInfo(m)),p}return RD(r,e,o)}function IX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s}=o,a=y.parseAxisParam(s,n.shape),i=N.getAxesPermutation(a,n.shape.length),l=n,u=[];i!=null&&(l=Mt({inputs:{x:n},backend:t,attrs:{perm:i}}),u.push(l),a=N.getInnerMostAxes(a.length,l.shape.length)),N.assertAxesAreInnerMostDims("argMax",[a[0]],l.shape.length);let c=ax(t,l,a[0],"max");return u.forEach(p=>t.disposeIntermediateTensorInfo(p)),c}var FD={kernelName:vn,backendName:"webgl",kernelFunc:IX};function NX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s}=o,a=y.parseAxisParam(s,n.shape),i=N.getAxesPermutation(a,n.shape.length),l=n,u=[];i!=null&&(l=Mt({inputs:{x:n},backend:t,attrs:{perm:i}}),u.push(l),a=N.getInnerMostAxes(a.length,l.shape.length)),N.assertAxesAreInnerMostDims("argMin",[a[0]],l.shape.length);let c=ax(t,l,a[0],"min");return u.forEach(p=>t.disposeIntermediateTensorInfo(p)),c}var OD={kernelName:Ga,backendName:"webgl",kernelFunc:NX};var SX=gr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return asin(x);
-`,W6=_e({opSnippet:G6}),r2={kernelName:hi,backendName:"webgl",kernelFunc:W6};var j6=gr+"return log(x + sqrt(x * x + 1.0));",U6=_e({opSnippet:j6}),o2={kernelName:gi,backendName:"webgl",kernelFunc:U6};var H6=gr+`
+`,TX=_e({opSnippet:SX}),PD={kernelName:wi,backendName:"webgl",kernelFunc:TX};var AX=gr+"return log(x + sqrt(x * x + 1.0));",EX=_e({opSnippet:AX}),MD={kernelName:_i,backendName:"webgl",kernelFunc:EX};var DX=gr+`
   return atan(x);
-`,q6=_e({opSnippet:H6}),n2={kernelName:xi,backendName:"webgl",kernelFunc:q6};var K6=RE+`
+`,$X=_e({opSnippet:DX}),LD={kernelName:ki,backendName:"webgl",kernelFunc:$X};var RX=fD+`
   return atan(a, b);
-`,X6=`
+`,FX=`
   vec4 result = atan(a, b);
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+FE+`
+  `+dD+`
   return result;
-`,Y6=nt({opSnippet:K6,packedOpSnippet:X6}),s2={kernelName:bi,backendName:"webgl",kernelFunc:Y6};var Z6=gr+`
+`,OX=nt({opSnippet:RX,packedOpSnippet:FX}),zD={kernelName:Ci,backendName:"webgl",kernelFunc:OX};var PX=gr+`
   if ((x < -1.0) || (x > 1.0)) return NAN;
-return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelName:yi,backendName:"webgl",kernelFunc:J6};var ti=class{constructor(e,t,o,n=!1,s=!1){if(this.variableNames=["x"],t==="avg"&&o)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,i=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,p=e.effectiveFilterHeight,m=e.effectiveFilterWidth,f=e.padInfo.top,d=e.padInfo.left;this.outputShape=e.outShape;let h=t==="avg",g=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,x=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,b="0.0";if(h||(b="-1.0 / 1e-20"),o){let R=">=";this.userCode=`
+return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,MX=_e({opSnippet:PX}),BD={kernelName:vi,backendName:"webgl",kernelFunc:MX};var ii=class{constructor(e,t,o,n=!1,s=!1){if(this.variableNames=["x"],t==="avg"&&o)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,i=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,p=e.effectiveFilterHeight,m=e.effectiveFilterWidth,f=e.padInfo.top,d=e.padInfo.left;this.outputShape=e.outShape;let h=t==="avg",g=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,x=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,b="0.0";if(h||(b="-1.0 / 1e-20"),o){let R=">=";this.userCode=`
         const ivec2 strides = ivec2(${i}, ${l});
         const ivec2 pads = ivec2(${f}, ${d});
 
@@ -1477,7 +1477,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         }
         setOutput(${_});
       }
-    `}},Cu=class{constructor(e,t,o,n=!1,s=!1){if(this.variableNames=["x"],t==="avg"&&o)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,i=e.strideDepth,l=e.strideHeight,u=e.strideWidth,c=e.dilationDepth,p=e.dilationHeight,m=e.dilationWidth,f=e.effectiveFilterDepth,d=e.effectiveFilterHeight,h=e.effectiveFilterWidth,g=e.padInfo.front,x=e.padInfo.top,b=e.padInfo.left;this.outputShape=e.outShape;let w=t==="avg",_="0.0";if(w||(_="-1.0 / 1e-20"),o){let M=">=";this.userCode=`
+    `}},Au=class{constructor(e,t,o,n=!1,s=!1){if(this.variableNames=["x"],t==="avg"&&o)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,i=e.strideDepth,l=e.strideHeight,u=e.strideWidth,c=e.dilationDepth,p=e.dilationHeight,m=e.dilationWidth,f=e.effectiveFilterDepth,d=e.effectiveFilterHeight,h=e.effectiveFilterWidth,g=e.padInfo.front,x=e.padInfo.top,b=e.padInfo.left;this.outputShape=e.outShape;let w=t==="avg",_="0.0";if(w||(_="-1.0 / 1e-20"),o){let M=">=";this.userCode=`
         const ivec3 strides =
             ivec3(${i}, ${l}, ${u});
         const ivec3 pads = ivec3(${g}, ${x}, ${b});
@@ -1640,7 +1640,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
           setOutput(${D});
         }
       }
-    `}};function Q6(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e;gs(n,"avgPool");let{filterSize:s,strides:a,pad:i,dimRoundingMode:l}=o,u=1;y.assert(N.eitherStridesOrDilationsAreOne(a,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=N.computePool2DInfo(n.shape,s,a,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&y.arraysEqual(c.inShape,c.outShape))return Wt({inputs:{x:n},backend:t});let p=new ti(c,"avg",!1);return t.runWebGLProgram(p,[n],"float32")}var a2={kernelName:bn,backendName:"webgl",kernelFunc:Q6};function e5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{filterSize:s,strides:a,pad:i,dimRoundingMode:l,dataFormat:u}=o,c=[1,1,1],p=N.computePool3DInfo(n.shape,s,a,c,i,l,u),m=new Cu(p,"avg",!1);return t.runWebGLProgram(m,[n],"float32")}var l2={kernelName:La,backendName:"webgl",kernelFunc:e5};var Mk=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,o=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=e.dilationHeight,i=e.dilationWidth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=l-1-e.padInfo.top,p=u-1-e.padInfo.left,m=1/(t*o);this.userCode=`
+    `}};function LX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e;_s(n,"avgPool");let{filterSize:s,strides:a,pad:i,dimRoundingMode:l}=o,u=1;y.assert(N.eitherStridesOrDilationsAreOne(a,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=N.computePool2DInfo(n.shape,s,a,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&y.arraysEqual(c.inShape,c.outShape))return Wt({inputs:{x:n},backend:t});let p=new ii(c,"avg",!1);return t.runWebGLProgram(p,[n],"float32")}var VD={kernelName:Cn,backendName:"webgl",kernelFunc:LX};function zX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{filterSize:s,strides:a,pad:i,dimRoundingMode:l,dataFormat:u}=o,c=[1,1,1],p=N.computePool3DInfo(n.shape,s,a,c,i,l,u),m=new Au(p,"avg",!1);return t.runWebGLProgram(m,[n],"float32")}var GD={kernelName:Wa,backendName:"webgl",kernelFunc:zX};var qk=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,o=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=e.dilationHeight,i=e.dilationWidth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=l-1-e.padInfo.top,p=u-1-e.padInfo.left,m=1/(t*o);this.userCode=`
       const ivec2 pads = ivec2(${c}, ${p});
       const float avgMultiplier = float(${m});
 
@@ -1682,7 +1682,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},Lk=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,o=e.filterHeight,n=e.filterWidth,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,l=e.dilationDepth,u=e.dilationHeight,c=e.dilationWidth,p=e.effectiveFilterDepth,m=e.effectiveFilterHeight,f=e.effectiveFilterWidth,d=p-1-e.padInfo.front,h=m-1-e.padInfo.top,g=f-1-e.padInfo.left,x=1/(t*o*n);this.userCode=`
+    `}},Kk=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,o=e.filterHeight,n=e.filterWidth,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,l=e.dilationDepth,u=e.dilationHeight,c=e.dilationWidth,p=e.effectiveFilterDepth,m=e.effectiveFilterHeight,f=e.effectiveFilterWidth,d=p-1-e.padInfo.front,h=m-1-e.padInfo.top,g=f-1-e.padInfo.left,x=1/(t*o*n);this.userCode=`
       const ivec3 pads = ivec3(${d}, ${h}, ${g});
       const float avgMultiplier = float(${x});
 
@@ -1738,7 +1738,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function t5(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=o,p=[1,1,1],m=N.computePool3DInfo(a.shape,i,l,p,u,c),f=new Lk(m);return t.runWebGLProgram(f,[n],a.dtype)}var u2={kernelName:lc,backendName:"webgl",kernelFunc:t5};function r5(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s;gs([n,s],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=o,c=N.computePool2DInfo(a.shape,i,l,1,u),p=new Mk(c);return t.runWebGLProgram(p,[n],a.dtype)}var c2={kernelName:ac,backendName:"webgl",kernelFunc:r5};function o5(r){let{inputs:e,backend:t,attrs:o}=r,{a:n,b:s}=e,{transposeA:a,transposeB:i}=o;return vu({a:n,b:s,transposeA:a,transposeB:i,backend:t})}var p2={kernelName:wn,backendName:"webgl",kernelFunc:o5};var zk=class{constructor(e,t,o,n,s,a){this.outputShape=[],this.variableNames=["x","mean","variance"],N.assertAndGetBroadcastShape(e,t),N.assertAndGetBroadcastShape(e,o);let i="0.0";n!=null&&(N.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let l="1.0";s!=null&&(N.assertAndGetBroadcastShape(e,s),this.variableNames.push("scale"),l="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}};function BX(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=o,p=[1,1,1],m=N.computePool3DInfo(a.shape,i,l,p,u,c),f=new Kk(m);return t.runWebGLProgram(f,[n],a.dtype)}var WD={kernelName:fc,backendName:"webgl",kernelFunc:BX};function VX(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s;_s([n,s],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=o,c=N.computePool2DInfo(a.shape,i,l,1,u),p=new qk(c);return t.runWebGLProgram(p,[n],a.dtype)}var jD={kernelName:mc,backendName:"webgl",kernelFunc:VX};function GX(r){let{inputs:e,backend:t,attrs:o}=r,{a:n,b:s}=e,{transposeA:a,transposeB:i}=o;return Tu({a:n,b:s,transposeA:a,transposeB:i,backend:t})}var UD={kernelName:In,backendName:"webgl",kernelFunc:GX};var Xk=class{constructor(e,t,o,n,s,a){this.outputShape=[],this.variableNames=["x","mean","variance"],N.assertAndGetBroadcastShape(e,t),N.assertAndGetBroadcastShape(e,o);let i="0.0";n!=null&&(N.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let l="1.0";s!=null&&(N.assertAndGetBroadcastShape(e,s),this.variableNames.push("scale"),l="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         float x = getXAtOutCoords();
         float mean = getMeanAtOutCoords();
@@ -1748,7 +1748,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         float inv = scale * inversesqrt(variance + float(${a}));
         setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
       }
-    `}};var Bk=class{constructor(e,t,o,n,s,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],N.assertAndGetBroadcastShape(e,t),N.assertAndGetBroadcastShape(e,o);let i="vec4(0.0)";n!=null&&(N.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let l="vec4(1.0)";s!=null&&(N.assertAndGetBroadcastShape(e,s),this.variableNames.push("scale"),l="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}};var Yk=class{constructor(e,t,o,n,s,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],N.assertAndGetBroadcastShape(e,t),N.assertAndGetBroadcastShape(e,o);let i="vec4(0.0)";n!=null&&(N.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let l="vec4(1.0)";s!=null&&(N.assertAndGetBroadcastShape(e,s),this.variableNames.push("scale"),l="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         vec4 offset = ${i};
         vec4 scale = ${l};
@@ -1761,7 +1761,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
 
         setOutput((x - mean) * inv + offset);
       }
-    `}};var n5=({inputs:r,backend:e,attrs:t})=>{let{x:o,mean:n,variance:s,offset:a,scale:i}=r;y.assert(n.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),y.assert(a==null||n.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),y.assert(i==null||n.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=t;l==null&&(l=.001);let u=[o,n,s],c=null;a!=null&&(c=a.shape,u.push(a));let p=null;i!=null&&(p=i.shape,u.push(i));let m=W().getBool("WEBGL_PACK_NORMALIZATION")?new Bk(o.shape,n.shape,s.shape,c,p,l):new zk(o.shape,n.shape,s.shape,c,p,l);return e.runWebGLProgram(m,u,u[0].dtype)},m2={kernelName:Dn,backendName:"webgl",kernelFunc:n5};var Vk=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=Le(this.rank),o=`uniform int start[${this.rank}];`,n=s5(this.rank),s,a=e.map((i,l)=>`sourceLoc.${Gk[l]} = start[${l}] + coords.${Gk[l]};`);s=`
+    `}};var WX=({inputs:r,backend:e,attrs:t})=>{let{x:o,mean:n,variance:s,offset:a,scale:i}=r;y.assert(n.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),y.assert(a==null||n.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),y.assert(i==null||n.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=t;l==null&&(l=.001);let u=[o,n,s],c=null;a!=null&&(c=a.shape,u.push(a));let p=null;i!=null&&(p=i.shape,u.push(i));let m=W().getBool("WEBGL_PACK_NORMALIZATION")?new Yk(o.shape,n.shape,s.shape,c,p,l):new Xk(o.shape,n.shape,s.shape,c,p,l);return e.runWebGLProgram(m,u,u[0].dtype)},HD={kernelName:Pn,backendName:"webgl",kernelFunc:WX};var Zk=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=Le(this.rank),o=`uniform int start[${this.rank}];`,n=jX(this.rank),s,a=e.map((i,l)=>`sourceLoc.${Jk[l]} = start[${l}] + coords.${Jk[l]};`);s=`
         ${t} sourceLoc;
         ${t} coords = getOutputCoords();
         ${a.join(`
@@ -1772,7 +1772,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         ${s}
         setOutput(getSource(${n}));
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,o)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(o,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}},Gk=["x","y","z","w","u","v"];function s5(r){if(r===1)return"sourceLoc";if(r<=6)return Gk.slice(0,r).map(e=>"sourceLoc."+e).join(",");throw Error(`Slicing for rank ${r} is not yet supported`)}var Wk=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=Le(this.rank),o=Gt("coords",this.rank),n=Gt("sourceLoc",this.rank),s=this.rank===1?"sourceLoc":`vec2(${n.slice(-2).join()})`,a=`getChannel(getSource(${n.join()}), ${s})`,i=`
+    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,o)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(o,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}},Jk=["x","y","z","w","u","v"];function jX(r){if(r===1)return"sourceLoc";if(r<=6)return Jk.slice(0,r).map(e=>"sourceLoc."+e).join(",");throw Error(`Slicing for rank ${r} is not yet supported`)}var Qk=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=Le(this.rank),o=Gt("coords",this.rank),n=Gt("sourceLoc",this.rank),s=this.rank===1?"sourceLoc":`vec2(${n.slice(-2).join()})`,a=`getChannel(getSource(${n.join()}), ${s})`,i=`
       result.x = ${a};
       if (++${o[this.rank-1]} < ${e[this.rank-1]}) {
         ++${n[this.rank-1]};
@@ -1802,7 +1802,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         ${l}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,o)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(o,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function i5(r,e,t,o){let n=o.texData.get(r.dataId),s=o.makeTensorInfo(t,r.dtype),a=o.texData.get(s.dataId);Object.assign(a,n),a.refCount=1,a.shape=t,a.dtype=r.dtype;let i=er.computeFlatOffset(e,y.computeStrides(r.shape));n.slice&&(i+=n.slice.flatOffset),a.slice={flatOffset:i,origDataId:n.slice&&n.slice.origDataId||r.dataId};let l=o.dataRefCount.get(a.slice.origDataId)||1;return o.dataRefCount.set(a.slice.origDataId,l+1),s}function _a(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{begin:s,size:a}=o,[i,l]=er.parseSliceParams(n,s,a);if(er.assertParamsValid(n,i,l),y.sizeFromShape(l)===0)return t.makeTensorInfo(l,n.dtype,[]);if(t.shouldExecuteOnCPU([n])||n.dtype==="string"){let p=t.texData.get(n.dataId),m=cE(p.values,i,l,n.shape,n.dtype);return t.makeTensorInfo(l,n.dtype,m)}let{isPacked:u}=t.texData.get(n.dataId),c=er.isSliceContinous(n.shape,i,l);if(u||!c){let p=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Wk(l):new Vk(l),m=p.getCustomSetupFunc(i);return t.runWebGLProgram(p,[n],n.dtype,m)}return t.uploadToGPU(n.dataId),i5(n,i,l,t)}var f2={kernelName:zs,backendName:"webgl",kernelFunc:_a};var a5=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockShape:s,crops:a}=o;y.assert(n.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let i=s.reduce((b,w)=>b*w),l=N.getReshaped(n.shape,s,i),u=N.getPermuted(l.length,s.length),c=N.getReshapedPermuted(n.shape,s,i),p=N.getSliceBeginCoords(a,s.length),m=N.getSliceSize(c,a,s.length),f=[],d=pe({inputs:{x:n},backend:t,attrs:{shape:l}}),h=Mt({inputs:{x:d},backend:t,attrs:{perm:u}}),g=pe({inputs:{x:h},backend:t,attrs:{shape:c}}),x=_a({inputs:{x:g},backend:t,attrs:{begin:p,size:m}});return f.push(d),f.push(h),f.push(g),f.forEach(b=>t.disposeIntermediateTensorInfo(b)),x},d2={kernelName:za,backendName:"webgl",kernelFunc:a5};function l5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a}=o,i=t.readSync(n.dataId),l=t.readSync(s.dataId),u=Wg(i,l,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,u)}var h2={kernelName:uc,backendName:"webgl",kernelFunc:l5};var u5="return float(a != b);",jk=nt({opSnippet:u5,dtype:"bool"}),g2={kernelName:Li,backendName:"webgl",kernelFunc:jk};function ka(r){let{inputs:e,backend:t}=r,{input:o}=e,n=t.texData.get(o.dataId);return Wt({inputs:{x:n.complexTensorInfos.real},backend:t})}var x2={kernelName:Tc,backendName:"webgl",kernelFunc:ka};var c5="return float(int(x));";function y2(r,e){let t=new ao(r.shape,c5),o=e.runWebGLProgram(t,[r],"int32");return{dataId:o.dataId,shape:o.shape,dtype:o.dtype}}function Uk(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{dtype:s}=o;if(s==="complex64"){if(n.dtype==="complex64")return Wt({inputs:{x:n},backend:t});let a=ht(n.shape),i=Uk({inputs:{x:n},backend:t,attrs:{dtype:"float32"}}),l=lo({inputs:{real:i,imag:a},backend:t});return a.dispose(),t.disposeIntermediateTensorInfo(i),l}if(n.dtype==="complex64"){let a=ka({inputs:{input:n},backend:t}),i=Uk({inputs:{x:a},backend:t,attrs:{dtype:s}});return t.disposeIntermediateTensorInfo(a),i}if(!y.hasEncodingLoss(n.dtype,s)){let a=Wt({inputs:{x:n},backend:t});return{dataId:a.dataId,shape:a.shape,dtype:s}}if(s==="int32")return y2(n,t);if(s==="bool"){let a=t.makeTensorInfo([],"bool",y.getTypedArrayFromDType("bool",1)),l=jk({inputs:{a:n,b:a},backend:t});return t.disposeIntermediateTensorInfo(a),l}throw new Error(`Error in Cast: failed to cast ${n.dtype} to ${s}`)}var b2={kernelName:Vo,backendName:"webgl",kernelFunc:Uk};var w2="return ceil(x);",p5=_e({opSnippet:w2,packedOpSnippet:w2,cpuKernelImpl:HA}),_2={kernelName:_n,backendName:"webgl",kernelFunc:p5};var Hk=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,o)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(o,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function UX(r,e,t,o){let n=o.texData.get(r.dataId),s=o.makeTensorInfo(t,r.dtype),a=o.texData.get(s.dataId);Object.assign(a,n),a.refCount=1,a.shape=t,a.dtype=r.dtype;let i=er.computeFlatOffset(e,y.computeStrides(r.shape));n.slice&&(i+=n.slice.flatOffset),a.slice={flatOffset:i,origDataId:n.slice&&n.slice.origDataId||r.dataId};let l=o.dataRefCount.get(a.slice.origDataId)||1;return o.dataRefCount.set(a.slice.origDataId,l+1),s}function Na(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{begin:s,size:a}=o,[i,l]=er.parseSliceParams(n,s,a);if(er.assertParamsValid(n,i,l),y.sizeFromShape(l)===0)return t.makeTensorInfo(l,n.dtype,[]);if(t.shouldExecuteOnCPU([n])||n.dtype==="string"){let p=t.texData.get(n.dataId),m=j2(p.values,i,l,n.shape,n.dtype);return t.makeTensorInfo(l,n.dtype,m)}let{isPacked:u}=t.texData.get(n.dataId),c=er.isSliceContinous(n.shape,i,l);if(u||!c){let p=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Qk(l):new Zk(l),m=p.getCustomSetupFunc(i);return t.runWebGLProgram(p,[n],n.dtype,m)}return t.uploadToGPU(n.dataId),UX(n,i,l,t)}var qD={kernelName:js,backendName:"webgl",kernelFunc:Na};var HX=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockShape:s,crops:a}=o;y.assert(n.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let i=s.reduce((b,w)=>b*w),l=N.getReshaped(n.shape,s,i),u=N.getPermuted(l.length,s.length),c=N.getReshapedPermuted(n.shape,s,i),p=N.getSliceBeginCoords(a,s.length),m=N.getSliceSize(c,a,s.length),f=[],d=pe({inputs:{x:n},backend:t,attrs:{shape:l}}),h=Mt({inputs:{x:d},backend:t,attrs:{perm:u}}),g=pe({inputs:{x:h},backend:t,attrs:{shape:c}}),x=Na({inputs:{x:g},backend:t,attrs:{begin:p,size:m}});return f.push(d),f.push(h),f.push(g),f.forEach(b=>t.disposeIntermediateTensorInfo(b)),x},KD={kernelName:ja,backendName:"webgl",kernelFunc:HX};function qX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a}=o,i=t.readSync(n.dataId),l=t.readSync(s.dataId),u=Qg(i,l,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,u)}var XD={kernelName:dc,backendName:"webgl",kernelFunc:qX};var KX="return float(a != b);",ev=nt({opSnippet:KX,dtype:"bool"}),YD={kernelName:Wi,backendName:"webgl",kernelFunc:ev};function Sa(r){let{inputs:e,backend:t}=r,{input:o}=e,n=t.texData.get(o.dataId);return Wt({inputs:{x:n.complexTensorInfos.real},backend:t})}var ZD={kernelName:Rc,backendName:"webgl",kernelFunc:Sa};var XX="return float(int(x));";function JD(r,e){let t=new mo(r.shape,XX),o=e.runWebGLProgram(t,[r],"int32");return{dataId:o.dataId,shape:o.shape,dtype:o.dtype}}function tv(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{dtype:s}=o;if(s==="complex64"){if(n.dtype==="complex64")return Wt({inputs:{x:n},backend:t});let a=ht(n.shape),i=tv({inputs:{x:n},backend:t,attrs:{dtype:"float32"}}),l=fo({inputs:{real:i,imag:a},backend:t});return a.dispose(),t.disposeIntermediateTensorInfo(i),l}if(n.dtype==="complex64"){let a=Sa({inputs:{input:n},backend:t}),i=tv({inputs:{x:a},backend:t,attrs:{dtype:s}});return t.disposeIntermediateTensorInfo(a),i}if(!y.hasEncodingLoss(n.dtype,s)){let a=Wt({inputs:{x:n},backend:t});return{dataId:a.dataId,shape:a.shape,dtype:s}}if(s==="int32")return JD(n,t);if(s==="bool"){let a=t.makeTensorInfo([],"bool",y.getTypedArrayFromDType("bool",1)),l=ev({inputs:{a:n,b:a},backend:t});return t.disposeIntermediateTensorInfo(a),l}throw new Error(`Error in Cast: failed to cast ${n.dtype} to ${s}`)}var QD={kernelName:Ho,backendName:"webgl",kernelFunc:tv};var e$="return ceil(x);",YX=_e({opSnippet:e$,packedOpSnippet:e$,cpuKernelImpl:N2}),t$={kernelName:Nn,backendName:"webgl",kernelFunc:YX};var rv=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1815,7 +1815,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
 
         setOutput(clamp(value, minVal, maxVal));
       }
-    `}getCustomSetupFunc(e,t){return(o,n)=>{this.minLoc==null&&(this.minLoc=o.getUniformLocationNoThrow(n,"minVal"),this.maxLoc=o.getUniformLocationNoThrow(n,"maxVal")),o.gl.uniform1f(this.minLoc,e),o.gl.uniform1f(this.maxLoc,t)}}};var qk=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e,t){return(o,n)=>{this.minLoc==null&&(this.minLoc=o.getUniformLocationNoThrow(n,"minVal"),this.maxLoc=o.getUniformLocationNoThrow(n,"maxVal")),o.gl.uniform1f(this.minLoc,e),o.gl.uniform1f(this.maxLoc,t)}}};var ov=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1829,7 +1829,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
 
         setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
       }
-    `}getCustomSetupFunc(e,t){return(o,n)=>{this.minLoc==null&&(this.minLoc=o.getUniformLocationNoThrow(n,"minVal"),this.maxLoc=o.getUniformLocationNoThrow(n,"maxVal")),o.gl.uniform1f(this.minLoc,e),o.gl.uniform1f(this.maxLoc,t)}}};function m5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{clipValueMin:s,clipValueMax:a}=o,i;W().getBool("WEBGL_PACK_CLIP")?i=new qk(n.shape):i=new Hk(n.shape);let l=i.getCustomSetupFunc(s,a);return t.runWebGLProgram(i,[n],n.dtype,l)}var k2={kernelName:Go,backendName:"webgl",kernelFunc:m5};var Kk=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e,t){return(o,n)=>{this.minLoc==null&&(this.minLoc=o.getUniformLocationNoThrow(n,"minVal"),this.maxLoc=o.getUniformLocationNoThrow(n,"maxVal")),o.gl.uniform1f(this.minLoc,e),o.gl.uniform1f(this.maxLoc,t)}}};function ZX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{clipValueMin:s,clipValueMax:a}=o,i;W().getBool("WEBGL_PACK_CLIP")?i=new ov(n.shape):i=new rv(n.shape);let l=i.getCustomSetupFunc(s,a);return t.runWebGLProgram(i,[n],n.dtype,l)}var r$={kernelName:qo,backendName:"webgl",kernelFunc:ZX};var nv=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
       void main() {
         float re = abs(getRealAtOutCoords());
         float im = abs(getImagAtOutCoords());
@@ -1842,7 +1842,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
           mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
         );
       }
-    `}};function v2(r,e){return{dataId:e.dataId,dtype:e.dtype,shape:r.shape}}function f5(r){let{inputs:e,backend:t}=r,{x:o}=e,n=t.texData.get(o.dataId),s=new Kk(o.shape),a=[v2(o,n.complexTensorInfos.real),v2(o,n.complexTensorInfos.imag)];return t.runWebGLProgram(s,a,a[0].dtype)}var C2={kernelName:Ba,backendName:"webgl",kernelFunc:f5};var Xk=class{constructor(e){this.outputShape=[],this.outputShape=N.computeOutShape(e,1),this.variableNames=e.map((a,i)=>`T${i}`);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 o=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let a=1;a<t.length;a++){let i=t[a-1];o.push(`else if (yC < ${t[a]}) setOutput(getT${a}(yR, yC-${i}));`)}let n=t.length,s=t[t.length-1];o.push(`else setOutput(getT${n}(yR, yC-${s}));`),this.userCode=`
+    `}};function o$(r,e){return{dataId:e.dataId,dtype:e.dtype,shape:r.shape}}function JX(r){let{inputs:e,backend:t}=r,{x:o}=e,n=t.texData.get(o.dataId),s=new nv(o.shape),a=[o$(o,n.complexTensorInfos.real),o$(o,n.complexTensorInfos.imag)];return t.runWebGLProgram(s,a,a[0].dtype)}var n$={kernelName:Ua,backendName:"webgl",kernelFunc:JX};var sv=class{constructor(e){this.outputShape=[],this.outputShape=N.computeOutShape(e,1),this.variableNames=e.map((a,i)=>`T${i}`);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 o=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let a=1;a<t.length;a++){let i=t[a-1];o.push(`else if (yC < ${t[a]}) setOutput(getT${a}(yR, yC-${i}));`)}let n=t.length,s=t[t.length-1];o.push(`else setOutput(getT${n}(yR, yC-${s}));`),this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int yR = coords.x;
@@ -1851,18 +1851,18 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         ${o.join(`
         `)}
       }
-    `}};var Yk=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=N.computeOutShape(e,t);let o=this.outputShape,n=o.length,s=Le(n),a=Gt("coords",n),i=["x","y","z","w","u","v"].slice(0,n);this.variableNames=e.map((h,g)=>`T${g}`);let l=new Array(e.length-1);l[0]=e[0][t];for(let h=1;h<l.length;h++)l[h]=l[h-1]+e[h][t];let u=i[t],c=i.slice(-2),p=i.join(),m=`if (${u} < ${l[0]}) {
+    `}};var iv=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=N.computeOutShape(e,t);let o=this.outputShape,n=o.length,s=Le(n),a=Gt("coords",n),i=["x","y","z","w","u","v"].slice(0,n);this.variableNames=e.map((h,g)=>`T${g}`);let l=new Array(e.length-1);l[0]=e[0][t];for(let h=1;h<l.length;h++)l[h]=l[h-1]+e[h][t];let u=i[t],c=i.slice(-2),p=i.join(),m=`if (${u} < ${l[0]}) {
         return getChannel(
             getT0(${p}), vec2(${c.join()}));
         }`;for(let h=1;h<l.length;h++){let g=l[h-1];m+=`
         if (${u} < ${l[h]}  && ${u} >= ${l[h-1]}) {
           return getChannel(
-            getT${h}(${Jg(i,u,g)}),
-            vec2(${Jg(c,u,g)}));
+            getT${h}(${lx(i,u,g)}),
+            vec2(${lx(c,u,g)}));
         }`}let f=l.length,d=l[l.length-1];m+=`
         return getChannel(
-          getT${f}(${Jg(i,u,d)}),
-          vec2(${Jg(c,u,d)}));`,this.userCode=`
+          getT${f}(${lx(i,u,d)}),
+          vec2(${lx(c,u,d)}));`,this.userCode=`
       float getValue(${i.map(h=>"int "+h)}) {
         ${m}
       }
@@ -1888,7 +1888,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         }
         setOutput(result);
       }
-    `}};function Jg(r,e,t){let o=r.indexOf(e);return r.map((s,a)=>a===o?`${s} - ${t}`:s).join()}function Iu(r){let{inputs:e,backend:t}=r,{input:o}=e,n=t.texData.get(o.dataId);return Wt({inputs:{x:n.complexTensorInfos.imag},backend:t})}var I2={kernelName:_c,backendName:"webgl",kernelFunc:Iu};function Nu(r,e,t){let o=r[0].dtype;if(o==="complex64"){let u=r.map(d=>ka({inputs:{input:d},backend:t})),c=r.map(d=>Iu({inputs:{input:d},backend:t})),p=Nu(u,e,t),m=Nu(c,e,t),f=lo({inputs:{real:p,imag:m},backend:t});return u.forEach(d=>t.disposeIntermediateTensorInfo(d)),c.forEach(d=>t.disposeIntermediateTensorInfo(d)),t.disposeIntermediateTensorInfo(p),t.disposeIntermediateTensorInfo(m),f}if(o==="string"){let{tensors2D:u,outShape:c}=N2(r,e,t),p=u.map(g=>({vals:t.readSync(g.dataId),shape:g.shape})),m=u[0].shape[0]===1,f=qA(p,c,o,m),d=N.computeOutShape(r.map(g=>g.shape),e),h=t.makeTensorInfo(d,o,f);return u.forEach(g=>t.disposeIntermediateTensorInfo(g)),h}if(r.length>W().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let u=Math.floor(r.length/2),c=Nu(r.slice(0,u),e,t),p=Nu(r.slice(u),e,t),m=Nu([c,p],e,t);return t.disposeIntermediateTensorInfo(c),t.disposeIntermediateTensorInfo(p),m}if(W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&r[0].shape.length>1){let u=new Yk(r.map(c=>c.shape),e);return t.runWebGLProgram(u,r,o)}let{tensors2D:n,outShape:s}=N2(r,e,t),a=new Xk(n.map(u=>u.shape)),i=t.runWebGLProgram(a,n,o);n.forEach(u=>t.disposeIntermediateTensorInfo(u));let l=pe({inputs:{x:i},attrs:{shape:s},backend:t});return t.disposeIntermediateTensorInfo(i),l}function N2(r,e,t){let o=N.computeOutShape(r.map(s=>s.shape),e);return{tensors2D:r.map(s=>pe({inputs:{x:s},attrs:{shape:[-1,y.sizeFromShape(s.shape.slice(e))]},backend:t})),outShape:o}}function Zk(r){let{inputs:e,backend:t,attrs:o}=r,{axis:n}=o,s=y.parseAxisParam(n,e[0].shape)[0],a=N.computeOutShape(e.map(u=>u.shape),s);if(y.sizeFromShape(a)===0)return t.makeTensorInfo(a,e[0].dtype,[]);let i=e.filter(u=>y.sizeFromShape(u.shape)>0);if(i.length===1)return Wt({inputs:{x:i[0]},backend:t});let l=i.map(u=>u.shape);return N.assertParamsConsistent(l,s),Nu(i,s,t)}var S2={kernelName:Ds,backendName:"webgl",kernelFunc:Zk};var wf=class{constructor(e,t=!1,o=null,n=!1,s=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.padInfo.top,i=e.padInfo.left,l=e.strideHeight,u=e.strideWidth,c=e.dilationHeight,p=e.dilationWidth,m=e.filterHeight,f=e.filterWidth,d=Math.floor(e.inChannels/4)*4,h=e.inChannels%4,g=e.dataFormat==="channelsLast",x=g?1:2,b=g?2:3,w=g?3:1,_="",k="";o&&(n?_=`float activation(float a) {
+    `}};function lx(r,e,t){let o=r.indexOf(e);return r.map((s,a)=>a===o?`${s} - ${t}`:s).join()}function Eu(r){let{inputs:e,backend:t}=r,{input:o}=e,n=t.texData.get(o.dataId);return Wt({inputs:{x:n.complexTensorInfos.imag},backend:t})}var s$={kernelName:Nc,backendName:"webgl",kernelFunc:Eu};function Du(r,e,t){let o=r[0].dtype;if(o==="complex64"){let u=r.map(d=>Sa({inputs:{input:d},backend:t})),c=r.map(d=>Eu({inputs:{input:d},backend:t})),p=Du(u,e,t),m=Du(c,e,t),f=fo({inputs:{real:p,imag:m},backend:t});return u.forEach(d=>t.disposeIntermediateTensorInfo(d)),c.forEach(d=>t.disposeIntermediateTensorInfo(d)),t.disposeIntermediateTensorInfo(p),t.disposeIntermediateTensorInfo(m),f}if(o==="string"){let{tensors2D:u,outShape:c}=i$(r,e,t),p=u.map(g=>({vals:t.readSync(g.dataId),shape:g.shape})),m=u[0].shape[0]===1,f=S2(p,c,o,m),d=N.computeOutShape(r.map(g=>g.shape),e),h=t.makeTensorInfo(d,o,f);return u.forEach(g=>t.disposeIntermediateTensorInfo(g)),h}if(r.length>W().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let u=Math.floor(r.length/2),c=Du(r.slice(0,u),e,t),p=Du(r.slice(u),e,t),m=Du([c,p],e,t);return t.disposeIntermediateTensorInfo(c),t.disposeIntermediateTensorInfo(p),m}if(W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&r[0].shape.length>1){let u=new iv(r.map(c=>c.shape),e);return t.runWebGLProgram(u,r,o)}let{tensors2D:n,outShape:s}=i$(r,e,t),a=new sv(n.map(u=>u.shape)),i=t.runWebGLProgram(a,n,o);n.forEach(u=>t.disposeIntermediateTensorInfo(u));let l=pe({inputs:{x:i},attrs:{shape:s},backend:t});return t.disposeIntermediateTensorInfo(i),l}function i$(r,e,t){let o=N.computeOutShape(r.map(s=>s.shape),e);return{tensors2D:r.map(s=>pe({inputs:{x:s},attrs:{shape:[-1,y.sizeFromShape(s.shape.slice(e))]},backend:t})),outShape:o}}function av(r){let{inputs:e,backend:t,attrs:o}=r,{axis:n}=o,s=y.parseAxisParam(n,e[0].shape)[0],a=N.computeOutShape(e.map(u=>u.shape),s);if(y.sizeFromShape(a)===0)return t.makeTensorInfo(a,e[0].dtype,[]);let i=e.filter(u=>y.sizeFromShape(u.shape)>0);if(i.length===1)return Wt({inputs:{x:i[0]},backend:t});let l=i.map(u=>u.shape);return N.assertParamsConsistent(l,s),Du(i,s,t)}var a$={kernelName:Ps,backendName:"webgl",kernelFunc:av};var Ef=class{constructor(e,t=!1,o=null,n=!1,s=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.padInfo.top,i=e.padInfo.left,l=e.strideHeight,u=e.strideWidth,c=e.dilationHeight,p=e.dilationWidth,m=e.filterHeight,f=e.filterWidth,d=Math.floor(e.inChannels/4)*4,h=e.inChannels%4,g=e.dataFormat==="channelsLast",x=g?1:2,b=g?2:3,w=g?3:1,_="",k="";o&&(n?_=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${o}
         }`:s?_=`float activation(float a) {
@@ -2022,7 +2022,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         ${k}
         setOutput(result);
       }
-    `}},Jk=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,o=e.padInfo.top,n=e.padInfo.left,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,l=e.dilationDepth,u=e.dilationHeight,c=e.dilationWidth,p=e.filterDepth,m=e.filterHeight,f=e.filterWidth,d=Math.floor(e.inChannels/4)*4,h=e.inChannels%4;this.userCode=`
+    `}},lv=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,o=e.padInfo.top,n=e.padInfo.left,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,l=e.dilationDepth,u=e.dilationHeight,c=e.dilationWidth,p=e.filterDepth,m=e.filterHeight,f=e.filterWidth,d=Math.floor(e.inChannels/4)*4,h=e.inChannels%4;this.userCode=`
       const ivec3 strides = ivec3(${s}, ${a}, ${i});
       const ivec3 pads = ivec3(${t}, ${o}, ${n});
 
@@ -2110,7 +2110,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};var Qk=class{constructor(e,t,o){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:n,inChannels:s,strideWidth:a,strideHeight:i,padInfo:l,outWidth:u,dilationWidth:c,dilationHeight:p,dataFormat:m}=o,{left:f,top:d}=l,h=s*n,g=Rt(),x=m==="channelsLast",b=x?0:1,w=x?1:2,_="";for(let k=0;k<=1;k++)for(let D=0;D<=1;D++)_+=`
+    `}};var uv=class{constructor(e,t,o){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:n,inChannels:s,strideWidth:a,strideHeight:i,padInfo:l,outWidth:u,dilationWidth:c,dilationHeight:p,dataFormat:m}=o,{left:f,top:d}=l,h=s*n,g=Rt(),x=m==="channelsLast",b=x?0:1,w=x?1:2,_="";for(let k=0;k<=1;k++)for(let D=0;D<=1;D++)_+=`
           blockIndex = rc.y + ${D};
           pos = rc.x + ${k};
 
@@ -2154,7 +2154,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
 
         ${g.output} = result;
       }
-    `}};function Qg({x:r,filter:e,convInfo:t,backend:o,bias:n=null,preluActivationWeights:s=null,leakyreluAlpha:a=0,activation:i=null}){let l=r.shape,u=o.texData.get(r.dataId),c=t.inChannels,p=l[0]*l[1]*l[2],m=t.outChannels,f=t.dataFormat==="channelsLast",d=!1,h=!1,g,x=[],b=(p===1||m===1)&&c>$k,w=l[2]%2!=0&&!!u.isPacked;if(b||!W().getBool("WEBGL_LAZILY_UNPACK")||!W().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let _=f?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],k=pe({inputs:{x:r},backend:o,attrs:{shape:[1,_,t.inChannels]}}),D=pe({inputs:{x:e},backend:o,attrs:{shape:[1,t.inChannels,t.outChannels]}}),T=vu({a:k,b:D,transposeA:d,transposeB:h,backend:o,bias:n,activation:i,preluActivationWeights:s,leakyreluAlpha:a});g=pe({inputs:{x:T},backend:o,attrs:{shape:t.outShape}}),x.push(k),x.push(D),x.push(T)}else{let _=f?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),k={dataId:r.dataId,shape:[1,_,t.inChannels],dtype:r.dtype},D=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,y.assert(ul(u.shape,k.shape),()=>`packed reshape ${u.shape} to ${k.shape} isn't free`);let T=pe({inputs:{x:e},backend:o,attrs:{shape:[1,t.inChannels,t.outChannels]}});x.push(T);let R=vu({a:k,b:T,backend:o,transposeA:d,transposeB:h,bias:n,activation:i,preluActivationWeights:s,leakyreluAlpha:a}),O=o.texData.get(R.dataId);y.assert(O.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=D,O.shape=t.outShape,g=Wt({inputs:{x:R},backend:o}),g.shape=t.outShape,x.push(R)}for(let _ of x)o.disposeIntermediateTensorInfo(_);return g}function ex({x:r,filter:e,convInfo:t,backend:o,bias:n=null,preluActivationWeights:s=null,leakyreluAlpha:a=0,activation:i=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:p,outHeight:m,dataFormat:f}=t,d=f==="channelsLast",h=l*u*c,g=m*p,x=[h,g],b=!0,w=!1,_=[],k=pe({inputs:{x:r},backend:o,attrs:{shape:r.shape.slice(1)}}),D=pe({inputs:{x:e},backend:o,attrs:{shape:[1,h,y.sizeFromShape(e.shape)/h]}});_.push(k),_.push(D);let T=new Qk(x,k.shape,t),R=o.runWebGLProgram(T,[k],"float32"),O=pe({inputs:{x:R},backend:o,attrs:{shape:[1,x[0],x[1]]}});_.push(R),_.push(O);let M=n!=null,G=s!=null,j=i==="leakyrelu",U=i?pl(i,!0):null,H=new yf(O.shape,D.shape,[1,g,t.outChannels],b,w,M,U,G,j),q=[O,D];if(n&&q.push(n),G&&q.push(s),j){let re=o.makeTensorInfo([],"float32",y.createScalarValue(a,"float32"));q.push(re),_.push(re)}let X=o.runWebGLProgram(H,q,"float32"),oe=d?[1,m,p,t.outChannels]:[1,t.outChannels,m,p],Y=pe({inputs:{x:X},backend:o,attrs:{shape:oe}});_.push(X);for(let re of _)o.disposeIntermediateTensorInfo(re);return Y}function d5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=o,p=N.convertConv2DDataFormat(l),m=N.computeConv2DInfo(n.shape,s.shape,a,u,i,c,!1,p),f;if(m.filterHeight===1&&m.filterWidth===1&&m.dilationHeight===1&&m.dilationWidth===1&&m.strideHeight===1&&m.strideWidth===1&&(m.padInfo.type==="SAME"||m.padInfo.type==="VALID"))f=Qg({x:n,filter:s,convInfo:m,backend:t});else if(W().getBool("WEBGL_CONV_IM2COL")&&n.shape[0]===1)f=ex({x:n,filter:s,convInfo:m,backend:t});else{let h=new wf(m);f=t.runWebGLProgram(h,[n,s],"float32")}let d=pe({inputs:{x:f},backend:t,attrs:{shape:m.outShape}});return t.disposeIntermediateTensorInfo(f),d}var T2={kernelName:kn,backendName:"webgl",kernelFunc:d5};var ev=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,o=e.strideWidth,n=e.padInfo.top,s=e.padInfo.left,a=e.dataFormat==="channelsLast";this.userCode=`
+    `}};function ux({x:r,filter:e,convInfo:t,backend:o,bias:n=null,preluActivationWeights:s=null,leakyreluAlpha:a=0,activation:i=null}){let l=r.shape,u=o.texData.get(r.dataId),c=t.inChannels,p=l[0]*l[1]*l[2],m=t.outChannels,f=t.dataFormat==="channelsLast",d=!1,h=!1,g,x=[],b=(p===1||m===1)&&c>Gk,w=l[2]%2!=0&&!!u.isPacked;if(b||!W().getBool("WEBGL_LAZILY_UNPACK")||!W().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let _=f?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],k=pe({inputs:{x:r},backend:o,attrs:{shape:[1,_,t.inChannels]}}),D=pe({inputs:{x:e},backend:o,attrs:{shape:[1,t.inChannels,t.outChannels]}}),T=Tu({a:k,b:D,transposeA:d,transposeB:h,backend:o,bias:n,activation:i,preluActivationWeights:s,leakyreluAlpha:a});g=pe({inputs:{x:T},backend:o,attrs:{shape:t.outShape}}),x.push(k),x.push(D),x.push(T)}else{let _=f?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),k={dataId:r.dataId,shape:[1,_,t.inChannels],dtype:r.dtype},D=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,y.assert(dl(u.shape,k.shape),()=>`packed reshape ${u.shape} to ${k.shape} isn't free`);let T=pe({inputs:{x:e},backend:o,attrs:{shape:[1,t.inChannels,t.outChannels]}});x.push(T);let R=Tu({a:k,b:T,backend:o,transposeA:d,transposeB:h,bias:n,activation:i,preluActivationWeights:s,leakyreluAlpha:a}),O=o.texData.get(R.dataId);y.assert(O.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=D,O.shape=t.outShape,g=Wt({inputs:{x:R},backend:o}),g.shape=t.outShape,x.push(R)}for(let _ of x)o.disposeIntermediateTensorInfo(_);return g}function cx({x:r,filter:e,convInfo:t,backend:o,bias:n=null,preluActivationWeights:s=null,leakyreluAlpha:a=0,activation:i=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:p,outHeight:m,dataFormat:f}=t,d=f==="channelsLast",h=l*u*c,g=m*p,x=[h,g],b=!0,w=!1,_=[],k=pe({inputs:{x:r},backend:o,attrs:{shape:r.shape.slice(1)}}),D=pe({inputs:{x:e},backend:o,attrs:{shape:[1,h,y.sizeFromShape(e.shape)/h]}});_.push(k),_.push(D);let T=new uv(x,k.shape,t),R=o.runWebGLProgram(T,[k],"float32"),O=pe({inputs:{x:R},backend:o,attrs:{shape:[1,x[0],x[1]]}});_.push(R),_.push(O);let M=n!=null,G=s!=null,j=i==="leakyrelu",U=i?gl(i,!0):null,H=new Tf(O.shape,D.shape,[1,g,t.outChannels],b,w,M,U,G,j),q=[O,D];if(n&&q.push(n),G&&q.push(s),j){let re=o.makeTensorInfo([],"float32",y.createScalarValue(a,"float32"));q.push(re),_.push(re)}let X=o.runWebGLProgram(H,q,"float32"),oe=d?[1,m,p,t.outChannels]:[1,t.outChannels,m,p],Y=pe({inputs:{x:X},backend:o,attrs:{shape:oe}});_.push(X);for(let re of _)o.disposeIntermediateTensorInfo(re);return Y}function QX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=o,p=N.convertConv2DDataFormat(l),m=N.computeConv2DInfo(n.shape,s.shape,a,u,i,c,!1,p),f;if(m.filterHeight===1&&m.filterWidth===1&&m.dilationHeight===1&&m.dilationWidth===1&&m.strideHeight===1&&m.strideWidth===1&&(m.padInfo.type==="SAME"||m.padInfo.type==="VALID"))f=ux({x:n,filter:s,convInfo:m,backend:t});else if(W().getBool("WEBGL_CONV_IM2COL")&&n.shape[0]===1)f=cx({x:n,filter:s,convInfo:m,backend:t});else{let h=new Ef(m);f=t.runWebGLProgram(h,[n,s],"float32")}let d=pe({inputs:{x:f},backend:t,attrs:{shape:m.outShape}});return t.disposeIntermediateTensorInfo(f),d}var l$={kernelName:Sn,backendName:"webgl",kernelFunc:QX};var cv=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,o=e.strideWidth,n=e.padInfo.top,s=e.padInfo.left,a=e.dataFormat==="channelsLast";this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2196,7 +2196,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},tv=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,o=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,l=o-1-e.padInfo.left,u=a?1:2,c=a?2:3,p=a?3:1;this.userCode=`
+    `}},pv=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,o=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,l=o-1-e.padInfo.left,u=a?1:2,c=a?2:3,p=a?3:1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${l});
 
       void main() {
@@ -2249,7 +2249,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},rv=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,o=e.strideHeight,n=e.strideWidth,s=e.padInfo.front,a=e.padInfo.top,i=e.padInfo.left;this.userCode=`
+    `}},mv=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,o=e.strideHeight,n=e.strideWidth,s=e.padInfo.front,a=e.padInfo.top,i=e.padInfo.left;this.userCode=`
       void main() {
         ivec5 coords = getOutputCoords();
         int wF = coords.x;
@@ -2291,7 +2291,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},ov=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,o=e.filterHeight,n=e.filterWidth,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,l=t-1-e.padInfo.front,u=o-1-e.padInfo.top,c=n-1-e.padInfo.left;this.userCode=`
+    `}},fv=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,o=e.filterHeight,n=e.filterWidth,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,l=t-1-e.padInfo.front,u=o-1-e.padInfo.top,c=n-1-e.padInfo.left;this.userCode=`
       const ivec3 pads = ivec3(${l}, ${u}, ${c});
 
       void main() {
@@ -2348,12 +2348,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function h5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,dy:s}=e,{strides:a,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=o,p=N.convertConv2DDataFormat(l),m=N.computeConv2DInfo(n.shape,c,a,1,i,u,!1,p),f=new ev(m);return t.runWebGLProgram(f,[n,s],"float32")}var A2={kernelName:pc,backendName:"webgl",kernelFunc:h5};function g5(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{inputShape:a,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=o,p=N.convertConv2DDataFormat(u),m=N.computeConv2DInfo(a,s.shape,i,1,l,c,!1,p),f=new tv(m);return t.runWebGLProgram(f,[n,s],"float32")}var E2={kernelName:vn,backendName:"webgl",kernelFunc:g5};function x5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:l}=o,u=N.computeConv3DInfo(n.shape,s.shape,a,l,i),c=new Jk(u);return t.runWebGLProgram(c,[n,s],"float32")}var D2={kernelName:Va,backendName:"webgl",kernelFunc:x5};function y5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,dy:s}=e,{strides:a,pad:i,filterShape:l}=o,u=N.computeConv3DInfo(n.shape,l,a,1,i),c=new rv(u);return t.runWebGLProgram(c,[n,s],"float32")}var $2={kernelName:mc,backendName:"webgl",kernelFunc:y5};function b5(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{pad:a,strides:i,inputShape:l}=o,u=N.computeConv3DInfo(l,s.shape,i,1,a),c=new ov(u);return t.runWebGLProgram(c,[n,s],"float32")}var R2={kernelName:fc,backendName:"webgl",kernelFunc:b5};var w5=qg+`
+    `}};function e8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,dy:s}=e,{strides:a,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=o,p=N.convertConv2DDataFormat(l),m=N.computeConv2DInfo(n.shape,c,a,1,i,u,!1,p),f=new cv(m);return t.runWebGLProgram(f,[n,s],"float32")}var u$={kernelName:gc,backendName:"webgl",kernelFunc:e8};function t8(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{inputShape:a,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=o,p=N.convertConv2DDataFormat(u),m=N.computeConv2DInfo(a,s.shape,i,1,l,c,!1,p),f=new pv(m);return t.runWebGLProgram(f,[n,s],"float32")}var c$={kernelName:Tn,backendName:"webgl",kernelFunc:t8};function r8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:l}=o,u=N.computeConv3DInfo(n.shape,s.shape,a,l,i),c=new lv(u);return t.runWebGLProgram(c,[n,s],"float32")}var p$={kernelName:Ha,backendName:"webgl",kernelFunc:r8};function o8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,dy:s}=e,{strides:a,pad:i,filterShape:l}=o,u=N.computeConv3DInfo(n.shape,l,a,1,i),c=new mv(u);return t.runWebGLProgram(c,[n,s],"float32")}var m$={kernelName:xc,backendName:"webgl",kernelFunc:o8};function n8(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{pad:a,strides:i,inputShape:l}=o,u=N.computeConv3DInfo(l,s.shape,i,1,a),c=new fv(u);return t.runWebGLProgram(c,[n,s],"float32")}var f$={kernelName:yc,backendName:"webgl",kernelFunc:n8};var s8=ox+`
   return cos(x);
-`,_5=_e({opSnippet:w5}),F2={kernelName:Cn,backendName:"webgl",kernelFunc:_5};var k5=`
+`,i8=_e({opSnippet:s8}),d$={kernelName:An,backendName:"webgl",kernelFunc:i8};var a8=`
   float e2x = exp(-x);
   return (e2x + 1.0 / e2x) / 2.0;
-`,v5=_e({opSnippet:k5}),O2={kernelName:wi,backendName:"webgl",kernelFunc:v5};var nv=class{constructor(e,t,o,n,s){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[a,i,l,u]=e,[c]=t,[p,m]=o;this.outputShape=[c,p,m,u];let f=n==="bilinear"?1:0,[d,h]=[`${i-1}.0`,`${l-1}.0`],[g,x,b]=p>1?[`${(i-1)/(p-1)}`,"(y2-y1) * height_ratio",`y1*${d} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${d}`],[w,_,k]=m>1?[`${(l-1)/(m-1)}`,"(x2-x1) * width_ratio",`x1*${h} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${h}`];this.userCode=`
+`,l8=_e({opSnippet:a8}),h$={kernelName:Ii,backendName:"webgl",kernelFunc:l8};var dv=class{constructor(e,t,o,n,s){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[a,i,l,u]=e,[c]=t,[p,m]=o;this.outputShape=[c,p,m,u];let f=n==="bilinear"?1:0,[d,h]=[`${i-1}.0`,`${l-1}.0`],[g,x,b]=p>1?[`${(i-1)/(p-1)}`,"(y2-y1) * height_ratio",`y1*${d} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${d}`],[w,_,k]=m>1?[`${(l-1)/(m-1)}`,"(x2-x1) * width_ratio",`x1*${h} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${h}`];this.userCode=`
       const float height_ratio = float(${g});
       const float width_ratio = float(${w});
       void main() {
@@ -2414,21 +2414,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
           setOutput(newValue);
         }
       }
-    `}};var C5=r=>{let{inputs:e,backend:t,attrs:o}=r,{image:n,boxes:s,boxInd:a}=e,{cropSize:i,method:l,extrapolationValue:u}=o,c=new nv(n.shape,s.shape,i,l,u);return t.runWebGLProgram(c,[n,s,a],"float32")},P2={kernelName:_i,backendName:"webgl",kernelFunc:C5};var tx=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=e;let n=e.length,s=t?"0.0":`getX(${M2(n,"coords")})`,a=e[e.length-1],i="",l="";t?(i=o?`end != ${a-1}`:"end != 0",l=o?"end + 1":"end - 1"):(i=o?`end + pow2 < ${a}`:"end >= pow2",l=o?"end + pow2":"end - pow2"),this.userCode=`
+    `}};var u8=r=>{let{inputs:e,backend:t,attrs:o}=r,{image:n,boxes:s,boxInd:a}=e,{cropSize:i,method:l,extrapolationValue:u}=o,c=new dv(n.shape,s.shape,i,l,u);return t.runWebGLProgram(c,[n,s,a],"float32")},g$={kernelName:Ni,backendName:"webgl",kernelFunc:u8};var px=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=e;let n=e.length,s=t?"0.0":`getX(${x$(n,"coords")})`,a=e[e.length-1],i="",l="";t?(i=o?`end != ${a-1}`:"end != 0",l=o?"end + 1":"end - 1"):(i=o?`end + pow2 < ${a}`:"end >= pow2",l=o?"end + pow2":"end - pow2"),this.userCode=`
       uniform float index;
       void main() {
         ${Le(n)} coords = getOutputCoords();
-        int end = ${L2(n,"coords")};
+        int end = ${y$(n,"coords")};
         float val = ${s};
         int pow2 = int(pow(2.0, index));
         if (${i}) {
           int idx = ${l};
-          ${L2(n,"coords")} = idx;
-          val += getX(${M2(n,"coords")});
+          ${y$(n,"coords")} = idx;
+          val += getX(${x$(n,"coords")});
         }
         setOutput(val);
       }
-    `}getCustomSetupFunc(e){return(t,o)=>{this.index==null&&(this.index=t.getUniformLocation(o,"index")),t.gl.uniform1f(this.index,e)}}};function M2(r,e){if(r===1)return`${e}`;if(r===2)return`${e}.x, ${e}.y`;if(r===3)return`${e}.x, ${e}.y, ${e}.z`;if(r===4)return`${e}.x, ${e}.y, ${e}.z, ${e}.w`;throw Error(`Cumulative sum for rank ${r} is not yet supported`)}function L2(r,e){if(r===1)return`${e}`;if(r===2)return`${e}.y`;if(r===3)return`${e}.z`;if(r===4)return`${e}.w`;throw Error(`Cumulative sum for rank ${r} is not yet supported`)}function I5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,exclusive:a,reverse:i}=o,l=n.shape.length,u=N.getAxesPermutation([s],l),c=n;u!=null&&(c=Mt({inputs:{x:n},backend:t,attrs:{perm:u}}));let p=N.getInnerMostAxes(1,l)[0];if(p!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${n.shape.length-1} but got axis=${s}`);let m=c.shape[p],f=Wt({inputs:{x:c},backend:t});for(let d=0;d<=Math.ceil(Math.log2(m))-1;d++){let h=new tx(c.shape,!1,i),g=h.getCustomSetupFunc(d),x=f;f=t.runWebGLProgram(h,[f],f.dtype,g),t.disposeIntermediateTensorInfo(x)}if(a){let d=new tx(c.shape,a,i),h=f;f=t.runWebGLProgram(d,[f],f.dtype),t.disposeIntermediateTensorInfo(h)}if(u!=null){let d=N.getUndoAxesPermutation(u),h=Mt({inputs:{x:f},backend:t,attrs:{perm:d}});return t.disposeIntermediateTensorInfo(f),t.disposeIntermediateTensorInfo(c),h}return f}var z2={kernelName:In,backendName:"webgl",kernelFunc:I5};function N5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a,binaryOutput:i}=o;if(n.shape.length===1){let l=t.readSync(n.dataId),u=t.readSync(s.dataId),c=Wg(l,u,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,c)}else if(n.shape.length===2){let l=t.bufferSync(n),u=t.bufferSync(s),c=UA(l,u,a,i);return t.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${n.shape.length}.`)}var B2={kernelName:dc,backendName:"webgl",kernelFunc:N5};var sv=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=o,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,o)=>{this.index==null&&(this.index=t.getUniformLocation(o,"index")),t.gl.uniform1f(this.index,e)}}};function x$(r,e){if(r===1)return`${e}`;if(r===2)return`${e}.x, ${e}.y`;if(r===3)return`${e}.x, ${e}.y, ${e}.z`;if(r===4)return`${e}.x, ${e}.y, ${e}.z, ${e}.w`;throw Error(`Cumulative sum for rank ${r} is not yet supported`)}function y$(r,e){if(r===1)return`${e}`;if(r===2)return`${e}.y`;if(r===3)return`${e}.z`;if(r===4)return`${e}.w`;throw Error(`Cumulative sum for rank ${r} is not yet supported`)}function c8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,exclusive:a,reverse:i}=o,l=n.shape.length,u=N.getAxesPermutation([s],l),c=n;u!=null&&(c=Mt({inputs:{x:n},backend:t,attrs:{perm:u}}));let p=N.getInnerMostAxes(1,l)[0];if(p!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${n.shape.length-1} but got axis=${s}`);let m=c.shape[p],f=Wt({inputs:{x:c},backend:t});for(let d=0;d<=Math.ceil(Math.log2(m))-1;d++){let h=new px(c.shape,!1,i),g=h.getCustomSetupFunc(d),x=f;f=t.runWebGLProgram(h,[f],f.dtype,g),t.disposeIntermediateTensorInfo(x)}if(a){let d=new px(c.shape,a,i),h=f;f=t.runWebGLProgram(d,[f],f.dtype),t.disposeIntermediateTensorInfo(h)}if(u!=null){let d=N.getUndoAxesPermutation(u),h=Mt({inputs:{x:f},backend:t,attrs:{perm:d}});return t.disposeIntermediateTensorInfo(f),t.disposeIntermediateTensorInfo(c),h}return f}var b$={kernelName:En,backendName:"webgl",kernelFunc:c8};function p8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a,binaryOutput:i}=o;if(n.shape.length===1){let l=t.readSync(n.dataId),u=t.readSync(s.dataId),c=Qg(l,u,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,c)}else if(n.shape.length===2){let l=t.bufferSync(n),u=t.bufferSync(s),c=I2(l,u,a,i);return t.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${n.shape.length}.`)}var w$={kernelName:bc,backendName:"webgl",kernelFunc:p8};var hv=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=o,this.userCode=`
     void main() {
       ivec4 coords = getOutputCoords();
       int b = coords[0];
@@ -2447,7 +2447,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
       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 S5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockSize:s,dataFormat:a}=o;y.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let i=n.shape[0],l=a==="NHWC"?n.shape[1]:n.shape[2],u=a==="NHWC"?n.shape[2]:n.shape[3],c=a==="NHWC"?n.shape[3]:n.shape[1],p=l*s,m=u*s,f=c/(s*s),d=a==="NHWC"?[i,p,m,f]:[i,f,p,m],h=new sv(d,s,a);return t.runWebGLProgram(h,[n],n.dtype)}var V2={kernelName:ki,backendName:"webgl",kernelFunc:S5};var _f=class{constructor(e,t=!1,o=null,n=!1,s=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.inHeight,i=e.inWidth,l=e.padInfo.top,u=e.padInfo.left,c=e.strideHeight,p=e.strideWidth,m=e.dilationHeight,f=e.dilationWidth,d=e.filterHeight,h=e.filterWidth,g=e.outChannels/e.inChannels,x="",b="";o&&(n?x=`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 m8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockSize:s,dataFormat:a}=o;y.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let i=n.shape[0],l=a==="NHWC"?n.shape[1]:n.shape[2],u=a==="NHWC"?n.shape[2]:n.shape[3],c=a==="NHWC"?n.shape[3]:n.shape[1],p=l*s,m=u*s,f=c/(s*s),d=a==="NHWC"?[i,p,m,f]:[i,f,p,m],h=new hv(d,s,a);return t.runWebGLProgram(h,[n],n.dtype)}var _$={kernelName:Si,backendName:"webgl",kernelFunc:m8};var Df=class{constructor(e,t=!1,o=null,n=!1,s=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.inHeight,i=e.inWidth,l=e.padInfo.top,u=e.padInfo.left,c=e.strideHeight,p=e.strideWidth,m=e.dilationHeight,f=e.dilationWidth,d=e.filterHeight,h=e.filterWidth,g=e.outChannels/e.inChannels,x="",b="";o&&(n?x=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${o}
         }`:s?x=`float activation(float a) {
@@ -2503,7 +2503,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         ${b}
         setOutput(result);
       }
-    `}};var kf=class{constructor(e,t=!1,o=null,n=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let a=e.inHeight,i=e.inWidth,l=e.padInfo.top,u=e.padInfo.left,c=e.strideHeight,p=e.strideWidth,m=e.dilationHeight,f=e.dilationWidth,d=e.filterHeight,h=e.filterWidth,g=h,x="int xR; int xC; int xCOffset;";for(let k=0;k<d;k++)for(let D=0;D<h;D++)x+=`
+    `}};var $f=class{constructor(e,t=!1,o=null,n=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let a=e.inHeight,i=e.inWidth,l=e.padInfo.top,u=e.padInfo.left,c=e.strideHeight,p=e.strideWidth,m=e.dilationHeight,f=e.dilationWidth,d=e.filterHeight,h=e.filterWidth,g=h,x="int xR; int xC; int xCOffset;";for(let k=0;k<d;k++)for(let D=0;D<h;D++)x+=`
           vec4 xTexelR${k}C${D*2} = vec4(0.);
           vec4 wR${k}C${D} = vec4(0.);
           vec4 xR${k}C${D} = vec4(0.);`;for(let k=0;k<d;k++)for(let D=0;D<g;D++){let T=D*2;if(x+=`
@@ -2656,7 +2656,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         ${w}
         setOutput(result);
       }
-    `}};function T5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:l,dimRoundingMode:u}=o,c=l;c==null&&(c=[1,1]),y.assert(N.eitherStridesOrDilationsAreOne(a,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${a} and dilations '${c}'`);let p=N.computeConv2DInfo(n.shape,s.shape,a,c,i,u,!0),m;return W().getBool("WEBGL_PACK_DEPTHWISECONV")&&p.strideWidth<=2&&p.outChannels/p.inChannels==1?m=new kf(p):m=new _f(p),t.runWebGLProgram(m,[n,s],"float32")}var G2={kernelName:Nn,backendName:"webgl",kernelFunc:T5};var iv=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,o=e.strideWidth,n=e.padInfo.top,s=e.padInfo.left,a=e.outChannels/e.inChannels;this.userCode=`
+    `}};function f8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:l,dimRoundingMode:u}=o,c=l;c==null&&(c=[1,1]),y.assert(N.eitherStridesOrDilationsAreOne(a,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${a} and dilations '${c}'`);let p=N.computeConv2DInfo(n.shape,s.shape,a,c,i,u,!0),m;return W().getBool("WEBGL_PACK_DEPTHWISECONV")&&p.strideWidth<=2&&p.outChannels/p.inChannels==1?m=new $f(p):m=new Df(p),t.runWebGLProgram(m,[n,s],"float32")}var k$={kernelName:Dn,backendName:"webgl",kernelFunc:f8};var gv=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,o=e.strideWidth,n=e.padInfo.top,s=e.padInfo.left,a=e.outChannels/e.inChannels;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2691,7 +2691,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},av=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,o=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=t-1-e.padInfo.top,i=o-1-e.padInfo.left,l=e.outChannels/e.inChannels;this.userCode=`
+    `}},xv=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,o=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=t-1-e.padInfo.top,i=o-1-e.padInfo.left,l=e.outChannels/e.inChannels;this.userCode=`
       const ivec2 pads = ivec2(${a}, ${i});
 
       void main() {
@@ -2736,13 +2736,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function A5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,dy:s}=e,{strides:a,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=o,p=N.computeConv2DInfo(n.shape,c,a,i,l,u,!0),m=new iv(p);return t.runWebGLProgram(m,[n,s],"float32")}var W2={kernelName:hc,backendName:"webgl",kernelFunc:A5};function E5(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{strides:a,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=o,p=N.computeConv2DInfo(c,s.shape,a,i,l,u,!0),m=new av(p);return t.runWebGLProgram(m,[n,s],"float32")}var j2={kernelName:gc,backendName:"webgl",kernelFunc:E5};var lv=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
+    `}};function d8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,dy:s}=e,{strides:a,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=o,p=N.computeConv2DInfo(n.shape,c,a,i,l,u,!0),m=new gv(p);return t.runWebGLProgram(m,[n,s],"float32")}var v$={kernelName:wc,backendName:"webgl",kernelFunc:d8};function h8(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{strides:a,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=o,p=N.computeConv2DInfo(c,s.shape,a,i,l,u,!0),m=new xv(p);return t.runWebGLProgram(m,[n,s],"float32")}var C$={kernelName:_c,backendName:"webgl",kernelFunc:h8};var yv=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 D5(r){let{inputs:e,backend:t}=r,{x:o}=e,n=[...o.shape,...o.shape],s=y.sizeFromShape(o.shape),a=pe({inputs:{x:o},backend:t,attrs:{shape:[s]}}),i=new lv(s),l=t.runWebGLProgram(i,[a],a.dtype),u=pe({inputs:{x:l},backend:t,attrs:{shape:n}});return t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(l),u}var U2={kernelName:xc,backendName:"webgl",kernelFunc:D5};var uv=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:o,padInfo:n,strideHeight:s,strideWidth:a,filterHeight:i,filterWidth:l,dilationHeight:u,dilationWidth:c}=e,{top:p,left:m}=n;this.userCode=`
+    `}};function g8(r){let{inputs:e,backend:t}=r,{x:o}=e,n=[...o.shape,...o.shape],s=y.sizeFromShape(o.shape),a=pe({inputs:{x:o},backend:t,attrs:{shape:[s]}}),i=new yv(s),l=t.runWebGLProgram(i,[a],a.dtype),u=pe({inputs:{x:l},backend:t,attrs:{shape:n}});return t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(l),u}var I$={kernelName:kc,backendName:"webgl",kernelFunc:g8};var bv=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:o,padInfo:n,strideHeight:s,strideWidth:a,filterHeight:i,filterWidth:l,dilationHeight:u,dilationWidth:c}=e,{top:p,left:m}=n;this.userCode=`
       const ivec2 strides = ivec2(${s}, ${a});
       const ivec2 pads = ivec2(${p}, ${m});
       const float neg_infinity = -3.4e38;
@@ -2780,7 +2780,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         float result = curVal;
         setOutput(result);
       }
-    `}};function $5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:l}=o,u=N.computeDilation2DInfo(n.shape,s.shape,a,i,"NHWC",l),c,p=new uv(u);c=t.runWebGLProgram(p,[n,s],"float32");let m=pe({inputs:{x:c},backend:t,attrs:{shape:u.outShape}});return t.disposeIntermediateTensorInfo(c),m}var H2={kernelName:Ga,backendName:"webgl",kernelFunc:$5};var R5="return (x >= 0.0) ? x : (exp(x) - 1.0);",F5=`
+    `}};function x8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:l}=o,u=N.computeDilation2DInfo(n.shape,s.shape,a,i,"NHWC",l),c,p=new bv(u);c=t.runWebGLProgram(p,[n,s],"float32");let m=pe({inputs:{x:c},backend:t,attrs:{shape:u.outShape}});return t.disposeIntermediateTensorInfo(c),m}var N$={kernelName:qa,backendName:"webgl",kernelFunc:x8};var y8="return (x >= 0.0) ? x : (exp(x) - 1.0);",b8=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -2789,12 +2789,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,O5=_e({opSnippet:R5,packedOpSnippet:F5}),q2={kernelName:vi,backendName:"webgl",kernelFunc:O5};var P5="return (b >= 1.0) ? a : a * (b + 1.0);",M5=`
+`,w8=_e({opSnippet:y8,packedOpSnippet:b8}),S$={kernelName:Ti,backendName:"webgl",kernelFunc:w8};var _8="return (b >= 1.0) ? a : a * (b + 1.0);",k8=`
   vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
   return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
-`,L5=r=>{let{inputs:e,backend:t}=r,{dy:o,y:n}=e,s=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new bs(M5,o.shape,n.shape):new nn(P5,o.shape,n.shape);return t.runWebGLProgram(s,[o,n],o.dtype)},K2={kernelName:yc,backendName:"webgl",kernelFunc:L5};var z5=`
+`,v8=r=>{let{inputs:e,backend:t}=r,{dy:o,y:n}=e,s=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Cs(k8,o.shape,n.shape):new cn(_8,o.shape,n.shape);return t.runWebGLProgram(s,[o,n],o.dtype)},T$={kernelName:vc,backendName:"webgl",kernelFunc:v8};var C8=`
   return vec4(equal(a, b));
-`,B5="return float(a == b);",V5=nt({opSnippet:B5,packedOpSnippet:z5,dtype:"bool"}),X2={kernelName:Ii,backendName:"webgl",kernelFunc:V5};var G5=`
+`,I8="return float(a == b);",N8=nt({opSnippet:I8,packedOpSnippet:C8,dtype:"bool"}),A$={kernelName:Ei,backendName:"webgl",kernelFunc:N8};var S8=`
   // Error function is calculated approximately with elementary function.
   // See "Handbook of Mathematical Functions with Formulas,
   // Graphs, and Mathematical Tables", Abramowitz and Stegun.
@@ -2809,7 +2809,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
   x = abs(x);
   float t = 1.0 / (1.0 + p * x);
   return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
-`,W5=_e({opSnippet:G5}),Y2={kernelName:Ci,backendName:"webgl",kernelFunc:W5};var Z2="return exp(x);",cv=_e({opSnippet:Z2,packedOpSnippet:Z2,cpuKernelImpl:KA}),J2={kernelName:Tn,backendName:"webgl",kernelFunc:cv};function rx(r){let{inputs:e,attrs:t,backend:o}=r,{dim:n}=t,{input:s}=e,a=s.shape.length,i=s.shape.slice(),l=n;return n<0&&(y.assert(-(a+1)<=n,()=>`Axis must be in the interval [${-(a+1)}, ${a}]`),l=a+n+1),i.splice(l,0,1),pe({inputs:{x:s},backend:o,attrs:{shape:i}})}var Q2={kernelName:$s,backendName:"webgl",kernelFunc:rx};var eD="return exp(x) - 1.0;",j5=_e({opSnippet:eD,packedOpSnippet:eD,cpuKernelImpl:XA}),tD={kernelName:Ni,backendName:"webgl",kernelFunc:j5};var ox=class{constructor(e,t,o){this.variableNames=["real","imag"];let n=t[1];this.outputShape=t;let s=o?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,a=o?`${n}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
+`,T8=_e({opSnippet:S8}),E$={kernelName:Ai,backendName:"webgl",kernelFunc:T8};var D$="return exp(x);",wv=_e({opSnippet:D$,packedOpSnippet:D$,cpuKernelImpl:T2}),$$={kernelName:Rn,backendName:"webgl",kernelFunc:wv};function mx(r){let{inputs:e,attrs:t,backend:o}=r,{dim:n}=t,{input:s}=e,a=s.shape.length,i=s.shape.slice(),l=n;return n<0&&(y.assert(-(a+1)<=n,()=>`Axis must be in the interval [${-(a+1)}, ${a}]`),l=a+n+1),i.splice(l,0,1),pe({inputs:{x:s},backend:o,attrs:{shape:i}})}var R$={kernelName:Ms,backendName:"webgl",kernelFunc:mx};var F$="return exp(x) - 1.0;",A8=_e({opSnippet:F$,packedOpSnippet:F$,cpuKernelImpl:A2}),O$={kernelName:Di,backendName:"webgl",kernelFunc:A8};var fx=class{constructor(e,t,o){this.variableNames=["real","imag"];let n=t[1];this.outputShape=t;let s=o?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,a=o?`${n}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
       const float exponentMultiplier = ${s};
 
       float unaryOpComplex(float real, float expR, float imag, float expI) {
@@ -2842,13 +2842,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         ivec2 coords = getOutputCoords();
         setOutput(mulMatDFT(coords[0], coords[1]));
       }
-    `}};function nx(r,e,t){let o=t.texData.get(r.dataId),n=y.sizeFromShape(r.shape),s=r.shape[r.shape.length-1],a=n/s,i=pe({inputs:{x:r},backend:t,attrs:{shape:[a,s]}}),l=i.shape,u=new ox("real",l,e),c=new ox("imag",l,e),p=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:l},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:l}],m=t.runWebGLProgram(u,p,"float32"),f=t.runWebGLProgram(c,p,"float32"),d=lo({inputs:{real:m,imag:f},backend:t});t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(f);let h=pe({inputs:{x:d},backend:t,attrs:{shape:r.shape}});return t.disposeIntermediateTensorInfo(i),t.disposeIntermediateTensorInfo(d),h}function U5(r){let{inputs:e,backend:t}=r,{input:o}=e;return nx(o,!1,t)}var rD={kernelName:bc,backendName:"webgl",kernelFunc:U5};var pv=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.outputShape=e,this.userCode=`
+    `}};function dx(r,e,t){let o=t.texData.get(r.dataId),n=y.sizeFromShape(r.shape),s=r.shape[r.shape.length-1],a=n/s,i=pe({inputs:{x:r},backend:t,attrs:{shape:[a,s]}}),l=i.shape,u=new fx("real",l,e),c=new fx("imag",l,e),p=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:l},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:l}],m=t.runWebGLProgram(u,p,"float32"),f=t.runWebGLProgram(c,p,"float32"),d=fo({inputs:{real:m,imag:f},backend:t});t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(f);let h=pe({inputs:{x:d},backend:t,attrs:{shape:r.shape}});return t.disposeIntermediateTensorInfo(i),t.disposeIntermediateTensorInfo(d),h}function E8(r){let{inputs:e,backend:t}=r,{input:o}=e;return dx(o,!1,t)}var P$={kernelName:Cc,backendName:"webgl",kernelFunc:E8};var _v=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.outputShape=e,this.userCode=`
       uniform float value;
       void main() {
         // Input can be obtained from uniform value.
         setOutput(value);
       }
-    `}getCustomSetupFunc(e){return(t,o)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(o,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function vf(r){let{backend:e,attrs:t}=r,{shape:o,value:n}=t,{dtype:s}=t;if(s=s||y.inferDtype(n),s==="string"){let a=y.getArrayFromDType(s,y.sizeFromShape(o));return a.fill(n),e.makeTensorInfo(o,s,a)}else{let a=new pv(o,n),i=a.getCustomSetupFunc(n);return e.runWebGLProgram(a,[],s,i)}}var oD={kernelName:Wa,backendName:"webgl",kernelFunc:vf};var mv=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,o)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(o,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function Rf(r){let{backend:e,attrs:t}=r,{shape:o,value:n}=t,{dtype:s}=t;if(s=s||y.inferDtype(n),s==="string"){let a=y.getArrayFromDType(s,y.sizeFromShape(o));return a.fill(n),e.makeTensorInfo(o,s,a)}else{let a=new _v(o,n),i=a.getCustomSetupFunc(n);return e.runWebGLProgram(a,[],s,i)}}var M$={kernelName:Ka,backendName:"webgl",kernelFunc:Rf};var kv=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];
@@ -2862,7 +2862,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
           }
           setOutput(outputValue);
         }
-    `}};var nD={kernelName:Si,backendName:"webgl",kernelFunc:({inputs:r,backend:e})=>{let{image:t}=r,o=e,n=new mv(t.shape);return o.runWebGLProgram(n,[t],t.dtype)}};var sD="return floor(x);",H5=_e({opSnippet:sD,packedOpSnippet:sD,cpuKernelImpl:YA}),iD={kernelName:An,backendName:"webgl",kernelFunc:H5};var q5=`
+    `}};var L$={kernelName:$i,backendName:"webgl",kernelFunc:({inputs:r,backend:e})=>{let{image:t}=r,o=e,n=new kv(t.shape);return o.runWebGLProgram(n,[t],t.dtype)}};var z$="return floor(x);",D8=_e({opSnippet:z$,packedOpSnippet:z$,cpuKernelImpl:E2}),B$={kernelName:Fn,backendName:"webgl",kernelFunc:D8};var $8=`
   float s = sign(a) * sign(b);
   int ia = round(a);
   int ib = round(b);
@@ -2872,7 +2872,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
   } else {
     return NAN;
   }
-`,K5=`
+`,R8=`
   ivec4 ia = round(a);
   ivec4 ib = round(b);
   bvec4 cond = notEqual(ib, ivec4(0));
@@ -2893,7 +2893,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
     result[3] = idiv(ia[3], ib[3], s[3]);
   }
   return vec4(result);
-`,X5=nt({opSnippet:q5,packedOpSnippet:K5,dtype:"int32"}),aD={kernelName:En,backendName:"webgl",kernelFunc:X5};var fv=class{constructor(e){this.variableNames=["A"];let t=Rt(),[o,n]=e;this.outputShape=e,this.userCode=`
+`,F8=nt({opSnippet:$8,packedOpSnippet:R8,dtype:"int32"}),V$={kernelName:On,backendName:"webgl",kernelFunc:F8};var vv=class{constructor(e){this.variableNames=["A"];let t=Rt(),[o,n]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -2915,7 +2915,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
 
         setOutput(floor(value * 255.0 + 0.5));
       }
-    `}};var dv=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=Rt(),[o,n]=e;this.outputShape=e,this.userCode=`
+    `}};var Cv=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=Rt(),[o,n]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -2949,7 +2949,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
 
         ${t.output} = result;
       }
-    `}};var lD={kernelName:um,backendName:"webgl",kernelFunc:Y5},hp;function Y5(r){let{inputs:e,backend:t,attrs:o}=r,{pixels:n}=e,{numChannels:s}=o,a=typeof HTMLVideoElement!="undefined"&&n instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&n instanceof HTMLImageElement,[l,u]=a?[n.videoWidth,n.videoHeight]:[n.width,n.height],c=[u,l],p=[u,l,s];(i||a)&&(hp==null&&(hp=document.createElement("canvas").getContext("2d")),hp.canvas.width=l,hp.canvas.height=u,hp.drawImage(n,0,0,l,u),n=hp.canvas);let m=t.makeTensorInfo(c,"int32");t.texData.get(m.dataId).usage=Dr.PIXELS,t.gpgpu.uploadPixelDataToTexture(t.getTexture(m.dataId),n);let f=W().getBool("WEBGL_PACK")?new dv(p):new fv(p),d=t.runWebGLProgram(f,[m],"int32");return t.disposeData(m.dataId),d}function Z5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s,bias:a,preluActivationWeights:i}=e,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:m,activation:f,leakyreluAlpha:d}=o,h=N.convertConv2DDataFormat(c),g=N.computeConv2DInfo(n.shape,s.shape,l,p,u,m,!1,h),x,b=[];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"))x=Qg({x:n,filter:s,convInfo:g,backend:t,bias:a,activation:f,preluActivationWeights:i,leakyreluAlpha:d});else if(W().getBool("WEBGL_CONV_IM2COL")&&n.shape[0]===1)x=ex({x:n,filter:s,convInfo:g,backend:t,bias:a,activation:f,preluActivationWeights:i,leakyreluAlpha:d});else{let _=a!=null,k=i!=null,D=f==="leakyrelu",T=f?pl(f,!1):null,R=new wf(g,_,T,k,D),O=[n,s];if(a&&O.push(a),i&&O.push(i),D){let M=t.makeTensorInfo([],"float32",y.createScalarValue(d,"float32"));O.push(M),b.push(M)}x=t.runWebGLProgram(R,O,"float32")}let w=pe({inputs:{x},backend:t,attrs:{shape:g.outShape}});return b.push(x),b.forEach(_=>t.disposeIntermediateTensorInfo(_)),w}var uD={kernelName:js,backendName:"webgl",kernelFunc:Z5};function J5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s,bias:a,preluActivationWeights:i}=e,{strides:l,pad:u,dilations:c,dimRoundingMode:p,activation:m,leakyreluAlpha:f}=o,d=[],h=c;h==null&&(h=[1,1]),y.assert(N.eitherStridesOrDilationsAreOne(l,h),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${h}'`);let g=N.computeConv2DInfo(n.shape,s.shape,l,h,u,p,!0),x=W().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels==1,b=m?pl(m,x):null,w=[n,s],_=a!=null,k=i!=null,D=m==="leakyrelu";if(_&&w.push(a),k&&w.push(i),D){let O=t.makeTensorInfo([],"float32",y.createScalarValue(f,"float32"));w.push(O),d.push(O)}let T;x?T=new kf(g,_,b,k,D):T=new _f(g,_,b,k,D);let R=t.runWebGLProgram(T,w,"float32");return d.forEach(O=>t.disposeIntermediateTensorInfo(O)),R}var cD={kernelName:Us,backendName:"webgl",kernelFunc:J5};var hv=class{constructor(e,t,o){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=o;let n=Le(t.length),s=Le(o.length),a=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
+    `}};var G$={kernelName:bm,backendName:"webgl",kernelFunc:O8},wp;function O8(r){let{inputs:e,backend:t,attrs:o}=r,{pixels:n}=e,{numChannels:s}=o,a=typeof HTMLVideoElement!="undefined"&&n instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&n instanceof HTMLImageElement,[l,u]=a?[n.videoWidth,n.videoHeight]:[n.width,n.height],c=[u,l],p=[u,l,s];(i||a)&&(wp==null&&(wp=document.createElement("canvas").getContext("2d")),wp.canvas.width=l,wp.canvas.height=u,wp.drawImage(n,0,0,l,u),n=wp.canvas);let m=t.makeTensorInfo(c,"int32");t.texData.get(m.dataId).usage=$r.PIXELS,t.gpgpu.uploadPixelDataToTexture(t.getTexture(m.dataId),n);let f=W().getBool("WEBGL_PACK")?new Cv(p):new vv(p),d=t.runWebGLProgram(f,[m],"int32");return t.disposeData(m.dataId),d}function P8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s,bias:a,preluActivationWeights:i}=e,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:m,activation:f,leakyreluAlpha:d}=o,h=N.convertConv2DDataFormat(c),g=N.computeConv2DInfo(n.shape,s.shape,l,p,u,m,!1,h),x,b=[];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"))x=ux({x:n,filter:s,convInfo:g,backend:t,bias:a,activation:f,preluActivationWeights:i,leakyreluAlpha:d});else if(W().getBool("WEBGL_CONV_IM2COL")&&n.shape[0]===1)x=cx({x:n,filter:s,convInfo:g,backend:t,bias:a,activation:f,preluActivationWeights:i,leakyreluAlpha:d});else{let _=a!=null,k=i!=null,D=f==="leakyrelu",T=f?gl(f,!1):null,R=new Ef(g,_,T,k,D),O=[n,s];if(a&&O.push(a),i&&O.push(i),D){let M=t.makeTensorInfo([],"float32",y.createScalarValue(d,"float32"));O.push(M),b.push(M)}x=t.runWebGLProgram(R,O,"float32")}let w=pe({inputs:{x},backend:t,attrs:{shape:g.outShape}});return b.push(x),b.forEach(_=>t.disposeIntermediateTensorInfo(_)),w}var W$={kernelName:Xs,backendName:"webgl",kernelFunc:P8};function M8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s,bias:a,preluActivationWeights:i}=e,{strides:l,pad:u,dilations:c,dimRoundingMode:p,activation:m,leakyreluAlpha:f}=o,d=[],h=c;h==null&&(h=[1,1]),y.assert(N.eitherStridesOrDilationsAreOne(l,h),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${h}'`);let g=N.computeConv2DInfo(n.shape,s.shape,l,h,u,p,!0),x=W().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels==1,b=m?gl(m,x):null,w=[n,s],_=a!=null,k=i!=null,D=m==="leakyrelu";if(_&&w.push(a),k&&w.push(i),D){let O=t.makeTensorInfo([],"float32",y.createScalarValue(f,"float32"));w.push(O),d.push(O)}let T;x?T=new $f(g,_,b,k,D):T=new Df(g,_,b,k,D);let R=t.runWebGLProgram(T,w,"float32");return d.forEach(O=>t.disposeIntermediateTensorInfo(O)),R}var j$={kernelName:Ys,backendName:"webgl",kernelFunc:M8};var Iv=class{constructor(e,t,o){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=o;let n=Le(t.length),s=Le(o.length),a=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
         ${n} strides = ${n}(${this.strides});
          void main() {
           ${s} coords = getOutputCoords();
@@ -2960,21 +2960,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
           }
           setOutput(getX(flattenIndex, coords[1]));
         }
-      `}};function Q5(r){let{inputs:e,backend:t}=r,{params:o,indices:n}=e,s=n.shape,a=s[s.length-1],[i,l,u,c]=N.prepareAndValidate(o,n),p=pe({inputs:{x:n},backend:t,attrs:{shape:[l,a]}}),m=pe({inputs:{x:o},backend:t,attrs:{shape:[y.sizeFromShape(o.shape)/u,u]}}),f=new hv(a,c,[l,u]),d=t.runWebGLProgram(f,[m,p],m.dtype),h=pe({inputs:{x:d},backend:t,attrs:{shape:i}});return t.disposeIntermediateTensorInfo(p),t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(d),h}var pD={kernelName:Ti,backendName:"webgl",kernelFunc:Q5};var gv=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let o=Le(this.rank),n=eX(e,2);this.userCode=`
+      `}};function L8(r){let{inputs:e,backend:t}=r,{params:o,indices:n}=e,s=n.shape,a=s[s.length-1],[i,l,u,c]=N.prepareAndValidate(o,n),p=pe({inputs:{x:n},backend:t,attrs:{shape:[l,a]}}),m=pe({inputs:{x:o},backend:t,attrs:{shape:[y.sizeFromShape(o.shape)/u,u]}}),f=new Iv(a,c,[l,u]),d=t.runWebGLProgram(f,[m,p],m.dtype),h=pe({inputs:{x:d},backend:t,attrs:{shape:i}});return t.disposeIntermediateTensorInfo(p),t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(d),h}var U$={kernelName:Ri,backendName:"webgl",kernelFunc:L8};var Nv=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let o=Le(this.rank),n=z8(e,2);this.userCode=`
       void main() {
         ${o} resRC = getOutputCoords();
         setOutput(getA(${n}));
       }
-    `}};function eX(r,e){let t=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[];for(let n=0;n<r.length;n++)n===2?o.push("int(getIndices(resRC.x, resRC.z))"):o.push(`${t[n]}`);return o.join()}function tX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,indices:s}=e,{axis:a,batchDims:i}=o,l=y.parseAxisParam(a,n.shape)[0],u=N.segment_util.collectGatherOpShapeInfo(n,s,l,i),c=y.sizeFromShape(s.shape),p=[],m=pe({inputs:{x:n},backend:t,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),f=pe({inputs:{x:s},backend:t,attrs:{shape:[u.batchSize,c/u.batchSize]}});p.push(m),p.push(f);let d=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(t.shouldExecuteOnCPU([n,s])||n.dtype==="string"){let b=t.bufferSync(f),w=t.bufferSync(m),_=ZA(w,b,d);return p.forEach(k=>t.disposeIntermediateTensorInfo(k)),t.makeTensorInfo(u.outputShape,_.dtype,_.values)}let h=new gv(m.shape,d),g=t.runWebGLProgram(h,[m,f],m.dtype);p.push(g);let x=pe({inputs:{x:g},backend:t,attrs:{shape:u.outputShape}});return p.forEach(b=>t.disposeIntermediateTensorInfo(b)),x}var mD={kernelName:Rs,backendName:"webgl",kernelFunc:tX};var rX="return float(a > b);",oX=`
+    `}};function z8(r,e){let t=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[];for(let n=0;n<r.length;n++)n===2?o.push("int(getIndices(resRC.x, resRC.z))"):o.push(`${t[n]}`);return o.join()}function B8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,indices:s}=e,{axis:a,batchDims:i}=o,l=y.parseAxisParam(a,n.shape)[0],u=N.segment_util.collectGatherOpShapeInfo(n,s,l,i),c=y.sizeFromShape(s.shape),p=[],m=pe({inputs:{x:n},backend:t,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),f=pe({inputs:{x:s},backend:t,attrs:{shape:[u.batchSize,c/u.batchSize]}});p.push(m),p.push(f);let d=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(t.shouldExecuteOnCPU([n,s])||n.dtype==="string"){let b=t.bufferSync(f),w=t.bufferSync(m),_=D2(w,b,d);return p.forEach(k=>t.disposeIntermediateTensorInfo(k)),t.makeTensorInfo(u.outputShape,_.dtype,_.values)}let h=new Nv(m.shape,d),g=t.runWebGLProgram(h,[m,f],m.dtype);p.push(g);let x=pe({inputs:{x:g},backend:t,attrs:{shape:u.outputShape}});return p.forEach(b=>t.disposeIntermediateTensorInfo(b)),x}var H$={kernelName:Ls,backendName:"webgl",kernelFunc:B8};var V8="return float(a > b);",G8=`
   return vec4(greaterThan(a, b));
-`,nX=nt({opSnippet:rX,packedOpSnippet:oX,cpuKernelImpl:JA,dtype:"bool"}),fD={kernelName:Ai,backendName:"webgl",kernelFunc:nX};var sX="return float(a >= b);",iX=`
+`,W8=nt({opSnippet:V8,packedOpSnippet:G8,cpuKernelImpl:$2,dtype:"bool"}),q$={kernelName:Fi,backendName:"webgl",kernelFunc:W8};var j8="return float(a >= b);",U8=`
   return vec4(greaterThanEqual(a, b));
-`,aX=nt({opSnippet:sX,packedOpSnippet:iX,dtype:"bool"}),dD={kernelName:$n,backendName:"webgl",kernelFunc:aX};function lX(r){let{inputs:e,backend:t}=r,{input:o}=e;return nx(o,!0,t)}var hD={kernelName:wc,backendName:"webgl",kernelFunc:lX};var uX="return float(!isnan(x) && !isinf(x));",cX=_e({opSnippet:uX,dtype:"bool"}),gD={kernelName:Ei,backendName:"webgl",kernelFunc:cX};var pX="return float(isinf(x));",mX=_e({opSnippet:pX,dtype:"bool"}),xD={kernelName:Di,backendName:"webgl",kernelFunc:mX};var fX="return float(isnan(x));",dX=_e({opSnippet:fX,dtype:"bool"}),yD={kernelName:$i,backendName:"webgl",kernelFunc:dX};var hX="return float(a < b);",gX=`
+`,H8=nt({opSnippet:j8,packedOpSnippet:U8,dtype:"bool"}),K$={kernelName:Mn,backendName:"webgl",kernelFunc:H8};function q8(r){let{inputs:e,backend:t}=r,{input:o}=e;return dx(o,!0,t)}var X$={kernelName:Ic,backendName:"webgl",kernelFunc:q8};var K8="return float(!isnan(x) && !isinf(x));",X8=_e({opSnippet:K8,dtype:"bool"}),Y$={kernelName:Oi,backendName:"webgl",kernelFunc:X8};var Y8="return float(isinf(x));",Z8=_e({opSnippet:Y8,dtype:"bool"}),Z$={kernelName:Pi,backendName:"webgl",kernelFunc:Z8};var J8="return float(isnan(x));",Q8=_e({opSnippet:J8,dtype:"bool"}),J$={kernelName:Mi,backendName:"webgl",kernelFunc:Q8};var eY="return float(a < b);",tY=`
   return vec4(lessThan(a, b));
-`,xX=nt({opSnippet:hX,packedOpSnippet:gX,cpuKernelImpl:QA,dtype:"bool"}),bD={kernelName:Ri,backendName:"webgl",kernelFunc:xX};var yX="return float(a <= b);",bX=`
+`,rY=nt({opSnippet:eY,packedOpSnippet:tY,cpuKernelImpl:R2,dtype:"bool"}),Q$={kernelName:Li,backendName:"webgl",kernelFunc:rY};var oY="return float(a <= b);",nY=`
   return vec4(lessThanEqual(a, b));
-`,wX=nt({opSnippet:yX,packedOpSnippet:bX,dtype:"bool"}),wD={kernelName:Fi,backendName:"webgl",kernelFunc:wX};function _X(r){let{backend:e,attrs:t}=r,{start:o,stop:n,num:s}=t,a=eE(o,n,s);return e.makeTensorInfo([a.length],"float32",a)}var _D={kernelName:kc,backendName:"webgl",kernelFunc:_X};var kX=`if (x < 0.0) return NAN;
-  return log(x);`,vX=`
+`,sY=nt({opSnippet:oY,packedOpSnippet:nY,dtype:"bool"}),eR={kernelName:zi,backendName:"webgl",kernelFunc:sY};function iY(r){let{backend:e,attrs:t}=r,{start:o,stop:n,num:s}=t,a=F2(o,n,s);return e.makeTensorInfo([a.length],"float32",a)}var tR={kernelName:Sc,backendName:"webgl",kernelFunc:iY};var aY=`if (x < 0.0) return NAN;
+  return log(x);`,lY=`
   vec4 result = log(x);
   vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
   result.r = isNaN.r == 1.0 ? NAN : result.r;
@@ -2983,16 +2983,16 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
   result.a = isNaN.a == 1.0 ? NAN : result.a;
 
   return result;
-`,CX=_e({opSnippet:kX,packedOpSnippet:vX,cpuKernelImpl:tE}),kD={kernelName:Fn,backendName:"webgl",kernelFunc:CX};var IX="return log(1.0 + x);",NX=_e({opSnippet:IX}),vD={kernelName:Oi,backendName:"webgl",kernelFunc:NX};var SX="return float(a >= 1.0 && b >= 1.0);",TX=`
+`,uY=_e({opSnippet:aY,packedOpSnippet:lY,cpuKernelImpl:O2}),rR={kernelName:zn,backendName:"webgl",kernelFunc:uY};var cY="return log(1.0 + x);",pY=_e({opSnippet:cY}),oR={kernelName:Bi,backendName:"webgl",kernelFunc:pY};var mY="return float(a >= 1.0 && b >= 1.0);",fY=`
   return vec4(
     vec4(greaterThanEqual(a, vec4(1.0))) *
     vec4(greaterThanEqual(b, vec4(1.0))));
-`,AX=nt({opSnippet:SX,packedOpSnippet:TX,dtype:"bool"}),CD={kernelName:Pi,backendName:"webgl",kernelFunc:AX};var EX="return float(!(x >= 1.0));",DX=_e({opSnippet:EX}),ID={kernelName:$l,backendName:"webgl",kernelFunc:DX};var $X="return float(a >= 1.0 || b >= 1.0);",RX=`
+`,dY=nt({opSnippet:mY,packedOpSnippet:fY,dtype:"bool"}),nR={kernelName:Vi,backendName:"webgl",kernelFunc:dY};var hY="return float(!(x >= 1.0));",gY=_e({opSnippet:hY}),sR={kernelName:Ml,backendName:"webgl",kernelFunc:gY};var xY="return float(a >= 1.0 || b >= 1.0);",yY=`
   return min(
     vec4(greaterThanEqual(a, vec4(1.0))) +
     vec4(greaterThanEqual(b, vec4(1.0))),
     vec4(1.0));
-`,FX=nt({opSnippet:$X,packedOpSnippet:RX,dtype:"bool"}),ND={kernelName:Rl,backendName:"webgl",kernelFunc:FX};var xv=class{constructor(e,t,o,n,s){this.variableNames=["x"],this.outputShape=[];let a=t,i=e[3]-1;this.outputShape=e;let l,u=`float(${o}) + float(${n}) * sum`;s===.5?l=`inversesqrt(${u})`:s===1?l=`1.0/(${u})`:l=`exp(log(${u}) * float(-${s}));`,this.userCode=`
+`,bY=nt({opSnippet:xY,packedOpSnippet:yY,dtype:"bool"}),iR={kernelName:Ll,backendName:"webgl",kernelFunc:bY};var Sv=class{constructor(e,t,o,n,s){this.variableNames=["x"],this.outputShape=[];let a=t,i=e[3]-1;this.outputShape=e;let l,u=`float(${o}) + float(${n}) * sum`;s===.5?l=`inversesqrt(${u})`:s===1?l=`1.0/(${u})`:l=`exp(log(${u}) * float(-${s}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3011,7 +3011,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         float val = x * ${l};
         setOutput(val);
       }
-    `}};var yv=class{constructor(e,t,o,n,s){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let a=t,i=e[3]-1;this.outputShape=e;let l,u=`float(${o}) + float(${n}) * sum`;s===.5?l=`inversesqrt(${u})`:s===1?l=`1.0/(${u})`:l=`exp(log(${u}) * float(-${s}));`,this.userCode=`
+    `}};var Tv=class{constructor(e,t,o,n,s){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let a=t,i=e[3]-1;this.outputShape=e;let l,u=`float(${o}) + float(${n}) * sum`;s===.5?l=`inversesqrt(${u})`:s===1?l=`1.0/(${u})`:l=`exp(log(${u}) * float(-${s}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords.x;
@@ -3073,7 +3073,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         vec4 result = xAtOutputCoords * ${l};
         setOutput(result);
       }
-    `}};var OX=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{depthRadius:s,bias:a,alpha:i,beta:l}=o,u=W().getBool("WEBGL_PACK_NORMALIZATION")?new yv(n.shape,s,a,i,l):new xv(n.shape,s,a,i,l);return t.runWebGLProgram(u,[n],n.dtype)},SD={kernelName:ja,backendName:"webgl",kernelFunc:OX};var bv=class{constructor(e,t,o,n,s){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=o,this.alpha=n,this.beta=s,this.userCode=`
+    `}};var wY=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{depthRadius:s,bias:a,alpha:i,beta:l}=o,u=W().getBool("WEBGL_PACK_NORMALIZATION")?new Tv(n.shape,s,a,i,l):new Sv(n.shape,s,a,i,l);return t.runWebGLProgram(u,[n],n.dtype)},aR={kernelName:Xa,backendName:"webgl",kernelFunc:wY};var Av=class{constructor(e,t,o,n,s){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=o,this.alpha=n,this.beta=s,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3128,14 +3128,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
       }
       setOutput(result);
       }
-    `}};var PX=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n,y:s,dy:a}=e,{depthRadius:i,bias:l,alpha:u,beta:c}=o,p=new bv(n.shape,i,l,u,c);return t.runWebGLProgram(p,[n,s,a],n.dtype)},TD={kernelName:vc,backendName:"webgl",kernelFunc:PX};function AD(r,e,t,o){let n=y.sizeFromShape(e),a=y.sizeFromShape(r.shape)/n,i=pe({inputs:{x:r},attrs:{shape:[a,n]},backend:o}),l=vo(i,r.dtype,"max",o),u=pe({inputs:{x:l},attrs:{shape:t},backend:o});return o.disposeIntermediateTensorInfo(i),o.disposeIntermediateTensorInfo(l),u}function wv(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{reductionIndices:s,keepDims:a}=o,i=n.shape.length,l=y.parseAxisParam(s,n.shape),u=l,c=N.getAxesPermutation(u,i),p=c!=null,m=t.shouldExecuteOnCPU([n]),f=n;if(p){if(m){let w=t.texData.get(f.dataId).values,_=new Array(i);for(let T=0;T<_.length;T++)_[T]=n.shape[c[T]];let k=ku(w,n.shape,n.dtype,c,_);f=t.makeTensorInfo(_,n.dtype);let D=t.texData.get(f.dataId);D.values=k}else f=ml(n,c,t);u=N.getInnerMostAxes(u.length,i)}N.assertAxesAreInnerMostDims("max",u,i);let[d,h]=N.computeOutAndReduceShapes(f.shape,u),g=d;a&&(g=N.expandShapeToKeepDim(d,l));let x;if(m){let w=t.texData.get(f.dataId).values,_=rE(w,y.sizeFromShape(h),g,n.dtype);x=t.makeTensorInfo(g,n.dtype);let k=t.texData.get(x.dataId);k.values=_}else x=AD(f,h,g,t);return p&&t.disposeIntermediateTensorInfo(f),x}var ED={kernelName:On,backendName:"webgl",kernelFunc:wv};var MX=Hg+`
+    `}};var _Y=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n,y:s,dy:a}=e,{depthRadius:i,bias:l,alpha:u,beta:c}=o,p=new Av(n.shape,i,l,u,c);return t.runWebGLProgram(p,[n,s,a],n.dtype)},lR={kernelName:Tc,backendName:"webgl",kernelFunc:_Y};function uR(r,e,t,o){let n=y.sizeFromShape(e),a=y.sizeFromShape(r.shape)/n,i=pe({inputs:{x:r},attrs:{shape:[a,n]},backend:o}),l=To(i,r.dtype,"max",o),u=pe({inputs:{x:l},attrs:{shape:t},backend:o});return o.disposeIntermediateTensorInfo(i),o.disposeIntermediateTensorInfo(l),u}function Ev(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{reductionIndices:s,keepDims:a}=o,i=n.shape.length,l=y.parseAxisParam(s,n.shape),u=l,c=N.getAxesPermutation(u,i),p=c!=null,m=t.shouldExecuteOnCPU([n]),f=n;if(p){if(m){let w=t.texData.get(f.dataId).values,_=new Array(i);for(let T=0;T<_.length;T++)_[T]=n.shape[c[T]];let k=Su(w,n.shape,n.dtype,c,_);f=t.makeTensorInfo(_,n.dtype);let D=t.texData.get(f.dataId);D.values=k}else f=xl(n,c,t);u=N.getInnerMostAxes(u.length,i)}N.assertAxesAreInnerMostDims("max",u,i);let[d,h]=N.computeOutAndReduceShapes(f.shape,u),g=d;a&&(g=N.expandShapeToKeepDim(d,l));let x;if(m){let w=t.texData.get(f.dataId).values,_=P2(w,y.sizeFromShape(h),g,n.dtype);x=t.makeTensorInfo(g,n.dtype);let k=t.texData.get(x.dataId);k.values=_}else x=uR(f,h,g,t);return p&&t.disposeIntermediateTensorInfo(f),x}var cR={kernelName:Bn,backendName:"webgl",kernelFunc:Ev};var kY=rx+`
   return max(a, b);
-`,LX=`
+`,vY=`
   vec4 result = vec4(max(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+cl+`
+  `+hl+`
   return result;
-`,zX=nt({opSnippet:MX,packedOpSnippet:LX,cpuKernelImpl:oE}),DD={kernelName:Pn,backendName:"webgl",kernelFunc:zX};function BX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e;gs(n,"maxPool");let{filterSize:s,strides:a,pad:i,dimRoundingMode:l}=o,u=1;y.assert(N.eitherStridesOrDilationsAreOne(a,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=N.computePool2DInfo(n.shape,s,a,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&y.arraysEqual(c.inShape,c.outShape))return Wt({inputs:{x:n},backend:t});let p=new ti(c,"max",!1);return t.runWebGLProgram(p,[n],n.dtype)}var $D={kernelName:Mn,backendName:"webgl",kernelFunc:BX};function VX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{filterSize:s,strides:a,pad:i,dataFormat:l,dimRoundingMode:u}=o,c=[1,1,1],p=N.computePool3DInfo(n.shape,s,a,c,i,u,l),m=new Cu(p,"max",!1);return t.runWebGLProgram(m,[n],n.dtype)}var RD={kernelName:Ua,backendName:"webgl",kernelFunc:VX};var _v=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,o=e.strideWidth,n=e.dilationHeight,s=e.effectiveFilterHeight,a=e.effectiveFilterWidth,i=s-1-e.padInfo.top,l=a-1-e.padInfo.left,u=s*a-1;this.userCode=`
+`,CY=nt({opSnippet:kY,packedOpSnippet:vY,cpuKernelImpl:M2}),pR={kernelName:Vn,backendName:"webgl",kernelFunc:CY};function IY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e;_s(n,"maxPool");let{filterSize:s,strides:a,pad:i,dimRoundingMode:l}=o,u=1;y.assert(N.eitherStridesOrDilationsAreOne(a,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=N.computePool2DInfo(n.shape,s,a,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&y.arraysEqual(c.inShape,c.outShape))return Wt({inputs:{x:n},backend:t});let p=new ii(c,"max",!1);return t.runWebGLProgram(p,[n],n.dtype)}var mR={kernelName:Gn,backendName:"webgl",kernelFunc:IY};function NY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{filterSize:s,strides:a,pad:i,dataFormat:l,dimRoundingMode:u}=o,c=[1,1,1],p=N.computePool3DInfo(n.shape,s,a,c,i,u,l),m=new Au(p,"max",!1);return t.runWebGLProgram(m,[n],n.dtype)}var fR={kernelName:Ya,backendName:"webgl",kernelFunc:NY};var Dv=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,o=e.strideWidth,n=e.dilationHeight,s=e.effectiveFilterHeight,a=e.effectiveFilterWidth,i=s-1-e.padInfo.top,l=a-1-e.padInfo.left,u=s*a-1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${l});
 
       void main() {
@@ -3181,7 +3181,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},kv=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,o=e.strideHeight,n=e.strideWidth,s=e.dilationDepth,a=e.dilationHeight,i=e.dilationWidth,l=e.effectiveFilterDepth,u=e.effectiveFilterHeight,c=e.effectiveFilterWidth,p=l-1-e.padInfo.front,m=u-1-e.padInfo.top,f=c-1-e.padInfo.left,d=l*u*c-1;this.userCode=`
+    `}},$v=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,o=e.strideHeight,n=e.strideWidth,s=e.dilationDepth,a=e.dilationHeight,i=e.dilationWidth,l=e.effectiveFilterDepth,u=e.effectiveFilterHeight,c=e.effectiveFilterWidth,p=l-1-e.padInfo.front,m=u-1-e.padInfo.top,f=c-1-e.padInfo.left,d=l*u*c-1;this.userCode=`
       const ivec3 pads = ivec3(${p}, ${m}, ${f});
 
       void main() {
@@ -3245,14 +3245,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function GX(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=o,p=[1,1,1],m=N.computePool3DInfo(a.shape,i,l,p,u,c),f=new Cu(m,"max",!0),d=t.runWebGLProgram(f,[a],a.dtype),h=new kv(m),g=t.runWebGLProgram(h,[n,d],a.dtype);return t.disposeIntermediateTensorInfo(d),g}var FD={kernelName:Ic,backendName:"webgl",kernelFunc:GX};function WX(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s,output:a}=e,i=s;gs([s,a],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:p}=o,m=N.computePool2DInfo(i.shape,l,u,1,c,p),f=!0,d=new ti(m,"max",f),h=t.runWebGLProgram(d,[i],i.dtype),g=new _v(m),x=t.runWebGLProgram(g,[n,h],i.dtype);return t.disposeIntermediateTensorInfo(h),x}var OD={kernelName:Cc,backendName:"webgl",kernelFunc:WX};function PD(r,e,t,o){let n=new ti(t,"max",!1),s=o.runWebGLProgram(n,[r],"float32");n=new ti(t,"max",!0,!0,e);let a=o.runWebGLProgram(n,[r],"float32");return[s,a]}var MD={kernelName:Nc,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{x:o}=r,{filterSize:n,strides:s,pad:a,includeBatchInIndex:i}=e,l=t;y.assert(o.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${o.shape.length}.`);let u=[1,1];y.assert(N.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let c=N.computePool2DInfo(o.shape,n,s,u,a),[p,m]=PD(o,i,c,l);return[p,m]}};function LD(r,e,t,o){let n=y.sizeFromShape(e),a=y.sizeFromShape(r.shape)/n,i=pe({inputs:{x:r},attrs:{shape:[a,n]},backend:o}),l=vo(i,"float32","mean",o),u=pe({inputs:{x:l},attrs:{shape:t},backend:o});return o.disposeIntermediateTensorInfo(i),o.disposeIntermediateTensorInfo(l),u}var zD={kernelName:Ln,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{x:o}=r,{keepDims:n,axis:s}=e,a=t,i=o.shape.length,l=y.parseAxisParam(s,o.shape),u=l,c=N.getAxesPermutation(u,i),p=c!=null,m=a.shouldExecuteOnCPU([o]),f=[],d=o;if(p){if(m){let _=a.texData.get(d.dataId).values,k=new Array(i);for(let R=0;R<k.length;R++)k[R]=o.shape[c[R]];let D=ku(_,o.shape,o.dtype,c,k);d=a.makeTensorInfo(k,o.dtype);let T=a.texData.get(d.dataId);T.values=D}else d=ml(o,c,a);f.push(d),u=N.getInnerMostAxes(u.length,i)}N.assertAxesAreInnerMostDims("sum",u,i);let[h,g]=N.computeOutAndReduceShapes(d.shape,u),x=h;n&&(x=N.expandShapeToKeepDim(h,l));let b=LD(d,g,x,a);for(let w of f)a.disposeIntermediateTensorInfo(w);return b}};function jX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,l=y.parseAxisParam(s,n.shape),u=l,c=N.getAxesPermutation(u,i),p=n;c!=null&&(p=Mt({inputs:{x:n},backend:t,attrs:{perm:c}}),u=N.getInnerMostAxes(u.length,n.shape.length)),N.assertAxesAreInnerMostDims("min",u,i);let[m,f]=N.computeOutAndReduceShapes(p.shape,u),d=y.sizeFromShape(f),h=pe({inputs:{x:p},backend:t,attrs:{shape:[-1,d]}}),g=vo(h,h.dtype,"min",t),x;if(a){let b=N.expandShapeToKeepDim(m,l);x=pe({inputs:{x:g},backend:t,attrs:{shape:b}})}else x=pe({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(p),x}var BD={kernelName:zn,backendName:"webgl",kernelFunc:jX};var UX=Hg+`
+    `}};function SY(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=o,p=[1,1,1],m=N.computePool3DInfo(a.shape,i,l,p,u,c),f=new Au(m,"max",!0),d=t.runWebGLProgram(f,[a],a.dtype),h=new $v(m),g=t.runWebGLProgram(h,[n,d],a.dtype);return t.disposeIntermediateTensorInfo(d),g}var dR={kernelName:Ec,backendName:"webgl",kernelFunc:SY};function TY(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s,output:a}=e,i=s;_s([s,a],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:p}=o,m=N.computePool2DInfo(i.shape,l,u,1,c,p),f=!0,d=new ii(m,"max",f),h=t.runWebGLProgram(d,[i],i.dtype),g=new Dv(m),x=t.runWebGLProgram(g,[n,h],i.dtype);return t.disposeIntermediateTensorInfo(h),x}var hR={kernelName:Ac,backendName:"webgl",kernelFunc:TY};function gR(r,e,t,o){let n=new ii(t,"max",!1),s=o.runWebGLProgram(n,[r],"float32");n=new ii(t,"max",!0,!0,e);let a=o.runWebGLProgram(n,[r],"float32");return[s,a]}var xR={kernelName:Dc,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{x:o}=r,{filterSize:n,strides:s,pad:a,includeBatchInIndex:i}=e,l=t;y.assert(o.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${o.shape.length}.`);let u=[1,1];y.assert(N.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let c=N.computePool2DInfo(o.shape,n,s,u,a),[p,m]=gR(o,i,c,l);return[p,m]}};function yR(r,e,t,o){let n=y.sizeFromShape(e),a=y.sizeFromShape(r.shape)/n,i=pe({inputs:{x:r},attrs:{shape:[a,n]},backend:o}),l=To(i,"float32","mean",o),u=pe({inputs:{x:l},attrs:{shape:t},backend:o});return o.disposeIntermediateTensorInfo(i),o.disposeIntermediateTensorInfo(l),u}var bR={kernelName:Wn,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{x:o}=r,{keepDims:n,axis:s}=e,a=t,i=o.shape.length,l=y.parseAxisParam(s,o.shape),u=l,c=N.getAxesPermutation(u,i),p=c!=null,m=a.shouldExecuteOnCPU([o]),f=[],d=o;if(p){if(m){let _=a.texData.get(d.dataId).values,k=new Array(i);for(let R=0;R<k.length;R++)k[R]=o.shape[c[R]];let D=Su(_,o.shape,o.dtype,c,k);d=a.makeTensorInfo(k,o.dtype);let T=a.texData.get(d.dataId);T.values=D}else d=xl(o,c,a);f.push(d),u=N.getInnerMostAxes(u.length,i)}N.assertAxesAreInnerMostDims("sum",u,i);let[h,g]=N.computeOutAndReduceShapes(d.shape,u),x=h;n&&(x=N.expandShapeToKeepDim(h,l));let b=yR(d,g,x,a);for(let w of f)a.disposeIntermediateTensorInfo(w);return b}};function AY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,l=y.parseAxisParam(s,n.shape),u=l,c=N.getAxesPermutation(u,i),p=n;c!=null&&(p=Mt({inputs:{x:n},backend:t,attrs:{perm:c}}),u=N.getInnerMostAxes(u.length,n.shape.length)),N.assertAxesAreInnerMostDims("min",u,i);let[m,f]=N.computeOutAndReduceShapes(p.shape,u),d=y.sizeFromShape(f),h=pe({inputs:{x:p},backend:t,attrs:{shape:[-1,d]}}),g=To(h,h.dtype,"min",t),x;if(a){let b=N.expandShapeToKeepDim(m,l);x=pe({inputs:{x:g},backend:t,attrs:{shape:b}})}else x=pe({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(p),x}var wR={kernelName:jn,backendName:"webgl",kernelFunc:AY};var EY=rx+`
   return min(a, b);
-`,HX=`
+`,DY=`
   vec4 result = vec4(min(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+cl+`
+  `+hl+`
   return result;
-`,qX=nt({opSnippet:UX,packedOpSnippet:HX,cpuKernelImpl:nE}),VD={kernelName:Bn,backendName:"webgl",kernelFunc:qX};var vv=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=t.map((c,p)=>c[0]+e[p]+c[1]);let n=e.length,s=Le(n),a=t.map(c=>c[0]).join(","),i=t.map((c,p)=>c[0]+e[p]).join(","),l=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n),u=o==="reflect"?0:1;if(n===1){this.userCode=`
+`,$Y=nt({opSnippet:EY,packedOpSnippet:DY,cpuKernelImpl:L2}),_R={kernelName:Un,backendName:"webgl",kernelFunc:$Y};var Rv=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=t.map((c,p)=>c[0]+e[p]+c[1]);let n=e.length,s=Le(n),a=t.map(c=>c[0]).join(","),i=t.map((c,p)=>c[0]+e[p]).join(","),l=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n),u=o==="reflect"?0:1;if(n===1){this.userCode=`
         int start = ${a};
         int end = ${i};
 
@@ -3281,7 +3281,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         ${s} coords = outC - start;
         setOutput(getX(${l}));
       }
-    `}};var Cv=class{constructor(e,t,o){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((d,h)=>d[0]+e[h]+d[1]);let n=e.length,s=Le(n),a=t.map(d=>d[0]).join(","),i=t.map((d,h)=>d[0]+e[h]).join(","),l=Gt("rc",n),u=Gt("source",n),c=`${l[n-1]} < ${this.outputShape[n-1]}`,p=n===1?"source":`vec2(${u.slice(-2).join()})`,m=o==="reflect"?0:1,f="";if(n===1){let d=`
+    `}};var Fv=class{constructor(e,t,o){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((d,h)=>d[0]+e[h]+d[1]);let n=e.length,s=Le(n),a=t.map(d=>d[0]).join(","),i=t.map((d,h)=>d[0]+e[h]).join(","),l=Gt("rc",n),u=Gt("source",n),c=`${l[n-1]} < ${this.outputShape[n-1]}`,p=n===1?"source":`vec2(${u.slice(-2).join()})`,m=o==="reflect"?0:1,f="";if(n===1){let d=`
         ${s} source = rc;
         if (source < start) {
           source = start * 2 - source - ${m};
@@ -3337,13 +3337,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         ${f}
         setOutput(result);
       }
-    `}};var KX=({inputs:r,backend:e,attrs:t})=>{let{x:o}=r,{paddings:n,mode:s}=t,a=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Cv(o.shape,n,s):new vv(o.shape,n,s);return e.runWebGLProgram(a,[o],o.dtype)},GD={kernelName:Ha,backendName:"webgl",kernelFunc:KX};var XX=`if (b == 0.0) return NAN;
-  return mod(a, b);`,YX=`
+    `}};var RY=({inputs:r,backend:e,attrs:t})=>{let{x:o}=r,{paddings:n,mode:s}=t,a=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Fv(o.shape,n,s):new Rv(o.shape,n,s);return e.runWebGLProgram(a,[o],o.dtype)},kR={kernelName:Za,backendName:"webgl",kernelFunc:RY};var FY=`if (b == 0.0) return NAN;
+  return mod(a, b);`,OY=`
   vec4 result = mod(a, b);
   vec4 isNaN = vec4(equal(b, vec4(0.0)));
-  `+cl+`
+  `+hl+`
   return result;
-`,ZX=nt({opSnippet:XX,packedOpSnippet:YX}),WD={kernelName:Mi,backendName:"webgl",kernelFunc:ZX};var Iv=class{constructor(e,t,o){this.variableNames=["probs"],this.outputShape=[e,o],this.userCode=`
+`,PY=nt({opSnippet:FY,packedOpSnippet:OY}),vR={kernelName:Gi,backendName:"webgl",kernelFunc:PY};var Ov=class{constructor(e,t,o){this.variableNames=["probs"],this.outputShape=[e,o],this.userCode=`
       uniform float seed;
 
       void main() {
@@ -3365,11 +3365,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,J6=_e({opSnippet:Z6}),i2={kernelNam
         // If no other event happened, last event happened.
         setOutput(float(${t-1}));
       }
-    `}getCustomSetupFunc(e){return(t,o)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(o,"seed")),t.gl.uniform1f(this.seedLoc,e)}}};var JX=`
+    `}getCustomSetupFunc(e){return(t,o)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(o,"seed")),t.gl.uniform1f(this.seedLoc,e)}}};var MY=`
 if (a == b) {
   return 1.0;
 };
-return a / b;`,QX=`
+return a / b;`,LY=`
   // vec4 one = vec4(equal(a, b));
   // return one + (vec4(1.0) - one) * a / b;
   vec4 result = a / b;
@@ -3387,14 +3387,14 @@ return a / b;`,QX=`
   }
 
   return result;
-`,Nv=nt({opSnippet:JX,packedOpSnippet:QX,checkOutOfBounds:!0}),jD={kernelName:Sn,backendName:"webgl",kernelFunc:Nv};var UD="return a - b;",Sv=nt({opSnippet:UD,packedOpSnippet:UD,supportsComplex:!0,cpuKernelImpl:mE}),HD={kernelName:ns,backendName:"webgl",kernelFunc:Sv};function Tv(r){let{inputs:e,backend:t,attrs:o}=r,{logits:n}=e,{dim:s}=o,a=y.parseAxisParam([s],n.shape),i=wv({inputs:{x:n},backend:t,attrs:{reductionIndices:a,keepDims:!1}}),l=N.expandShapeToKeepDim(i.shape,a),u=pe({inputs:{x:i},backend:t,attrs:{shape:l}}),c=Sv({inputs:{a:n,b:u},backend:t}),p=cv({inputs:{x:c},backend:t}),m=bf({inputs:{x:p},backend:t,attrs:{axis:a,keepDims:!1}}),f=pe({inputs:{x:m},backend:t,attrs:{shape:l}}),d=Nv({inputs:{a:p,b:f},backend:t});return t.disposeIntermediateTensorInfo(i),t.disposeIntermediateTensorInfo(u),t.disposeIntermediateTensorInfo(c),t.disposeIntermediateTensorInfo(p),t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(f),d}var qD={kernelName:rs,backendName:"webgl",kernelFunc:Tv};function e8(r){let{inputs:e,backend:t,attrs:o}=r,{logits:n}=e,{numSamples:s,seed:a,normalized:i}=o,l=i?n:Tv({inputs:{logits:n},backend:t,attrs:{dim:n.shape.length-1}}),u=l.shape[0],c=l.shape[1],p=new Iv(u,c,s),m=p.getCustomSetupFunc(a),f=t.runWebGLProgram(p,[l],"int32",m);return i||t.disposeIntermediateTensorInfo(l),f}var KD={kernelName:Sc,backendName:"webgl",kernelFunc:e8};var XD="return -x;";function t8(r){let{inputs:e,backend:t}=r,{x:o}=e;if(t.shouldExecuteOnCPU([o])){let s=t.texData.get(o.dataId),[a,i]=iE(s.values,o.shape,o.dtype);return t.makeTensorInfo(i,o.dtype,a)}let n;return W().getBool("WEBGL_PACK_UNARY_OPERATIONS")?n=new ys(o.shape,XD):n=new ao(o.shape,XD),t.runWebGLProgram(n,[o],o.dtype)}var YD={kernelName:Fs,backendName:"webgl",kernelFunc:t8};var r8=Ar.nonMaxSuppressionV3Impl;function o8(r){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:l}=o,u=t.readSync(n.dataId),c=t.readSync(s.dataId),{selectedIndices:p}=r8(u,c,a,i,l);return t.makeTensorInfo([p.length],"int32",new Int32Array(p))}var ZD={kernelName:zi,backendName:"webgl",kernelFunc:o8};var n8=Ar.nonMaxSuppressionV4Impl;function s8(r){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=o,c=t.readSync(n.dataId),p=t.readSync(s.dataId),{selectedIndices:m,validOutputs:f}=n8(c,p,a,i,l,u);return[t.makeTensorInfo([m.length],"int32",new Int32Array(m)),t.makeTensorInfo([],"int32",new Int32Array([f]))]}var JD={kernelName:Bi,backendName:"webgl",kernelFunc:s8};var i8=Ar.nonMaxSuppressionV5Impl;function a8(r){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=o,c=t.readSync(n.dataId),p=t.readSync(s.dataId),m=a,f=i,d=l,h=u,{selectedIndices:g,selectedScores:x}=i8(c,p,m,f,d,h);return[t.makeTensorInfo([g.length],"int32",new Int32Array(g)),t.makeTensorInfo([x.length],"float32",new Float32Array(x))]}var QD={kernelName:Vi,backendName:"webgl",kernelFunc:a8};var Av=class{constructor(e,t,o,n){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
+`,Pv=nt({opSnippet:MY,packedOpSnippet:LY,checkOutOfBounds:!0}),CR={kernelName:$n,backendName:"webgl",kernelFunc:Pv};var IR="return a - b;",Mv=nt({opSnippet:IR,packedOpSnippet:IR,supportsComplex:!0,cpuKernelImpl:H2}),NR={kernelName:us,backendName:"webgl",kernelFunc:Mv};function Lv(r){let{inputs:e,backend:t,attrs:o}=r,{logits:n}=e,{dim:s}=o,a=y.parseAxisParam([s],n.shape),i=Ev({inputs:{x:n},backend:t,attrs:{reductionIndices:a,keepDims:!1}}),l=N.expandShapeToKeepDim(i.shape,a),u=pe({inputs:{x:i},backend:t,attrs:{shape:l}}),c=Mv({inputs:{a:n,b:u},backend:t}),p=wv({inputs:{x:c},backend:t}),m=Af({inputs:{x:p},backend:t,attrs:{axis:a,keepDims:!1}}),f=pe({inputs:{x:m},backend:t,attrs:{shape:l}}),d=Pv({inputs:{a:p,b:f},backend:t});return t.disposeIntermediateTensorInfo(i),t.disposeIntermediateTensorInfo(u),t.disposeIntermediateTensorInfo(c),t.disposeIntermediateTensorInfo(p),t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(f),d}var SR={kernelName:as,backendName:"webgl",kernelFunc:Lv};function zY(r){let{inputs:e,backend:t,attrs:o}=r,{logits:n}=e,{numSamples:s,seed:a,normalized:i}=o,l=i?n:Lv({inputs:{logits:n},backend:t,attrs:{dim:n.shape.length-1}}),u=l.shape[0],c=l.shape[1],p=new Ov(u,c,s),m=p.getCustomSetupFunc(a),f=t.runWebGLProgram(p,[l],"int32",m);return i||t.disposeIntermediateTensorInfo(l),f}var TR={kernelName:$c,backendName:"webgl",kernelFunc:zY};var AR="return -x;";function BY(r){let{inputs:e,backend:t}=r,{x:o}=e;if(t.shouldExecuteOnCPU([o])){let s=t.texData.get(o.dataId),[a,i]=B2(s.values,o.shape,o.dtype);return t.makeTensorInfo(i,o.dtype,a)}let n;return W().getBool("WEBGL_PACK_UNARY_OPERATIONS")?n=new vs(o.shape,AR):n=new mo(o.shape,AR),t.runWebGLProgram(n,[o],o.dtype)}var ER={kernelName:zs,backendName:"webgl",kernelFunc:BY};var VY=Er.nonMaxSuppressionV3Impl;function GY(r){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:l}=o,u=t.readSync(n.dataId),c=t.readSync(s.dataId),{selectedIndices:p}=VY(u,c,a,i,l);return t.makeTensorInfo([p.length],"int32",new Int32Array(p))}var DR={kernelName:ji,backendName:"webgl",kernelFunc:GY};var WY=Er.nonMaxSuppressionV4Impl;function jY(r){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=o,c=t.readSync(n.dataId),p=t.readSync(s.dataId),{selectedIndices:m,validOutputs:f}=WY(c,p,a,i,l,u);return[t.makeTensorInfo([m.length],"int32",new Int32Array(m)),t.makeTensorInfo([],"int32",new Int32Array([f]))]}var $R={kernelName:Ui,backendName:"webgl",kernelFunc:jY};var UY=Er.nonMaxSuppressionV5Impl;function HY(r){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=o,c=t.readSync(n.dataId),p=t.readSync(s.dataId),m=a,f=i,d=l,h=u,{selectedIndices:g,selectedScores:x}=UY(c,p,m,f,d,h);return[t.makeTensorInfo([g.length],"int32",new Int32Array(g)),t.makeTensorInfo([x.length],"float32",new Float32Array(x))]}var RR={kernelName:Hi,backendName:"webgl",kernelFunc:HY};var zv=class{constructor(e,t,o,n){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int index = round(getIndices(coords.x));
         setOutput(mix(float(${n}), float(${o}),
                       float(index == coords.y)));
       }
-    `}};var l8=r=>{let{inputs:e,backend:t,attrs:o}=r,{indices:n}=e,{depth:s,onValue:a,offValue:i}=o,l=y.sizeFromShape(n.shape),u=new Av(l,s,a,i),c=pe({inputs:{x:n},backend:t,attrs:{shape:[l]}}),p=t.runWebGLProgram(u,[c],n.dtype);t.disposeIntermediateTensorInfo(c);let m=[...n.shape,s],f=pe({inputs:{x:p},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(p),f},e$={kernelName:Gn,backendName:"webgl",kernelFunc:l8};function Cf(r){let{inputs:e,backend:t}=r,{x:o}=e;if(o.dtype==="complex64"){let n=ka({inputs:{input:o},backend:t}),s=Cf({inputs:{x:n},backend:t}),a=Iu({inputs:{input:o},backend:t}),i=Cf({inputs:{x:a},backend:t}),l=lo({inputs:{real:s,imag:i},backend:t});return t.disposeIntermediateTensorInfo(n),t.disposeIntermediateTensorInfo(s),t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(i),l}else return vf({attrs:{shape:o.shape,dtype:o.dtype,value:o.dtype==="string"?"":0},backend:t})}var t$={kernelName:Gs,backendName:"webgl",kernelFunc:Cf};function r$(r){let{inputs:e,backend:t}=r,{x:o}=e;if(o.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(o.dtype==="complex64"){let n=ka({inputs:{input:o},backend:t}),s=r$({inputs:{x:n},backend:t}),a=Iu({inputs:{input:o},backend:t}),i=Cf({inputs:{x:a},backend:t}),l=lo({inputs:{real:s,imag:i},backend:t});return t.disposeIntermediateTensorInfo(n),t.disposeIntermediateTensorInfo(s),t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(i),l}else return vf({attrs:{shape:o.shape,dtype:o.dtype,value:1},backend:t})}var o$={kernelName:Os,backendName:"webgl",kernelFunc:r$};function u8(r){let{inputs:e,backend:t,attrs:o}=r,{axis:n}=o;if(e.length===1)return rx({inputs:{input:e[0]},backend:t,attrs:{dim:n}});let s=e[0].shape,a=e[0].dtype;e.forEach(c=>{y.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),y.assert(a===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=e.map(c=>{let p=rx({inputs:{input:c},backend:t,attrs:{dim:n}});return i.push(p),p}),u=Zk({inputs:l,backend:t,attrs:{axis:n}});return i.forEach(c=>t.disposeIntermediateTensorInfo(c)),u}var n$={kernelName:Ps,backendName:"webgl",kernelFunc:u8};var Ev=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let n=e.length,s=Le(n),a=t.map(u=>u[0]).join(","),i=t.map((u,c)=>u[0]+e[c]).join(","),l=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n);if(n===1){this.userCode=`
+    `}};var qY=r=>{let{inputs:e,backend:t,attrs:o}=r,{indices:n}=e,{depth:s,onValue:a,offValue:i}=o,l=y.sizeFromShape(n.shape),u=new zv(l,s,a,i),c=pe({inputs:{x:n},backend:t,attrs:{shape:[l]}}),p=t.runWebGLProgram(u,[c],n.dtype);t.disposeIntermediateTensorInfo(c);let m=[...n.shape,s],f=pe({inputs:{x:p},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(p),f},FR={kernelName:qn,backendName:"webgl",kernelFunc:qY};function Ff(r){let{inputs:e,backend:t}=r,{x:o}=e;if(o.dtype==="complex64"){let n=Sa({inputs:{input:o},backend:t}),s=Ff({inputs:{x:n},backend:t}),a=Eu({inputs:{input:o},backend:t}),i=Ff({inputs:{x:a},backend:t}),l=fo({inputs:{real:s,imag:i},backend:t});return t.disposeIntermediateTensorInfo(n),t.disposeIntermediateTensorInfo(s),t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(i),l}else return Rf({attrs:{shape:o.shape,dtype:o.dtype,value:o.dtype==="string"?"":0},backend:t})}var OR={kernelName:qs,backendName:"webgl",kernelFunc:Ff};function PR(r){let{inputs:e,backend:t}=r,{x:o}=e;if(o.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(o.dtype==="complex64"){let n=Sa({inputs:{input:o},backend:t}),s=PR({inputs:{x:n},backend:t}),a=Eu({inputs:{input:o},backend:t}),i=Ff({inputs:{x:a},backend:t}),l=fo({inputs:{real:s,imag:i},backend:t});return t.disposeIntermediateTensorInfo(n),t.disposeIntermediateTensorInfo(s),t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(i),l}else return Rf({attrs:{shape:o.shape,dtype:o.dtype,value:1},backend:t})}var MR={kernelName:Bs,backendName:"webgl",kernelFunc:PR};function KY(r){let{inputs:e,backend:t,attrs:o}=r,{axis:n}=o;if(e.length===1)return mx({inputs:{input:e[0]},backend:t,attrs:{dim:n}});let s=e[0].shape,a=e[0].dtype;e.forEach(c=>{y.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),y.assert(a===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=e.map(c=>{let p=mx({inputs:{input:c},backend:t,attrs:{dim:n}});return i.push(p),p}),u=av({inputs:l,backend:t,attrs:{axis:n}});return i.forEach(c=>t.disposeIntermediateTensorInfo(c)),u}var LR={kernelName:Vs,backendName:"webgl",kernelFunc:KY};var Bv=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let n=e.length,s=Le(n),a=t.map(u=>u[0]).join(","),i=t.map((u,c)=>u[0]+e[c]).join(","),l=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n);if(n===1){this.userCode=`
         int start = ${a};
         int end = ${i};
         uniform float value;
@@ -3421,7 +3421,7 @@ return a / b;`,QX=`
           setOutput(getX(${l}));
         }
       }
-    `}getCustomSetupFunc(e){return(t,o)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(o,"value")),t.gl.uniform1f(this.valueLoc,e)}}};var Dv=class{constructor(e,t,o){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((h,g)=>h[0]+e[g]+h[1]);let n=e.length,s=Le(n),a=t.map(h=>h[0]).join(","),i=t.map((h,g)=>h[0]+e[g]).join(","),l=Gt("rc",n),u=Gt("source",n),c=`${l[n-1]} < ${this.outputShape[n-1]}`,p=n===1?"source":`vec2(${u.slice(-2).join()})`,m=[`${s} rc = outputLoc;`,`${l[n-1]} += 1;
+    `}getCustomSetupFunc(e){return(t,o)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(o,"value")),t.gl.uniform1f(this.valueLoc,e)}}};var Vv=class{constructor(e,t,o){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((h,g)=>h[0]+e[g]+h[1]);let n=e.length,s=Le(n),a=t.map(h=>h[0]).join(","),i=t.map((h,g)=>h[0]+e[g]).join(","),l=Gt("rc",n),u=Gt("source",n),c=`${l[n-1]} < ${this.outputShape[n-1]}`,p=n===1?"source":`vec2(${u.slice(-2).join()})`,m=[`${s} rc = outputLoc;`,`${l[n-1]} += 1;
        if(${c}) {
       `,n===1?"":`}
        rc = outputLoc;
@@ -3446,7 +3446,7 @@ return a / b;`,QX=`
         ${d}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){return(t,o)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(o,"value")),t.gl.uniform1f(this.valueLoc,e)}}};var $v=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{paddings:s,constantValue:a}=o,i=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Dv(n.shape,s,a):new Ev(n.shape,s,a),l=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[n],n.dtype,l)},s$={kernelName:Wn,backendName:"webgl",kernelFunc:$v};var c8=`
+    `}getCustomSetupFunc(e){return(t,o)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(o,"value")),t.gl.uniform1f(this.valueLoc,e)}}};var Gv=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{paddings:s,constantValue:a}=o,i=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Vv(n.shape,s,a):new Bv(n.shape,s,a),l=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[n],n.dtype,l)},zR={kernelName:Kn,backendName:"webgl",kernelFunc:Gv};var XY=`
   if(a < 0.0 && floor(b) < b){
     return NAN;
   }
@@ -3455,7 +3455,7 @@ return a / b;`,QX=`
   }
   return (round(mod(b, 2.0)) != 1) ?
       pow(abs(a), b) : sign(a) * pow(abs(a), b);
-`,p8=`
+`,YY=`
   // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
   vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
   vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
@@ -3469,11 +3469,11 @@ return a / b;`,QX=`
   result.a = isExpZero.a ? 1.0 : result.a;
 
   vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
-  `+cl+`
+  `+hl+`
   return result;
-`,m8=nt({opSnippet:c8,packedOpSnippet:p8}),i$={kernelName:jn,backendName:"webgl",kernelFunc:m8};function f8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,l=[],u=y.parseAxisParam(s,n.shape),c=u,p=N.getAxesPermutation(c,i),m=n;p!=null&&(m=Mt({inputs:{x:n},backend:t,attrs:{perm:p}}),c=N.getInnerMostAxes(c.length,i),l.push(m)),N.assertAxesAreInnerMostDims("prod",c,i);let f;if(t.shouldExecuteOnCPU([m])){let d=t.texData.get(m.dataId).values,{outVals:h,outShape:g,outDtype:x}=aE(m.shape,m.dtype,d,c);f=t.makeTensorInfo(g,x,h)}else{let[d,h]=N.computeOutAndReduceShapes(m.shape,c),g=y.sizeFromShape(h),x=pe({inputs:{x:m},backend:t,attrs:{shape:[-1,g]}}),b=Pl(n.dtype),w=vo(x,b,"prod",t);f=pe({inputs:{x:w},backend:t,attrs:{shape:d}}),l.push(x),l.push(w)}if(a){l.push(f);let d=N.expandShapeToKeepDim(f.shape,u);f=pe({inputs:{x:f},backend:t,attrs:{shape:d}})}return l.forEach(d=>t.disposeIntermediateTensorInfo(d)),f}var a$={kernelName:Gi,backendName:"webgl",kernelFunc:f8};var Rv=r=>{let{backend:e,attrs:t}=r,{start:o,stop:n,step:s,dtype:a}=t,i=lE(o,n,s,a);return e.makeTensorInfo([i.length],a,i)},l$={kernelName:qa,backendName:"webgl",kernelFunc:Rv};var d8="return 1.0 / x;",h8=_e({opSnippet:d8}),u$={kernelName:Wi,backendName:"webgl",kernelFunc:h8};var g8=gr+`
+`,ZY=nt({opSnippet:XY,packedOpSnippet:YY}),BR={kernelName:Xn,backendName:"webgl",kernelFunc:ZY};function JY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,l=[],u=y.parseAxisParam(s,n.shape),c=u,p=N.getAxesPermutation(c,i),m=n;p!=null&&(m=Mt({inputs:{x:n},backend:t,attrs:{perm:p}}),c=N.getInnerMostAxes(c.length,i),l.push(m)),N.assertAxesAreInnerMostDims("prod",c,i);let f;if(t.shouldExecuteOnCPU([m])){let d=t.texData.get(m.dataId).values,{outVals:h,outShape:g,outDtype:x}=V2(m.shape,m.dtype,d,c);f=t.makeTensorInfo(g,x,h)}else{let[d,h]=N.computeOutAndReduceShapes(m.shape,c),g=y.sizeFromShape(h),x=pe({inputs:{x:m},backend:t,attrs:{shape:[-1,g]}}),b=Vl(n.dtype),w=To(x,b,"prod",t);f=pe({inputs:{x:w},backend:t,attrs:{shape:d}}),l.push(x),l.push(w)}if(a){l.push(f);let d=N.expandShapeToKeepDim(f.shape,u);f=pe({inputs:{x:f},backend:t,attrs:{shape:d}})}return l.forEach(d=>t.disposeIntermediateTensorInfo(d)),f}var VR={kernelName:qi,backendName:"webgl",kernelFunc:JY};var Wv=r=>{let{backend:e,attrs:t}=r,{start:o,stop:n,step:s,dtype:a}=t,i=G2(o,n,s,a);return e.makeTensorInfo([i.length],a,i)},GR={kernelName:Ja,backendName:"webgl",kernelFunc:Wv};var QY="return 1.0 / x;",e7=_e({opSnippet:QY}),WR={kernelName:Ki,backendName:"webgl",kernelFunc:e7};var t7=gr+`
   return (x < 0.0) ? 0.0 : x;
-`,x8=`
+`,r7=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3483,9 +3483,9 @@ return a / b;`,QX=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,y8=_e({opSnippet:g8,packedOpSnippet:x8}),c$={kernelName:Hn,backendName:"webgl",kernelFunc:y8};var b8=gr+`
+`,o7=_e({opSnippet:t7,packedOpSnippet:r7}),jR={kernelName:Zn,backendName:"webgl",kernelFunc:o7};var n7=gr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,w8=`
+`,s7=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3495,7 +3495,7 @@ return a / b;`,QX=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,_8=_e({opSnippet:b8,packedOpSnippet:w8}),p$={kernelName:Kn,backendName:"webgl",kernelFunc:_8};var Fv=class{constructor(e,t,o,n,s){this.variableNames=["A"],this.outputShape=[];let[a,i,l,u]=e;this.outputShape=[a,t,o,u];let c=[n&&t>1?i-1:i,n&&o>1?l-1:l],p=[n&&t>1?t-1:t,n&&o>1?o-1:o],m;s?m="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":m="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+`,i7=_e({opSnippet:n7,packedOpSnippet:s7}),UR={kernelName:Qn,backendName:"webgl",kernelFunc:i7};var jv=class{constructor(e,t,o,n,s){this.variableNames=["A"],this.outputShape=[];let[a,i,l,u]=e;this.outputShape=[a,t,o,u];let c=[n&&t>1?i-1:i,n&&o>1?l-1:l],p=[n&&t>1?t-1:t,n&&o>1?o-1:o],m;s?m="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":m="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
           ${c[0]/p[0]},
           ${c[1]/p[1]});
@@ -3528,7 +3528,7 @@ return a / b;`,QX=`
 
         setOutput(newValue);
       }
-    `}};var Ov=class{constructor(e,t,o,n,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[a,i,l,u]=e;this.outputShape=[a,t,o,u];let c=[n&&t>1?i-1:i,n&&o>1?l-1:l],p=[n&&t>1?t-1:t,n&&o>1?o-1:o],m;s?m="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":m="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}};var Uv=class{constructor(e,t,o,n,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[a,i,l,u]=e;this.outputShape=[a,t,o,u];let c=[n&&t>1?i-1:i,n&&o>1?l-1:l],p=[n&&t>1?t-1:t,n&&o>1?o-1:o],m;s?m="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":m="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec3 effectiveInputOverOutputRatioRC = vec3(
           ${c[0]/p[0]},
           ${c[1]/p[1]},
@@ -3605,7 +3605,7 @@ return a / b;`,QX=`
 
         setOutput(newValue);
       }
-    `}};function k8(r){let{inputs:e,backend:t,attrs:o}=r,{images:n}=e,{alignCorners:s,halfPixelCenters:a,size:i}=o,[l,u]=i,c=W().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Ov(n.shape,l,u,s,a):new Fv(n.shape,l,u,s,a);return t.runWebGLProgram(c,[n],"float32")}var m$={kernelName:qn,backendName:"webgl",kernelFunc:k8};var Pv=class{constructor(e,t,o){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,s]=t,[,a,i]=e,l=[o&&a>1?n-1:n,o&&i>1?s-1:s],u=[o&&a>1?a-1:a,o&&i>1?i-1:i],c=l[0]/u[0],p=l[1]/u[1],m=1/c,f=1/p,d=Math.ceil(m)*2+2,h=Math.ceil(f)*2+2;this.userCode=`
+    `}};function a7(r){let{inputs:e,backend:t,attrs:o}=r,{images:n}=e,{alignCorners:s,halfPixelCenters:a,size:i}=o,[l,u]=i,c=W().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Uv(n.shape,l,u,s,a):new jv(n.shape,l,u,s,a);return t.runWebGLProgram(c,[n],"float32")}var HR={kernelName:Jn,backendName:"webgl",kernelFunc:a7};var Hv=class{constructor(e,t,o){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,s]=t,[,a,i]=e,l=[o&&a>1?n-1:n,o&&i>1?s-1:s],u=[o&&a>1?a-1:a,o&&i>1?i-1:i],c=l[0]/u[0],p=l[1]/u[1],m=1/c,f=1/p,d=Math.ceil(m)*2+2,h=Math.ceil(f)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3686,7 +3686,7 @@ return a / b;`,QX=`
 
         setOutput(accumulator);
       }
-    `}};function v8(r){let{inputs:e,backend:t,attrs:o}=r,{images:n,dy:s}=e,{alignCorners:a}=o,i=new Pv(s.shape,n.shape,a);return t.runWebGLProgram(i,[s],s.dtype)}var f$={kernelName:Ec,backendName:"webgl",kernelFunc:v8};var Mv=class{constructor(e,t,o,n,s){this.variableNames=["A"],this.outputShape=[];let[a,i,l,u]=e;this.outputShape=[a,t,o,u];let c=[n&&t>1?i-1:i,n&&o>1?l-1:l],p=[n&&t>1?t-1:t,n&&o>1?o-1:o],m=n?"0.5":"0.0",f;s?f="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":f="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}};function l7(r){let{inputs:e,backend:t,attrs:o}=r,{images:n,dy:s}=e,{alignCorners:a}=o,i=new Hv(s.shape,n.shape,a);return t.runWebGLProgram(i,[s],s.dtype)}var qR={kernelName:Oc,backendName:"webgl",kernelFunc:l7};var qv=class{constructor(e,t,o,n,s){this.variableNames=["A"],this.outputShape=[];let[a,i,l,u]=e;this.outputShape=[a,t,o,u];let c=[n&&t>1?i-1:i,n&&o>1?l-1:l],p=[n&&t>1?t-1:t,n&&o>1?o-1:o],m=n?"0.5":"0.0",f;s?f="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":f="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
           ${c[0]/p[0]},
           ${c[1]/p[1]});
@@ -3708,7 +3708,7 @@ return a / b;`,QX=`
 
         setOutput(newValue);
       }
-    `}};function C8(r){let{inputs:e,backend:t,attrs:o}=r,{images:n}=e,{alignCorners:s,halfPixelCenters:a,size:i}=o,[l,u]=i,c=new Mv(n.shape,l,u,s,a);return t.runWebGLProgram(c,[n],n.dtype)}var d$={kernelName:Ka,backendName:"webgl",kernelFunc:C8};var Lv=class{constructor(e,t,o){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,s]=t,[,a,i]=e,l=[o&&a>1?n-1:n,o&&i>1?s-1:s],u=[o&&a>1?a-1:a,o&&i>1?i-1:i],c=l[0]/u[0],p=l[1]/u[1],m=1/c,f=1/p,d=Math.ceil(m)*2+2,h=Math.ceil(f)*2+2;this.userCode=`
+    `}};function u7(r){let{inputs:e,backend:t,attrs:o}=r,{images:n}=e,{alignCorners:s,halfPixelCenters:a,size:i}=o,[l,u]=i,c=new qv(n.shape,l,u,s,a);return t.runWebGLProgram(c,[n],n.dtype)}var KR={kernelName:Qa,backendName:"webgl",kernelFunc:u7};var Kv=class{constructor(e,t,o){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,s]=t,[,a,i]=e,l=[o&&a>1?n-1:n,o&&i>1?s-1:s],u=[o&&a>1?a-1:a,o&&i>1?i-1:i],c=l[0]/u[0],p=l[1]/u[1],m=1/c,f=1/p,d=Math.ceil(m)*2+2,h=Math.ceil(f)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3778,7 +3778,7 @@ return a / b;`,QX=`
 
         setOutput(accumulator);
       }
-    `}};function I8(r){let{inputs:e,backend:t,attrs:o}=r,{images:n,dy:s}=e,{alignCorners:a}=o,i=new Lv(s.shape,n.shape,a);return t.runWebGLProgram(i,[s],s.dtype)}var h$={kernelName:Ac,backendName:"webgl",kernelFunc:I8};var zv=class{constructor(e,t){this.variableNames=["x"];let o=e.length;if(o>4)throw new Error(`WebGL backend: Reverse of rank-${o} tensor is not yet supported`);if(this.outputShape=e,o===1){this.userCode=`
+    `}};function c7(r){let{inputs:e,backend:t,attrs:o}=r,{images:n,dy:s}=e,{alignCorners:a}=o,i=new Kv(s.shape,n.shape,a);return t.runWebGLProgram(i,[s],s.dtype)}var XR={kernelName:Fc,backendName:"webgl",kernelFunc:c7};var Xv=class{constructor(e,t){this.variableNames=["x"];let o=e.length;if(o>4)throw new Error(`WebGL backend: Reverse of rank-${o} tensor is not yet supported`);if(this.outputShape=e,o===1){this.userCode=`
         void main() {
           int coord = getOutputCoords();
           setOutput(getX(${e[0]} - coord - 1));
@@ -3788,7 +3788,7 @@ return a / b;`,QX=`
         ${a} coords = getOutputCoords();
         setOutput(getX(${s}));
       }
-    `}};var Bv=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let o=e.length;if(o>4)throw new Error(`WebGL backend: Reverse of rank-${o} tensor is not yet supported`);this.outputShape=e;let n=Gt("rc",o),s=`${n[o-1]} + 1 < ${this.outputShape[o-1]}`,a=`${n[o-2]} + 1 < ${this.outputShape[o-2]}`,i=Le(o);o===1?this.userCode=`
+    `}};var Yv=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let o=e.length;if(o>4)throw new Error(`WebGL backend: Reverse of rank-${o} tensor is not yet supported`);this.outputShape=e;let n=Gt("rc",o),s=`${n[o-1]} + 1 < ${this.outputShape[o-1]}`,a=`${n[o-2]} + 1 < ${this.outputShape[o-2]}`,i=Le(o);o===1?this.userCode=`
         void main(){
           int rc = getOutputCoords();
           vec4 result = vec4(0.);
@@ -3816,7 +3816,7 @@ return a / b;`,QX=`
           }
           setOutput(result);
         }
-    `;function l(d){return m(d)}function u(d){return d[o-1]="("+d[o-1]+" + 1)",m(d)}function c(d){return d[o-2]="("+d[o-2]+" + 1)",m(d)}function p(d){return d[o-1]="("+d[o-1]+" + 1)",d[o-2]="("+d[o-2]+" + 1)",m(d)}function m(d){let h=e.map((b,w)=>f(w,d)),g=h.join(","),x=h.slice(-2).join(",");return`getChannel(getX(${g}), vec2(${x}))`}function f(d,h){return t.indexOf(d)!==-1&&e[d]!==1?`${e[d]} - ${h[d]} - 1`:`${h[d]}`}}};function N8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{dims:s}=o,a=n.shape.length,i=y.parseAxisParam(s,n.shape);if(a===0)return Wt({inputs:{x:n},backend:t});let l=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Bv(n.shape,i):new zv(n.shape,i);return t.runWebGLProgram(l,[n],n.dtype)}var g$={kernelName:Xn,backendName:"webgl",kernelFunc:N8};var Vv=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let o=e[1],n=e[2];this.outputShape=e;let s="";typeof t=="number"?s=`float outputValue = ${t.toFixed(2)};`:s=`
+    `;function l(d){return m(d)}function u(d){return d[o-1]="("+d[o-1]+" + 1)",m(d)}function c(d){return d[o-2]="("+d[o-2]+" + 1)",m(d)}function p(d){return d[o-1]="("+d[o-1]+" + 1)",d[o-2]="("+d[o-2]+" + 1)",m(d)}function m(d){let h=e.map((b,w)=>f(w,d)),g=h.join(","),x=h.slice(-2).join(",");return`getChannel(getX(${g}), vec2(${x}))`}function f(d,h){return t.indexOf(d)!==-1&&e[d]!==1?`${e[d]} - ${h[d]} - 1`:`${h[d]}`}}};function p7(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{dims:s}=o,a=n.shape.length,i=y.parseAxisParam(s,n.shape);if(a===0)return Wt({inputs:{x:n},backend:t});let l=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Yv(n.shape,i):new Xv(n.shape,i);return t.runWebGLProgram(l,[n],n.dtype)}var YR={kernelName:es,backendName:"webgl",kernelFunc:p7};var Zv=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let o=e[1],n=e[2];this.outputShape=e;let s="";typeof t=="number"?s=`float outputValue = ${t.toFixed(2)};`:s=`
         vec3 fill = vec3(${t.join(",")});
         float outputValue = fill[coords[3]];`,this.userCode=`
         uniform vec4 params;
@@ -3836,7 +3836,7 @@ return a / b;`,QX=`
           }
           setOutput(outputValue);
         }
-    `}getCustomSetupFunc(e,t,o,n){return(s,a)=>{this.paramsLoc==null&&(this.paramsLoc=s.getUniformLocationNoThrow(a,"params")),s.gl.uniform4f(this.paramsLoc,e,t,o,n)}}};var x$={kernelName:Ji,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{image:o}=r,{radians:n,fillValue:s,center:a}=e,i=t,l=new Vv(o.shape,s),[u,c]=N.getImageCenter(a,o.shape[1],o.shape[2]),p=l.getCustomSetupFunc(u,c,Math.sin(n),Math.cos(n));return i.runWebGLProgram(l,[o],o.dtype,p)}};var S8=`
+    `}getCustomSetupFunc(e,t,o,n){return(s,a)=>{this.paramsLoc==null&&(this.paramsLoc=s.getUniformLocationNoThrow(a,"params")),s.gl.uniform4f(this.paramsLoc,e,t,o,n)}}};var ZR={kernelName:oa,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{image:o}=r,{radians:n,fillValue:s,center:a}=e,i=t,l=new Zv(o.shape,s),[u,c]=N.getImageCenter(a,o.shape[1],o.shape[2]),p=l.getCustomSetupFunc(u,c,Math.sin(n),Math.cos(n));return i.runWebGLProgram(l,[o],o.dtype,p)}};var m7=`
   // OpenGL ES does not support round function.
   // The algorithm is based on banker's rounding.
   float base = floor(x);
@@ -3851,7 +3851,7 @@ return a / b;`,QX=`
       return base + 1.0;
     }
   }
-`,T8=_e({opSnippet:S8}),y$={kernelName:Yn,backendName:"webgl",kernelFunc:T8};var A8="return inversesqrt(x);",E8=_e({opSnippet:A8,cpuKernelImpl:uE}),b$={kernelName:Zn,backendName:"webgl",kernelFunc:E8};var If=class{constructor(e,t,o,n,s,a,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;let l=Le(s.length),u=Le(a.length),c="";o===1?c="i":o===2&&(c="i, j");let p=`getIndices(${c})`,m="";n===1?m="i":n===2&&(m="i, coords[1]");let f=`getUpdates(${m})`,d=t>1?"strides[j]":"strides";this.userCode=`
+`,f7=_e({opSnippet:m7}),JR={kernelName:ts,backendName:"webgl",kernelFunc:f7};var d7="return inversesqrt(x);",h7=_e({opSnippet:d7,cpuKernelImpl:W2}),QR={kernelName:rs,backendName:"webgl",kernelFunc:h7};var Of=class{constructor(e,t,o,n,s,a,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;let l=Le(s.length),u=Le(a.length),c="";o===1?c="i":o===2&&(c="i, j");let p=`getIndices(${c})`,m="";n===1?m="i":n===2&&(m="i, coords[1]");let f=`getUpdates(${m})`,d=t>1?"strides[j]":"strides";this.userCode=`
         ${l} strides = ${l}(${s});
 
         void main() {
@@ -3871,7 +3871,7 @@ return a / b;`,QX=`
           }
           setOutput(mix(getDefaultValue(), sum, float(found)));
         }
-      `}};function D8(r){let{inputs:e,backend:t,attrs:o}=r,{indices:n,updates:s}=e,{shape:a}=o,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:p}=N.calculateShapes(s,n,a),m=[p/u,u];if(p===0)return t.makeTensorInfo(a,n.dtype);let f=pe({inputs:{x:n},backend:t,attrs:{shape:[l,i]}}),d=pe({inputs:{x:s},backend:t,attrs:{shape:[l,u]}}),h=t.makeTensorInfo([],"float32",new Float32Array([0])),g=new If(l,i,f.shape.length,d.shape.length,c,m),x=t.runWebGLProgram(g,[d,f,h],d.dtype),b=pe({inputs:{x},backend:t,attrs:{shape:a}});return t.disposeIntermediateTensorInfo(f),t.disposeIntermediateTensorInfo(d),t.disposeIntermediateTensorInfo(x),t.disposeIntermediateTensorInfo(h),b}var w$={kernelName:ji,backendName:"webgl",kernelFunc:D8};var Gv=class{constructor(e,t,o){this.variableNames=["c","a","b"],this.outputShape=t;let n,s;if(o>4)throw Error(`Where for rank ${o} is not yet supported`);if(o===1)s="resRC",n="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],l=[],u=[];for(let c=0;c<t.length;c++)u.push(`${i[c]}`),c<e&&l.push(`${i[c]}`);n=l.join(),s=u.join()}let a=Le(o);this.userCode=`
+      `}};function g7(r){let{inputs:e,backend:t,attrs:o}=r,{indices:n,updates:s}=e,{shape:a}=o,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:p}=N.calculateShapes(s,n,a),m=[p/u,u];if(p===0)return t.makeTensorInfo(a,n.dtype);let f=pe({inputs:{x:n},backend:t,attrs:{shape:[l,i]}}),d=pe({inputs:{x:s},backend:t,attrs:{shape:[l,u]}}),h=t.makeTensorInfo([],"float32",new Float32Array([0])),g=new Of(l,i,f.shape.length,d.shape.length,c,m),x=t.runWebGLProgram(g,[d,f,h],d.dtype),b=pe({inputs:{x},backend:t,attrs:{shape:a}});return t.disposeIntermediateTensorInfo(f),t.disposeIntermediateTensorInfo(d),t.disposeIntermediateTensorInfo(x),t.disposeIntermediateTensorInfo(h),b}var eF={kernelName:Xi,backendName:"webgl",kernelFunc:g7};var Jv=class{constructor(e,t,o){this.variableNames=["c","a","b"],this.outputShape=t;let n,s;if(o>4)throw Error(`Where for rank ${o} is not yet supported`);if(o===1)s="resRC",n="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],l=[],u=[];for(let c=0;c<t.length;c++)u.push(`${i[c]}`),c<e&&l.push(`${i[c]}`);n=l.join(),s=u.join()}let a=Le(o);this.userCode=`
       void main() {
         ${a} resRC = getOutputCoords();
         float cVal = getC(${n});
@@ -3881,21 +3881,21 @@ return a / b;`,QX=`
           setOutput(getB(${s}));
         }
       }
-    `}};function $8(r){let{inputs:e,backend:t}=r,{condition:o,t:n,e:s}=e,a=new Gv(o.shape.length,n.shape,n.shape.length);return t.runWebGLProgram(a,[o,n,s],ir(n.dtype,s.dtype))}var _$={kernelName:Ls,backendName:"webgl",kernelFunc:$8};var R8=`
+    `}};function x7(r){let{inputs:e,backend:t}=r,{condition:o,t:n,e:s}=e,a=new Jv(o.shape.length,n.shape,n.shape.length);return t.runWebGLProgram(a,[o,n,s],ir(n.dtype,s.dtype))}var tF={kernelName:Ws,backendName:"webgl",kernelFunc:x7};var y7=`
   // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
   // see: https://arxiv.org/abs/1706.02515
   float scaleAlpha = ${N.SELU_SCALEALPHA};
   float scale = ${N.SELU_SCALE};
   return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
-`,F8=_e({opSnippet:R8}),k$={kernelName:Ui,backendName:"webgl",kernelFunc:F8};var O8="return 1.0 / (1.0 + exp(-1.0 * x));",P8=_e({opSnippet:O8}),v$={kernelName:Qn,backendName:"webgl",kernelFunc:P8};var M8=`
+`,b7=_e({opSnippet:y7}),rF={kernelName:Yi,backendName:"webgl",kernelFunc:b7};var w7="return 1.0 / (1.0 + exp(-1.0 * x));",_7=_e({opSnippet:w7}),oF={kernelName:ns,backendName:"webgl",kernelFunc:_7};var k7=`
   if (isnan(x)) { return 0.0; }
   return sign(x);
-`,L8=_e({opSnippet:M8}),C$={kernelName:qi,backendName:"webgl",kernelFunc:L8};var z8=qg+`
+`,v7=_e({opSnippet:k7}),nF={kernelName:Ji,backendName:"webgl",kernelFunc:v7};var C7=ox+`
   return sin(x);
-`,B8=_e({opSnippet:z8}),I$={kernelName:Jn,backendName:"webgl",kernelFunc:B8};var V8=`
+`,I7=_e({opSnippet:C7}),sF={kernelName:os,backendName:"webgl",kernelFunc:I7};var N7=`
   float e2x = exp(x);
   return (e2x - 1.0 / e2x) / 2.0;
-`,G8=_e({opSnippet:V8}),N$={kernelName:Hi,backendName:"webgl",kernelFunc:G8};var W8=`
+`,S7=_e({opSnippet:N7}),iF={kernelName:Zi,backendName:"webgl",kernelFunc:S7};var T7=`
   float epsilon = 1.1920928955078125e-7;
   float threshold = log(epsilon) + 2.0;
 
@@ -3915,9 +3915,9 @@ return a / b;`,QX=`
     result = log(exp_x + 1.0);
   }
   return result;
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@@ -3925,15 +3925,15 @@ return a / b;`,QX=`
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@@ -4045,7 +4045,7 @@ return a / b;`,QX=`
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@@ -4151,19 +4151,19 @@ return a / b;`,QX=`
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r){let{sorted:a,recipientMap:i}=eL(s,e);for(let l of a)n.has(l.name)||(t.push(l),n.add(l.name));for(let l in i)o[l]==null&&(o[l]=new Set),i[l].forEach(u=>o[l].add(u))}}return{sorted:t,recipientCounts:$9(o)}}function $9(r){let e={};for(let t in r)e[t]=r[t].size;return e}function eL(r,e){let t=new Set,o=[],n={};for(let i of e.names())t.add(i);let s=[],a=[];for(s.push(r);s.length>0;){let i=s[s.length-1];if(t.has(i.name)){s.pop();continue}let l=a[a.length-1]===s.length-1;if(i.inputs.length===0||l)s.pop(),o.push(i),t.add(i.name),l&&a.pop();else{a.push(s.length-1);for(let u of i.inputs)n[u.name]==null&&(n[u.name]=new Set),n[u.name].add(i.name),!t.has(u.name)&&s.push(u)}}return{sorted:o,recipientMap:n}}function D9(r){let e;if(r.sourceLayer.inboundNodes.length===1)e=r.sourceLayer.output;else{let t=null;for(let o=0;o<r.sourceLayer.inboundNodes.length;++o)for(let n of r.sourceLayer.inboundNodes[o].outputTensors)if(n.id===r.id){t=o;break}e=r.sourceLayer.getOutputAt(t)}return e}var Mo=class 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All inputs should only appear once. Found: ${this.inputs.map(b=>b.name)}`);cn(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(b=>b.name)}`),this.inputLayers=[],this.inputLayersNodeIndices=[],this.inputLayersTensorIndices=[],this.outputLayers=[],this.outputLayersNodeIndices=[],this.outputLayersTensorIndices=[],this.layers=[],this.internalContainerRefs=[];for(let b of this.outputs){let w=b.sourceLayer,_=b.nodeIndex,k=b.tensorIndex;this.outputLayers.push(w),this.outputLayersNodeIndices.push(_),this.outputLayersTensorIndices.push(k)}for(let b of this.inputs){let w=b.sourceLayer,_=b.nodeIndex,k=b.tensorIndex;Po(_===0,"input layer has >1 nodes"),Po(k===0,"input layer has >1 tensors"),this.inputLayers.push(w),this.inputLayersNodeIndices.push(_),this.inputLayersTensorIndices.push(k)}this.inputNames=[],this.outputNames=[],this.feedInputShapes=[],this.feedInputNames=[],this.feedOutputNames=[];for(let b=0;b<this.inputLayers.length;b++){let w=this.inputLayers[b];if(!(w instanceof ni))throw new TypeError(`Input layers to a LayersModel must be InputLayer objects. Received inputs: ${e.inputs}. Input ${b} (0-based) originates from layer type ${w.getClassName()}.`);this.inputNames.push(w.name),this.feedInputShapes.push(w.batchInputShape),this.feedInputNames.push(w.name)}for(let b of this.outputLayers)this.outputNames.push(b.name);this.internalInputShapes=this.inputs.map(b=>b.shape),this.internalOutputShapes=this.outputs.map(b=>b.shape);let t={},o={},n={},s={},a={},i=[],l=(b,w,_,k,D,T)=>{(k==null||D==null||T==null)&&(k=b.sourceLayer,D=b.nodeIndex,T=b.tensorIndex);let R=k.inboundNodes[D];if(_.indexOf(R)!==-1)throw new Lr(`The tensor ${b.name} at layer "${k.name}" is part of a cycle.`);if(w.indexOf(R)!==-1)return;this.containerNodes.add(Mo.nodeKey(k,D)),k.id in a||(a[k.id]=Object.keys(a).length),_.indexOf(R)===-1&&_.push(R);let O=R.inboundLayers.length;for(let M=0;M<O;M++){let G=R.inputTensors[M],j=R.inboundLayers[M],U=R.nodeIndices[M],H=R.tensorIndices[M];l(G,w,_,j,U,H)}for(w.push(R);_.indexOf(R)>=0;)_.splice(_.indexOf(R),1);i.push(R)},u=[],c=[];for(let b of this.outputs)l(b,u,c);let p=i.slice().reverse();for(let b of p){o[b.id]=b,b.id in t||(t[b.id]=0);let w=t[b.id],_=n[b.outboundLayer.id]==null?0:n[b.outboundLayer.id];w=Math.max(w,_),n[b.outboundLayer.id]=w,s[b.outboundLayer.id]=b.outboundLayer,t[b.id]=w;for(let k=0;k<b.inboundLayers.length;k++){let D=b.inboundLayers[k],T=b.nodeIndices[k],R=D.inboundNodes[T],O=t[R.id]==null?0:t[R.id];t[R.id]=Math.max(w+1,O),o[R.id]=R}}let m={};for(let b in t){let w=t[b];w in m||(m[w]=[]),m[w].push(o[b])}let f={};for(let b in n){let w=n[b];w in f||(f[w]=[]),f[w].push(s[b])}let d=Object.keys(f).map(b=>parseInt(b,10)).sort(Ef);this.layers=[];for(let b of d){let w=f[b];w.sort((_,k)=>{let D=a[_.id],T=a[k.id];return D<T?-1:D>T?1:0});for(let _ of w)_ instanceof Mo&&this.internalContainerRefs.push(_),this.layers.push(_)}this.layersByDepth=f,d=Object.keys(m).map(b=>parseInt(b,10)).sort(Ef);let h=this.inputs.slice(),g=[];for(let b of d)for(let w of m[b]){let _=w.outboundLayer;if(_!=null){for(let k of w.inputTensors)if(h.indexOf(k)===-1)throw new Lr(`Graph disconnected: cannot obtain value for tensor ${k} at layer "${_.name}". The following previous layers were accessed without issue: ${g}`);for(let k of w.outputTensors)h.push(k);g.push(_.name)}}this.nodesByDepth=m;let x=this.layers.map(b=>b.name);for(let b of x){let w=x.filter(_=>_===b).length;if(w!==1)throw new Lr(`The name "${b}" is used ${w} times in the model. All layer names should be unique. Layer names: `+JSON.stringify(x))}this.outboundNodes=[],this.inboundNodes=[],new gl({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:this.inputs.map(b=>null),outputMasks:this.outputs.map(b=>null),inputShapes:this.inputs.map(b=>b.shape),outputShapes:this.outputs.map(b=>b.shape)}),this.built=!0,this._refCount=1}assertNotDisposed(){if(this._refCount===0)throw new Error(`Container '${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(o=>o.trainable=e)}),this.trainable_=e}get trainableWeights(){if(this._trainableWeights.length>0)throw new z("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 o of this.layers)t.push(...o.trainableWeights);return t.concat(e)}return e}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}loadWeights(e,t=!0){let o={},n=0;for(let a of this.layers)for(let i of a.weights){if(o[i.originalName]!=null)throw new z(`Duplicate weight name: ${i.originalName}`);o[i.originalName]=i,n++}let s=[];for(let a in e){let i=a;if(o[a]==null){let l=a.split("/");i=l.slice(0,-2).concat([l[l.length-1]]).join("/")}if(o[i]!=null)s.push([o[i],e[a]]);else if(t)throw new z(`Provided weight data has no target variable: ${a}`);delete o[i]}if(t){let a=[];for(let i in o)a.push(i);if(a.length>0)throw new z(`${a.length} of ${n} weights are not set: ${a}`)}$p(s)}updatedConfig(){let e=this.getConfig(),t={};return t.className=this.getClassName(),t.config=e,t.kerasVersion=`tfjs-layers ${Jf}`,t.backend="TensorFlow.js",t}toJSON(e,t=!0){let o=Dx(this.updatedConfig());return t?JSON.stringify(o):o}call(e,t){return V(()=>{e=yt(e);let o=new ks;for(let n=0;n<this.inputs.length;++n)o.add(this.inputs[n],e[n]);return Ou(this.outputs,o,t)})}computeMask(e,t){return V(()=>{e=yt(e);let o;return t==null?o=an(null,e.length):o=yt(t),this.runInternalGraph(e,o)[1]})}computeOutputShape(e){let t=Ep(e);if(t.length!==this.inputLayers.length)throw new z(`Invalid inputShape argument ${e}: model has ${this.inputLayers.length} tensor inputs.`);let o={};for(let i=0;i<t.length;i++){let l=this.inputLayers[i],u=t[i],c=l.name+"_0_0";o[c]=u}let n=Object.keys(this.nodesByDepth).map(i=>parseInt(i,10)).sort(Ef);if(n.length>1)for(let i of n){let l=this.nodesByDepth[i];for(let u of l){let c=u.outboundLayer;if(this.inputLayers.map(h=>h.id).indexOf(c.id)!==-1)continue;let p=[];for(let h=0;h<u.inboundLayers.length;h++){let g=u.inboundLayers[h],x=u.nodeIndices[h],b=u.tensorIndices[h],w=`${g.name}_${x}_${b}`,_=o[w];p.push(_)}let m=c.computeOutputShape(xr(p)),f=Ep(m),d=c.inboundNodes.indexOf(u);for(let h=0;h<f.length;h++){let g=`${c.name}_${d}_${h}`;o[g]=f[h]}}}let s=[],a=[];for(let i=0;i<this.outputLayers.length;i++){let l=this.outputLayers[i],u=this.outputLayersNodeIndices[i],c=this.outputLayersTensorIndices[i],p=`${l.name}_${u}_${c}`;a.push(p)}for(let i=0;i<a.length;i++){let l=a[i];Po(l in o),s.push(o[l])}return xr(s)}runInternalGraph(e,t){t==null&&(t=an(null,e.length));let o={};for(let l=0;l<this.inputs.length;++l){let u=this.inputs[l],c=e[l],p=t[l];o[u.id]=[c,p]}let n=Object.keys(this.nodesByDepth).map(l=>parseInt(l,10)).sort(Ef);for(let l of n){let u=this.nodesByDepth[l];for(let c of u){let p=c.outboundLayer,m=c.inputTensors,f=c.outputTensors,d=new Array;for(let h of m)h.id in o&&d.push(o[h.id]);if(d.length===m.length){let h={},g,x,b,w;if(c.callArgs!=null&&(h=c.callArgs),d.length===1){let[_,k]=d[0];h.mask==null&&(h.mask=k),b=yt(p.call(_,h)),w=yt(p.computeMask(_,k)),g=[_],x=[k]}else g=d.map(_=>_[0]),x=d.map(_=>_[1]),h.mask==null&&(h.mask=x),b=yt(p.call(g,h)),w=yt(p.computeMask(g,x));if(p.activityRegularizer)throw new Se("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let _=0;_<f.length;++_){let k=f[_],D=b[_],T=w[_];o[k.id]=[D,T]}}}}let s=[],a=[],i=[];for(let l of this.outputs){Po(l.id in o,`Could not compute output ${l.name} : ${l.id}`);let[u,c]=o[l.id];i.push(u.shape),s.push(u),a.push(c)}return[s,a,i]}buildNodeConversionMap(e){let t={},o;for(let n of this.layers){o=n instanceof Mo?1:0;for(let s=0;s<n.inboundNodes.length;s++){let a=Mo.nodeKey(n,s);this.containerNodes.has(a)&&(t[a]=o,o+=1)}}return t}getLayer(e,t){if(t!=null){if(this.layers.length<=t)throw new z(`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 z("Provide either a layer name or layer index");for(let o of this.layers)if(o.name===e)return o;throw new z(`No such layer: ${e}`)}calculateLosses(){return V(()=>{let e=[];for(let t of this.layers)for(let o=0;o<t.inboundNodes.length;++o){let n=Mo.nodeKey(t,o);this.containerNodes.has(n)&&e.push(...t.calculateLosses())}return e})}getConfig(){let e={name:this.name},t=this.buildNodeConversionMap(this.layers),o=[];for(let a of this.layers){let i=a.getClassName(),l=a.getConfig(),u=[];for(let p=0;p<a.inboundNodes.length;p++){let m=a.inboundNodes[p],f=Mo.nodeKey(a,p),d={};if(this.containerNodes.has(f)){if(m.callArgs)try{JSON.stringify(m.callArgs),d=m.callArgs}catch(h){console.warn(`Layer ${a.name} was passed non-serializable keyword arguments: ${m.callArgs}. They will not be included in the serialized model (and thus will be missing at deserialization time).`),d={}}if(m.inboundLayers.length>0){let h=[];for(let g=0;g<m.inboundLayers.length;g++){let x=m.inboundLayers[g],b=m.nodeIndices[g],w=m.tensorIndices[g],_=Mo.nodeKey(x,b),k=t[_];k==null&&(k=0),h.push([x.name,k,w,d])}u.push(h)}}}let c={};c.name=a.name,c.className=i,c.config=l,c.inboundNodes=u,o.push(c)}e.layers=o;let n=[];for(let a=0;a<this.inputLayers.length;a++){let i=this.inputLayers[a],l=this.inputLayersNodeIndices[a],u=Mo.nodeKey(i,l);if(!this.containerNodes.has(u))continue;let c=t[u];c==null&&(c=0);let p=this.inputLayersTensorIndices[a];n.push([i.name,c,p])}e.inputLayers=n;let s=[];for(let a=0;a<this.outputLayers.length;a++){let i=this.outputLayers[a],l=this.outputLayersNodeIndices[a],u=Mo.nodeKey(i,l);if(!this.containerNodes.has(u))continue;let c=t[u];c==null&&(c=0);let p=this.outputLayersTensorIndices[a];s.push([i.name,c,p])}return e.outputLayers=s,e}static fromConfig(e,t,o={},n=!1){let s={},a={};function i(g,x){g.name in a?a[g.name].push(x):a[g.name]=[x]}function l(g,x){let b=[],w;for(let _ of x){let k=_[0],D=_[1],T=_[2];if(w=_[3]==null?{}:_[3],!(k in s)){i(g,x);return}let R=s[k];if(R.inboundNodes.length<=D){i(g,x);return}let O=R.inboundNodes[D];b.push(O.outputTensors[T])}b.length>0&&g.apply(xr(b),w)}function u(g){let x=g.name,b=Jr(g,t.customObjects!=null?t.customObjects:{});b.setFastWeightInitDuringBuild(n),s[x]=b,g.inboundNodes.forEach(_=>{if(!(_ instanceof Array))throw new z(`Corrupted configuration, expected array for nodeData: ${_}`);i(b,_)})}let c=t.name,p=t.layers;for(let g of p)u(g);for(;!gM(a);)for(let g of p){let x=s[g.name];if(x.name in a){let b=a[x.name];delete a[x.name];for(let w of b)l(x,w)}}let m=[],f=[],d=t.inputLayers;for(let g of d){let x=g[0],b=g[1],w=g[2];Po(x in s);let k=s[x].inboundNodes[b].outputTensors;m.push(k[w])}let h=t.outputLayers;for(let g of h){let x=g[0],b=g[1],w=g[2];Po(x in s);let k=s[x].inboundNodes[b].outputTensors;f.push(k[w])}return new e({inputs:m,outputs:f,name:c})}get stateful(){if(this._stateful)throw new z("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(){V(()=>{this.layers.forEach(e=>{e.stateful&&e.resetStates()})})}};function R9(r,e,t){let o=e.length;if(r==null||Array.isArray(r)&&r.length===0)return e.map(n=>null);if(o===1)return Array.isArray(r)&&r.length===1?r:typeof r=="object"&&e[0]in r?[r[e[0]]]:[r];if(Array.isArray(r)){if(r.length!==o)throw new Error(`Provided ${t} is an array of ${r.length} element(s), but the model has ${o} outputs. Make sure a set of weights is provided for each model output.`);return r}else if(typeof r=="object"&&Object.keys(r).length>0&&typeof r[Object.keys(r)[0]]=="object"){let n=[];return e.forEach(s=>{s in r?n.push(r[s]):n.push(null)}),n}else throw new Error(`The model has multiple (${o}) outputs, so ${t} must be either an array with ${o} elements or an object with ${e} keys. Provided ${t} not understood: ${JSON.stringify(r)}`)}function $x(r,e){return R9(r,e,"classWeight")}async function Rx(r,e,t,o){if(e!=null||o!=null)throw new Error("Support sampleWeight is not implemented yet");if(t!=null){let n=V(()=>{if(r.shape.length===1)return r.clone();if(r.shape.length===2)if(r.shape[1]>1){let i=1;return r.argMax(i)}else{if(r.shape[1]===1)return r.reshape([r.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${r.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${r.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),s=Array.from(await n.data());Ae(n);let a=[];return s.forEach(i=>{if(t[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`);a.push(t[i])}),Vt(a,"float32")}else return null}function tL(r,e){return P(r,e)}var F9=32;function oL(r,e){let t,o,n=e;t=n.xs,o=n.ys,y.assert(t!=null&&o!=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 ${e}`);let s=rL("input",r.inputNames,t),a=rL("output",r.outputNames,o),i=s[0].shape[0];y.assert(s.length===r.inputs.length,()=>`LayersModel has ${r.inputs.length} inputs, but the dataset provides ${s.length} inputs.  (Expected input keys: ${JSON.stringify(r.inputNames)})`),y.assert(a.length===r.outputs.length,()=>`LayersModel has ${r.outputs.length} outputs, but the dataset provides ${a.length} outputs.  (Expected output keys: ${JSON.stringify(r.outputNames)})`);for(let l=0;l<s.length;l++)y.assert(s[l].shape[0]===i,()=>`Batch size mismatch: input ${r.inputNames[l]} has ${s[l].shape[0]}; expected  ${i} based on input ${r.inputNames[0]}.`);for(let l=0;l<a.length;l++)y.assert(a[l].shape[0]===i,()=>`Batch size mismatch: output ${r.outputNames[l]} has ${a[l].shape[0]}; expected  ${i} based on input ${r.inputNames[0]}.`);return{xs:s,ys:a}}function rL(r,e,t){if(t instanceof Ve)return[t];if(Array.isArray(t))return y.assert(t.length===e.length,()=>`Received an array of ${t.length} Tensors, but expected ${e.length} to match the ${r} keys ${e}.`),t;{let o=[];for(let n of e){if(t[n]==null)throw new z(`The feature data generated by the dataset lacks the required ${r} key '${n}'.`);o.push(t[n])}return o}}function O9(r){if(r.length===3)throw new Se("Validation with sample weights is not implemented yet.");return{xs:r[0],ys:r[1]}}async function sL(r,e,t){let o=t.batchesPerEpoch!=null;if(y.assert(r.optimizer!=null,()=>"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig)."),y.assert(t!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),y.assert(t.epochs!=null&&t.epochs>0&&Number.isInteger(t.epochs),()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${t.epochs}`),y.assert(!o||t.batchesPerEpoch>0&&Number.isInteger(t.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${t.batchesPerEpoch}`),y.assert(t.validationSplit==null,()=>"`validationSplit` is not supported by `fitDataset()`. 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t}makeTrainFunction(){return e=>{let t=[],o=e.slice(0,this.inputs.length),n=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),s=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+this.outputs.length*2),a=[],i=()=>{let p=[];for(let h=0;h<this.inputs.length;++h)p.push({key:this.inputs[h],value:o[h]});let m=new ks(p),f=Ou(this.outputs,m,{training:!0}),d;for(let h=0;h<this.lossFunctions.length;++h){let x=this.lossFunctions[h](n[h],f[h]);s[h]!=null&&(x=tL(x,s[h]));let b=dt(x);t.push(b),h===0?d=x:d=ee(d,x)}for(let h=0;h<this.metricsTensors.length;++h){let g;if(this.outputs.length>1&&h<this.outputs.length)g=t[h];else{let x=this.metricsTensors[h][0],b=this.metricsTensors[h][1];g=dt(x(n[b],f[b]))}Et(g),a.push(g)}return d=dt(d),this.calculateLosses().forEach(h=>{d=ee(d,h)}),d},l=this.collectedTrainableWeights.map(p=>p.read()),u=!0;return[this.optimizer_.minimize(i,u,l)].concat(a)}}makeTestFunction(){this.testFunction=e=>V(()=>{let 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e.metrics)s[a]=va(e.metrics[a])}this.compile({loss:n,metrics:s,optimizer:o})}async save(e,t){if(typeof e=="string"){let u=Ir.getSaveHandlers(e);if(u.length===0)throw new z(`Cannot find any save handlers for URL '${e}'`);if(u.length>1)throw new z(`Found more than one (${u.length}) save handlers for URL '${e}'`);e=u[0]}if(e.save==null)throw new z("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let o=await Ir.encodeWeights(this.getNamedWeights(t)),n=!1,s=null,i={modelTopology:this.toJSON(s,n),format:W9,generatedBy:`TensorFlow.js tfjs-layers v${Jf}`,convertedBy:null};if((t==null?!1:t.includeOptimizer)&&this.optimizer!=null){i.trainingConfig=this.getTrainingConfig();let u="optimizer",{data:c,specs:p}=await Ir.encodeWeights(await this.optimizer.getWeights(),u);o.specs.push(...p),o.data=Ir.concatenateArrayBuffers([o.data,c])}if(this.userDefinedMetadata!=null){let 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compiled before being used.");return this.model.evaluate(e,t,o)}async evaluateDataset(e,t){if(!this.built)throw new Lr("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,o={}){if(!this.built)throw new Lr("The model needs to be compiled before being used.");return this.model.fit(e,t,o)}async fitDataset(e,t){if(!this.built)throw new Lr("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,o={},n=!1){let s,a={};if(t instanceof Array){if(t[0].className==null||t[0].className==="Merge")throw new z("Legacy serialization format not supported yet.");s=t}else y.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."),s=t.layers,delete t.layers,a=t;let i=new e(a);if(!(i instanceof Sa))throw new Se(`Sequential.fromConfig called on non-Sequential input: ${i}`);for(let l of s){let c=Jr(l,void 0,n);n&&c.setFastWeightInitDuringBuild(!0),i.add(c)}return i}set stopTraining(e){if(this.model==null)throw new z("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 z("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 o={};o.className=t.getClassName(),o.config=t.getConfig(),e.push(o)}return{name:this.name,layers:e}}};Sa.className="Sequential";Q.registerClass(Sa);function H9(r){return new Lo(r)}function q9(r){return new Sa(r)}function K9(r,e){return e==null&&(e={}),mL(r,e)}function AC(r){return kx(r)}function X9(r,e){po.registerCallbackConstructor(r,e)}var mo=class extends Q.Serializable{getConfig(){return{}}},EC=class extends mo{apply(e,t=1){return OM(e,t)}};EC.className="elu";Q.registerClass(EC);var DC=class extends mo{apply(e){return ou(e)}};DC.className="selu";Q.registerClass(DC);var $C=class extends mo{apply(e){return Sr(e)}};$C.className="relu";Q.registerClass($C);var RC=class extends mo{apply(e){return V(()=>fs(6,Sr(e)))}};RC.className="relu6";Q.registerClass(RC);var FC=class extends mo{apply(e){return e}};FC.className="linear";Q.registerClass(FC);var OC=class extends mo{apply(e){return 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e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};nd.className="ThresholdedReLU";Q.registerClass(nd);var sd=class extends Me{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new Qf().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let o=Fe(e);return this.softmax(o,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};sd.className="Softmax";Q.registerClass(sd);function wl(r,e,t){if(typeof r=="number")return an(r,e);if(r.length!==e)throw new z(`The ${t} argument must be an integer or tuple of ${e} integers. 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Received: ${JSON.stringify(r)} including a non-integer number ${n}`)}return r}function fo(r,e,t,o,n=1){if(r==null)return r;let s=e+(e-1)*(n-1),a;return t==="same"?a=r:a=r-s+1,Math.floor((a+o-1)/o)}function id(r,e,t,o){if(r==null)return null;if(o==="valid")r=r*e+_s([t-e,0]);else if(o==="same")r=r*e;else throw new z(`Unsupport padding mode: ${o}.`);return r}function ad(r,e){return V(()=>($t(e),e==="channelsFirst"?qe(r,[0,2,3,1]):r))}function UC(r,e){return V(()=>($t(e),e==="channelsFirst"?qe(r,[0,2,3,4,1]):r))}function Y9(r,e,t,o=1,n="valid",s,a=1){return V(()=>{if(s==null&&(s=Xr()),$t(s),r.shape.length!==3)throw new z(`The input of a conv1dWithBias operation should be 3, but is ${r.shape.length} instead.`);if(e.shape.length!==3)throw new z(`The kernel for a conv1dWithBias operation should be 3, but is ${e.shape.length} instead`);if(t!=null&&t.shape.length!==1)throw new z(`The bias for a conv1dWithBias operation should be 1, but is ${e.shape.length} instead`);if(s==="channelsFirst"&&(r=qe(r,[0,2,1])),n==="causal")throw new Se("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let i=jl(r,e,o,n==="same"?"same":"valid","NWC",a);return t!=null&&(i=uo(i,t)),i})}function xL(r,e,t,o=[1,1],n="valid",s,a,i=null){return V(()=>{if(s==null&&(s=Xr()),$t(s),r.rank!==3&&r.rank!==4)throw new z(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${r.rank}.`);if(e.rank!==3&&e.rank!==4)throw new z(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${r.rank}.`);let l=ad(r,s);if(n==="causal")throw new Se("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Zo.conv2d({x:l,filter:e,strides:o,pad:n==="same"?"same":"valid",dilations:a,dataFormat:"NHWC",bias:t,activation:i}),s==="channelsFirst"&&(l=qe(l,[0,3,1,2])),l})}function Z9(r,e,t,o=[1,1,1],n="valid",s,a){return V(()=>{if(s==null&&(s=Xr()),$t(s),r.rank!==4&&r.rank!==5)throw new z(`conv3dWithBias expects input to be of rank 4 or 5, but received ${r.rank}.`);if(e.rank!==4&&e.rank!==5)throw new z(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${r.rank}.`);let i=UC(r,s);if(n==="causal")throw new Se("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return i=Tm(i,e,o,n==="same"?"same":"valid","NDHWC",a),t!=null&&(i=uo(i,t)),s==="channelsFirst"&&(i=qe(i,[0,4,1,2,3])),i})}var Mp=class extends Me{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",Mp.verifyArgs(t),this.rank=e,jt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Se(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=wl(t.kernelSize,e,"kernelSize"),this.strides=wl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Yr(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,$t(this.dataFormat),this.activation=Cs(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=pt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Ot(t.biasConstraint),this.biasRegularizer=bt(t.biasRegularizer),this.activityRegularizer=bt(t.activityRegularizer),this.dilationRate=wl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new z(`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 z(`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 z(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Po("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!px(e.kernelSize,"number",1,3))throw new z(`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:vs(this.activation),useBias:this.useBias,biasInitializer:kt(this.biasInitializer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),biasConstraint:Ft(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Mu=class extends Mp{constructor(e,t){super(e,t);this.kernel=null,Mu.verifyArgs(t),this.filters=t.filters,jt(this.filters,"filters"),this.kernelInitializer=pt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Ot(t.kernelConstraint),this.kernelRegularizer=bt(t.kernelRegularizer)}build(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new z(`The channel dimension of the input should be defined. Found ${e[t]}`);let o=e[t],n=this.kernelSize.concat([o,this.filters]);this.kernel=this.addWeight("kernel",n,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]:o}}],this.built=!0}call(e,t){return V(()=>{e=Fe(e);let o,n=this.bias==null?null:this.bias.read(),s=mx(this.activation.getClassName());if(s!=null&&this.rank===2)o=xL(e,this.kernel.read(),n,this.strides,this.padding,this.dataFormat,this.dilationRate,s);else{if(this.rank===1)o=Y9(e,this.kernel.read(),n,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)o=xL(e,this.kernel.read(),n,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)o=Z9(e,this.kernel.read(),n,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Se("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(o=this.activation.apply(o))}return o})}computeOutputShape(e){e=Je(e);let t=[],o=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let s=0;s<o.length;++s){let a=fo(o[s],this.kernelSize[s],this.padding,this.strides[s],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[s]);t.push(a)}let n=[e[0]];return this.dataFormat==="channelsLast"?(n=n.concat(t),n.push(this.filters)):(n.push(this.filters),n=n.concat(t)),n}getConfig(){let e={filters:this.filters,kernelInitializer:kt(this.kernelInitializer),kernelRegularizer:st(this.kernelRegularizer),kernelConstraint:Ft(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 z(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},_l=class extends Mu{constructor(e){super(2,e);_l.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!px(e.kernelSize,"number",1,2))throw new z(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};_l.className="Conv2D";Q.registerClass(_l);var Lu=class extends Mu{constructor(e){super(3,e);Lu.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 z(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};Lu.className="Conv3D";Q.registerClass(Lu);var ld=class extends _l{constructor(e){super(e);if(this.inputSpec=[new At({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new z(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=Je(e),e.length!==4)throw new z("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new z("The channel dimension of the inputs should be defined. Found `None`.");let o=e[t],n=this.kernelSize.concat([this.filters,o]);this.kernel=this.addWeight("kernel",n,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new At({ndim:4,axes:{[t]:o}})],this.built=!0}call(e,t){return V(()=>{let o=Fe(e);if(o.shape.length!==4)throw new z(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${o.shape.length}`);let n=o.shape,s=n[0],a,i;this.dataFormat==="channelsFirst"?(a=2,i=3):(a=1,i=2);let l=n[a],u=n[i],c=this.kernelSize[0],p=this.kernelSize[1],m=this.strides[0],f=this.strides[1],d=id(l,m,c,this.padding),h=id(u,f,p,this.padding),g=[s,d,h,this.filters];this.dataFormat!=="channelsLast"&&(o=qe(o,[0,2,3,1]));let x=Ul(o,this.kernel.read(),g,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(x=qe(x,[0,3,1,2])),this.bias!=null&&(x=uo(x,this.bias.read(),this.dataFormat)),this.activation!=null&&(x=this.activation.apply(x)),x})}computeOutputShape(e){e=Je(e);let t=e.slice(),o,n,s;this.dataFormat==="channelsFirst"?(o=1,n=2,s=3):(o=3,n=1,s=2);let a=this.kernelSize[0],i=this.kernelSize[1],l=this.strides[0],u=this.strides[1];return t[o]=this.filters,t[n]=id(t[n],l,a,this.padding),t[s]=id(t[s],u,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};ld.className="Conv2DTranspose";Q.registerClass(ld);var HC=class extends Mu{constructor(e,t){super(e,t);if(this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new z("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new z("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 z(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=pt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=bt(t.depthwiseRegularizer),this.depthwiseConstraint=Ot(t.depthwiseConstraint),this.pointwiseInitializer=pt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=bt(t.pointwiseRegularizer),this.pointwiseConstraint=Ot(t.pointwiseConstraint)}build(e){if(e=Je(e),e.length<this.rank+2)throw new z(`Inputs to SeparableConv${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 z(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let o=e[t],n=this.kernelSize.concat([o,this.depthMultiplier]),s=[];for(let i=0;i<this.rank;++i)s.push(1);s.push(o*this.depthMultiplier,this.filters);let a=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",n,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,a,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",s,"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 At({ndim:this.rank+2,axes:{[t]:o}})],this.built=!0}call(e,t){return V(()=>{e=Fe(e);let o;if(this.rank===1)throw new Se("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=qe(e,[0,2,3,1])),o=Vm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(o=uo(o,this.bias.read(),this.dataFormat)),this.activation!=null&&(o=this.activation.apply(o)),this.dataFormat==="channelsFirst"&&(o=qe(o,[0,3,1,2])),o})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=kt(this.depthwiseInitializer),e.pointwiseInitializer=kt(this.pointwiseInitializer),e.depthwiseRegularizer=st(this.depthwiseRegularizer),e.pointwiseRegularizer=st(this.pointwiseRegularizer),e.depthwiseConstraint=Ft(this.depthwiseConstraint),e.pointwiseConstraint=Ft(this.pointwiseConstraint),e}};HC.className="SeparableConv";var ud=class extends HC{constructor(e){super(2,e)}};ud.className="SeparableConv2D";Q.registerClass(ud);var zu=class extends Mu{constructor(e){super(1,e);zu.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"&&!px(e.kernelSize,"number",1,1))throw new z(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};zu.className="Conv1D";Q.registerClass(zu);var cd=class extends Me{constructor(e){super(e);typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return this.dataFormat==="channelsFirst"?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}call(e,t){return V(()=>{if(e=Fe(e),this.dataFormat==="channelsLast"){let o=Pf(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Pf(o,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let o=Pf(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Pf(o,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};cd.className="Cropping2D";Q.registerClass(cd);var pd=class extends Me{constructor(e){super(e);this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,$t(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,SM(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],o=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,o]}else{let t=e[1]==null?null:this.size[0]*e[1],o=e[2]==null?null:this.size[1]*e[2];return[e[0],t,o,e[3]]}}call(e,t){return V(()=>{let o=Fe(e),n=o.shape;if(this.dataFormat==="channelsFirst"){o=qe(o,[0,2,3,1]);let s=this.size[0]*n[2],a=this.size[1]*n[3],i=this.interpolation==="nearest"?o.resizeNearestNeighbor([s,a]):o.resizeBilinear([s,a]);return qe(i,[0,3,1,2])}else{let s=this.size[0]*n[1],a=this.size[1]*n[2];return this.interpolation==="nearest"?o.resizeNearestNeighbor([s,a]):o.resizeBilinear([s,a])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};pd.className="UpSampling2D";Q.registerClass(pd);function J9(r,e,t=[1,1],o="valid",n,s){return V(()=>{n==null&&(n=Xr()),$t(n);let a=ad(r,n);if(r.rank!==4)throw new z(`Input for depthwiseConv2d is required to be 4-D, but is instead ${r.rank}-D`);if(e.rank!==4)throw new z(`depthwiseKernel is required to be 4-D, but is instead ${e.rank}-D`);return a=us(a,e,t,o==="same"?"same":"valid","NHWC",s),n==="channelsFirst"&&(a=qe(a,[0,3,1,2])),a})}var md=class extends Mp{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=pt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Ot(e.depthwiseConstraint),this.depthwiseRegularizer=bt(e.depthwiseRegularizer)}build(e){if(e=Je(e),e.length<4)throw new z(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new z(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let o=e[t],n=[this.kernelSize[0],this.kernelSize[1],o,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",n,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[o*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return V(()=>{e=Fe(e);let o=J9(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(o=uo(o,this.bias.read(),this.dataFormat)),this.activation!=null&&(o=this.activation.apply(o)),o})}computeOutputShape(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],o=this.dataFormat==="channelsFirst"?e[3]:e[2],n=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,s=fo(t,this.kernelSize[0],this.padding,this.strides[0]),a=fo(o,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],n,s,a]:[e[0],s,a,n]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=kt(this.depthwiseInitializer),e.depthwiseRegularizer=st(this.depthwiseRegularizer),e.depthwiseConstraint=Ft(this.depthwiseRegularizer),e}};md.className="DepthwiseConv2D";Q.registerClass(md);function qC(r,e,t,o){if(Array.isArray(r)){if(e!=null||t!=null)throw new z("When inputs is an array, neither initialState or constants should be provided");o!=null&&(t=r.slice(r.length-o,r.length),r=r.slice(0,r.length-o)),r.length>1&&(e=r.slice(1,r.length)),r=r[0]}function n(s){return s==null||Array.isArray(s)?s:[s]}return e=n(e),t=n(t),{inputs:r,initialState:e,constants:t}}function KC(r,e,t,o=!1,n,s,a=!1,i=!1){return V(()=>{let l=e.shape.length;if(l<3)throw new z(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(zr(2,l));if(e=qe(e,u),s!=null)throw new Se("The rnn() functoin of the deeplearn.js backend does not support constants yet.");a&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),n!=null&&(n=n.asType("bool").asType("float32"),n.rank===l-1&&(n=lr(n,-1)),n=qe(n,u)),o&&(e=Ht(e,0),n!=null&&(n=Ht(n,0)));let c=[],p,m=t,f=e.shape[0],d=mr(e),h;n!=null&&(h=mr(n));for(let x=0;x<f;++x){let b=d[x],w=V(()=>r(b,m));if(n==null)p=w[0],m=w[1];else{let _=V(()=>{let k=h[x],D=rr(k).sub(k),T=w[0].mul(k).add(m[0].mul(D)),R=m.map((O,M)=>w[1][M].mul(k).add(O.mul(D)));return{output:T,newStates:R}});p=_.output,m=_.newStates}i&&c.push(p)}let g;return i&&(g=Bt(c,1)),[p,g,m]})}var Io=class extends Me{constructor(e){super(e);let t;if(e.cell==null)throw new z("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Lp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new z("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 At({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 zr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){wx(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let o=t[0],n;if(this.returnSequences?n=[e[0],e[1],o]:n=[e[0],o],this.returnState){let s=[];for(let a of t)s.push([e[0],a]);return[n].concat(s)}else return n}computeMask(e,t){return V(()=>{Array.isArray(t)&&(t=t[0]);let o=this.returnSequences?t:null;if(this.returnState){let n=this.states.map(s=>null);return[o].concat(n)}else return o})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let o=0;o<e;++o)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){let t=null;if(this.numConstants!=null)throw new Se("Constants support is not implemented in RNN yet.");wx(e)&&(e=e[0]),e=e;let o=this.stateful?e[0]:null,n=e.slice(2);this.inputSpec[0]=new At({shape:[o,null,...n]});let s=[e[0]].concat(e.slice(2));if(t!=null)throw new Se("Constants support is not implemented in RNN yet.");this.cell.build(s);let a;if(Array.isArray(this.cell.stateSize)?a=this.cell.stateSize:a=[this.cell.stateSize],this.stateSpec!=null){if(!y.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),a))throw new z(`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(i=>new At({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){V(()=>{if(!this.stateful)throw new Co("Cannot call resetStates() on an RNN Layer that is not stateful.");let o=this.inputSpec[0].shape[0];if(o==null)throw new z("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(n=>ht([o,n])):this.states_=[ht([o,this.cell.stateSize])];else if(e==null)Ae(this.states_),this.keptStates!=null&&(Ae(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(n=>ht([o,n])):this.states_[0]=ht([o,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new z(`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()):Ae(this.states_);for(let n=0;n<this.states_.length;++n){let s=e[n],a=Array.isArray(this.cell.stateSize)?this.cell.stateSize[n]:this.cell.stateSize,i=[o,a];if(!y.arraysEqual(s.shape,i))throw new z(`State ${n} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${s.shape}`);this.states_[n]=s}}this.states_=this.states_.map(n=>Et(n.clone()))})}apply(e,t){let o=t==null?null:t.initialState,n=t==null?null:t.constants;t==null&&(t={});let s=qC(e,o,n,this.numConstants);e=s.inputs,o=s.initialState,n=s.constants;let a=[],i=[];if(o!=null){t.initialState=o,a=a.concat(o),this.stateSpec=[];for(let u of o)this.stateSpec.push(new At({shape:u.shape}));i=i.concat(this.stateSpec)}if(n!=null&&(t.constants=n,a=a.concat(n),this.numConstants=n.length),a[0]instanceof Zr){let u=[e].concat(a),c=this.inputSpec.concat(i),p=this.inputSpec;this.inputSpec=c;let m=super.apply(u,t);return this.inputSpec=p,m}else return super.apply(e,t)}call(e,t){return V(()=>{let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;e=Fe(e),s==null&&(this.stateful?s=this.states_:s=this.getInitialState(e));let a=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(s.length!==a)throw new z(`RNN Layer has ${a} state(s) but was passed ${s.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:n},u=KC((d,h)=>{let g=this.cell.call([d].concat(h),i);return[g[0],g.slice(1)]},e,s,this.goBackwards,o,null,this.unroll,this.returnSequences),c=u[0],p=u[1],m=u[2];this.stateful&&this.resetStates(m,n);let f=this.returnSequences?p:c;return this.returnState?[f].concat(m):f})}getInitialState(e){return V(()=>{let t=ht(e.shape);return t=ge(t,[1,2]),t=Ia(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(o=>o>1?hx(t,[1,o]):t):this.cell.stateSize>1?[hx(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 o=this.cell.getConfig();return this.getClassName()===Io.className&&(t.cell={className:this.cell.getClassName(),config:o}),Object.assign({},o,e,t)}static fromConfig(e,t,o={}){let n=t.cell,s=Jr(n,o);return new e(Object.assign(t,{cell:s}))}};Io.className="RNN";Q.registerClass(Io);var kl=class extends Me{},zp=class extends kl{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,jt(this.units,"units"),this.activation=Cs(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=pt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=bt(e.kernelRegularizer),this.recurrentRegularizer=bt(e.recurrentRegularizer),this.biasRegularizer=bt(e.biasRegularizer),this.kernelConstraint=Ot(e.kernelConstraint),this.recurrentConstraint=Ot(e.recurrentConstraint),this.biasConstraint=Ot(e.biasConstraint),this.dropout=Eu([1,_s([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Eu([1,_s([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=Je(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 V(()=>{if(e=e,e.length!==2)throw new z(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let o=e[1];e=e[0];let n=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Ta({ones:()=>rr(e),rate:this.dropout,training:n})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Ta({ones:()=>rr(o),rate:this.recurrentDropout,training:n}));let s,a=this.dropoutMask,i=this.recurrentDropoutMask;a!=null?s=mn(P(e,a),this.kernel.read()):s=mn(e,this.kernel.read()),this.bias!=null&&(s=uo(s,this.bias.read())),i!=null&&(o=P(o,i));let l=ee(s,mn(o,this.recurrentKernel.read()));return this.activation!=null&&(l=this.activation.apply(l)),[l,l]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:vs(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:st(this.kernelRegularizer),recurrentRegularizer:st(this.recurrentRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ft(this.kernelConstraint),recurrentConstraint:Ft(this.recurrentConstraint),biasConstraint:Ft(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};zp.className="SimpleRNNCell";Q.registerClass(zp);var fd=class extends Io{constructor(e){e.cell=new zp(e),super(e)}call(e,t){return V(()=>{this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:o,training:n,initialState:s})})}static fromConfig(e,t){return new e(t)}};fd.className="SimpleRNN";Q.registerClass(fd);var Bp=class extends kl{constructor(e){super(e);if(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 z("GRUCell does not support reset_after parameter set to true.");this.units=e.units,jt(this.units,"units"),this.activation=Cs(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Cs(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=pt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=bt(e.kernelRegularizer),this.recurrentRegularizer=bt(e.recurrentRegularizer),this.biasRegularizer=bt(e.biasRegularizer),this.kernelConstraint=Ot(e.kernelConstraint),this.recurrentConstraint=Ot(e.recurrentConstraint),this.biasConstraint=Ot(e.biasConstraint),this.dropout=Eu([1,_s([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Eu([1,_s([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=Je(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 V(()=>{if(e=e,e.length!==2)throw new z(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let o=t.training==null?!1:t.training,n=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Ta({ones:()=>rr(e),rate:this.dropout,training:o,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Ta({ones:()=>rr(n),rate:this.recurrentDropout,training:o,count:3}));let s=this.dropoutMask,a=this.recurrentDropoutMask,i,l,u;0<this.dropout&&this.dropout<1&&(e=P(e,s[0]));let c=mn(e,this.kernel.read());this.useBias&&(c=uo(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(n=P(n,a[0]));let p=this.recurrentKernel.read(),[m,f]=pr(p,[2*this.units,this.units],p.rank-1),d=mn(n,m),[h,g,x]=pr(c,3,c.rank-1),[b,w]=pr(d,2,d.rank-1);i=this.recurrentActivation.apply(ee(h,b)),l=this.recurrentActivation.apply(ee(g,w));let _=mn(P(l,n),f);u=this.activation.apply(ee(x,_));let k=ee(P(i,n),P(ee(1,Ue(i)),u));return[k,k]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:vs(this.activation),recurrentActivation:vs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:st(this.kernelRegularizer),recurrentRegularizer:st(this.recurrentRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ft(this.kernelConstraint),recurrentConstraint:Ft(this.recurrentConstraint),biasConstraint:Ft(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};Bp.className="GRUCell";Q.registerClass(Bp);var dd=class extends Io{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 Bp(e),super(e)}call(e,t){return V(()=>{this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:o,training:n,initialState:s})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};dd.className="GRU";Q.registerClass(dd);var vl=class extends kl{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,jt(this.units,"units"),this.activation=Cs(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Cs(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=pt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=bt(e.kernelRegularizer),this.recurrentRegularizer=bt(e.recurrentRegularizer),this.biasRegularizer=bt(e.biasRegularizer),this.kernelConstraint=Ot(e.kernelConstraint),this.recurrentConstraint=Ot(e.recurrentConstraint),this.biasConstraint=Ot(e.biasConstraint),this.dropout=Eu([1,_s([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Eu([1,_s([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=Je(e);let o=e[e.length-1];this.kernel=this.addWeight("kernel",[o,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 n;if(this.useBias){if(this.unitForgetBias){let s=this.biasInitializer,a=this.units;n=new(t=class extends co{apply(l,u){let c=s.apply([a]),p=new $u().apply([a]),m=s.apply([a*2]);return hC(hC(c,p),m)}},t.className="CustomInit",t)}else n=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,n,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return V(()=>{let o=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new z(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=e[1],s=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Ta({ones:()=>rr(e),rate:this.dropout,training:o,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Ta({ones:()=>rr(n),rate:this.recurrentDropout,training:o,count:4}));let a=this.dropoutMask,i=this.recurrentDropoutMask,l,u,c,p;0<this.dropout&&this.dropout<1&&(e=P(e,a[0]));let m=mn(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(n=P(n,i[0])),m=ee(m,mn(n,this.recurrentKernel.read())),this.useBias&&(m=uo(m,this.bias.read()));let[f,d,h,g]=pr(m,4,m.rank-1);l=this.recurrentActivation.apply(f),u=this.recurrentActivation.apply(d),c=ee(P(u,s),P(l,this.activation.apply(h))),p=this.recurrentActivation.apply(g);let x=P(p,this.activation.apply(c));return[x,x,c]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:vs(this.activation),recurrentActivation:vs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:st(this.kernelRegularizer),recurrentRegularizer:st(this.recurrentRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ft(this.kernelConstraint),recurrentConstraint:Ft(this.recurrentConstraint),biasConstraint:Ft(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};vl.className="LSTMCell";Q.registerClass(vl);var hd=class extends Io{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 vl(e),super(e)}call(e,t){return V(()=>{this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:o,training:n,initialState:s})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};hd.className="LSTM";Q.registerClass(hd);var Lp=class extends kl{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 V(()=>{e=e;let o=e.slice(1),n=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?n.push(o.splice(0,i.stateSize.length)):n.push(o.splice(0,1));n.reverse();let s=[],a;for(let i=0;i<this.cells.length;++i){let l=this.cells[i];o=n[i],i===0?a=[e[0]].concat(o):a=[a[0]].concat(o),a=l.call(a,t),s.push(a.slice(1))}o=[];for(let i of s.slice().reverse())o.push(...i);return[a[0]].concat(o)})}build(e){wx(e)&&(e=e[0]),e=e;let t;this.cells.forEach((o,n)=>{ws(`RNNCell_${n}`,()=>{o.build(e),Array.isArray(o.stateSize)?t=o.stateSize[0]:t=o.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=s=>({className:s.getClassName(),config:s.getConfig()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,o={}){let n=[];for(let s of t.cells)n.push(Jr(s,o));return new e({cells:n})}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 o of this.cells)t.push(...o.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return jf(e)}setWeights(e){let t=[];for(let o of this.cells){let n=o.weights.length,s=e.splice(n);for(let a=0;a<o.weights.length;++a)t.push([o.weights[a],s[a]])}$p(t)}};Lp.className="StackedRNNCells";Q.registerClass(Lp);function Ta(r){let{ones:e,rate:t,training:o=!1,count:n=1}=r,s=()=>xx(e(),t),a=()=>dl(s,e,o);return!n||n<=1?Et(a().clone()):Array(n).fill(void 0).map(a).map(l=>Et(l.clone()))}var Q9=function(r,e){var t={};for(var o in r)Object.prototype.hasOwnProperty.call(r,o)&&e.indexOf(o)<0&&(t[o]=r[o]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var n=0,o=Object.getOwnPropertySymbols(r);n<o.length;n++)e.indexOf(o[n])<0&&Object.prototype.propertyIsEnumerable.call(r,o[n])&&(t[o[n]]=r[o[n]]);return t};var XC=class extends Io{constructor(e){if(e.unroll)throw new Se("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Se("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new At({ndim:5})]}call(e,t){return V(()=>{if(this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new z("ConvRNN2D cell does not support constants");let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:o,training:n,initialState:s})})}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 V(()=>{let{stateSize:t}=this.cell,o=e.shape,n=this.computeSingleOutputShape(o),s=[n[0],...n.slice(2)],a=ht(s);return Array.isArray(t)?Array(t.length).fill(a):[a]})}resetStates(e,t=!1){V(()=>{if(!this.stateful)throw new Co("Cannot call resetStates() on an RNN Layer that is not stateful.");let o=this.inputSpec[0].shape,n=this.computeSingleOutputShape(o),s=[n[0],...n.slice(2)];if(o[0]==null)throw new z("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(()=>ht(s)):this.states_=[ht(s)];else if(e==null)Ae(this.states_),this.keptStates!=null&&(Ae(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>ht(s)):this.states_[0]=ht(s);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new z(`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()):Ae(this.states_);for(let i=0;i<this.states_.length;++i){let l=e[i],u=s;if(!y.arraysEqual(l.shape,u))throw new z(`State ${i} is incompatible with layer ${this.name}: expected shape=${u}, received shape=${l.shape}`);this.states_[i]=l}}this.states_=this.states_.map(i=>Et(i.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:o,kernelSize:n,padding:s,strides:a,dilationRate:i}=this.cell,l=t==="channelsFirst",u=e[l?3:2],c=e[l?4:3],p=fo(u,n[0],s,a[0],i[0]),m=fo(c,n[1],s,a[1],i[1]);return[...e.slice(0,2),...l?[o,p,m]:[p,m,o]]}};XC.className="ConvRNN2D";var Vp=class extends vl{constructor(e){let{filters:t,kernelSize:o,strides:n,padding:s,dataFormat:a,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,jt(this.filters,"filters"),this.kernelSize=wl(o,2,"kernelSize"),this.kernelSize.forEach(l=>jt(l,"kernelSize")),this.strides=wl(n||1,2,"strides"),this.strides.forEach(l=>jt(l,"strides")),this.padding=s||"valid",Yr(this.padding),this.dataFormat=a||"channelsLast",$t(this.dataFormat),this.dilationRate=wl(i||1,2,"dilationRate"),this.dilationRate.forEach(l=>jt(l,"dilationRate"))}build(e){var t;e=Je(e);let o=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[o]==null)throw new z(`The channel dimension of the input should be defined. Found ${e[o]}`);let n=e[o],s=4,a=this.kernelSize.concat([n,this.filters*s]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*s]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let l;if(this.unitForgetBias){let u=this.biasInitializer,c=this.filters;l=new(t=class extends co{apply(m,f){let d=u.apply([c]),h=Nr([c]),g=u.apply([c*2]);return kp([d,h,g])}},t.className="CustomInit",t)}else l=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*s],null,l,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return V(()=>{if(e.length!==3)throw new z(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let o=t.training||!1,n=e[0],s=e[1],a=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Ta({ones:()=>rr(n),rate:this.dropout,training:o,count:i}));let l=this.dropoutMask,u=(J,ie,ue)=>!ie||!ie[ue]?J:P(ie[ue],J),c=u(n,l,0),p=u(n,l,1),m=u(n,l,2),f=u(n,l,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Ta({ones:()=>rr(s),rate:this.recurrentDropout,training:o,count:i}));let d=this.recurrentDropoutMask,h=u(s,d,0),g=u(s,d,1),x=u(s,d,2),b=u(s,d,3),w=3,[_,k,D,T]=pr(this.kernel.read(),i,w),[R,O,M,G]=this.useBias?pr(this.bias.read(),i):[null,null,null,null];c=this.inputConv(c,_,R,this.padding),p=this.inputConv(p,k,O,this.padding),m=this.inputConv(m,D,M,this.padding),f=this.inputConv(f,T,G,this.padding);let[j,U,H,q]=pr(this.recurrentKernel.read(),i,w);h=this.recurrentConv(h,j),g=this.recurrentConv(g,U),x=this.recurrentConv(x,H),b=this.recurrentConv(b,q);let X=this.recurrentActivation.apply(ee(c,h)),oe=this.recurrentActivation.apply(ee(p,g)),Y=ee(P(oe,a),P(X,this.activation.apply(ee(m,x)))),re=P(this.recurrentActivation.apply(ee(f,b)),this.activation.apply(Y));return[re,re,Y]})}getConfig(){let e=super.getConfig(),{units:t}=e,o=Q9(e,["units"]),n={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},o,n)}inputConv(e,t,o,n){let s=qr(e,t,this.strides,n||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return o?uo(s,o,this.dataFormat):s}recurrentConv(e,t){return qr(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};Vp.className="ConvLSTM2DCell";Q.registerClass(Vp);var gd=class extends XC{constructor(e){let t=new Vp(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};gd.className="ConvLSTM2D";Q.registerClass(gd);var Gp=class extends Me{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,o=[];for(let n=0;n<this.noiseShape.length;++n)o.push(this.noiseShape[n]==null?t[n]:this.noiseShape[n]);return o}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e);if(0<this.rate&&this.rate<1){let n=t.training==null?!1:t.training,s=this.getNoiseShape(o);return dl(()=>xx(o,this.rate,s,this.seed),()=>o,n)}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()}};Gp.className="Dropout";Q.registerClass(Gp);var xd=class extends Gp{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};xd.className="SpatialDropout1D";Q.registerClass(xd);var yd=class extends Me{constructor(e){super(e);if(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,jt(this.units,"units"),this.activation=Cs(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Ot(e.kernelConstraint),this.biasConstraint=Ot(e.biasConstraint),this.kernelRegularizer=bt(e.kernelRegularizer),this.biasRegularizer=bt(e.biasRegularizer),this.activityRegularizer=bt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=Je(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=Je(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e),n=mx(this.activation.getClassName()),s;return n!=null?s=mn(o,this.kernel.read(),n,this.bias?this.bias.read():null):(s=mn(o,this.kernel.read()),this.bias!=null&&(s=uo(s,this.bias.read())),this.activation!=null&&(s=this.activation.apply(s))),s})}getConfig(){let e={units:this.units,activation:vs(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:st(this.kernelRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ft(this.kernelConstraint),biasConstraint:Ft(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};yd.className="Dense";Q.registerClass(yd);var bd=class extends Me{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=Je(e);for(let t of e.slice(1))if(t==null)throw new z(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],pn(e,1)]}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e);if(this.dataFormat==="channelsFirst"&&o.rank>1){let n=[0];for(let s=2;s<o.rank;++s)n.push(s);n.push(1),o=o.transpose(n)}return FM(o)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};bd.className="Flatten";Q.registerClass(bd);var wd=class extends Me{constructor(e){super(e);this.supportsMasking=!0,this.activation=Cs(e.activation)}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e);return this.activation.apply(o)})}getConfig(){let e={activation:vs(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};wd.className="Activation";Q.registerClass(wd);var _d=class extends Me{constructor(e){super(e);this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return V(()=>(e=Fe(e),$M(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};_d.className="RepeatVector";Q.registerClass(_d);var kd=class extends Me{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 o="Total size of new array must be unchanged.",n=t.slice(),s=1,a=null;for(let l=0;l<n.length;++l){let u=n[l];if(this.isUnknown(u))if(a===null)a=l;else throw new z("Can only specifiy one unknown dimension.");else s*=u}let i=pn(e);if(a!==null){if(s===0||i%s!=0)throw new z(o);n[a]=i/s}else if(i!==s)throw new z(o);return n}computeOutputShape(e){let t=!1;for(let o=0;o<e.length;++o)if(this.isUnknown(e[o])){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 V(()=>{this.invokeCallHook(e,t);let o=Fe(e),n=o.shape,s=n.slice(0,1).concat(this.fixUnknownDimension(n.slice(1),this.targetShape));return o.reshape(s)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};kd.className="Reshape";Q.registerClass(kd);var vd=class extends Me{constructor(e){super(e);if(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=zr(1,e.dims.length+1);if(!y.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 At({ndim:this.dims.length+1})]}computeOutputShape(e){e=Je(e);let t=e.slice();return this.dims.forEach((o,n)=>{t[n+1]=e[o]}),t}call(e,t){return qe(Fe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};vd.className="Permute";Q.registerClass(vd);var Cd=class extends Me{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 o=Fe(e),n=-1;return rl(Yo(o,this.maskValue),n)}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e),n=-1,s=!0,a=rl(Yo(o,this.maskValue),n,s);return o.mul(a.asType(o.dtype))})}};Cd.className="Masking";Q.registerClass(Cd);var Id=class extends Me{constructor(e){super(e);if(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(yt(e.inputLength))}this.inputDim=e.inputDim,jt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,jt(this.outputDim,"outputDim"),this.embeddingsInitializer=pt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=bt(e.embeddingsRegularizer),this.activityRegularizer=bt(e.activityRegularizer),this.embeddingsConstraint=Ot(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 V(()=>this.maskZero?(e=Fe(e),Yo(e,Ce(e))):null)}computeOutputShape(e){if(e=Je(e),this.inputLength==null)return[...e,this.outputDim];let 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extends Me{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new Se}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 o=e.slice(0,e.length-t.length);for(let n=0;n<t.length;++n){let s=e[e.length-t.length+n],a=t[n];if(s==null||a==null||s<0||a<0)o.push(null);else if(s===1)o.push(a);else if(a===1)o.push(s);else{if(s!==a)throw new z("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));o.push(s)}}return o}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[Je(e)]),e=e,e.length<2)throw new z(`A merge layer should be called on an Array of at least 2 inputs. 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e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Dd.className="Concatenate";Q.registerClass(Dd);function $d(r,e){for(;r<0;)r+=e;return r}function eJ(r,e,t){if(r.shape.length>3||e.shape.length>3)throw new Se("batchDot is not implemented for tensors of 4D or higher rank yet");if(y.assert(r.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${r.shape.length}`),y.assert(r.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${e.shape.length}`),typeof t=="number"&&(t=[t,t]),r.dtype==="complex64"||e.dtype==="complex64")throw new Se("batchDot is not implemented for complex64-type Tensors yet.");let o=r.shape.length,n=e.shape.length;t==null&&(t=[o-1,n-2]);let s=t;return V(()=>{let a;if(o>n){a=o-n;let l=[];for(let u=0;u<a;++u)l.push(1);e=e.reshape(e.shape.concat(l))}else if(n>o){a=n-o;let l=[];for(let u=0;u<a;++u)l.push(1);r=r.reshape(r.shape.concat(l))}else a=0;let i;if(r.shape.length===2&&e.shape.length===2)s[0]===s[1]?i=r.mul(e).sum(s[0]):i=r.transpose([1,0]).mul(e).sum(s[1]);else{let l=s[0]!==r.shape.length-1,u=s[1]===e.shape.length-1;i=r.matMul(e,l,u)}if(a>0){let l;o>n?l=o+n-3:l=o-1;let u=[];for(let c=l;c<l+a;++c)u.push(c);i=i.squeeze(u)}return i.shape.length===1&&(i=i.expandDims(1)),i})}var Rd=class extends Cl{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){y.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],o=e[1];if(t.length>3||o.length>3)throw new Se("Dot layer does not support tensors of 4D or higher rank yet.");let n=this.interpretAxes(t,o);if(t[n[0]]!==o[n[1]])throw new z(`Dimension incompatibility: ${t[n[0]]} !== ${o[n[1]]}`)}mergeFunction(e){if(e.length!==2)throw new z(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],o=e[1],n;return Array.isArray(this.axes)?n=this.axes.map((s,a)=>$d(s,e[a].shape.length)):n=[$d(this.axes,t.shape.length),$d(this.axes,o.shape.length)],this.normalize&&(t=Uf(t,n[0]),o=Uf(o,n[1])),eJ(t,o,n)}interpretAxes(e,t){let o;return Array.isArray(this.axes)?o=this.axes:o=[$d(this.axes,e.length),$d(this.axes,t.length)],o}computeOutputShape(e){y.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(),o=e[1].slice();if(t.length>3||o.length>3)throw new Se("Dot layer does not support tensors of 4D or higher rank yet.");let n=this.interpretAxes(t,o);t.splice(n[0],1),o.splice(n[1],1),o.splice(0,1);let s=t.concat(o);return s.length===1&&s.push(1),s}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};Rd.className="Dot";Q.registerClass(Rd);var Fd=class extends Me{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 V(()=>{this.invokeCallHook(e,t);let o=Fe(e);return dl(()=>vp(o.shape,0,this.stddev).add(o),()=>o,t.training||!1)})}};Fd.className="GaussianNoise";Q.registerClass(Fd);var Od=class extends Me{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 V(()=>{this.invokeCallHook(e,t);let o=Fe(e);return this.rate>0&&this.rate<1?dl(()=>{let s=Math.sqrt(this.rate/(1-this.rate));return o.mul(vp(o.shape,1,s))},()=>o,t.training||!1):o})}};Od.className="GaussianDropout";Q.registerClass(Od);var Pd=class extends Me{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Fe(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 V(()=>{if(this.rate<1&&this.rate>0){let o=this._getNoiseShape(e);return dl(()=>{let s=Fe(e),a=1.6732632423543772,i=1.0507009873554805,l=-a*i,u=so(ds(o),this.rate);u=Ca(u,"float32");let c=((1-this.rate)*(1+this.rate*l**2))**-.5,p=-c*l*this.rate;return s.mul(u).add(u.add(-1).mul(l)).mul(c).add(p)},()=>Fe(e),t.training||!1)}return e})}};Pd.className="AlphaDropout";Q.registerClass(Pd);function Md(r,e,t,o,n,s=.001){let a;if(r.rank===2)a=pw(r,e,t,o,n,s);else if(r.rank===3)a=mw(r,e,t,o,n,s);else if(r.rank===4)a=fw(r,e,t,o,n,s);else throw new Se(`batchNormalization is not implemented for array of rank ${r.rank} yet`);return a}function tJ(r,e,t,o,n=.001){return V(()=>{let s=Hc(r,o),a=s.mean,i=s.variance;return[Md(r,a,i,t,e,n),a,i]})}function rJ(r,e,t,o,n=.001){return V(()=>{let s=Hc(r,o),a=s.mean,i=s.variance,l=[];for(let d of zr(0,r.rank))o.indexOf(d)!==-1?l.push(1):l.push(r.shape[d]);let u=a.reshape(l),c=i.reshape(l),p=e==null?null:e.reshape(l),m=t==null?null:t.reshape(l);return[Md(r,u,c,m,p,n),a,i]})}function oJ(r,e,t,o,n=.001){return y.arraysEqual(o.slice().sort(),zr(0,r.rank-1))?tJ(r,e,t,o,n):rJ(r,e,t,o,n)}var Ld=class extends Me{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=pt(e.betaInitializer||"zeros"),this.gammaInitializer=pt(e.gammaInitializer||"ones"),this.movingMeanInitializer=pt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=pt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Ot(e.betaConstraint),this.gammaConstraint=Ot(e.gammaConstraint),this.betaRegularizer=bt(e.betaRegularizer),this.gammaRegularizer=bt(e.gammaRegularizer)}build(e){e=Je(e);let t=this.axis>=0?this.axis:this.axis+e.length,o=e[t];if(o==null)throw new z(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new At({ndim:e.length,axes:{[t]:o}})];let n=[o];this.scale&&(this.gamma=this.addWeight("gamma",n,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",n,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",n,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",n,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return V(()=>{let o=t.training==null?!1:t.training,n=Fe(e),s=n.shape,a=s.length,i=zr(0,a),l=this.axis>=0?this.axis:this.axis+a;i.splice(l,1);let u=an(1,a);u[l]=s[l];let c=i.slice();c.sort();let p=!y.arraysEqual(c,zr(0,a).slice(0,a-1)),m=()=>{if(p){let b=this.movingMean.read().reshape(u),w=this.movingVariance.read().reshape(u),_=this.center?this.beta.read().reshape(u):null,k=this.scale?this.gamma.read().reshape(u):null;return Md(n,b,w,_,k,this.epsilon)}else return Md(n,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!o)return m();let[f,d,h]=oJ(n,this.gamma.read(),this.beta.read(),i,this.epsilon),g=(b,w,_)=>{V(()=>{let k=1-_,D=b.read(),T=D.sub(w).mul(k);b.write(D.sub(T))})};return(()=>{g(this.movingMean,d,this.momentum),g(this.movingVariance,h,this.momentum)})(),f})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:kt(this.betaInitializer),gammaInitializer:kt(this.gammaInitializer),movingMeanInitializer:kt(this.movingMeanInitializer),movingVarianceInitializer:kt(this.movingVarianceInitializer),betaRegularizer:st(this.betaRegularizer),gammaRegularizer:st(this.gammaRegularizer),betaConstraint:Ft(this.betaConstraint),gammaConstraint:Ft(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Ld.className="BatchNormalization";Q.registerClass(Ld);var zd=class extends Me{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=pt(e.betaInitializer||"zeros"),this.gammaInitializer=pt(e.gammaInitializer||"ones"),this.betaRegularizer=bt(e.betaRegularizer),this.gammaRegularizer=bt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=Je(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let s=0;s<this.axis.length;++s)this.axis[s]<0&&(this.axis[s]+=t);for(let s of this.axis)if(s<0||s>=t)throw new Error(`Invalid axis: ${s}`);if(this.axis.length!==cn(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let o=this.axis.map(s=>e[s]),n=!0;this.scale?this.gamma=this.addWeight("gamma",o,"float32",this.gammaInitializer,this.gammaRegularizer,n):this.gamma=null,this.center?this.beta=this.addWeight("beta",o,"float32",this.betaInitializer,this.betaRegularizer,n):this.beta=null,this.built=!0}call(e,t){let o=Fe(e),n=o.shape,s=n.length;return V(()=>{let a=!0,{mean:i,variance:l}=Hc(o,this.axis,a),u=an(1,s);for(let h of this.axis)u[h]=n[h];let c=h=>h!=null&&h.shape.length!==s&&this.axis!==[s-1]?h.reshape(u):h,p=c(this.gamma.read()),m=c(this.beta.read()),f=[],d=[];for(let h=0;h<s;++h)this.axis.indexOf(h)!==-1?(f.push(n[h]),d.push(1)):(f.push(1),d.push(n[h]));return i=i.tile(f),l=l.tile(f),p=p.tile(d),m=m.tile(d),Md(o,i,l,m,p,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:kt(this.betaInitializer),gammaInitializer:kt(this.gammaInitializer),betaRegularizer:st(this.betaRegularizer),gammaRegularizer:st(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};zd.className="LayerNormalization";Q.registerClass(zd);function nJ(r,e,t){return V(()=>{if(r.rank!==4)throw new z(`temporalPadding expects input tensor to be 4-D, but received a ${r.rank}-D tensor.`);if(e==null&&(e=[[1,1],[1,1]]),e.length!==2||e[0].length!==2||e[1].length!==2)throw new z("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(t==null&&(t=Xr()),t!=="channelsLast"&&t!=="channelsFirst")throw new z(`Unknown data format: ${t}. 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s==="max"?a=ca(r,e,t,i):a=na(r,e,t,i),n==="channelsFirst"&&(a=qe(a,[0,3,1,2])),a})}function yL(r,e,t,o,n,s){return V(()=>{$t(n),fC(s),Yr(o),t==null&&(t=[1,1,1]),o==null&&(o="valid"),n==null&&(n=Xr()),s==null&&(s="max"),r=UC(r,n);let a,i=o==="same"?"same":"valid";return s==="max"?a=Pm(r,e,t,i):a=Nm(r,e,t,i),n==="channelsFirst"&&(a=qe(a,[0,4,1,2,3])),a})}var YC=class extends Me{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 z(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(jt(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 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t=fo(t,this.poolSize[0],this.padding,this.strides[0]),o=fo(o,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,o]:[e[0],t,o,e[3]]}call(e,t){return V(()=>(this.invokeCallHook(e,t),this.poolingFunction(Fe(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}},Wd=class extends ZC{constructor(e){super(e)}poolingFunction(e,t,o,n,s){return $t(s),Yr(n),Mx(e,t,o,n,s,"max")}};Wd.className="MaxPooling2D";Q.registerClass(Wd);var jd=class extends ZC{constructor(e){super(e)}poolingFunction(e,t,o,n,s){return $t(s),Yr(n),Mx(e,t,o,n,s,"avg")}};jd.className="AveragePooling2D";Q.registerClass(jd);var JC=class extends Me{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 z(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];jt(this.poolSize,"poolSize"),jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,$t(this.dataFormat),Yr(this.padding),this.inputSpec=[new At({ndim:5})]}computeOutputShape(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],o=this.dataFormat==="channelsFirst"?e[3]:e[2],n=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=fo(t,this.poolSize[0],this.padding,this.strides[0]),o=fo(o,this.poolSize[1],this.padding,this.strides[1]),n=fo(n,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,o,n]:[e[0],t,o,n,e[4]]}call(e,t){return V(()=>(this.invokeCallHook(e,t),this.poolingFunction(Fe(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}},Ud=class extends JC{constructor(e){super(e)}poolingFunction(e,t,o,n,s){return $t(s),Yr(n),yL(e,t,o,n,s,"max")}};Ud.className="MaxPooling3D";Q.registerClass(Ud);var Hd=class extends JC{constructor(e){super(e)}poolingFunction(e,t,o,n,s){return $t(s),Yr(n),yL(e,t,o,n,s,"avg")}};Hd.className="AveragePooling3D";Q.registerClass(Hd);var QC=class extends Me{constructor(e){super(e);this.inputSpec=[new At({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new 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e(a)}},Zd=class extends t0{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=Je(e),e.length<3)throw new z(`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=Je(e);let t=[e[0]].concat(e.slice(2)),o=this.layer.computeOutputShape(t),n=e[1];return[o[0],n].concat(o.slice(1))}call(e,t){return V(()=>(e=Fe(e),KC((a,i)=>[Fe(this.layer.call(a,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};Zd.className="TimeDistributed";Q.registerClass(Zd);function sJ(r){oi(NM,"BidirectionalMergeMode",r)}var iJ="concat",Jd=class extends t0{constructor(e){super(e);let t=e.layer.getConfig(),o={};o.className=e.layer.getClassName(),o.config=t,this.forwardLayer=Jr(o),t.goBackwards=t.goBackwards!==!0;let n={};if(n.className=e.layer.getClassName(),n.config=t,this.backwardLayer=Jr(n),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?iJ:e.mergeMode,sJ(this.mergeMode),e.weights)throw new Se("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,o=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,o)),this.backwardLayer.setWeights(e.slice(o))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let o,n,s;return this.returnState&&(s=t.slice(1)),o=t[0],o=o,this.mergeMode==="concat"?(o[o.length-1]*=2,n=[o]):this.mergeMode==null?n=[o,o.slice()]:n=[o],this.returnState?this.mergeMode==null?n.concat(s).concat(s.slice()):[o].concat(s).concat(s.slice()):xr(n)}apply(e,t){let o=t==null?null:t.initialState,n=t==null?null:t.constants;t==null&&(t={});let s=qC(e,o,n,this.numConstants);if(e=s.inputs,o=s.initialState,n=s.constants,Array.isArray(e)&&(o=e.slice(1),e=e[0]),(o==null||o.length===0)&&n==null)return super.apply(e,t);let a=[],i=[];if(o!=null){let u=o.length;if(u%2>0)throw new z("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=o,a.push(...o);let c=o.map(p=>new 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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 o of this.layers)t.push(...o.trainableWeights);return t.concat(e)}return e}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}loadWeights(e,t=!0){let o={},n=0;for(let a of this.layers)for(let i of a.weights){if(o[i.originalName]!=null)throw new z(`Duplicate weight name: ${i.originalName}`);o[i.originalName]=i,n++}let s=[];for(let a in e){let i=a;if(o[a]==null){let l=a.split("/");i=l.slice(0,-2).concat([l[l.length-1]]).join("/")}if(o[i]!=null)s.push([o[i],e[a]]);else if(t)throw new z(`Provided weight data has no target variable: ${a}`);delete o[i]}if(t){let a=[];for(let i in o)a.push(i);if(a.length>0)throw new z(`${a.length} of ${n} weights are not set: ${a}`)}Mp(s)}updatedConfig(){let e=this.getConfig(),t={};return t.className=this.getClassName(),t.config=e,t.kerasVersion=`tfjs-layers ${ld}`,t.backend="TensorFlow.js",t}toJSON(e,t=!0){let o=Vx(this.updatedConfig());return t?JSON.stringify(o):o}call(e,t){return V(()=>{e=yt(e);let o=new Ss;for(let n=0;n<this.inputs.length;++n)o.add(this.inputs[n],e[n]);return Bu(this.outputs,o,t)})}computeMask(e,t){return V(()=>{e=yt(e);let o;return t==null?o=mn(null,e.length):o=yt(t),this.runInternalGraph(e,o)[1]})}computeOutputShape(e){let t=Op(e);if(t.length!==this.inputLayers.length)throw new z(`Invalid inputShape argument ${e}: model has ${this.inputLayers.length} tensor inputs.`);let o={};for(let i=0;i<t.length;i++){let l=this.inputLayers[i],u=t[i],c=l.name+"_0_0";o[c]=u}let n=Object.keys(this.nodesByDepth).map(i=>parseInt(i,10)).sort(Bf);if(n.length>1)for(let i of n){let l=this.nodesByDepth[i];for(let u of l){let c=u.outboundLayer;if(this.inputLayers.map(h=>h.id).indexOf(c.id)!==-1)continue;let p=[];for(let h=0;h<u.inboundLayers.length;h++){let g=u.inboundLayers[h],x=u.nodeIndices[h],b=u.tensorIndices[h],w=`${g.name}_${x}_${b}`,_=o[w];p.push(_)}let m=c.computeOutputShape(xr(p)),f=Op(m),d=c.inboundNodes.indexOf(u);for(let h=0;h<f.length;h++){let g=`${c.name}_${d}_${h}`;o[g]=f[h]}}}let s=[],a=[];for(let i=0;i<this.outputLayers.length;i++){let l=this.outputLayers[i],u=this.outputLayersNodeIndices[i],c=this.outputLayersTensorIndices[i],p=`${l.name}_${u}_${c}`;a.push(p)}for(let i=0;i<a.length;i++){let l=a[i];Vo(l in o),s.push(o[l])}return xr(s)}runInternalGraph(e,t){t==null&&(t=mn(null,e.length));let o={};for(let l=0;l<this.inputs.length;++l){let u=this.inputs[l],c=e[l],p=t[l];o[u.id]=[c,p]}let n=Object.keys(this.nodesByDepth).map(l=>parseInt(l,10)).sort(Bf);for(let l of n){let u=this.nodesByDepth[l];for(let c of u){let p=c.outboundLayer,m=c.inputTensors,f=c.outputTensors,d=new Array;for(let h of m)h.id in o&&d.push(o[h.id]);if(d.length===m.length){let h={},g,x,b,w;if(c.callArgs!=null&&(h=c.callArgs),d.length===1){let[_,k]=d[0];h.mask==null&&(h.mask=k),b=yt(p.call(_,h)),w=yt(p.computeMask(_,k)),g=[_],x=[k]}else g=d.map(_=>_[0]),x=d.map(_=>_[1]),h.mask==null&&(h.mask=x),b=yt(p.call(g,h)),w=yt(p.computeMask(g,x));if(p.activityRegularizer)throw new Se("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let _=0;_<f.length;++_){let k=f[_],D=b[_],T=w[_];o[k.id]=[D,T]}}}}let s=[],a=[],i=[];for(let l of this.outputs){Vo(l.id in o,`Could not compute output ${l.name} : ${l.id}`);let[u,c]=o[l.id];i.push(u.shape),s.push(u),a.push(c)}return[s,a,i]}buildNodeConversionMap(e){let t={},o;for(let n of this.layers){o=n instanceof Go?1:0;for(let s=0;s<n.inboundNodes.length;s++){let a=Go.nodeKey(n,s);this.containerNodes.has(a)&&(t[a]=o,o+=1)}}return t}getLayer(e,t){if(t!=null){if(this.layers.length<=t)throw new z(`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 z("Provide either a layer name or layer index");for(let o of this.layers)if(o.name===e)return o;throw new z(`No such layer: ${e}`)}calculateLosses(){return V(()=>{let e=[];for(let t of this.layers)for(let o=0;o<t.inboundNodes.length;++o){let n=Go.nodeKey(t,o);this.containerNodes.has(n)&&e.push(...t.calculateLosses())}return e})}getConfig(){let e={name:this.name},t=this.buildNodeConversionMap(this.layers),o=[];for(let a of this.layers){let i=a.getClassName(),l=a.getConfig(),u=[];for(let p=0;p<a.inboundNodes.length;p++){let m=a.inboundNodes[p],f=Go.nodeKey(a,p),d={};if(this.containerNodes.has(f)){if(m.callArgs)try{JSON.stringify(m.callArgs),d=m.callArgs}catch(h){console.warn(`Layer ${a.name} was passed non-serializable keyword arguments: ${m.callArgs}. 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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(){V(()=>{this.layers.forEach(e=>{e.stateful&&e.resetStates()})})}};function yQ(r,e,t){let o=e.length;if(r==null||Array.isArray(r)&&r.length===0)return e.map(n=>null);if(o===1)return Array.isArray(r)&&r.length===1?r:typeof r=="object"&&e[0]in r?[r[e[0]]]:[r];if(Array.isArray(r)){if(r.length!==o)throw new Error(`Provided ${t} is an array of ${r.length} element(s), but the model has ${o} outputs. Make sure a set of weights is provided for each model output.`);return r}else if(typeof r=="object"&&Object.keys(r).length>0&&typeof r[Object.keys(r)[0]]=="object"){let n=[];return e.forEach(s=>{s in r?n.push(r[s]):n.push(null)}),n}else throw new Error(`The model has multiple (${o}) outputs, so ${t} must be either an array with ${o} elements or an object with ${e} keys. Provided ${t} not understood: ${JSON.stringify(r)}`)}function Gx(r,e){return yQ(r,e,"classWeight")}async function Wx(r,e,t,o){if(e!=null||o!=null)throw new Error("Support sampleWeight is not implemented yet");if(t!=null){let n=V(()=>{if(r.shape.length===1)return r.clone();if(r.shape.length===2)if(r.shape[1]>1){let i=1;return r.argMax(i)}else{if(r.shape[1]===1)return r.reshape([r.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${r.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${r.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),s=Array.from(await n.data());Ae(n);let a=[];return s.forEach(i=>{if(t[i]==null)throw new Error(`classWeight must contain all classes in the training data. 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Use LayersModel.compile(modelCompileConfig)."),y.assert(t!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),y.assert(t.epochs!=null&&t.epochs>0&&Number.isInteger(t.epochs),()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${t.epochs}`),y.assert(!o||t.batchesPerEpoch>0&&Number.isInteger(t.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${t.batchesPerEpoch}`),y.assert(t.validationSplit==null,()=>"`validationSplit` is not supported by `fitDataset()`. 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e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};dd.className="ThresholdedReLU";Q.registerClass(dd);var hd=class extends Me{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new ud().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let o=Fe(e);return this.softmax(o,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};hd.className="Softmax";Q.registerClass(hd);function Il(r,e,t){if(typeof r=="number")return mn(r,e);if(r.length!==e)throw new z(`The ${t} argument must be an integer or tuple of ${e} integers. 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Received: ${JSON.stringify(r)} including a non-integer number ${n}`)}return r}function bo(r,e,t,o,n=1){if(r==null)return r;let s=e+(e-1)*(n-1),a;return t==="same"?a=r:a=r-s+1,Math.floor((a+o-1)/o)}function gd(r,e,t,o){if(r==null)return null;if(o==="valid")r=r*e+Ns([t-e,0]);else if(o==="same")r=r*e;else throw new z(`Unsupport padding mode: ${o}.`);return r}function xd(r,e){return V(()=>($t(e),e==="channelsFirst"?Ke(r,[0,2,3,1]):r))}function t0(r,e){return V(()=>($t(e),e==="channelsFirst"?Ke(r,[0,2,3,4,1]):r))}function OQ(r,e,t,o=1,n="valid",s,a=1){return V(()=>{if(s==null&&(s=Jr()),$t(s),r.shape.length!==3)throw new z(`The input of a conv1dWithBias operation should be 3, but is ${r.shape.length} instead.`);if(e.shape.length!==3)throw new z(`The kernel for a conv1dWithBias operation should be 3, but is ${e.shape.length} instead`);if(t!=null&&t.shape.length!==1)throw new z(`The bias for a conv1dWithBias operation should be 1, but is ${e.shape.length} instead`);if(s==="channelsFirst"&&(r=Ke(r,[0,2,1])),n==="causal")throw new Se("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let i=Xl(r,e,o,n==="same"?"same":"valid","NWC",a);return t!=null&&(i=ho(i,t)),i})}function Zz(r,e,t,o=[1,1],n="valid",s,a,i=null){return V(()=>{if(s==null&&(s=Jr()),$t(s),r.rank!==3&&r.rank!==4)throw new z(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${r.rank}.`);if(e.rank!==3&&e.rank!==4)throw new z(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${r.rank}.`);let l=xd(r,s);if(n==="causal")throw new Se("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=rn.conv2d({x:l,filter:e,strides:o,pad:n==="same"?"same":"valid",dilations:a,dataFormat:"NHWC",bias:t,activation:i}),s==="channelsFirst"&&(l=Ke(l,[0,3,1,2])),l})}function PQ(r,e,t,o=[1,1,1],n="valid",s,a){return V(()=>{if(s==null&&(s=Jr()),$t(s),r.rank!==4&&r.rank!==5)throw new z(`conv3dWithBias expects input to be of rank 4 or 5, but received ${r.rank}.`);if(e.rank!==4&&e.rank!==5)throw new z(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${r.rank}.`);let i=t0(r,s);if(n==="causal")throw new Se("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return i=Lm(i,e,o,n==="same"?"same":"valid","NDHWC",a),t!=null&&(i=ho(i,t)),s==="channelsFirst"&&(i=Ke(i,[0,4,1,2,3])),i})}var Gp=class extends Me{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",Gp.verifyArgs(t),this.rank=e,jt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Se(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Il(t.kernelSize,e,"kernelSize"),this.strides=Il(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Qr(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,$t(this.dataFormat),this.activation=As(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=pt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Ot(t.biasConstraint),this.biasRegularizer=bt(t.biasRegularizer),this.activityRegularizer=bt(t.activityRegularizer),this.dilationRate=Il(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new z(`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 z(`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 z(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Vo("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!_x(e.kernelSize,"number",1,3))throw new z(`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:Ts(this.activation),useBias:this.useBias,biasInitializer:kt(this.biasInitializer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),biasConstraint:Ft(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Gu=class extends Gp{constructor(e,t){super(e,t);this.kernel=null,Gu.verifyArgs(t),this.filters=t.filters,jt(this.filters,"filters"),this.kernelInitializer=pt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Ot(t.kernelConstraint),this.kernelRegularizer=bt(t.kernelRegularizer)}build(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new z(`The channel dimension of the input should be defined. Found ${e[t]}`);let o=e[t],n=this.kernelSize.concat([o,this.filters]);this.kernel=this.addWeight("kernel",n,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]:o}}],this.built=!0}call(e,t){return V(()=>{e=Fe(e);let o,n=this.bias==null?null:this.bias.read(),s=kx(this.activation.getClassName());if(s!=null&&this.rank===2)o=Zz(e,this.kernel.read(),n,this.strides,this.padding,this.dataFormat,this.dilationRate,s);else{if(this.rank===1)o=OQ(e,this.kernel.read(),n,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)o=Zz(e,this.kernel.read(),n,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)o=PQ(e,this.kernel.read(),n,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Se("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(o=this.activation.apply(o))}return o})}computeOutputShape(e){e=Je(e);let t=[],o=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let s=0;s<o.length;++s){let a=bo(o[s],this.kernelSize[s],this.padding,this.strides[s],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[s]);t.push(a)}let n=[e[0]];return this.dataFormat==="channelsLast"?(n=n.concat(t),n.push(this.filters)):(n.push(this.filters),n=n.concat(t)),n}getConfig(){let e={filters:this.filters,kernelInitializer:kt(this.kernelInitializer),kernelRegularizer:st(this.kernelRegularizer),kernelConstraint:Ft(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 z(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Nl=class extends Gu{constructor(e){super(2,e);Nl.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!_x(e.kernelSize,"number",1,2))throw new z(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Nl.className="Conv2D";Q.registerClass(Nl);var Wu=class extends Gu{constructor(e){super(3,e);Wu.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 z(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};Wu.className="Conv3D";Q.registerClass(Wu);var yd=class extends Nl{constructor(e){super(e);if(this.inputSpec=[new At({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new z(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=Je(e),e.length!==4)throw new z("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new z("The channel dimension of the inputs should be defined. Found `None`.");let o=e[t],n=this.kernelSize.concat([this.filters,o]);this.kernel=this.addWeight("kernel",n,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new At({ndim:4,axes:{[t]:o}})],this.built=!0}call(e,t){return V(()=>{let o=Fe(e);if(o.shape.length!==4)throw new z(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${o.shape.length}`);let n=o.shape,s=n[0],a,i;this.dataFormat==="channelsFirst"?(a=2,i=3):(a=1,i=2);let l=n[a],u=n[i],c=this.kernelSize[0],p=this.kernelSize[1],m=this.strides[0],f=this.strides[1],d=gd(l,m,c,this.padding),h=gd(u,f,p,this.padding),g=[s,d,h,this.filters];this.dataFormat!=="channelsLast"&&(o=Ke(o,[0,2,3,1]));let x=Yl(o,this.kernel.read(),g,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(x=Ke(x,[0,3,1,2])),this.bias!=null&&(x=ho(x,this.bias.read(),this.dataFormat)),this.activation!=null&&(x=this.activation.apply(x)),x})}computeOutputShape(e){e=Je(e);let t=e.slice(),o,n,s;this.dataFormat==="channelsFirst"?(o=1,n=2,s=3):(o=3,n=1,s=2);let a=this.kernelSize[0],i=this.kernelSize[1],l=this.strides[0],u=this.strides[1];return t[o]=this.filters,t[n]=gd(t[n],l,a,this.padding),t[s]=gd(t[s],u,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};yd.className="Conv2DTranspose";Q.registerClass(yd);var r0=class extends Gu{constructor(e,t){super(e,t);if(this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new z("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new z("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 z(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=pt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=bt(t.depthwiseRegularizer),this.depthwiseConstraint=Ot(t.depthwiseConstraint),this.pointwiseInitializer=pt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=bt(t.pointwiseRegularizer),this.pointwiseConstraint=Ot(t.pointwiseConstraint)}build(e){if(e=Je(e),e.length<this.rank+2)throw new z(`Inputs to SeparableConv${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 z(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let o=e[t],n=this.kernelSize.concat([o,this.depthMultiplier]),s=[];for(let i=0;i<this.rank;++i)s.push(1);s.push(o*this.depthMultiplier,this.filters);let a=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",n,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,a,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",s,"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 At({ndim:this.rank+2,axes:{[t]:o}})],this.built=!0}call(e,t){return V(()=>{e=Fe(e);let o;if(this.rank===1)throw new Se("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=Ke(e,[0,2,3,1])),o=Zm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(o=ho(o,this.bias.read(),this.dataFormat)),this.activation!=null&&(o=this.activation.apply(o)),this.dataFormat==="channelsFirst"&&(o=Ke(o,[0,3,1,2])),o})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=kt(this.depthwiseInitializer),e.pointwiseInitializer=kt(this.pointwiseInitializer),e.depthwiseRegularizer=st(this.depthwiseRegularizer),e.pointwiseRegularizer=st(this.pointwiseRegularizer),e.depthwiseConstraint=Ft(this.depthwiseConstraint),e.pointwiseConstraint=Ft(this.pointwiseConstraint),e}};r0.className="SeparableConv";var bd=class extends r0{constructor(e){super(2,e)}};bd.className="SeparableConv2D";Q.registerClass(bd);var ju=class extends Gu{constructor(e){super(1,e);ju.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"&&!_x(e.kernelSize,"number",1,1))throw new z(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};ju.className="Conv1D";Q.registerClass(ju);var wd=class extends Me{constructor(e){super(e);typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return this.dataFormat==="channelsFirst"?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}call(e,t){return V(()=>{if(e=Fe(e),this.dataFormat==="channelsLast"){let o=Hf(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Hf(o,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let o=Hf(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Hf(o,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};wd.className="Cropping2D";Q.registerClass(wd);var _d=class extends Me{constructor(e){super(e);this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,$t(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,az(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],o=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,o]}else{let t=e[1]==null?null:this.size[0]*e[1],o=e[2]==null?null:this.size[1]*e[2];return[e[0],t,o,e[3]]}}call(e,t){return V(()=>{let o=Fe(e),n=o.shape;if(this.dataFormat==="channelsFirst"){o=Ke(o,[0,2,3,1]);let s=this.size[0]*n[2],a=this.size[1]*n[3],i=this.interpolation==="nearest"?o.resizeNearestNeighbor([s,a]):o.resizeBilinear([s,a]);return Ke(i,[0,3,1,2])}else{let s=this.size[0]*n[1],a=this.size[1]*n[2];return this.interpolation==="nearest"?o.resizeNearestNeighbor([s,a]):o.resizeBilinear([s,a])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};_d.className="UpSampling2D";Q.registerClass(_d);function MQ(r,e,t=[1,1],o="valid",n,s){return V(()=>{n==null&&(n=Jr()),$t(n);let a=xd(r,n);if(r.rank!==4)throw new z(`Input for depthwiseConv2d is required to be 4-D, but is instead ${r.rank}-D`);if(e.rank!==4)throw new z(`depthwiseKernel is required to be 4-D, but is instead ${e.rank}-D`);return a=ds(a,e,t,o==="same"?"same":"valid","NHWC",s),n==="channelsFirst"&&(a=Ke(a,[0,3,1,2])),a})}var kd=class extends Gp{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=pt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Ot(e.depthwiseConstraint),this.depthwiseRegularizer=bt(e.depthwiseRegularizer)}build(e){if(e=Je(e),e.length<4)throw new z(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new z(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let o=e[t],n=[this.kernelSize[0],this.kernelSize[1],o,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",n,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[o*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return V(()=>{e=Fe(e);let o=MQ(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(o=ho(o,this.bias.read(),this.dataFormat)),this.activation!=null&&(o=this.activation.apply(o)),o})}computeOutputShape(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],o=this.dataFormat==="channelsFirst"?e[3]:e[2],n=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,s=bo(t,this.kernelSize[0],this.padding,this.strides[0]),a=bo(o,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],n,s,a]:[e[0],s,a,n]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=kt(this.depthwiseInitializer),e.depthwiseRegularizer=st(this.depthwiseRegularizer),e.depthwiseConstraint=Ft(this.depthwiseRegularizer),e}};kd.className="DepthwiseConv2D";Q.registerClass(kd);function o0(r,e,t,o){if(Array.isArray(r)){if(e!=null||t!=null)throw new z("When inputs is an array, neither initialState or constants should be provided");o!=null&&(t=r.slice(r.length-o,r.length),r=r.slice(0,r.length-o)),r.length>1&&(e=r.slice(1,r.length)),r=r[0]}function n(s){return s==null||Array.isArray(s)?s:[s]}return e=n(e),t=n(t),{inputs:r,initialState:e,constants:t}}function n0(r,e,t,o=!1,n,s,a=!1,i=!1){return V(()=>{let l=e.shape.length;if(l<3)throw new z(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(Gr(2,l));if(e=Ke(e,u),s!=null)throw new Se("The rnn() functoin of the deeplearn.js backend does not support constants yet.");a&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),n!=null&&(n=n.asType("bool").asType("float32"),n.rank===l-1&&(n=lr(n,-1)),n=Ke(n,u)),o&&(e=Ht(e,0),n!=null&&(n=Ht(n,0)));let c=[],p,m=t,f=e.shape[0],d=mr(e),h;n!=null&&(h=mr(n));for(let x=0;x<f;++x){let b=d[x],w=V(()=>r(b,m));if(n==null)p=w[0],m=w[1];else{let _=V(()=>{let k=h[x],D=rr(k).sub(k),T=w[0].mul(k).add(m[0].mul(D)),R=m.map((O,M)=>w[1][M].mul(k).add(O.mul(D)));return{output:T,newStates:R}});p=_.output,m=_.newStates}i&&c.push(p)}let g;return i&&(g=Bt(c,1)),[p,g,m]})}var Eo=class extends Me{constructor(e){super(e);let t;if(e.cell==null)throw new z("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Wp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new z("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 At({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 Gr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){Ex(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let o=t[0],n;if(this.returnSequences?n=[e[0],e[1],o]:n=[e[0],o],this.returnState){let s=[];for(let a of t)s.push([e[0],a]);return[n].concat(s)}else return n}computeMask(e,t){return V(()=>{Array.isArray(t)&&(t=t[0]);let o=this.returnSequences?t:null;if(this.returnState){let n=this.states.map(s=>null);return[o].concat(n)}else return o})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let o=0;o<e;++o)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){let t=null;if(this.numConstants!=null)throw new Se("Constants support is not implemented in RNN yet.");Ex(e)&&(e=e[0]),e=e;let o=this.stateful?e[0]:null,n=e.slice(2);this.inputSpec[0]=new At({shape:[o,null,...n]});let s=[e[0]].concat(e.slice(2));if(t!=null)throw new Se("Constants support is not implemented in RNN yet.");this.cell.build(s);let a;if(Array.isArray(this.cell.stateSize)?a=this.cell.stateSize:a=[this.cell.stateSize],this.stateSpec!=null){if(!y.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),a))throw new z(`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(i=>new At({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){V(()=>{if(!this.stateful)throw new Ao("Cannot call resetStates() on an RNN Layer that is not stateful.");let o=this.inputSpec[0].shape[0];if(o==null)throw new z("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(n=>ht([o,n])):this.states_=[ht([o,this.cell.stateSize])];else if(e==null)Ae(this.states_),this.keptStates!=null&&(Ae(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(n=>ht([o,n])):this.states_[0]=ht([o,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new z(`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()):Ae(this.states_);for(let n=0;n<this.states_.length;++n){let s=e[n],a=Array.isArray(this.cell.stateSize)?this.cell.stateSize[n]:this.cell.stateSize,i=[o,a];if(!y.arraysEqual(s.shape,i))throw new z(`State ${n} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${s.shape}`);this.states_[n]=s}}this.states_=this.states_.map(n=>Et(n.clone()))})}apply(e,t){let o=t==null?null:t.initialState,n=t==null?null:t.constants;t==null&&(t={});let s=o0(e,o,n,this.numConstants);e=s.inputs,o=s.initialState,n=s.constants;let a=[],i=[];if(o!=null){t.initialState=o,a=a.concat(o),this.stateSpec=[];for(let u of o)this.stateSpec.push(new At({shape:u.shape}));i=i.concat(this.stateSpec)}if(n!=null&&(t.constants=n,a=a.concat(n),this.numConstants=n.length),a[0]instanceof eo){let u=[e].concat(a),c=this.inputSpec.concat(i),p=this.inputSpec;this.inputSpec=c;let m=super.apply(u,t);return this.inputSpec=p,m}else return super.apply(e,t)}call(e,t){return V(()=>{let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;e=Fe(e),s==null&&(this.stateful?s=this.states_:s=this.getInitialState(e));let a=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(s.length!==a)throw new z(`RNN Layer has ${a} state(s) but was passed ${s.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:n},u=n0((d,h)=>{let g=this.cell.call([d].concat(h),i);return[g[0],g.slice(1)]},e,s,this.goBackwards,o,null,this.unroll,this.returnSequences),c=u[0],p=u[1],m=u[2];this.stateful&&this.resetStates(m,n);let f=this.returnSequences?p:c;return this.returnState?[f].concat(m):f})}getInitialState(e){return V(()=>{let t=ht(e.shape);return t=ge(t,[1,2]),t=Ea(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(o=>o>1?Ix(t,[1,o]):t):this.cell.stateSize>1?[Ix(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 o=this.cell.getConfig();return this.getClassName()===Eo.className&&(t.cell={className:this.cell.getClassName(),config:o}),Object.assign({},o,e,t)}static fromConfig(e,t,o={}){let n=t.cell,s=to(n,o);return new e(Object.assign(t,{cell:s}))}};Eo.className="RNN";Q.registerClass(Eo);var Sl=class extends Me{},jp=class extends Sl{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,jt(this.units,"units"),this.activation=As(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=pt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=bt(e.kernelRegularizer),this.recurrentRegularizer=bt(e.recurrentRegularizer),this.biasRegularizer=bt(e.biasRegularizer),this.kernelConstraint=Ot(e.kernelConstraint),this.recurrentConstraint=Ot(e.recurrentConstraint),this.biasConstraint=Ot(e.biasConstraint),this.dropout=Ou([1,Ns([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Ou([1,Ns([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=Je(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 V(()=>{if(e=e,e.length!==2)throw new z(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let o=e[1];e=e[0];let n=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Ra({ones:()=>rr(e),rate:this.dropout,training:n})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Ra({ones:()=>rr(o),rate:this.recurrentDropout,training:n}));let s,a=this.dropoutMask,i=this.recurrentDropoutMask;a!=null?s=xn(P(e,a),this.kernel.read()):s=xn(e,this.kernel.read()),this.bias!=null&&(s=ho(s,this.bias.read())),i!=null&&(o=P(o,i));let l=ee(s,xn(o,this.recurrentKernel.read()));return this.activation!=null&&(l=this.activation.apply(l)),[l,l]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ts(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:st(this.kernelRegularizer),recurrentRegularizer:st(this.recurrentRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ft(this.kernelConstraint),recurrentConstraint:Ft(this.recurrentConstraint),biasConstraint:Ft(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};jp.className="SimpleRNNCell";Q.registerClass(jp);var vd=class extends Eo{constructor(e){e.cell=new jp(e),super(e)}call(e,t){return V(()=>{this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:o,training:n,initialState:s})})}static fromConfig(e,t){return new e(t)}};vd.className="SimpleRNN";Q.registerClass(vd);var Up=class extends Sl{constructor(e){super(e);if(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 z("GRUCell does not support reset_after parameter set to true.");this.units=e.units,jt(this.units,"units"),this.activation=As(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=As(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=pt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=bt(e.kernelRegularizer),this.recurrentRegularizer=bt(e.recurrentRegularizer),this.biasRegularizer=bt(e.biasRegularizer),this.kernelConstraint=Ot(e.kernelConstraint),this.recurrentConstraint=Ot(e.recurrentConstraint),this.biasConstraint=Ot(e.biasConstraint),this.dropout=Ou([1,Ns([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Ou([1,Ns([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=Je(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 V(()=>{if(e=e,e.length!==2)throw new z(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let o=t.training==null?!1:t.training,n=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Ra({ones:()=>rr(e),rate:this.dropout,training:o,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Ra({ones:()=>rr(n),rate:this.recurrentDropout,training:o,count:3}));let s=this.dropoutMask,a=this.recurrentDropoutMask,i,l,u;0<this.dropout&&this.dropout<1&&(e=P(e,s[0]));let c=xn(e,this.kernel.read());this.useBias&&(c=ho(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(n=P(n,a[0]));let p=this.recurrentKernel.read(),[m,f]=pr(p,[2*this.units,this.units],p.rank-1),d=xn(n,m),[h,g,x]=pr(c,3,c.rank-1),[b,w]=pr(d,2,d.rank-1);i=this.recurrentActivation.apply(ee(h,b)),l=this.recurrentActivation.apply(ee(g,w));let _=xn(P(l,n),f);u=this.activation.apply(ee(x,_));let k=ee(P(i,n),P(ee(1,He(i)),u));return[k,k]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ts(this.activation),recurrentActivation:Ts(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:st(this.kernelRegularizer),recurrentRegularizer:st(this.recurrentRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ft(this.kernelConstraint),recurrentConstraint:Ft(this.recurrentConstraint),biasConstraint:Ft(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};Up.className="GRUCell";Q.registerClass(Up);var Cd=class extends Eo{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 Up(e),super(e)}call(e,t){return V(()=>{this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:o,training:n,initialState:s})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Cd.className="GRU";Q.registerClass(Cd);var Tl=class extends Sl{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,jt(this.units,"units"),this.activation=As(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=As(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=pt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=bt(e.kernelRegularizer),this.recurrentRegularizer=bt(e.recurrentRegularizer),this.biasRegularizer=bt(e.biasRegularizer),this.kernelConstraint=Ot(e.kernelConstraint),this.recurrentConstraint=Ot(e.recurrentConstraint),this.biasConstraint=Ot(e.biasConstraint),this.dropout=Ou([1,Ns([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Ou([1,Ns([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=Je(e);let o=e[e.length-1];this.kernel=this.addWeight("kernel",[o,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 n;if(this.useBias){if(this.unitForgetBias){let s=this.biasInitializer,a=this.units;n=new(t=class extends go{apply(l,u){let c=s.apply([a]),p=new Mu().apply([a]),m=s.apply([a*2]);return IC(IC(c,p),m)}},t.className="CustomInit",t)}else n=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,n,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return V(()=>{let o=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new z(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=e[1],s=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Ra({ones:()=>rr(e),rate:this.dropout,training:o,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Ra({ones:()=>rr(n),rate:this.recurrentDropout,training:o,count:4}));let a=this.dropoutMask,i=this.recurrentDropoutMask,l,u,c,p;0<this.dropout&&this.dropout<1&&(e=P(e,a[0]));let m=xn(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(n=P(n,i[0])),m=ee(m,xn(n,this.recurrentKernel.read())),this.useBias&&(m=ho(m,this.bias.read()));let[f,d,h,g]=pr(m,4,m.rank-1);l=this.recurrentActivation.apply(f),u=this.recurrentActivation.apply(d),c=ee(P(u,s),P(l,this.activation.apply(h))),p=this.recurrentActivation.apply(g);let x=P(p,this.activation.apply(c));return[x,x,c]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Ts(this.activation),recurrentActivation:Ts(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:st(this.kernelRegularizer),recurrentRegularizer:st(this.recurrentRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ft(this.kernelConstraint),recurrentConstraint:Ft(this.recurrentConstraint),biasConstraint:Ft(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Tl.className="LSTMCell";Q.registerClass(Tl);var Id=class extends Eo{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 Tl(e),super(e)}call(e,t){return V(()=>{this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:o,training:n,initialState:s})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Id.className="LSTM";Q.registerClass(Id);var Wp=class extends Sl{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 V(()=>{e=e;let o=e.slice(1),n=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?n.push(o.splice(0,i.stateSize.length)):n.push(o.splice(0,1));n.reverse();let s=[],a;for(let i=0;i<this.cells.length;++i){let l=this.cells[i];o=n[i],i===0?a=[e[0]].concat(o):a=[a[0]].concat(o),a=l.call(a,t),s.push(a.slice(1))}o=[];for(let i of s.slice().reverse())o.push(...i);return[a[0]].concat(o)})}build(e){Ex(e)&&(e=e[0]),e=e;let t;this.cells.forEach((o,n)=>{Is(`RNNCell_${n}`,()=>{o.build(e),Array.isArray(o.stateSize)?t=o.stateSize[0]:t=o.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=s=>({className:s.getClassName(),config:s.getConfig()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,o={}){let n=[];for(let s of t.cells)n.push(to(s,o));return new e({cells:n})}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 o of this.cells)t.push(...o.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return ed(e)}setWeights(e){let t=[];for(let o of this.cells){let n=o.weights.length,s=e.splice(n);for(let a=0;a<o.weights.length;++a)t.push([o.weights[a],s[a]])}Mp(t)}};Wp.className="StackedRNNCells";Q.registerClass(Wp);function Ra(r){let{ones:e,rate:t,training:o=!1,count:n=1}=r,s=()=>Sx(e(),t),a=()=>bl(s,e,o);return!n||n<=1?Et(a().clone()):Array(n).fill(void 0).map(a).map(l=>Et(l.clone()))}var LQ=function(r,e){var t={};for(var o in r)Object.prototype.hasOwnProperty.call(r,o)&&e.indexOf(o)<0&&(t[o]=r[o]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var n=0,o=Object.getOwnPropertySymbols(r);n<o.length;n++)e.indexOf(o[n])<0&&Object.prototype.propertyIsEnumerable.call(r,o[n])&&(t[o[n]]=r[o[n]]);return t};var s0=class extends Eo{constructor(e){if(e.unroll)throw new Se("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Se("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new At({ndim:5})]}call(e,t){return V(()=>{if(this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new z("ConvRNN2D cell does not support constants");let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:o,training:n,initialState:s})})}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 V(()=>{let{stateSize:t}=this.cell,o=e.shape,n=this.computeSingleOutputShape(o),s=[n[0],...n.slice(2)],a=ht(s);return Array.isArray(t)?Array(t.length).fill(a):[a]})}resetStates(e,t=!1){V(()=>{if(!this.stateful)throw new Ao("Cannot call resetStates() on an RNN Layer that is not stateful.");let o=this.inputSpec[0].shape,n=this.computeSingleOutputShape(o),s=[n[0],...n.slice(2)];if(o[0]==null)throw new z("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(()=>ht(s)):this.states_=[ht(s)];else if(e==null)Ae(this.states_),this.keptStates!=null&&(Ae(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>ht(s)):this.states_[0]=ht(s);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new z(`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()):Ae(this.states_);for(let i=0;i<this.states_.length;++i){let l=e[i],u=s;if(!y.arraysEqual(l.shape,u))throw new z(`State ${i} is incompatible with layer ${this.name}: expected shape=${u}, received shape=${l.shape}`);this.states_[i]=l}}this.states_=this.states_.map(i=>Et(i.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:o,kernelSize:n,padding:s,strides:a,dilationRate:i}=this.cell,l=t==="channelsFirst",u=e[l?3:2],c=e[l?4:3],p=bo(u,n[0],s,a[0],i[0]),m=bo(c,n[1],s,a[1],i[1]);return[...e.slice(0,2),...l?[o,p,m]:[p,m,o]]}};s0.className="ConvRNN2D";var Hp=class extends Tl{constructor(e){let{filters:t,kernelSize:o,strides:n,padding:s,dataFormat:a,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,jt(this.filters,"filters"),this.kernelSize=Il(o,2,"kernelSize"),this.kernelSize.forEach(l=>jt(l,"kernelSize")),this.strides=Il(n||1,2,"strides"),this.strides.forEach(l=>jt(l,"strides")),this.padding=s||"valid",Qr(this.padding),this.dataFormat=a||"channelsLast",$t(this.dataFormat),this.dilationRate=Il(i||1,2,"dilationRate"),this.dilationRate.forEach(l=>jt(l,"dilationRate"))}build(e){var t;e=Je(e);let o=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[o]==null)throw new z(`The channel dimension of the input should be defined. Found ${e[o]}`);let n=e[o],s=4,a=this.kernelSize.concat([n,this.filters*s]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*s]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let l;if(this.unitForgetBias){let u=this.biasInitializer,c=this.filters;l=new(t=class extends go{apply(m,f){let d=u.apply([c]),h=Sr([c]),g=u.apply([c*2]);return Sp([d,h,g])}},t.className="CustomInit",t)}else l=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*s],null,l,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return V(()=>{if(e.length!==3)throw new z(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let o=t.training||!1,n=e[0],s=e[1],a=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Ra({ones:()=>rr(n),rate:this.dropout,training:o,count:i}));let l=this.dropoutMask,u=(J,ie,ue)=>!ie||!ie[ue]?J:P(ie[ue],J),c=u(n,l,0),p=u(n,l,1),m=u(n,l,2),f=u(n,l,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Ra({ones:()=>rr(s),rate:this.recurrentDropout,training:o,count:i}));let d=this.recurrentDropoutMask,h=u(s,d,0),g=u(s,d,1),x=u(s,d,2),b=u(s,d,3),w=3,[_,k,D,T]=pr(this.kernel.read(),i,w),[R,O,M,G]=this.useBias?pr(this.bias.read(),i):[null,null,null,null];c=this.inputConv(c,_,R,this.padding),p=this.inputConv(p,k,O,this.padding),m=this.inputConv(m,D,M,this.padding),f=this.inputConv(f,T,G,this.padding);let[j,U,H,q]=pr(this.recurrentKernel.read(),i,w);h=this.recurrentConv(h,j),g=this.recurrentConv(g,U),x=this.recurrentConv(x,H),b=this.recurrentConv(b,q);let X=this.recurrentActivation.apply(ee(c,h)),oe=this.recurrentActivation.apply(ee(p,g)),Y=ee(P(oe,a),P(X,this.activation.apply(ee(m,x)))),re=P(this.recurrentActivation.apply(ee(f,b)),this.activation.apply(Y));return[re,re,Y]})}getConfig(){let e=super.getConfig(),{units:t}=e,o=LQ(e,["units"]),n={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},o,n)}inputConv(e,t,o,n){let s=Yr(e,t,this.strides,n||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return o?ho(s,o,this.dataFormat):s}recurrentConv(e,t){return Yr(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};Hp.className="ConvLSTM2DCell";Q.registerClass(Hp);var Nd=class extends s0{constructor(e){let t=new Hp(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};Nd.className="ConvLSTM2D";Q.registerClass(Nd);var qp=class extends Me{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,o=[];for(let n=0;n<this.noiseShape.length;++n)o.push(this.noiseShape[n]==null?t[n]:this.noiseShape[n]);return o}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e);if(0<this.rate&&this.rate<1){let n=t.training==null?!1:t.training,s=this.getNoiseShape(o);return bl(()=>Sx(o,this.rate,s,this.seed),()=>o,n)}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()}};qp.className="Dropout";Q.registerClass(qp);var Sd=class extends qp{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};Sd.className="SpatialDropout1D";Q.registerClass(Sd);var Td=class extends Me{constructor(e){super(e);if(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,jt(this.units,"units"),this.activation=As(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Ot(e.kernelConstraint),this.biasConstraint=Ot(e.biasConstraint),this.kernelRegularizer=bt(e.kernelRegularizer),this.biasRegularizer=bt(e.biasRegularizer),this.activityRegularizer=bt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=Je(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=Je(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e),n=kx(this.activation.getClassName()),s;return n!=null?s=xn(o,this.kernel.read(),n,this.bias?this.bias.read():null):(s=xn(o,this.kernel.read()),this.bias!=null&&(s=ho(s,this.bias.read())),this.activation!=null&&(s=this.activation.apply(s))),s})}getConfig(){let e={units:this.units,activation:Ts(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:st(this.kernelRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ft(this.kernelConstraint),biasConstraint:Ft(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Td.className="Dense";Q.registerClass(Td);var Ad=class extends Me{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=Je(e);for(let t of e.slice(1))if(t==null)throw new z(`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],gn(e,1)]}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e);if(this.dataFormat==="channelsFirst"&&o.rank>1){let n=[0];for(let s=2;s<o.rank;++s)n.push(s);n.push(1),o=o.transpose(n)}return dz(o)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};Ad.className="Flatten";Q.registerClass(Ad);var Ed=class extends Me{constructor(e){super(e);this.supportsMasking=!0,this.activation=As(e.activation)}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e);return this.activation.apply(o)})}getConfig(){let e={activation:Ts(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};Ed.className="Activation";Q.registerClass(Ed);var Dd=class extends Me{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 V(()=>(e=Fe(e),mz(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};Dd.className="RepeatVector";Q.registerClass(Dd);var $d=class extends Me{constructor(e){super(e);this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let o="Total size of new array must be unchanged.",n=t.slice(),s=1,a=null;for(let l=0;l<n.length;++l){let u=n[l];if(this.isUnknown(u))if(a===null)a=l;else throw new z("Can only specifiy one unknown dimension.");else s*=u}let i=gn(e);if(a!==null){if(s===0||i%s!=0)throw new z(o);n[a]=i/s}else if(i!==s)throw new z(o);return n}computeOutputShape(e){let t=!1;for(let o=0;o<e.length;++o)if(this.isUnknown(e[o])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e),n=o.shape,s=n.slice(0,1).concat(this.fixUnknownDimension(n.slice(1),this.targetShape));return o.reshape(s)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};$d.className="Reshape";Q.registerClass($d);var Rd=class extends Me{constructor(e){super(e);if(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=Gr(1,e.dims.length+1);if(!y.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 At({ndim:this.dims.length+1})]}computeOutputShape(e){e=Je(e);let t=e.slice();return this.dims.forEach((o,n)=>{t[n+1]=e[o]}),t}call(e,t){return Ke(Fe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Rd.className="Permute";Q.registerClass(Rd);var Fd=class extends Me{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 o=Fe(e),n=-1;return al(tn(o,this.maskValue),n)}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e),n=-1,s=!0,a=al(tn(o,this.maskValue),n,s);return o.mul(a.asType(o.dtype))})}};Fd.className="Masking";Q.registerClass(Fd);var Od=class extends Me{constructor(e){super(e);if(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(yt(e.inputLength))}this.inputDim=e.inputDim,jt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,jt(this.outputDim,"outputDim"),this.embeddingsInitializer=pt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=bt(e.embeddingsRegularizer),this.activityRegularizer=bt(e.activityRegularizer),this.embeddingsConstraint=Ot(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 V(()=>this.maskZero?(e=Fe(e),tn(e,Ce(e))):null)}computeOutputShape(e){if(e=Je(e),this.inputLength==null)return[...e,this.outputDim];let t=yt(this.inputLength);if(t.length!==e.length-1)throw new z(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let o=0;for(let n=0;n<t.length;++n){let s=t[n],a=e[n+1];if(s!=null&&a!=null&&s!==a)throw new z(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);s==null&&(t[o]=a),o++}}return[e[0],...t,this.outputDim]}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e);return o.dtype!=="int32"&&(o=Aa(o,"int32")),Nx(this.embeddings.read(),o.as1D()).reshape(Je(this.computeOutputShape(o.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:kt(this.embeddingsInitializer),embeddingsRegularizer:st(this.embeddingsRegularizer),activityRegularizer:st(this.activityRegularizer),embeddingsConstraint:Ft(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Od.className="Embedding";Q.registerClass(Od);var Al=class extends Me{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new Se}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 o=e.slice(0,e.length-t.length);for(let n=0;n<t.length;++n){let s=e[e.length-t.length+n],a=t[n];if(s==null||a==null||s<0||a<0)o.push(null);else if(s===1)o.push(a);else if(a===1)o.push(s);else{if(s!==a)throw new z("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));o.push(s)}}return o}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[Je(e)]),e=e,e.length<2)throw new z(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let s of e)s!=null&&s[0]!==null&&t.push(s[0]);if(t=hn(t),t.length>1)throw new z(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let o=e[0]==null?null:e[0].slice(1);for(let s=1;s<e.length;++s){let a=e[s]==null?null:e[s].slice(1);o=this.computeElementwiseOpOutputShape(o,a)}let n=e.map(s=>s.length);e.indexOf(null)===-1&&hn(n).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return V(()=>{if(e=e,this.reshapeRequired){let o=[],n=e.map(s=>s.rank);if(n.indexOf(null)===-1){let s=Ns(n);for(let a of e){let i=a.rank;for(let l=0;l<s-i;++l)a=Ea(a,1);o.push(a)}return this.mergeFunction(o)}else{let s=!1;for(let l of e){let u=l.rank;if(u==null){let c=l.shape,p=c[0],m=c.slice(1).concat([p]),f=l.reshape([p].concat(gn(c.slice(1))));f=Ke(f,[1,0]),f=f.reshape(m),o.push(f),s=!0}else if(u>1){let c=Gr(1,u).concat([0]);o.push(Ke(l,c)),s=!0}else o.push(l)}let a=this.mergeFunction(o),i=a.rank;if(s){if(i==null){let l=a.shape,u=l.length,c=l[u-1],p=[c].concat(l.slice(0,l.length-1));a=Ke(a.reshape([-1,c]),[1,0]).reshape(p)}else if(i>1){let l=[i-1].concat(Gr(0,i-1));a=Ke(a,l)}}return a}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let n=1;n<e.length;++n){let s=e[n]==null?null:e[n].slice(1);t=this.computeElementwiseOpOutputShape(t,s)}let o=[];for(let n of e)n!=null&&n[0]!==null&&o.push(n[0]);return o=hn(o),o.length===1?t=o.concat(t):t=[null].concat(t),t}computeMask(e,t){return V(()=>{if(t==null)return null;if(!Array.isArray(t))throw new z("`mask` should be an Array");if(!Array.isArray(e))throw new z("`inputs` should be an Array");if(t.length!==e.length)throw new z(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(n=>n==null))return null;t=t.map(n=>n==null?n:lr(n,0));let o=t[0];for(let n=1;n<t.length-1;++n)o=hr(o,t[n]);return o})}},Pd=class extends Al{constructor(e){super(e)}mergeFunction(e){return V(()=>{let t=e[0].clone();for(let o=1;o<e.length;++o)t=ee(t,e[o]);return t})}};Pd.className="Add";Q.registerClass(Pd);var Md=class extends Al{constructor(e){super(e)}mergeFunction(e){return V(()=>{let t=e[0].clone();for(let o=1;o<e.length;++o)t=P(t,e[o]);return t})}};Md.className="Multiply";Q.registerClass(Md);var Ld=class extends Al{constructor(e){super(e)}mergeFunction(e){return V(()=>{let t=e[0].clone();for(let o=1;o<e.length;++o)t=ee(t,e[o]);return P(1/e.length,t)})}};Ld.className="Average";Q.registerClass(Ld);var zd=class extends Al{constructor(e){super(e)}mergeFunction(e){return V(()=>{let t=e[0];for(let o=1;o<e.length;++o)t=Zr(t,e[o]);return t})}};zd.className="Maximum";Q.registerClass(zd);var Bd=class extends Al{constructor(e){super(e)}mergeFunction(e){return V(()=>{let t=e[0];for(let o=1;o<e.length;++o)t=ys(t,e[o]);return t})}};Bd.className="Minimum";Q.registerClass(Bd);var Vd=class extends Al{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 z("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let n of e)if(n!=null){t=!1;break}if(t)return;let o=[];for(let n=0;n<e.length;++n){let s=e[n].slice();s.splice(this.axis,1);let a=!1;for(let i of o)if(y.arraysEqual(i,s)){a=!0;break}a||o.push(s)}if(o.length>1)throw new z("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return V(()=>Sp(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new z("A `Concatenate` layer should be called on a list of inputs.");let t=e,o=t[0].slice(),n=this.axis<0?o.length+this.axis:this.axis;for(let s of t.slice(1)){if(o[n]==null||s[n]==null){o[n]=null;break}o[n]+=s[n]}return o}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new z("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new z("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new z(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return V(()=>{let o=!0;if(t.forEach(a=>{if(a!=null){o=!1;return}}),o)return null;let n=[];for(let a=0;a<e.length;++a)t[a]==null?n.push(rr(e[a]).asType("bool")):t[a].rank<e[a].rank?n.push(lr(t[a],-1)):n.push(t[a]);let s=Ze(n,this.axis);return Hl(s,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Vd.className="Concatenate";Q.registerClass(Vd);function Gd(r,e){for(;r<0;)r+=e;return r}function zQ(r,e,t){if(r.shape.length>3||e.shape.length>3)throw new Se("batchDot is not implemented for tensors of 4D or higher rank yet");if(y.assert(r.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${r.shape.length}`),y.assert(r.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${e.shape.length}`),typeof t=="number"&&(t=[t,t]),r.dtype==="complex64"||e.dtype==="complex64")throw new Se("batchDot is not implemented for complex64-type Tensors yet.");let o=r.shape.length,n=e.shape.length;t==null&&(t=[o-1,n-2]);let s=t;return V(()=>{let a;if(o>n){a=o-n;let l=[];for(let u=0;u<a;++u)l.push(1);e=e.reshape(e.shape.concat(l))}else if(n>o){a=n-o;let l=[];for(let u=0;u<a;++u)l.push(1);r=r.reshape(r.shape.concat(l))}else a=0;let i;if(r.shape.length===2&&e.shape.length===2)s[0]===s[1]?i=r.mul(e).sum(s[0]):i=r.transpose([1,0]).mul(e).sum(s[1]);else{let l=s[0]!==r.shape.length-1,u=s[1]===e.shape.length-1;i=r.matMul(e,l,u)}if(a>0){let l;o>n?l=o+n-3:l=o-1;let u=[];for(let c=l;c<l+a;++c)u.push(c);i=i.squeeze(u)}return i.shape.length===1&&(i=i.expandDims(1)),i})}var Wd=class extends Al{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){y.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],o=e[1];if(t.length>3||o.length>3)throw new Se("Dot layer does not support tensors of 4D or higher rank yet.");let n=this.interpretAxes(t,o);if(t[n[0]]!==o[n[1]])throw new z(`Dimension incompatibility: ${t[n[0]]} !== ${o[n[1]]}`)}mergeFunction(e){if(e.length!==2)throw new z(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],o=e[1],n;return Array.isArray(this.axes)?n=this.axes.map((s,a)=>Gd(s,e[a].shape.length)):n=[Gd(this.axes,t.shape.length),Gd(this.axes,o.shape.length)],this.normalize&&(t=td(t,n[0]),o=td(o,n[1])),zQ(t,o,n)}interpretAxes(e,t){let o;return Array.isArray(this.axes)?o=this.axes:o=[Gd(this.axes,e.length),Gd(this.axes,t.length)],o}computeOutputShape(e){y.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(),o=e[1].slice();if(t.length>3||o.length>3)throw new Se("Dot layer does not support tensors of 4D or higher rank yet.");let n=this.interpretAxes(t,o);t.splice(n[0],1),o.splice(n[1],1),o.splice(0,1);let s=t.concat(o);return s.length===1&&s.push(1),s}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};Wd.className="Dot";Q.registerClass(Wd);var jd=class extends Me{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 V(()=>{this.invokeCallHook(e,t);let o=Fe(e);return bl(()=>Tp(o.shape,0,this.stddev).add(o),()=>o,t.training||!1)})}};jd.className="GaussianNoise";Q.registerClass(jd);var Ud=class extends Me{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 V(()=>{this.invokeCallHook(e,t);let o=Fe(e);return this.rate>0&&this.rate<1?bl(()=>{let s=Math.sqrt(this.rate/(1-this.rate));return o.mul(Tp(o.shape,1,s))},()=>o,t.training||!1):o})}};Ud.className="GaussianDropout";Q.registerClass(Ud);var Hd=class extends Me{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Fe(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 V(()=>{if(this.rate<1&&this.rate>0){let o=this._getNoiseShape(e);return bl(()=>{let s=Fe(e),a=1.6732632423543772,i=1.0507009873554805,l=-a*i,u=co(bs(o),this.rate);u=Aa(u,"float32");let c=((1-this.rate)*(1+this.rate*l**2))**-.5,p=-c*l*this.rate;return s.mul(u).add(u.add(-1).mul(l)).mul(c).add(p)},()=>Fe(e),t.training||!1)}return e})}};Hd.className="AlphaDropout";Q.registerClass(Hd);function qd(r,e,t,o,n,s=.001){let a;if(r.rank===2)a=_w(r,e,t,o,n,s);else if(r.rank===3)a=kw(r,e,t,o,n,s);else if(r.rank===4)a=vw(r,e,t,o,n,s);else throw new Se(`batchNormalization is not implemented for array of rank ${r.rank} yet`);return a}function BQ(r,e,t,o,n=.001){return V(()=>{let s=Zc(r,o),a=s.mean,i=s.variance;return[qd(r,a,i,t,e,n),a,i]})}function VQ(r,e,t,o,n=.001){return V(()=>{let s=Zc(r,o),a=s.mean,i=s.variance,l=[];for(let d of Gr(0,r.rank))o.indexOf(d)!==-1?l.push(1):l.push(r.shape[d]);let u=a.reshape(l),c=i.reshape(l),p=e==null?null:e.reshape(l),m=t==null?null:t.reshape(l);return[qd(r,u,c,m,p,n),a,i]})}function GQ(r,e,t,o,n=.001){return y.arraysEqual(o.slice().sort(),Gr(0,r.rank-1))?BQ(r,e,t,o,n):VQ(r,e,t,o,n)}var Kd=class extends Me{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=pt(e.betaInitializer||"zeros"),this.gammaInitializer=pt(e.gammaInitializer||"ones"),this.movingMeanInitializer=pt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=pt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Ot(e.betaConstraint),this.gammaConstraint=Ot(e.gammaConstraint),this.betaRegularizer=bt(e.betaRegularizer),this.gammaRegularizer=bt(e.gammaRegularizer)}build(e){e=Je(e);let t=this.axis>=0?this.axis:this.axis+e.length,o=e[t];if(o==null)throw new z(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new At({ndim:e.length,axes:{[t]:o}})];let n=[o];this.scale&&(this.gamma=this.addWeight("gamma",n,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",n,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",n,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",n,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return V(()=>{let o=t.training==null?!1:t.training,n=Fe(e),s=n.shape,a=s.length,i=Gr(0,a),l=this.axis>=0?this.axis:this.axis+a;i.splice(l,1);let u=mn(1,a);u[l]=s[l];let c=i.slice();c.sort();let p=!y.arraysEqual(c,Gr(0,a).slice(0,a-1)),m=()=>{if(p){let b=this.movingMean.read().reshape(u),w=this.movingVariance.read().reshape(u),_=this.center?this.beta.read().reshape(u):null,k=this.scale?this.gamma.read().reshape(u):null;return qd(n,b,w,_,k,this.epsilon)}else return qd(n,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!o)return m();let[f,d,h]=GQ(n,this.gamma.read(),this.beta.read(),i,this.epsilon),g=(b,w,_)=>{V(()=>{let k=1-_,D=b.read(),T=D.sub(w).mul(k);b.write(D.sub(T))})};return(()=>{g(this.movingMean,d,this.momentum),g(this.movingVariance,h,this.momentum)})(),f})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:kt(this.betaInitializer),gammaInitializer:kt(this.gammaInitializer),movingMeanInitializer:kt(this.movingMeanInitializer),movingVarianceInitializer:kt(this.movingVarianceInitializer),betaRegularizer:st(this.betaRegularizer),gammaRegularizer:st(this.gammaRegularizer),betaConstraint:Ft(this.betaConstraint),gammaConstraint:Ft(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Kd.className="BatchNormalization";Q.registerClass(Kd);var Xd=class 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Me{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 z(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];jt(this.poolSize,"poolSize"),jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,$t(this.dataFormat),Qr(this.padding),this.inputSpec=[new At({ndim:5})]}computeOutputShape(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],o=this.dataFormat==="channelsFirst"?e[3]:e[2],n=this.dataFormat==="channelsFirst"?e[4]:e[3];return 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n={};if(n.className=e.layer.getClassName(),n.config=t,this.backwardLayer=to(n),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?UQ:e.mergeMode,jQ(this.mergeMode),e.weights)throw new Se("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 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i;return this.mergeMode==="concat"?i=Sp([n,s]):this.mergeMode==="sum"?i=ee(n,s):this.mergeMode==="ave"?i=P(.5,ee(n,s)):this.mergeMode==="mul"?i=P(n,s):this.mergeMode==null&&(i=[n,s]),this.returnState?this.mergeMode==null?i.concat(a):[i].concat(a):i})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){Is(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),Is(this.backwardLayer.name,()=>{this.backwardLayer.build(e)}),this.built=!0}computeMask(e,t){Array.isArray(t)&&(t=t[0]);let o;if(this.returnSequences?this.mergeMode==null?o=[t,t]:o=t:this.mergeMode==null?o=[null,null]:o=null,this.returnState){let s=this.forwardLayer.states.map(a=>null);return Array.isArray(o)?o.concat(s).concat(s):[o].concat(s).concat(s)}else return o}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return 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o=C("boxes",r,e,t),n=C("scores",r,e,t),s=C("maxOutputSize",r,e,t),a=C("iouThreshold",r,e,t),i=C("scoreThreshold",r,e,t),l=C("softNmsSigma",r,e,t);return{boxes:o,scores:n,maxOutputSize:s,iouThreshold:a,scoreThreshold:i,softNmsSigma:l}}var jL=async(r,e,t)=>{switch(r.op){case"NonMaxSuppressionV5":{let{boxes:o,scores:n,maxOutputSize:s,iouThreshold:a,scoreThreshold:i,softNmsSigma:l}=T0(r,e,t),u=await Js.nonMaxSuppressionWithScoreAsync(o,n,s,a,i,l);return[u.selectedIndices,u.selectedScores]}case"NonMaxSuppressionV4":{let{boxes:o,scores:n,maxOutputSize:s,iouThreshold:a,scoreThreshold:i}=T0(r,e,t),l=C("padToMaxOutputSize",r,e,t),u=await Js.nonMaxSuppressionPaddedAsync(o,n,s,a,i,l);return[u.selectedIndices,u.validOutputs]}case"NonMaxSuppressionV3":case"NonMaxSuppressionV2":{let{boxes:o,scores:n,maxOutputSize:s,iouThreshold:a,scoreThreshold:i}=T0(r,e,t);return[await Js.nonMaxSuppressionAsync(o,n,s,a,i)]}case"Where":{let o=ne(C("condition",r,e,t),"bool"),n=[await Km(o)];return 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C("x",r,e,t).map(u=>Vt(u.shape));case"Size":return[le(C("x",r,e,t).size,"int32")];case"Rank":return[le(C("x",r,e,t).rank,"int32")];case"NoOp":return[le(1)];case"Print":let s=C("x",r,e,t),a=C("data",r,e,t),i=C("message",r,e,t),l=C("summarize",r,e,t);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(i);for(let u=0;u<a.length;u++)console.log(Array.prototype.slice.call(a[u].dataSync()).slice(0,l));return[s];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var A0=class{constructor(e,t){this.keyDType=e,this.valueDType=t,this.handle=le(0),this.tensorMap=new Map,Et(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 le(this.size(),"int32")}async import(e,t){this.checkKeyAndValueTensor(e,t);let o=await e.data();return this.tensorMap.forEach(n=>n.dispose()),this.tensorMap.clear(),V(()=>{let n=mr(t),s=o.length,a=n.length;y.assert(s===a,()=>`The number of elements doesn't match, keys has ${s} elements, the values has ${a} elements.`);for(let i=0;i<s;i++){let l=o[i],u=n[i];Et(u),this.tensorMap.set(l,u)}return this.handle})}async find(e,t){this.checkKeyAndValueTensor(e,t);let o=await e.data();return V(()=>{let n=[];for(let s=0;s<o.length;s++){let a=o[s],i=this.findWithDefault(a,t);n.push(i)}return Bt(n)})}findWithDefault(e,t){let o=this.tensorMap.get(e);return o!=null?o: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}`)}};var qL=async(r,e,t,o)=>{switch(r.op){case"HashTable":case"HashTableV2":{let n=C("keyDType",r,e,t),s=C("valueDType",r,e,t),a=new A0(n,s);return 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o=C("image",r,e,t),n=C("boxes",r,e,t),s=C("boxInd",r,e,t),a=C("cropSize",r,e,t),i=C("method",r,e,t),l=C("extrapolationValue",r,e,t);return[Js.cropAndResize(o,n,s,a,i,l)]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var XL=(r,e,t)=>{switch(r.op){case"Equal":return[wo(C("a",r,e,t),C("b",r,e,t))];case"NotEqual":return[Yo(C("a",r,e,t),C("b",r,e,t))];case"Greater":return[tr(C("a",r,e,t),C("b",r,e,t))];case"GreaterEqual":return[so(C("a",r,e,t),C("b",r,e,t))];case"Less":return[Xl(C("a",r,e,t),C("b",r,e,t))];case"LessEqual":return[Fo(C("a",r,e,t),C("b",r,e,t))];case"LogicalAnd":return[hr(C("a",r,e,t),C("b",r,e,t))];case"LogicalNot":return[ua(C("a",r,e,t))];case"LogicalOr":return[Jl(C("a",r,e,t),C("b",r,e,t))];case"Select":case"SelectV2":return[Dt(C("condition",r,e,t),C("a",r,e,t),C("b",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var YL=(r,e,t)=>{switch(r.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[We(C("a",r,e,t),C("b",r,e,t),C("transposeA",r,e,t),C("transposeB",r,e,t))];case"Transpose":return[qe(C("x",r,e,t),C("perm",r,e,t))];case"_FusedMatMul":let[o,n]=C("fusedOps",r,e,t),s=o==="biasadd",a=n==="prelu",i=C("numArgs",r,e,t),l=C("leakyreluAlpha",r,e,t);if(s){if(a&&i!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!a&&i!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[u,c]=C("args",r,e,t);return[Zo.matMul({a:C("a",r,e,t),b:C("b",r,e,t),transposeA:C("transposeA",r,e,t),transposeB:C("transposeB",r,e,t),bias:u,activation:n,preluActivationWeights:c,leakyreluAlpha:l})];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var ZL=(r,e,t)=>{switch(r.op){case"FusedBatchNorm":case"FusedBatchNormV2":return[qo(C("x",r,e,t),C("mean",r,e,t),C("variance",r,e,t),C("offset",r,e,t),C("scale",r,e,t),C("epsilon",r,e,t))];case"FusedBatchNormV3":return[qo(C("x",r,e,t),C("mean",r,e,t),C("variance",r,e,t),C("offset",r,e,t),C("scale",r,e,t),C("epsilon",r,e,t))];case"LRN":return[Fm(C("x",r,e,t),C("radius",r,e,t),C("bias",r,e,t),C("alpha",r,e,t),C("beta",r,e,t))];case"Softmax":return[fa(C("x",r,e,t))];case"LogSoftmax":return[Zl(C("x",r,e,t))];case"SparseToDense":return[ig(C("sparseIndices",r,e,t),C("outputShape",r,e,t),C("sparseValues",r,e,t),C("defaultValue",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var JL=(r,e,t)=>{switch(r.op){case"Max":{let a=C("axis",r,e,t),i=C("keepDims",r,e,t);return[cr(C("x",r,e,t),a,i)]}case"Mean":{let a=C("axis",r,e,t),i=C("keepDims",r,e,t);return[dt(C("x",r,e,t),a,i)]}case"Min":{let a=C("axis",r,e,t),i=C("keepDims",r,e,t);return[Xs(C("x",r,e,t),a,i)]}case"Sum":{let 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tz=(r,e,t)=>{switch(r.op){case"Cast":return[ne(C("x",r,e,t),C("dtype",r,e,t))];case"ExpandDims":{let o=C("axis",r,e,t);return[lr(C("x",r,e,t),o)]}case"Squeeze":{let o=C("axis",r,e,t);return[_o(C("x",r,e,t),o)]}case"Reshape":return[L(C("x",r,e,t),C("shape",r,e,t))];case"MirrorPad":return[Mm(C("x",r,e,t),C("padding",r,e,t),C("mode",r,e,t))];case"PadV2":case"Pad":return[Fr(C("x",r,e,t),C("padding",r,e,t),C("constantValue",r,e,t))];case"SpaceToBatchND":{let o=C("blockShape",r,e,t),n=C("paddings",r,e,t);return[pa(C("x",r,e,t),o,n)]}case"BatchToSpaceND":{let o=C("blockShape",r,e,t),n=C("crops",r,e,t);return[sa(C("x",r,e,t),o,n)]}case"DepthToSpace":{let o=C("blockSize",r,e,t),n=C("dataFormat",r,e,t).toUpperCase();return[Am(C("x",r,e,t),o,n)]}case"BroadcastTo":return[nl(C("x",r,e,t),C("shape",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};function E0(r,e,t,o){let n=((s,a,i)=>{switch(s.category){case"arithmetic":return V(()=>RL(s,a,i));case"basic_math":return 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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 $0(r,e,t,o){let n=new Set,s=[],a=null,i=null,l=new Set,u=Object.keys(r).map(m=>Qr(m)[0]),c=[];o!=null&&(c=o.map(m=>Qr(m.name)[0]));let p=[...e];for(;p.length>0;){let m=p.pop();if((D0(m)||ree(m)||oee(m))&&a==null&&(a=m,i=a.children.map(f=>f.name).filter(f=>n.has(f))),n.add(m.name),t[m.name]==null&&u.indexOf(m.name)===-1&&c.indexOf(m.name)===-1){if(m.inputs.length===0){s.push(m.name);continue}m.inputs.forEach(f=>{l.has(f.name)||(l.add(f.name),p.push(f))})}}return{inputs:r,outputs:e,usedNodes:n,missingInputs:s,dynamicNode:a,syncInputs:i}}function 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Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},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(o=>{this._functionExecutorMap[o]=new jp(e.functions[o],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(o=>e[o].map(n=>n.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 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forEachAsync(e){return this.map(e).resolveFully()}async serialForEach(e){return this.serialMapAsync(e).resolveWhile(t=>t===!0)}rowMajorBatch(e,t=!0){return new $z(this,e,t)}columnMajorBatch(e,t=!0,o=G0){return this.rowMajorBatch(e,t).map(s=>wz(s,o))}concatenate(e,t){return new j0(W0([this,e]),t)}take(e){return e<0||e==null?this:new Dz(this,e)}skip(e){return e<0||e==null?this:new Ez(this,e)}prefetch(e){return new H0(this,e)}shuffle(e,t){return new Mz(this,e,t)}serial(){return new Az(this)}},Cz=class extends Kt{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:kz(e),done:!1}}},Iz=class extends Kt{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: ${e.message}`,e}}},Az=class extends 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Kt{constructor(e,t,o=!0){super();this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=o,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${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}}},Rz=class extends Kt{constructor(e,t){super();this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;Ae(e.value)}}},Fz=class extends Kt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Uo.getTensorsInContainer(e.value),o=this.transform(e.value),n=Uo.getTensorsInContainer(o);for(let s of t)Uo.isTensorInList(s,n)||s.dispose();return{value:o,done:!1}}},Oz=class extends Kt{constructor(e,t){super();this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},U0=class extends Kt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Uo.getTensorsInContainer(e.value),o=await this.transform(e.value),n=Uo.getTensorsInContainer(o);for(let s of t)Uo.isTensorInList(s,n)||s.dispose();return{value:o,done:!1}}},Hp=class extends Kt{constructor(){super();this.outputQueue=new Up,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}}},Pz=class extends Hp{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=Uo.getTensorsInContainer(e.value),o=this.transform(e.value),n=Uo.getTensorsInContainer(o);this.outputQueue.pushAll(o);for(let s of t)Uo.isTensorInList(s,n)||s.dispose();return!0}},j0=class extends Kt{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 o=await this.moreIterators.next();if(o.done)return{value:null,done:!0};this.iterator=o.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}},Aa;(function(r){r[r.FAIL=0]="FAIL",r[r.SHORTEST=1]="SHORTEST",r[r.LONGEST=2]="LONGEST"})(Aa||(Aa={}));var Sz=class extends Kt{constructor(e,t=Aa.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,o=0;function n(a){return a instanceof 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-      ${e}`);let n;return this.size===Infinity||this.size==null?n=this.size:t?n=Math.ceil(this.size/e):n=Math.floor(this.size/e),ho(async()=>(await o.iterator()).columnMajorBatch(e,t,bee),n)}concatenate(e){let t=this,o;return this.size===Infinity||e.size===Infinity?o=Infinity:this.size!=null&&e.size!=null?o=this.size+e.size:o=null,ho(async()=>(await t.iterator()).concatenate(await e.iterator()),o)}filter(e){let t=this,o;return this.size===Infinity?o=Infinity:o=null,ho(async()=>(await t.iterator()).filter(n=>V(()=>e(n))),o)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return ho(async()=>(await t.iterator()).map(o=>V(()=>e(o))),this.size)}mapAsync(e){let t=this;return ho(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return ho(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,o;return this.size!=null&&e>0?o=this.size*e:e===0?o=0:this.size!=null&&(e===void 0||e<0)?o=Infinity:o=null,ho(async()=>{let n=th(async()=>({value:await t.iterator(),done:!1}));return Nz(n.take(e))},o)}skip(e){let t=this,o;return this.size!=null&&e>=0&&this.size>=e?o=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?o=0:o=null,ho(async()=>(await t.iterator()).skip(e),o)}shuffle(e,t,o=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified.  If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let n=this,s=Lz.alea(t||y.now().toString());return ho(async()=>{let a=s.int32();return o&&(a+=s.int32()),(await n.iterator()).shuffle(e,a.toString())},this.size)}take(e){let t=this,o;return this.size!=null&&this.size>e?o=e:this.size!=null&&this.size<=e?o=this.size:o=null,ho(async()=>(await t.iterator()).take(e),o)}async toArray(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};ai.MAX_BUFFER_SIZE=1e4;function ho(r,e=null){return new class extends ai{constructor(){super(...arguments);this.size=e}async iterator(){return r()}}}function zz(r){return ho(async()=>W0(r),r.length)}function Bz(r){if(!Il(r))throw new Error("The argument to zip() must be an object or array.");let e;if(Array.isArray(r))for(let t=0;t<r.length;t++)e=e==null?r[t].size:Math.min(e,r[t].size);else if(r instanceof Object)for(let t in r)e=e==null?r[t].size:Math.min(e,r[t].size);return ho(async()=>{let t=await ry(r,o=>{if(o instanceof ai)return{value:o.iterator(),recurse:!1};if(Il(o))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return Tz(t,Aa.SHORTEST)},e)}function bee(r){if(r===null)return null;let e=r[0];return _z(e)?{value:wee(r),recurse:!1}:{value:null,recurse:!0}}function wee(r){if(r.length===0)throw new Error("Can't make a batch of zero elements.");return r[0]instanceof Ve?Bt(r):Rr(r)}var rh=class extends ai{constructor(e){super();this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
-`).map(n=>(n.endsWith("\r")&&(n=n.slice(0,-1)),n))}};var oy='"',oh=Symbol("out"),Vz=Symbol("field"),ny=Symbol("quote"),q0=Symbol("quoteafterquote"),Gz=Symbol("quoteinquote"),nh=class extends ai{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 rh(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(y.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&&y.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((n,s)=>(n[s]=n[s]+1||1,n),{}),o=Object.keys(t).filter(n=>t[n]>1);if(y.assert(o.length===0,()=>"Duplicate column names found: "+o.toString()),this.columnConfigs){for(let n of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(n)===-1)throw new Error('The key "'+n+'" 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 o=t.value;return this.parseRow(o,!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),o={},n={};for(let s=0;s<this.fullColumnNames.length;s++){let a=this.fullColumnNames[s],i=this.columnConfigs?this.columnConfigs[a]:null;if(!(this.configuredColumnsOnly&&!i)){let l=t[s],u=null;if(l==="")if(i&&i.default!==void 0)u=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${a} is empty in this line: ${e}`);u=void 0}else{let c=Number(l);if(isNaN(c))i&&i.dtype==="bool"?u=this.getBoolean(l):u=l;else if(!i||!i.dtype)u=c;else switch(i.dtype){case"float32":u=c;break;case"int32":u=Math.floor(c);break;case"bool":u=this.getBoolean(l);break;default:u=c}}i&&i.isLabel?n[a]=u:o[a]=u}}return Object.keys(n).length===0?o:{xs:o,ys:n}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let o=[],n=0,s=e.length,a=oh;for(let i=0;i<s;i++)switch(a){case oh:switch(e.charAt(i)){case oy:n=i+1,a=ny;break;case this.delimiter:if(n=i+1,this.delimiter===" "&&this.delimWhitespace)break;o.push(""),a=oh;break;default:a=Vz,n=i;break}break;case Vz:switch(e.charAt(i)){case this.delimiter:o.push(e.substring(n,i)),a=oh,n=i+1;break;default:}break;case ny:switch(e.charAt(i)){case oy:a=q0;break;default:}break;case q0:switch(e.charAt(i)){case this.delimiter:o.push(e.substring(n,i-1)),a=oh,n=i+1;break;case oy:a=ny;break;default:a=Gz;break}break;case Gz:switch(e.charAt(i)){case oy:a=ny;break;default:}break;default:}if(a===q0?o.push(e.substring(n,s-1)):o.push(e.substring(n)),t&&o.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${o}`);return o}};var sh=class extends Kt{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(W().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new sh(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(o){throw new Error(`Error thrown while initializing video stream: ${o.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,o=await this.getAudioData();if(this.includeSpectrogram){let n=this.flattenQueue(o.freqDataQueue);e=this.getTensorFromAudioDataArray(n,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let n=this.flattenQueue(o.timeDataQueue);t=this.getTensorFromAudioDataArray(n,[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=[],o=0;return new Promise(n=>{let s=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&n({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++o===this.numFrames&&(clearInterval(s),n({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,o=new Float32Array(e.length*t);return e.forEach((n,s)=>o.set(n,s*t)),o}getTensorFromAudioDataArray(e,t){let o=new Float32Array(y.sizeFromShape(t));return o.set(e,o.length-e.length),Rr(o,t)}};var ih=class extends Kt{constructor(e,t){super();if(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=Vt([0],"int32"),this.webcamConfig.centerCrop){let o=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,n=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,s=(1-o)/2,a=(1-n)/2,i=s+o,l=n+a;this.cropBox=Zs([a,s,l,i],[1,4])}else this.cropBox=Zs([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(W().get("IS_NODE"))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 o=new ih(e,t);return await o.start(),o}async start(){this.webcamConfig.facingMode&&y.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=jh.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return V(()=>{let t=lr(ne(e,"float32"),0),o;o=Js.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let n=o.shape;return L(o,n.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(t=>t.stop());try{this.webcamVideoElement.srcObject=null}catch(t){console.log(t),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}};var ah=class{};var sy=class extends Kt{split(e){return new Wz(this,e)}},Wz=class extends sy{constructor(e,t){super();this.upstream=e,this.impl=new jz(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},jz=class extends Hp{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let o of t.slice(0,-1))this.outputQueue.push(o);return this.carryover=t[t.length-1],!0}};var K0=class extends Kt{decodeUTF8(){return new Hz(this)}},Hz=class extends sy{constructor(e){super();this.upstream=e,this.impl=new qz(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},qz=class extends Hp{constructor(e){super();if(this.upstream=e,W().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=Uz();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let o;return W().get("IS_BROWSER")?o=this.decoder.decode(t,{stream:!0}):o=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(o),!0}};var lh=class extends K0{constructor(e,t={}){super();this.file=e,this.options=t,y.assert(e instanceof Uint8Array||(W().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,o)=>{let n=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)t(new Uint8Array(this.file.slice(this.offset,n)));else{let s=new FileReader;s.onload=i=>{let l=s.result;if(l instanceof ArrayBuffer&&(l=new Uint8Array(l)),!(l instanceof Uint8Array))return o(new TypeError("FileReader returned unknown type."));t(l)},s.onabort=i=>o(new Error("Aborted")),s.onerror=i=>o(new Error(i.type));let a=this.file.slice(this.offset,n);s.readAsArrayBuffer(a)}this.offset=n}),done:!1}}};async function Kz(r,e={}){let t,o;typeof r=="string"?t=r:(t=r.url,o=_ee(r));let n=await y.fetch(t,o);if(n.ok){let s=new Uint8Array(await n.arrayBuffer());return new lh(s,e)}else throw new Error(n.statusText)}var _ee=r=>({method:r.method,headers:r.headers,body:r.body,mode:r.mode,credentials:r.credentials,cache:r.cache,redirect:r.redirect,referrer:r.referrer,integrity:r.integrity});function iy(r){return typeof r=="string"&&r.substr(0,7)==="file://"}var uh=class extends ah{constructor(e,t={}){super();this.input=e,this.options=t}async iterator(){if(iy(this.input)&&W().get("IS_NODE")){let e=require("fs");this.input=e.readFileSync(this.input.substr(7))}return new lh(this.input,this.options)}};var ch=class extends ah{constructor(e,t={}){super();this.url=e,this.fileOptions=t}async iterator(){return iy(this.url)?new uh(this.url,this.fileOptions).iterator():Kz(this.url,this.fileOptions)}};function Xz(r,e={}){return new nh(new ch(r),e)}function Yz(r){let e=th(r);return ho(async()=>e)}function Zz(r){return ho(async()=>{let e=await r();return th(()=>e.next())})}async function Jz(r,e){return ih.create(r,e)}async function Qz(r){return sh.create(r)}var e3="3.3.0";var xBt={tfjs:lI,"tfjs-core":uI,"tfjs-data":cI,"tfjs-layers":pI,"tfjs-converter":mI,"tfjs-backend-cpu":m_,"tfjs-backend-webgl":kk,"tfjs-backend-wasm":nC};export{Es as Abs,fi as Acos,di as Acosh,Xm as AdadeltaOptimizer,Ym as AdagradOptimizer,Zm as AdamOptimizer,Jm as AdamaxOptimizer,Ao as Add,xn as AddN,sc as All,ic as Any,yn as ArgMax,Ma as ArgMin,hi as Asin,gi as Asinh,xi as Atan,bi as Atan2,yi as Atanh,bn as AvgPool,La as AvgPool3D,lc as AvgPool3DGrad,ac as AvgPoolGrad,rC as BackendWasm,wn as BatchMatMul,za as BatchToSpaceND,uc as Bincount,bI as BroadcastTo,s0 as Callback,yC as CallbackList,Vo as Cast,_n as Ceil,Go as ClipByValue,cc as Complex,Ba as ComplexAbs,Ds as Concat,kn as Conv2D,pc as Conv2DBackpropFilter,vn as Conv2DBackpropInput,Va as Conv3D,mc as Conv3DBackpropFilterV2,fc as Conv3DBackpropInputV2,Cn as Cos,wi as Cosh,_i as CropAndResize,In as Cumsum,wC as CustomCallback,Pa as DataStorage,dc as DenseBincount,ki as DepthToSpace,Nn as DepthwiseConv2dNative,hc as DepthwiseConv2dNativeBackpropFilter,gc as DepthwiseConv2dNativeBackpropInput,xc as Diag,Ga as Dilation2D,lm as Dilation2DBackpropFilter,am as Dilation2DBackpropInput,Sb as ENV,i0 as EarlyStopping,vi as Elu,yc as EluGrad,Fh as Environment,Ii as Equal,Ci as Erf,Tn as Exp,$s as ExpandDims,Ni as Expm1,bc as FFT,Wa as Fill,Si as FlipLeftRight,An as Floor,En as FloorDiv,um as FromPixels,Dn as FusedBatchNorm,js as FusedConv2D,Us as FusedDepthwiseConv2D,gk as GPGPUContext,Ti as GatherNd,Rs as GatherV2,F0 as GraphModel,Ai as Greater,$n as GreaterEqual,bC as History,wc as IFFT,Wo as Identity,_c as Imag,At as InputSpec,Ei as IsFinite,Di as IsInf,$i as IsNan,Ss as KernelBackend,ja as LRN,vc as LRNGrad,_x as LayerVariable,Lo as LayersModel,Rn as LeakyRelu,Ri as Less,Fi as LessEqual,kc as LinSpace,Fn as Log,Oi as Log1p,wI as LogSoftmax,Pi as LogicalAnd,$l as LogicalNot,Rl as LogicalOr,Qc as MathBackendCPU,dp as MathBackendWebGL,On as Max,Mn as MaxPool,Ua as MaxPool3D,Ic as MaxPool3DGrad,Cc as MaxPoolGrad,Nc as MaxPoolWithArgmax,Pn as Maximum,Ln as Mean,zn as Min,Bn as Minimum,Ha as MirrorPad,Mi as Mod,Qm as MomentumOptimizer,Sc as Multinomial,Vn as Multiply,Fs as Neg,zi as NonMaxSuppressionV3,Bi as NonMaxSuppressionV4,Vi as NonMaxSuppressionV5,Li as NotEqual,FB as OP_SCOPE_SUFFIX,Gn as OneHot,Os as OnesLike,Pr as Optimizer,Ps as Pack,Wn as PadV2,zee as Pool,jn as Pow,Un as Prelu,Gi as Prod,ef as RMSPropOptimizer,Io as RNN,qa as Range,Fb as Rank,Tc as Real,Sn as RealDiv,Wi as Reciprocal,qt as Reduction,Hn as Relu,Kn as Relu6,Ms as Reshape,qn as ResizeBilinear,Ec as ResizeBilinearGrad,Ka as ResizeNearestNeighbor,Ac as ResizeNearestNeighborGrad,Xn as Reverse,Ji as RotateWithOffset,Yn as Round,Zn as Rsqrt,fu as SGDOptimizer,ji as ScatterNd,Ls as Select,Ui as Selu,Sa as Sequential,Qn as Sigmoid,qi as Sign,Jn as Sin,Hi as Sinh,zs as Slice,rs as Softmax,Ki as Softplus,Xa as SpaceToBatchND,Dc as SparseToDense,Bs as SplitV,es as Sqrt,Ya as Square,os as SquaredDifference,jo as Step,Xi as StridedSlice,ns as Sub,ts as Sum,Zr as SymbolicTensor,Yi as Tan,ss as Tanh,Ve as Tensor,lt as TensorBuffer,Eo as Tile,Zi as TopK,$c as Transform,is as Transpose,Rc as Unique,Vs as Unpack,Za as UnsortedSegmentSum,Qa as Variable,Gs as ZerosLike,Ws as _FusedMatMul,It as abs,ym as acos,bm as acosh,ee as add,aw as addN,Vl as all,rl as any,ol as argMax,wm as argMin,_m as asin,km as asinh,vm as atan,Cm as atan2,Im as atanh,na as avgPool,Nm as avgPool3d,TN as backend,N as backend_util,yae as basicLSTMCell,qo as batchNorm,pw as batchNorm2d,mw as batchNorm3d,fw as batchNorm4d,sa as batchToSpaceND,dw as bincount,_ve as booleanMaskAsync,nl as broadcastTo,jh as browser,ve as buffer,OQ as callbacks,ne as cast,Sm as ceil,ar as clipByValue,Do as clone,bo as complex,Ze as concat,hw as concat1d,gw as concat2d,xw as concat3d,yw as concat4d,_M as constraints,jl as conv1d,qr as conv2d,Ul as conv2dTranspose,Tm as conv3d,_ue as conv3dTranspose,Uee as copyRegisteredKernels,ia as cos,Hl as cosh,ag as cosineWindow,ql as cumsum,io as customGrad,X0 as data,bw as denseBincount,iw as deprecationWarn,Am as depthToSpace,us as depthwiseConv2d,MQ as deregisterOp,Ll as device_util,ace as diag,Em as dilation2d,vne as disableDeprecationWarnings,Ae as dispose,Cne as disposeVariables,me as div,Dm as divNoNan,$N as dot,tS as dropout,cs as elu,kne as enableDebugMode,_ne as enableProdMode,rS as enclosingPowerOfTwo,Ho as engine,W as env,wo as equal,$m as erf,Zt as exp,lr as expandDims,Rm as expm1,Uc as eye,da as fft,aa as fill,Ene as findBackend,Dne as findBackendFactory,ps as floor,Bl as floorDiv,TE as forceHalfFloat,Zo as fused,Ko as gather,QN as gatherND,Uh as gather_util,Tne as getBackend,Db as getGradient,pm as getKernel,Oh as getKernelsForBackend,TK as gpgpu_util,bfe as grad,wfe as grads,tr as greater,so as greaterEqual,Ys as ifft,Kl as imag,Js as image,DCe as inTopKAsync,GM as initializers,AC as input,Ir as io,iu as irfft,ww as isFinite,_w as isInf,kw as isNaN,Et as keep,Ar as kernel_impls,bL as layers,la as leakyRelu,Xl as less,Fo as lessEqual,$S as linalg,vw as linspace,uee as loadGraphModel,K9 as loadLayersModel,Fm as localResponseNormalization,ur as log,Yl as log1p,Iw as logSigmoid,Zl as logSoftmax,Qh as logSumExp,hr as logicalAnd,ua as logicalNot,Jl as logicalOr,FN as logicalXor,kDe as losses,We as matMul,mV as math,cr as max,ca as maxPool,Pm as maxPool3d,Aw as maxPoolWithArgmax,Kr as maximum,dt as mean,xm as memory,CL as metrics,Xs as min,fs as minimum,Mm as mirrorPad,Lm as mod,H9 as model,IL as models,Hc as moments,qve as movingAverage,P as mul,wge as multiRNNCell,Ew as multinomial,Ue as neg,tf as nextFrame,Zc as norm,Yo as notEqual,ls as oneHot,Nr as ones,rr as onesLike,S as op,exe as outerProduct,Fr as pad,cxe as pad1d,hxe as pad2d,wxe as pad3d,Ixe as pad4d,ON as pool,Or as pow,ma as prelu,tN as print,Ql as prod,Ine as profile,uye as rand,bye as randomGamma,rg as randomNormal,ds as randomUniform,Kc as range,Sne as ready,sl as real,zm as reciprocal,Gc as registerBackend,X9 as registerCallbackConstructor,_I as registerGradient,Fl as registerKernel,PQ as registerOp,NL as regularizers,Sr as relu,tu as relu6,Ane as removeBackend,L as reshape,Ht as reverse,abe as reverse1d,fbe as reverse2d,bbe as reverse3d,Ibe as reverse4d,ha as rfft,Bm as round,ru as rsqrt,le as scalar,ZN as scatterND,Hh as scatter_util,ou as selu,Vm as separableConv2d,q9 as sequential,Q as serialization,$V as setBackend,$ne as setPlatform,ndt as setWasmPath,sdt as setWasmPaths,AA as setWebGLContext,Vw as setdiff1dAsync,p_ as shared,Hr as sigmoid,Gm as sign,_De as signal,nu as sin,su as sinh,Re as slice,Wm as slice1d,og as slice2d,jm as slice3d,Xc as slice4d,er as slice_util,fa as softmax,ms as softplus,pa as spaceToBatchND,ig as sparseToDense,wDe as spectral,pr as split,gt as sqrt,Oe as square,au as squaredDifference,_o as squeeze,Bt as stack,hs as step,Um as stridedSlice,ce as sub,ge as sum,Pl as sumOutType,Hm as tan,Ks as tanh,Rr as tensor,Vt as tensor1d,Zs as tensor2d,mN as tensor3d,vke as tensor4d,Tke as tensor5d,Rke as tensor6d,Uo as tensor_util,CV as test_util,V as tidy,Ro as tile,Nne as time,qm as topk,du as train,qe as transpose,lu as truncatedNormal,Yc as unique,jee as unregisterGradient,Wee as unregisterKernel,ng as unsortedSegmentSum,mr as unstack,ir as upcastType,y as util,_fe as valueAndGrad,kfe as valueAndGrads,Gw as variable,Cw as variableGrads,xBt as version,cee as version_converter,hne as version_core,m_ as version_cpu,Jf as version_layers,nC as version_wasm,kk as version_webgl,s6e as webgl,gK as webgl_util,Dt as where,Km as whereAsync,ht as zeros,Ce as zerosLike};
+        ${o}, and tensor's shape is: ${r.shape}`);let s=r.shape.slice(1),a=ly(s,t),i=o===0?0:r.size/o,l=V(()=>{let c=[];r=L(r,[1,o,i]);for(let p=0;p<e.length;++p){let m=p===0?0:n[p-1],f=[0,m,0],d=[1,e[p],i];c[p]=L(Re(r,f,d),a)}return r.dispose(),c}),u=new Uu([],t,r.dtype,e.length);for(let c=0;c<l.length;c++)u.setItem(c,l[c]);return u}var w3=async(r,e,t)=>{switch(r.op){case"If":case"StatelessIf":{let o=C("thenBranch",r,e,t),n=C("elseBranch",r,e,t),s=C("cond",r,e,t),a=C("args",r,e,t);return(await s.data())[0]?t.functionMap[o].executeFunctionAsync(a,t.tensorArrayMap,t.tensorListMap):t.functionMap[n].executeFunctionAsync(a,t.tensorArrayMap,t.tensorListMap)}case"While":case"StatelessWhile":{let o=C("body",r,e,t),n=C("cond",r,e,t),s=C("args",r,e,t),a=await t.functionMap[n].executeFunctionAsync(s,t.tensorArrayMap,t.tensorListMap),i=s.map(c=>c.id),l=await a[0].data();a.forEach(c=>{!c.kept&&i.indexOf(c.id)===-1&&c.dispose()});let u=s;for(;l[0];){let c=u;u=await t.functionMap[o].executeFunctionAsync(u,t.tensorArrayMap,t.tensorListMap);let p=u.map(f=>f.id);c.forEach(f=>{!f.kept&&i.indexOf(f.id)===-1&&p.indexOf(f.id)===-1&&f.dispose()});let m=await t.functionMap[n].executeFunctionAsync(u,t.tensorArrayMap,t.tensorListMap);l=await m[0].data(),m.forEach(f=>{!f.kept&&i.indexOf(f.id)===-1&&p.indexOf(f.id)===-1&&f.dispose()})}return u}case"LoopCond":{let o=C("pred",r,e,t);return[Ds(o)]}case"Switch":{let o=C("pred",r,e,t),n=C("data",r,e,t);return n.kept||(n=Ds(n)),(await o.data())[0]?[void 0,n]:[n,void 0]}case"Merge":{let o=r.inputNames.find(n=>yr(n,e,t)!==void 0);if(o){let n=yr(o,e,t);return[Ds(n)]}return}case"Enter":{let o=C("frameName",r,e,t),n=C("tensor",r,e,t);return t.enterFrame(o),[Ds(n)]}case"Exit":{let o=C("tensor",r,e,t);return t.exitFrame(),[Ds(o)]}case"NextIteration":{let o=C("tensor",r,e,t);return t.nextIteration(),[Ds(o)]}case"TensorArrayV3":{let 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s=s.slice(0,o),[Ze(s,n)]}case"Gather":{let o=C("x",r,e,t),n=C("indices",r,e,t);return[Qo(o,ne(n,"int32"),0)]}case"GatherV2":{let o=C("axis",r,e,t),n=C("batchDims",r,e,t),s=C("x",r,e,t),a=C("indices",r,e,t);return[Qo(s,ne(a,"int32"),o,n)]}case"Reverse":{let o=C("dims",r,e,t),n=[];for(let a=0;a<o.length;a++)o[a]&&n.push(a);let s=C("x",r,e,t);return[Ht(s,n)]}case"ReverseV2":{let o=C("axis",r,e,t),n=C("x",r,e,t);return[Ht(n,o)]}case"Slice":{let o=C("begin",r,e,t),n=C("size",r,e,t);return[Re(C("x",r,e,t),o,n)]}case"StridedSlice":{let o=C("begin",r,e,t),n=C("end",r,e,t),s=C("strides",r,e,t),a=C("beginMask",r,e,t),i=C("endMask",r,e,t),l=C("ellipsisMask",r,e,t),u=C("newAxisMask",r,e,t),c=C("shrinkAxisMask",r,e,t),p=C("x",r,e,t);return[tf(p,o,n,s,a,i,l,u,c)]}case"Pack":return V(()=>{let o=C("axis",r,e,t),n=C("tensors",r,e,t),s=n[0].shape,a=No(n[0]).shape,i=n.map(l=>{let u=y.arraysEqual(l.shape,s);if(!u&&!y.arraysEqual(No(l).shape,a))throw new Error("the input tensors shape does not match");return u?l:L(l,s)});return[Bt(i,o)]});case"Unpack":{let o=C("axis",r,e,t),n=C("tensor",r,e,t);return mr(n,o)}case"Tile":{let o=C("reps",r,e,t);return[Lo(C("x",r,e,t),o)]}case"Split":case"SplitV":{let o=C("axis",r,e,t),n=C("numOrSizeSplits",r,e,t),s=C("x",r,e,t);return pr(s,n,o)}case"ScatterNd":{let o=C("indices",r,e,t),n=C("values",r,e,t),s=C("shape",r,e,t);return[DT(o,n,s)]}case"GatherNd":{let o=C("x",r,e,t),n=C("indices",r,e,t);return[RT(o,n)]}case"SparseToDense":{let o=C("sparseIndices",r,e,t),n=C("outputShape",r,e,t),s=C("sparseValues",r,e,t),a=C("defaultValue",r,e,t);return[gg(o,s,n,s.dtype===a.dtype?a:ne(a,s.dtype))]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var F3=(r,e,t)=>{switch(r.op){case"FFT":return[ba(C("x",r,e,t))];case"IFFT":return[ti(C("x",r,e,t))];case"RFFT":return[wa(C("x",r,e,t))];case"IRFFT":return[pu(C("x",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var O3=(r,e,t)=>{switch(r.op){case"Cast":return[ne(C("x",r,e,t),C("dtype",r,e,t))];case"ExpandDims":{let o=C("axis",r,e,t);return[lr(C("x",r,e,t),o)]}case"Squeeze":{let o=C("axis",r,e,t);return[No(C("x",r,e,t),o)]}case"Reshape":return[L(C("x",r,e,t),C("shape",r,e,t))];case"MirrorPad":return[qm(C("x",r,e,t),C("padding",r,e,t),C("mode",r,e,t))];case"PadV2":case"Pad":return[Mr(C("x",r,e,t),C("padding",r,e,t),C("constantValue",r,e,t))];case"SpaceToBatchND":{let o=C("blockShape",r,e,t),n=C("paddings",r,e,t);return[ga(C("x",r,e,t),o,n)]}case"BatchToSpaceND":{let o=C("blockShape",r,e,t),n=C("crops",r,e,t);return[ca(C("x",r,e,t),o,n)]}case"DepthToSpace":{let o=C("blockSize",r,e,t),n=C("dataFormat",r,e,t).toUpperCase();return[zm(C("x",r,e,t),o,n)]}case"BroadcastTo":return[ul(C("x",r,e,t),C("shape",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};function B0(r,e,t,o){let n=((s,a,i)=>{switch(s.category){case"arithmetic":return V(()=>f3(s,a,i));case"basic_math":return V(()=>d3(s,a,i));case"control":return w3(s,a,i);case"convolution":return V(()=>k3(s,a,i));case"creation":return V(()=>v3(s,a,i));case"dynamic":return C3(s,a,i);case"evaluation":return V(()=>I3(s,a,i));case"image":return V(()=>T3(s,a,i));case"graph":return V(()=>N3(s,a,i));case"logical":return V(()=>A3(s,a,i));case"matrices":return V(()=>E3(s,a,i));case"normalization":return V(()=>D3(s,a,i));case"reduction":return V(()=>$3(s,a,i));case"slice_join":return V(()=>R3(s,a,i));case"spectral":return V(()=>F3(s,a,i));case"transformation":return V(()=>O3(s,a,i));case"hash_table":return S3(s,a,i,o);case"custom":let l=Xx(s.op);if(l&&l.customExecutor)return l.customExecutor(new P0(s,a,i));throw TypeError(`Custom op ${s.op} is not registered.`);default:throw TypeError(`Unknown op '${s.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`)}})(r,e,t);return y.isPromise(n)?n.then(s=>[].concat(s)):[].concat(n)}var uy=class{constructor(e={},t={},o={},n={}){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=o,this.functionMap=n,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 o=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(o))}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 G0(r,e,t,o){let n=new Set,s=[],a=null,i=null,l=new Set,u=Object.keys(r).map(m=>ro(m)[0]),c=[];o!=null&&(c=o.map(m=>ro(m.name)[0]));let p=[...e];for(;p.length>0;){let m=p.pop();if((V0(m)||Vte(m)||Gte(m))&&a==null&&(a=m,i=a.children.map(f=>f.name).filter(f=>n.has(f))),n.add(m.name),t[m.name]==null&&u.indexOf(m.name)===-1&&c.indexOf(m.name)===-1){if(m.inputs.length===0){s.push(m.name);continue}m.inputs.forEach(f=>{l.has(f.name)||(l.add(f.name),p.push(f))})}}return{inputs:r,outputs:e,usedNodes:n,missingInputs:s,dynamicNode:a,syncInputs:i}}function P3(r,e,t){let{usedNodes:o,inputs:n}=t,s=[],a=Object.keys(n).map(c=>ro(c)[0]).map(c=>r.nodes[c]),i=r.initNodes;a.forEach(c=>{o.has(c.name)&&s.push(c)}),r.weights.forEach(c=>{o.has(c.name)&&s.push(c)}),i!=null&&i.forEach(c=>{o.has(c.name)&&s.push(c)});let l=new Set,u=[];for(;s.length>0;){let c=s.pop();l.add(c.name),e[c.name]||u.push(c),c.children.forEach(p=>{!l.has(p.name)&&o.has(p.name)&&p.inputs.every(m=>l.has(m.name))&&s.push(p)})}return u}var Wte=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],jte=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],Ute=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function V0(r){return Wte.indexOf(r.op)>=0}function Vte(r){return jte.indexOf(r.op)>=0}function Gte(r){return Ute.indexOf(r.op)>=0}var Xp=class{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},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(o=>{this._functionExecutorMap[o]=new Xp(e.functions[o],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(o=>e[o].map(n=>n.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 o=e.map(s=>s.name).sort(),n=t.map(s=>s.name).sort();return o.join(this.SEPERATOR)+"--"+n.join(this.SEPERATOR)}compile(e,t){let o=G0(e,t,this.weightMap,this._initNodes),{missingInputs:n,dynamicNode:s,syncInputs:a}=o;if(s!=null)throw new Error(`This execution contains the node '${s.name}', which has the dynamic op '${s.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${a}]`);if(n.length>0){let i=t.map(u=>u.name),l=Object.keys(e);throw new Error(`Cannot compute the outputs [${i}] from the provided inputs [${l}]. Missing the following inputs: [${n}]`)}return P3(this.graph,this.weightMap,o)}execute(e,t){e=this.mapInputs(e);let o=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let n=o.map(p=>this.graph.nodes[ro(p)[0]]),s=t.map(p=>ro(p)[0]),a=s.map(p=>this.graph.nodes[p]);a.length===0&&(a=this._outputs);let i=this.getCompilationKey(n,a),l=this.compiledMap.get(i);l==null&&(l=this.compile(e,a),this.compiledMap.set(i,l));let u={},c={};return V(()=>{let p=new uy(this.weightMap,u,c,this.functionExecutorMap),m=Object.assign({},this.weightMap);Object.keys(e).forEach(h=>{let[g,x]=ro(h),b=[];b[x]=e[h],m[g]=b});let f=this.getFrozenTensorIds(m),d={};for(let h=0;h<l.length;h++){let g=l[h];if(!m[g.name]){let x=B0(g,m,p,this._resourceManager);if(y.isPromise(x))throw new Error(`The execution of the op '${g.op}' returned a promise. 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You can use model.execute() instead.");let b=l.filter(w=>!V0(w)&&!yr(w.name,d,t)).map(w=>w.name);if(b.length>0){let w="";throw p!=null&&(w=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${m}]`),new Error(`Cannot compute the outputs [${b}] from the provided inputs [${s}]. Consider providing the following inputs: [${c}]. ${w}`)}return d}processStack(e,t,o,n,s,a,i,l,u){let c=[];for(;t.length>0;){let p=t.pop();o.currentContext=p.contexts;let m="";if(p.node.op==="Enter"&&C("isConstant",p.node,n,o)&&([m]=Es(p.node.name,o)),n[p.node.name]==null){let f=B0(p.node,n,o,this._resourceManager);m||([m]=Es(p.node.name,o));let d=o.currentContext;y.isPromise(f)?c.push(f.then(h=>(n[m]=h,o.currentContext=d,this.checkTensorForDisposal(m,p.node,n,o,a,i,l),this.processChildNodes(p.node,t,o,n,s,u),h))):(n[m]=f,this.checkTensorForDisposal(m,p.node,n,o,a,i,l),this.processChildNodes(p.node,t,o,n,s,u))}else this.processChildNodes(p.node,t,o,n,s,u)}return c}processChildNodes(e,t,o,n,s,a){e.children.forEach(i=>{let[l]=Es(i.name,o);s[l]||!a.has(i.name)||(i.op==="Merge"?i.inputNames.some(u=>!!yr(u,n,o))&&(s[l]=!0,t.push({contexts:o.currentContext,node:i})):i.inputNames.every(u=>!!yr(u,n,o))&&(s[l]=!0,t.push({contexts:o.currentContext,node:i})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let o=e[t],[n]=ro(t),s=this.graph.nodes[n];if(s.attrParams.shape&&s.attrParams.shape.value){let a=s.attrParams.shape.value,i=a.length===o.shape.length&&o.shape.every((l,u)=>a[u]===-1||a[u]===l);y.assert(i,()=>`The shape of dict['${s.name}'] provided in model.execute(dict) must be [${a}], but was [${o.shape}]`)}s.attrParams.dtype&&s.attrParams.dtype.value&&y.assert(o.dtype===s.attrParams.dtype.value,()=>`The dtype of dict['${s.name}'] provided in model.execute(dict) must be ${s.attrParams.dtype.value}, but was ${o.dtype}`)})}mapInputs(e){let t={};for(let o 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+`).map(n=>(n.endsWith("\r")&&(n=n.slice(0,-1)),n))}};var fy='"',fh=Symbol("out"),_B=Symbol("field"),dy=Symbol("quote"),oI=Symbol("quoteafterquote"),kB=Symbol("quoteinquote"),dh=class extends mi{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 mh(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(y.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&&y.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((n,s)=>(n[s]=n[s]+1||1,n),{}),o=Object.keys(t).filter(n=>t[n]>1);if(y.assert(o.length===0,()=>"Duplicate column names found: "+o.toString()),this.columnConfigs){for(let n of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(n)===-1)throw new Error('The key "'+n+'" 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 o=t.value;return this.parseRow(o,!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),o={},n={};for(let s=0;s<this.fullColumnNames.length;s++){let a=this.fullColumnNames[s],i=this.columnConfigs?this.columnConfigs[a]:null;if(!(this.configuredColumnsOnly&&!i)){let l=t[s],u=null;if(l==="")if(i&&i.default!==void 0)u=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${a} is empty in this line: ${e}`);u=void 0}else{let c=Number(l);if(isNaN(c))i&&i.dtype==="bool"?u=this.getBoolean(l):u=l;else if(!i||!i.dtype)u=c;else switch(i.dtype){case"float32":u=c;break;case"int32":u=Math.floor(c);break;case"bool":u=this.getBoolean(l);break;default:u=c}}i&&i.isLabel?n[a]=u:o[a]=u}}return Object.keys(n).length===0?o:{xs:o,ys:n}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let o=[],n=0,s=e.length,a=fh;for(let i=0;i<s;i++)switch(a){case fh:switch(e.charAt(i)){case fy:n=i+1,a=dy;break;case this.delimiter:if(n=i+1,this.delimiter===" "&&this.delimWhitespace)break;o.push(""),a=fh;break;default:a=_B,n=i;break}break;case _B:switch(e.charAt(i)){case this.delimiter:o.push(e.substring(n,i)),a=fh,n=i+1;break;default:}break;case dy:switch(e.charAt(i)){case fy:a=oI;break;default:}break;case oI:switch(e.charAt(i)){case this.delimiter:o.push(e.substring(n,i-1)),a=fh,n=i+1;break;case fy:a=dy;break;default:a=kB;break}break;case kB:switch(e.charAt(i)){case fy:a=dy;break;default:}break;default:}if(a===oI?o.push(e.substring(n,s-1)):o.push(e.substring(n)),t&&o.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${o}`);return o}};var hh=class extends Kt{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(W().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new hh(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(o){throw new Error(`Error thrown while initializing video stream: ${o.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,o=await this.getAudioData();if(this.includeSpectrogram){let n=this.flattenQueue(o.freqDataQueue);e=this.getTensorFromAudioDataArray(n,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let n=this.flattenQueue(o.timeDataQueue);t=this.getTensorFromAudioDataArray(n,[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=[],o=0;return new Promise(n=>{let s=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&n({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++o===this.numFrames&&(clearInterval(s),n({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,o=new Float32Array(e.length*t);return e.forEach((n,s)=>o.set(n,s*t)),o}getTensorFromAudioDataArray(e,t){let o=new Float32Array(y.sizeFromShape(t));return o.set(e,o.length-e.length),Pr(o,t)}};var gh=class extends Kt{constructor(e,t){super();if(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=Vt([0],"int32"),this.webcamConfig.centerCrop){let o=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,n=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,s=(1-o)/2,a=(1-n)/2,i=s+o,l=n+a;this.cropBox=ri([a,s,l,i],[1,4])}else this.cropBox=ri([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(W().get("IS_NODE"))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 o=new gh(e,t);return await o.start(),o}async start(){this.webcamConfig.facingMode&&y.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=eg.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return V(()=>{let t=lr(ne(e,"float32"),0),o;o=oi.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let n=o.shape;return L(o,n.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(t=>t.stop());try{this.webcamVideoElement.srcObject=null}catch(t){console.log(t),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}};var xh=class{};var hy=class extends Kt{split(e){return new vB(this,e)}},vB=class extends hy{constructor(e,t){super();this.upstream=e,this.impl=new CB(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},CB=class extends Zp{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let o of t.slice(0,-1))this.outputQueue.push(o);return this.carryover=t[t.length-1],!0}};var nI=class extends Kt{decodeUTF8(){return new NB(this)}},NB=class extends hy{constructor(e){super();this.upstream=e,this.impl=new SB(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},SB=class extends Zp{constructor(e){super();if(this.upstream=e,W().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=IB();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let o;return W().get("IS_BROWSER")?o=this.decoder.decode(t,{stream:!0}):o=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(o),!0}};var yh=class extends nI{constructor(e,t={}){super();this.file=e,this.options=t,y.assert(e instanceof Uint8Array||(W().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,o)=>{let n=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)t(new Uint8Array(this.file.slice(this.offset,n)));else{let s=new FileReader;s.onload=i=>{let l=s.result;if(l instanceof ArrayBuffer&&(l=new Uint8Array(l)),!(l instanceof Uint8Array))return o(new TypeError("FileReader returned unknown type."));t(l)},s.onabort=i=>o(new Error("Aborted")),s.onerror=i=>o(new Error(i.type));let a=this.file.slice(this.offset,n);s.readAsArrayBuffer(a)}this.offset=n}),done:!1}}};async function TB(r,e={}){let t,o;typeof r=="string"?t=r:(t=r.url,o=ire(r));let n=await y.fetch(t,o);if(n.ok){let s=new Uint8Array(await n.arrayBuffer());return new yh(s,e)}else throw new Error(n.statusText)}var ire=r=>({method:r.method,headers:r.headers,body:r.body,mode:r.mode,credentials:r.credentials,cache:r.cache,redirect:r.redirect,referrer:r.referrer,integrity:r.integrity});function gy(r){return typeof r=="string"&&r.substr(0,7)==="file://"}var bh=class extends xh{constructor(e,t={}){super();this.input=e,this.options=t}async iterator(){if(gy(this.input)&&W().get("IS_NODE")){let e=require("fs");this.input=e.readFileSync(this.input.substr(7))}return new yh(this.input,this.options)}};var wh=class extends xh{constructor(e,t={}){super();this.url=e,this.fileOptions=t}async iterator(){return gy(this.url)?new bh(this.url,this.fileOptions).iterator():TB(this.url,this.fileOptions)}};function AB(r,e={}){return new dh(new wh(r),e)}function EB(r){let e=ph(r);return wo(async()=>e)}function DB(r){return wo(async()=>{let e=await r();return ph(()=>e.next())})}async function $B(r,e){return gh.create(r,e)}async function RB(r){return hh.create(r)}var FB="3.3.0";var VVt={tfjs:(lm==null?void 0:lm.version)||void 0,"tfjs-core":(um==null?void 0:um.version)||void 0,"tfjs-data":(cm==null?void 0:cm.version)||void 0,"tfjs-layers":(pm==null?void 0:pm.version)||void 0,"tfjs-converter":(mm==null?void 0:mm.version)||void 0,"tfjs-backend-cpu":k_||void 0,"tfjs-backend-webgl":$k||void 0,"tfjs-backend-wasm":dC||void 0};export{Os as Abs,yi as Acos,bi as Acosh,sf as AdadeltaOptimizer,af as AdagradOptimizer,lf as AdamOptimizer,uf as AdamaxOptimizer,Fo as Add,kn as AddN,cc as All,pc as Any,vn as ArgMax,Ga as ArgMin,wi as Asin,_i as Asinh,ki as Atan,Ci as Atan2,vi as Atanh,Cn as AvgPool,Wa as AvgPool3D,fc as AvgPool3DGrad,mc as AvgPoolGrad,mC as BackendWasm,In as BatchMatMul,ja as BatchToSpaceND,dc as Bincount,QN as BroadcastTo,h0 as Callback,TC as CallbackList,Ho as Cast,Nn as Ceil,qo as ClipByValue,hc as Complex,Ua as ComplexAbs,Ps as Concat,Sn as Conv2D,gc as Conv2DBackpropFilter,Tn as Conv2DBackpropInput,Ha as Conv3D,xc as Conv3DBackpropFilterV2,yc as Conv3DBackpropInputV2,An as Cos,Ii as Cosh,Ni as CropAndResize,En as Cumsum,EC as CustomCallback,Va as DataStorage,bc as DenseBincount,Si as DepthToSpace,Dn as DepthwiseConv2dNative,wc as DepthwiseConv2dNativeBackpropFilter,_c as DepthwiseConv2dNativeBackpropInput,kc as Diag,qa as Dilation2D,ym as Dilation2DBackpropFilter,xm as Dilation2DBackpropInput,Mb as ENV,g0 as EarlyStopping,Ti as Elu,vc as EluGrad,jh as Environment,Ei as Equal,Ai as Erf,Rn as Exp,Ms as ExpandDims,Di as Expm1,Cc as FFT,Ka as Fill,$i as FlipLeftRight,Fn as Floor,On as FloorDiv,bm as FromPixels,Pn as FusedBatchNorm,Xs as FusedConv2D,Ys as FusedDepthwiseConv2D,Nk as GPGPUContext,Ri as GatherNd,Ls as GatherV2,j0 as GraphModel,Fi as Greater,Mn as GreaterEqual,AC as History,Ic as IFFT,Ko as Identity,Nc as Imag,At as InputSpec,Oi as IsFinite,Pi as IsInf,Mi as IsNan,$s as KernelBackend,Xa as LRN,Tc as LRNGrad,Dx as LayerVariable,Wo as LayersModel,Ln as LeakyRelu,Li as Less,zi as LessEqual,Sc as LinSpace,zn as Log,Bi as Log1p,eS as LogSoftmax,Vi as LogicalAnd,Ml as LogicalNot,Ll as LogicalOr,np as MathBackendCPU,bp as MathBackendWebGL,Bn as Max,Gn as MaxPool,Ya as MaxPool3D,Ec as MaxPool3DGrad,Ac as MaxPoolGrad,Dc as MaxPoolWithArgmax,Vn as Maximum,Wn as Mean,jn as Min,Un as Minimum,Za as MirrorPad,Gi as Mod,cf as MomentumOptimizer,$c as Multinomial,Hn as Multiply,zs as Neg,ji as NonMaxSuppressionV3,Ui as NonMaxSuppressionV4,Hi as NonMaxSuppressionV5,Wi as NotEqual,bG as OP_SCOPE_SUFFIX,qn as OneHot,Bs as OnesLike,zr as Optimizer,Vs as Pack,Kn as PadV2,dre as Pool,Xn as Pow,Yn as Prelu,qi as Prod,pf as RMSPropOptimizer,Eo as RNN,Ja as Range,jb as Rank,Rc as Real,$n as RealDiv,Ki as Reciprocal,qt as Reduction,Zn as Relu,Qn as Relu6,Gs as Reshape,Jn as ResizeBilinear,Oc as ResizeBilinearGrad,Qa as ResizeNearestNeighbor,Fc as ResizeNearestNeighborGrad,es as Reverse,oa as RotateWithOffset,ts as Round,rs as Rsqrt,yu as SGDOptimizer,Xi as ScatterNd,Ws as Select,Yi as Selu,$a as Sequential,ns as Sigmoid,Ji as Sign,os as Sin,Zi as Sinh,js as Slice,as as Softmax,Qi as Softplus,el as SpaceToBatchND,Pc as SparseToDense,Us as SplitV,ss as Sqrt,tl as Square,ls as SquaredDifference,Xo as Step,ea as StridedSlice,us as Sub,is as Sum,eo as SymbolicTensor,ta as Tan,cs as Tanh,Ve as Tensor,lt as TensorBuffer,Oo as Tile,ra as TopK,Mc as Transform,ps as Transpose,Lc as Unique,Hs as Unpack,rl as UnsortedSegmentSum,nl as Variable,qs as ZerosLike,Ks as _FusedMatMul,It as abs,Tm as acos,Am as acosh,ee as add,xw as addN,Hl as all,al as any,ll as argMax,Em as 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as enableProdMode,PT as enclosingPowerOfTwo,Zo as engine,W as env,Io as equal,Gm as erf,Zt as exp,lr as expandDims,Wm as expm1,Yc as eye,ba as fft,ma as fill,sie as findBackend,iie as findBackendFactory,gs as floor,Ul as floorDiv,lD as forceHalfFloat,rn as fused,Qo as gather,RT as gatherND,tg as gather_util,oie as getBackend,Vb as getGradient,_m as getKernel,Uh as getKernelsForBackend,f5 as gpgpu_util,Kde as grad,Xde as grads,tr as greater,co as greaterEqual,ti as ifft,Ql as imag,oi as image,iIe as inTopKAsync,kz as initializers,zC as input,Nr as io,pu as irfft,Ew as isFinite,Dw as isInf,$w as isNaN,Et as keep,Er as kernel_impls,Qz as layers,fa as leakyRelu,eu as less,zo as lessEqual,m1 as linalg,Rw as linspace,Kte as loadGraphModel,RQ as loadLayersModel,jm as localResponseNormalization,ur as log,tu as log1p,Ow as logSigmoid,ru as logSoftmax,ug as logSumExp,hr as logicalAnd,da as logicalNot,ou as logicalOr,dT as logicalXor,Z$e as losses,je as matMul,ZG as math,cr as max,ha as maxPool,Hm as maxPool3d,zw as maxPoolWithArgmax,Zr as maximum,dt as mean,Sm as memory,n3 as metrics,ei as min,ys as minimum,qm as mirrorPad,Km as mod,DQ as model,s3 as models,Zc as moments,k0e as movingAverage,P as mul,Xxe as multiRNNCell,Bw as multinomial,He as neg,mf as nextFrame,rp as norm,tn as notEqual,fs as oneHot,Sr as ones,rr as onesLike,S as op,Aye as outerProduct,Mr as pad,zye as pad1d,jye as pad2d,Xye as pad3d,ebe as pad4d,hT as pool,Lr as pow,xa as prelu,OS as print,nu as prod,eie as profile,Lbe as rand,Kbe as randomGamma,mg as randomNormal,bs as randomUniform,Qc as range,rie as ready,cl as real,Xm as reciprocal,qc as registerBackend,FQ as registerCallbackConstructor,tS as registerGradient,zl as registerKernel,_te as registerOp,i3 as regularizers,Tr as relu,iu as relu6,nie as removeBackend,L as reshape,Ht as reverse,Pwe as reverse1d,Gwe as reverse2d,Kwe as reverse3d,e_e as reverse4d,wa as rfft,Ym as round,au as rsqrt,le as scalar,DT as scatterND,rg as scatter_util,lu as selu,Zm as separableConv2d,$Q as sequential,Q as serialization,xW as setBackend,aie as setPlatform,Rht as setWasmPath,Fht as setWasmPaths,u2 as setWebGLContext,Zw as setdiff1dAsync,__ as shared,Xr as sigmoid,Jm as sign,Y$e as signal,uu as sin,cu as sinh,Re as slice,Qm as slice1d,fg as slice2d,ef as slice3d,ep as slice4d,er as slice_util,ya as softmax,xs as softplus,ga as spaceToBatchND,gg as sparseToDense,X$e as spectral,pr as split,gt as sqrt,Oe as square,mu as squaredDifference,No as squeeze,Bt as stack,ws as step,tf as stridedSlice,ce as sub,ge as sum,Vl as sumOutType,rf as tan,Qs as tanh,Pr as tensor,Vt as tensor1d,ri as tensor2d,HS as tensor3d,Jve as tensor4d,oCe as tensor5d,lCe as tensor6d,Yo as tensor_util,uW as test_util,V as tidy,Lo as tile,tie as time,of as topk,bu as train,Ke as transpose,fu as truncatedNormal,tp as unique,bre as unregisterGradient,yre as unregisterKernel,dg as unsortedSegmentSum,mr as unstack,ir as upcastType,y as util,Yde as valueAndGrad,Zde as valueAndGrads,Jw as variable,Fw as variableGrads,VVt as version,Xte as version_converter,jse as version_core,k_ as version_cpu,ld as version_layers,dC as version_wasm,$k as version_webgl,F5e as webgl,t5 as webgl_util,Dt as where,nf as whereAsync,ht as zeros,Ce as zerosLike};
 /**
  * @license
  * Copyright 2017 Google LLC. All Rights Reserved.
diff --git a/dist/tfjs.esm.js.map b/dist/tfjs.esm.js.map
index 9484cb01..bd00fd27 100644
--- a/dist/tfjs.esm.js.map
+++ b/dist/tfjs.esm.js.map
@@ -1,7 +1,7 @@
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-  "sourcesContent": ["", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\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) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = 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) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\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\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) 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 + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\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\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModuleThreadedSimd) {\n  WasmBackendModuleThreadedSimd = WasmBackendModuleThreadedSimd || {};\n\nfunction GROWABLE_HEAP_I8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP8}function GROWABLE_HEAP_U8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU8}function GROWABLE_HEAP_I32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP32}function GROWABLE_HEAP_U32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU32}function GROWABLE_HEAP_F64(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPF64}var Module=typeof WasmBackendModuleThreadedSimd!==\"undefined\"?WasmBackendModuleThreadedSimd:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var ENVIRONMENT_IS_PTHREAD=Module[\"ENVIRONMENT_IS_PTHREAD\"]||false;if(ENVIRONMENT_IS_PTHREAD){buffer=Module[\"buffer\"]}var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process[\"on\"](\"unhandledRejection\",abort);quit_=function(status){process[\"exit\"](status)};Module[\"inspect\"]=function(){return\"[Emscripten Module object]\"};var nodeWorkerThreads;try{nodeWorkerThreads=require(\"worker_threads\")}catch(e){console.error('The \"worker_threads\" module is not supported in this node.js build - perhaps a newer version is needed?');throw e}global.Worker=nodeWorkerThreads.Worker}else if(ENVIRONMENT_IS_SHELL){if(typeof read!=\"undefined\"){read_=function shell_read(f){return read(f)}}readBinary=function readBinary(f){var data;if(typeof readbuffer===\"function\"){return new Uint8Array(readbuffer(f))}data=read(f,\"binary\");assert(typeof data===\"object\");return data};if(typeof scriptArgs!=\"undefined\"){arguments_=scriptArgs}else if(typeof arguments!=\"undefined\"){arguments_=arguments}if(typeof quit===\"function\"){quit_=function(status){quit(status)}}if(typeof print!==\"undefined\"){if(typeof console===\"undefined\")console={};console.log=print;console.warn=console.error=typeof printErr!==\"undefined\"?printErr:print}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href}else if(typeof document!==\"undefined\"&&document.currentScript){scriptDirectory=document.currentScript.src}if(typeof _scriptDir !== \"undefined\" && _scriptDir){scriptDirectory=_scriptDir}if(scriptDirectory.indexOf(\"blob:\")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf(\"/\")+1)}else{scriptDirectory=\"\"}if(ENVIRONMENT_IS_NODE){read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret}}else{read_=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}if(ENVIRONMENT_IS_NODE){if(typeof performance===\"undefined\"){global.performance=require(\"perf_hooks\").performance}}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var Atomics_load=Atomics.load;var Atomics_store=Atomics.store;var Atomics_compareExchange=Atomics.compareExchange;var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var wasmModule;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module[\"wasmMemory\"];buffer=Module[\"buffer\"]}else{if(Module[\"wasmMemory\"]){wasmMemory=Module[\"wasmMemory\"]}else{wasmMemory=new WebAssembly.Memory({\"initial\":INITIAL_MEMORY/65536,\"maximum\":2147483648/65536,\"shared\":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){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\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];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)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={\"e\":___assert_fail,\"r\":___call_main,\"x\":__emscripten_notify_thread_queue,\"b\":_abort,\"y\":_emscripten_asm_const_int,\"j\":_emscripten_conditional_set_current_thread_status,\"c\":_emscripten_futex_wait,\"d\":_emscripten_futex_wake,\"f\":_emscripten_get_now,\"p\":_emscripten_memcpy_big,\"z\":_emscripten_num_logical_cores,\"u\":_emscripten_receive_on_main_thread_js,\"q\":_emscripten_resize_heap,\"v\":_emscripten_set_canvas_element_size,\"i\":_emscripten_set_current_thread_status,\"t\":_emscripten_set_thread_name,\"w\":_emscripten_webgl_create_context,\"m\":_fd_close,\"n\":_fd_seek,\"g\":_fd_write,\"o\":initPthreadsJS,\"a\":wasmMemory||Module[\"wasmMemory\"],\"k\":_pthread_cleanup_pop,\"l\":_pthread_cleanup_push,\"h\":_pthread_create,\"s\":_sysconf};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var _ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"X\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"Y\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"Z\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"_\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"$\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"aa\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"ba\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"ca\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"da\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"ea\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"fa\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"ga\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"ha\"]).apply(null,arguments)};var 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_emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=function(){return(_emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=Module[\"asm\"][\"gb\"]).apply(null,arguments)};var __emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=function(){return(__emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=Module[\"asm\"][\"hb\"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=function(){return(_emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=Module[\"asm\"][\"ib\"]).apply(null,arguments)};var _emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=function(){return(_emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=Module[\"asm\"][\"jb\"]).apply(null,arguments)};var __emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=function(){return(__emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=Module[\"asm\"][\"kb\"]).apply(null,arguments)};var _emscripten_tls_init=Module[\"_emscripten_tls_init\"]=function(){return(_emscripten_tls_init=Module[\"_emscripten_tls_init\"]=Module[\"asm\"][\"lb\"]).apply(null,arguments)};var __emscripten_thread_init=Module[\"__emscripten_thread_init\"]=function(){return(__emscripten_thread_init=Module[\"__emscripten_thread_init\"]=Module[\"asm\"][\"mb\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"nb\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"ob\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"pb\"]).apply(null,arguments)};var _emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=function(){return(_emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=Module[\"asm\"][\"qb\"]).apply(null,arguments)};var _memalign=Module[\"_memalign\"]=function(){return(_memalign=Module[\"_memalign\"]=Module[\"asm\"][\"rb\"]).apply(null,arguments)};var __emscripten_allow_main_runtime_queued_calls=Module[\"__emscripten_allow_main_runtime_queued_calls\"]=9880;var __emscripten_main_thread_futex=Module[\"__emscripten_main_thread_futex\"]=11368;Module[\"cwrap\"]=cwrap;Module[\"PThread\"]=PThread;Module[\"PThread\"]=PThread;Module[\"wasmMemory\"]=wasmMemory;Module[\"ExitStatus\"]=ExitStatus;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}if(ENVIRONMENT_IS_PTHREAD){readyPromiseResolve(Module);postMessage({\"cmd\":\"loaded\"});return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;function exit(status,implicit){if(implicit&&noExitRuntime&&status===0){return}if(!implicit){if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exitProcess\",\"returnCode\":status});throw new ExitStatus(status)}else{}}if(noExitRuntime){}else{PThread.terminateAllThreads();EXITSTATUS=status;exitRuntime();if(Module[\"onExit\"])Module[\"onExit\"](status);ABORT=true}quit_(status,new ExitStatus(status))}if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}if(ENVIRONMENT_IS_PTHREAD){noExitRuntime=false;PThread.initWorker()}run();\n\n\n  return WasmBackendModuleThreadedSimd.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModuleThreadedSimd;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModuleThreadedSimd; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModuleThreadedSimd\"] = WasmBackendModuleThreadedSimd;\n", "\nvar WasmBackendModule = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModule) {\n  WasmBackendModule = WasmBackendModule || {};\n\nvar Module=typeof WasmBackendModule!==\"undefined\"?WasmBackendModule:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var 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XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return 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Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function 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_Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\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) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = 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) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\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\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) 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 + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\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\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, 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null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");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;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(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;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}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);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}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);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var nodeFS=require(\"fs\");var nodeRead=function(filename){return nodeFS.readFileSync(filename,\"utf8\")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance===\"undefined\"){performance={now:function(){return Date.now()}}}}';", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }\n\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export versions\nexport const version = {\n  tfjs: packageBundle.version,\n  'tfjs-core': packageCore.version,\n  'tfjs-data': packageData.version,\n  'tfjs-layers': packageLayers.version,\n  'tfjs-converter': packageConverter.version,\n  'tfjs-backend-cpu': version_cpu,\n  'tfjs-backend-webgl': version_webgl,\n  'tfjs-backend-wasm': version_wasm,\n};\n"],
-  "mappings": 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+  "sourcesContent": ["", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\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) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = 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) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\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\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) 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 + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\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\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModuleThreadedSimd) {\n  WasmBackendModuleThreadedSimd = WasmBackendModuleThreadedSimd || {};\n\nfunction GROWABLE_HEAP_I8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP8}function GROWABLE_HEAP_U8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU8}function GROWABLE_HEAP_I32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP32}function GROWABLE_HEAP_U32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU32}function GROWABLE_HEAP_F64(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPF64}var Module=typeof WasmBackendModuleThreadedSimd!==\"undefined\"?WasmBackendModuleThreadedSimd:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var ENVIRONMENT_IS_PTHREAD=Module[\"ENVIRONMENT_IS_PTHREAD\"]||false;if(ENVIRONMENT_IS_PTHREAD){buffer=Module[\"buffer\"]}var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process[\"on\"](\"unhandledRejection\",abort);quit_=function(status){process[\"exit\"](status)};Module[\"inspect\"]=function(){return\"[Emscripten Module object]\"};var nodeWorkerThreads;try{nodeWorkerThreads=require(\"worker_threads\")}catch(e){console.error('The \"worker_threads\" module is not supported in this node.js build - perhaps a newer version is needed?');throw e}global.Worker=nodeWorkerThreads.Worker}else if(ENVIRONMENT_IS_SHELL){if(typeof read!=\"undefined\"){read_=function shell_read(f){return read(f)}}readBinary=function readBinary(f){var data;if(typeof readbuffer===\"function\"){return new Uint8Array(readbuffer(f))}data=read(f,\"binary\");assert(typeof data===\"object\");return data};if(typeof scriptArgs!=\"undefined\"){arguments_=scriptArgs}else if(typeof arguments!=\"undefined\"){arguments_=arguments}if(typeof quit===\"function\"){quit_=function(status){quit(status)}}if(typeof print!==\"undefined\"){if(typeof console===\"undefined\")console={};console.log=print;console.warn=console.error=typeof printErr!==\"undefined\"?printErr:print}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href}else if(typeof document!==\"undefined\"&&document.currentScript){scriptDirectory=document.currentScript.src}if(typeof _scriptDir !== \"undefined\" && _scriptDir){scriptDirectory=_scriptDir}if(scriptDirectory.indexOf(\"blob:\")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf(\"/\")+1)}else{scriptDirectory=\"\"}if(ENVIRONMENT_IS_NODE){read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret}}else{read_=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}if(ENVIRONMENT_IS_NODE){if(typeof performance===\"undefined\"){global.performance=require(\"perf_hooks\").performance}}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var Atomics_load=Atomics.load;var Atomics_store=Atomics.store;var Atomics_compareExchange=Atomics.compareExchange;var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var wasmModule;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module[\"wasmMemory\"];buffer=Module[\"buffer\"]}else{if(Module[\"wasmMemory\"]){wasmMemory=Module[\"wasmMemory\"]}else{wasmMemory=new WebAssembly.Memory({\"initial\":INITIAL_MEMORY/65536,\"maximum\":2147483648/65536,\"shared\":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){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\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];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)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={\"e\":___assert_fail,\"r\":___call_main,\"x\":__emscripten_notify_thread_queue,\"b\":_abort,\"y\":_emscripten_asm_const_int,\"j\":_emscripten_conditional_set_current_thread_status,\"c\":_emscripten_futex_wait,\"d\":_emscripten_futex_wake,\"f\":_emscripten_get_now,\"p\":_emscripten_memcpy_big,\"z\":_emscripten_num_logical_cores,\"u\":_emscripten_receive_on_main_thread_js,\"q\":_emscripten_resize_heap,\"v\":_emscripten_set_canvas_element_size,\"i\":_emscripten_set_current_thread_status,\"t\":_emscripten_set_thread_name,\"w\":_emscripten_webgl_create_context,\"m\":_fd_close,\"n\":_fd_seek,\"g\":_fd_write,\"o\":initPthreadsJS,\"a\":wasmMemory||Module[\"wasmMemory\"],\"k\":_pthread_cleanup_pop,\"l\":_pthread_cleanup_push,\"h\":_pthread_create,\"s\":_sysconf};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var 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_ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"X\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"Y\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"Z\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"_\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"$\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"aa\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"ba\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"ca\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"da\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"ea\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"fa\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"ga\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"ha\"]).apply(null,arguments)};var _Log=Module[\"_Log\"]=function(){return(_Log=Module[\"_Log\"]=Module[\"asm\"][\"ia\"]).apply(null,arguments)};var _LogicalAnd=Module[\"_LogicalAnd\"]=function(){return(_LogicalAnd=Module[\"_LogicalAnd\"]=Module[\"asm\"][\"ja\"]).apply(null,arguments)};var _Max=Module[\"_Max\"]=function(){return(_Max=Module[\"_Max\"]=Module[\"asm\"][\"ka\"]).apply(null,arguments)};var _MaxPool=Module[\"_MaxPool\"]=function(){return(_MaxPool=Module[\"_MaxPool\"]=Module[\"asm\"][\"la\"]).apply(null,arguments)};var _Maximum=Module[\"_Maximum\"]=function(){return(_Maximum=Module[\"_Maximum\"]=Module[\"asm\"][\"ma\"]).apply(null,arguments)};var _Mean=Module[\"_Mean\"]=function(){return(_Mean=Module[\"_Mean\"]=Module[\"asm\"][\"na\"]).apply(null,arguments)};var _Min=Module[\"_Min\"]=function(){return(_Min=Module[\"_Min\"]=Module[\"asm\"][\"oa\"]).apply(null,arguments)};var _Minimum=Module[\"_Minimum\"]=function(){return(_Minimum=Module[\"_Minimum\"]=Module[\"asm\"][\"pa\"]).apply(null,arguments)};var 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_OneHot=Module[\"_OneHot\"]=function(){return(_OneHot=Module[\"_OneHot\"]=Module[\"asm\"][\"wa\"]).apply(null,arguments)};var _PadV2=Module[\"_PadV2\"]=function(){return(_PadV2=Module[\"_PadV2\"]=Module[\"asm\"][\"xa\"]).apply(null,arguments)};var _Pow=Module[\"_Pow\"]=function(){return(_Pow=Module[\"_Pow\"]=Module[\"asm\"][\"ya\"]).apply(null,arguments)};var _Prelu=Module[\"_Prelu\"]=function(){return(_Prelu=Module[\"_Prelu\"]=Module[\"asm\"][\"za\"]).apply(null,arguments)};var _Prod=Module[\"_Prod\"]=function(){return(_Prod=Module[\"_Prod\"]=Module[\"asm\"][\"Aa\"]).apply(null,arguments)};var _RealDiv=Module[\"_RealDiv\"]=function(){return(_RealDiv=Module[\"_RealDiv\"]=Module[\"asm\"][\"Ba\"]).apply(null,arguments)};var _Relu=Module[\"_Relu\"]=function(){return(_Relu=Module[\"_Relu\"]=Module[\"asm\"][\"Ca\"]).apply(null,arguments)};var _Relu6=Module[\"_Relu6\"]=function(){return(_Relu6=Module[\"_Relu6\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var 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___pthread_tsd_run_dtors=Module[\"___pthread_tsd_run_dtors\"]=function(){return(___pthread_tsd_run_dtors=Module[\"___pthread_tsd_run_dtors\"]=Module[\"asm\"][\"db\"]).apply(null,arguments)};var _emscripten_main_thread_process_queued_calls=Module[\"_emscripten_main_thread_process_queued_calls\"]=function(){return(_emscripten_main_thread_process_queued_calls=Module[\"_emscripten_main_thread_process_queued_calls\"]=Module[\"asm\"][\"eb\"]).apply(null,arguments)};var _emscripten_current_thread_process_queued_calls=Module[\"_emscripten_current_thread_process_queued_calls\"]=function(){return(_emscripten_current_thread_process_queued_calls=Module[\"_emscripten_current_thread_process_queued_calls\"]=Module[\"asm\"][\"fb\"]).apply(null,arguments)};var _emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=function(){return(_emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=Module[\"asm\"][\"gb\"]).apply(null,arguments)};var __emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=function(){return(__emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=Module[\"asm\"][\"hb\"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=function(){return(_emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=Module[\"asm\"][\"ib\"]).apply(null,arguments)};var _emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=function(){return(_emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=Module[\"asm\"][\"jb\"]).apply(null,arguments)};var __emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=function(){return(__emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=Module[\"asm\"][\"kb\"]).apply(null,arguments)};var _emscripten_tls_init=Module[\"_emscripten_tls_init\"]=function(){return(_emscripten_tls_init=Module[\"_emscripten_tls_init\"]=Module[\"asm\"][\"lb\"]).apply(null,arguments)};var __emscripten_thread_init=Module[\"__emscripten_thread_init\"]=function(){return(__emscripten_thread_init=Module[\"__emscripten_thread_init\"]=Module[\"asm\"][\"mb\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"nb\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"ob\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"pb\"]).apply(null,arguments)};var _emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=function(){return(_emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=Module[\"asm\"][\"qb\"]).apply(null,arguments)};var _memalign=Module[\"_memalign\"]=function(){return(_memalign=Module[\"_memalign\"]=Module[\"asm\"][\"rb\"]).apply(null,arguments)};var __emscripten_allow_main_runtime_queued_calls=Module[\"__emscripten_allow_main_runtime_queued_calls\"]=9880;var __emscripten_main_thread_futex=Module[\"__emscripten_main_thread_futex\"]=11368;Module[\"cwrap\"]=cwrap;Module[\"PThread\"]=PThread;Module[\"PThread\"]=PThread;Module[\"wasmMemory\"]=wasmMemory;Module[\"ExitStatus\"]=ExitStatus;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}if(ENVIRONMENT_IS_PTHREAD){readyPromiseResolve(Module);postMessage({\"cmd\":\"loaded\"});return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;function exit(status,implicit){if(implicit&&noExitRuntime&&status===0){return}if(!implicit){if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exitProcess\",\"returnCode\":status});throw new ExitStatus(status)}else{}}if(noExitRuntime){}else{PThread.terminateAllThreads();EXITSTATUS=status;exitRuntime();if(Module[\"onExit\"])Module[\"onExit\"](status);ABORT=true}quit_(status,new ExitStatus(status))}if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}if(ENVIRONMENT_IS_PTHREAD){noExitRuntime=false;PThread.initWorker()}run();\n\n\n  return WasmBackendModuleThreadedSimd.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModuleThreadedSimd;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModuleThreadedSimd; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModuleThreadedSimd\"] = WasmBackendModuleThreadedSimd;\n", "\nvar WasmBackendModule = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModule) {\n  WasmBackendModule = WasmBackendModule || {};\n\nvar Module=typeof WasmBackendModule!==\"undefined\"?WasmBackendModule:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process[\"on\"](\"unhandledRejection\",abort);quit_=function(status){process[\"exit\"](status)};Module[\"inspect\"]=function(){return\"[Emscripten Module object]\"}}else if(ENVIRONMENT_IS_SHELL){if(typeof read!=\"undefined\"){read_=function shell_read(f){return read(f)}}readBinary=function readBinary(f){var data;if(typeof readbuffer===\"function\"){return new Uint8Array(readbuffer(f))}data=read(f,\"binary\");assert(typeof data===\"object\");return data};if(typeof scriptArgs!=\"undefined\"){arguments_=scriptArgs}else if(typeof arguments!=\"undefined\"){arguments_=arguments}if(typeof quit===\"function\"){quit_=function(status){quit(status)}}if(typeof print!==\"undefined\"){if(typeof console===\"undefined\")console={};console.log=print;console.warn=console.error=typeof printErr!==\"undefined\"?printErr:print}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href}else if(typeof document!==\"undefined\"&&document.currentScript){scriptDirectory=document.currentScript.src}if(_scriptDir){scriptDirectory=_scriptDir}if(scriptDirectory.indexOf(\"blob:\")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf(\"/\")+1)}else{scriptDirectory=\"\"}{read_=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return 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Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). 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fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmMemory=Module[\"asm\"][\"g\"];updateGlobalBufferAndViews(wasmMemory.buffer);wasmTable=Module[\"asm\"][\"m\"];removeRunDependency(\"wasm-instantiate\")}addRunDependency(\"wasm-instantiate\");function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"])}function instantiateArrayBuffer(receiver){return 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false}}instantiateAsync().catch(readyPromiseReject);return{}}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _abort(){abort()}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num)}function _emscripten_get_heap_size(){return HEAPU8.length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var 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_Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\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) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = 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) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\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\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) 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 + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\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\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          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') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");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;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(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;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}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);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}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);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var nodeFS=require(\"fs\");var nodeRead=function(filename){return nodeFS.readFileSync(filename,\"utf8\")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance===\"undefined\"){performance={now:function(){return Date.now()}}}}';", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1250, moduleBytes: 4013323, imports: 7, importBytes: 2255, outputBytes: 2991826, outputFiles: 'dist/tfjs.esm.js' }\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1253, moduleBytes: 4029357, imports: 7, importBytes: 2285, outputBytes: 2998298, outputFiles: 'dist/tfjs.esm.js' }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all - compiled\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all - sources\n/*\nexport * from '@tensorflow/tfjs-core/src/index';\nexport * from '@tensorflow/tfjs-layers/src/index';\nexport * from '@tensorflow/tfjs-converter/src/index';\nexport * as data from '@tensorflow/tfjs-data/src/index';\nexport * from '@tensorflow/tfjs-backend-cpu/src/index';\nexport * from '@tensorflow/tfjs-backend-webgl/src/index';\nexport * from '@tensorflow/tfjs-backend-wasm/src/index';\n*/\n\n// export versions\nexport const version = {\n  tfjs: packageBundle?.version || undefined,\n  'tfjs-core': packageCore?.version || undefined,\n  'tfjs-data': packageData?.version || undefined,\n  'tfjs-layers': packageLayers?.version || undefined,\n  'tfjs-converter': packageConverter?.version || undefined,\n  'tfjs-backend-cpu': version_cpu || undefined,\n  'tfjs-backend-webgl': version_webgl || undefined,\n  'tfjs-backend-wasm': version_wasm || undefined,\n};\n// export const version = {};\n"],
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   "names": []
 }
diff --git a/package.json b/package.json
index 847ff2ba..dac63b13 100644
--- a/package.json
+++ b/package.json
@@ -64,10 +64,10 @@
     "@types/node": "^14.14.37",
     "@typescript-eslint/eslint-plugin": "^4.21.0",
     "@typescript-eslint/parser": "^4.21.0",
-    "@vladmandic/pilogger": "^0.2.15",
+    "@vladmandic/pilogger": "^0.2.16",
     "chokidar": "^3.5.1",
     "dayjs": "^1.10.4",
-    "esbuild": "^0.11.5",
+    "esbuild": "^0.11.6",
     "eslint": "^7.23.0",
     "eslint-config-airbnb-base": "^14.2.1",
     "eslint-plugin-import": "^2.22.1",
@@ -79,6 +79,6 @@
     "simple-git": "^2.37.0",
     "tslib": "^2.2.0",
     "typedoc": "^0.20.35",
-    "typescript": "^4.2.3"
+    "typescript": "^4.2.4"
   }
 }
diff --git a/server/build.js b/server/build.js
index 30088cd2..1012d857 100755
--- a/server/build.js
+++ b/server/build.js
@@ -223,7 +223,7 @@ async function build(f, msg, dev = false) {
     for (const [targetGroupName, targetGroup] of Object.entries(targets)) {
       for (const [targetName, targetOptions] of Object.entries(targetGroup)) {
         // if triggered from watch mode, rebuild only browser bundle
-        if ((require.main !== module) && ((targetGroupName === 'browserNoBundle') || (targetGroupName === 'nodeGPU'))) continue;
+        // if ((require.main !== module) && ((targetGroupName === 'browserNoBundle') || (targetGroupName === 'nodeGPU'))) continue;
         const meta = dev
           // @ts-ignore
           ? await esbuild.build({ ...config.common, ...config.debug, ...targetOptions })
diff --git a/src/tfjs/tf-browser.ts b/src/tfjs/tf-browser.ts
index af1f5b1a..27e0fdda 100644
--- a/src/tfjs/tf-browser.ts
+++ b/src/tfjs/tf-browser.ts
@@ -1,13 +1,12 @@
 // wrapper to load tfjs in a single place so version can be changed quickly
 
 // simplified
-// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }
-
+// { modules: 1250, moduleBytes: 4013323, imports: 7, importBytes: 2255, outputBytes: 2991826, outputFiles: 'dist/tfjs.esm.js' }
 // export * from '@tensorflow/tfjs/dist/index.js';
 // export * from '@tensorflow/tfjs-backend-wasm';
 
 // modular
-// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }
+// { modules: 1253, moduleBytes: 4029357, imports: 7, importBytes: 2285, outputBytes: 2998298, outputFiles: 'dist/tfjs.esm.js' }
 
 // get versions of all packages.
 import * as packageBundle from '@tensorflow/tfjs/package.json';
@@ -20,7 +19,7 @@ import { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';
 import { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';
 import { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';
 
-// export all
+// export all - compiled
 export * from '@tensorflow/tfjs-core/dist/index.js';
 export * from '@tensorflow/tfjs-layers/dist/index.js';
 export * from '@tensorflow/tfjs-converter/dist/index.js';
@@ -29,14 +28,26 @@ export * from '@tensorflow/tfjs-backend-cpu/dist/index.js';
 export * from '@tensorflow/tfjs-backend-webgl/dist/index.js';
 export * from '@tensorflow/tfjs-backend-wasm/dist/index.js';
 
+// export all - sources
+/*
+export * from '@tensorflow/tfjs-core/src/index';
+export * from '@tensorflow/tfjs-layers/src/index';
+export * from '@tensorflow/tfjs-converter/src/index';
+export * as data from '@tensorflow/tfjs-data/src/index';
+export * from '@tensorflow/tfjs-backend-cpu/src/index';
+export * from '@tensorflow/tfjs-backend-webgl/src/index';
+export * from '@tensorflow/tfjs-backend-wasm/src/index';
+*/
+
 // export versions
 export const version = {
-  tfjs: packageBundle.version,
-  'tfjs-core': packageCore.version,
-  'tfjs-data': packageData.version,
-  'tfjs-layers': packageLayers.version,
-  'tfjs-converter': packageConverter.version,
-  'tfjs-backend-cpu': version_cpu,
-  'tfjs-backend-webgl': version_webgl,
-  'tfjs-backend-wasm': version_wasm,
+  tfjs: packageBundle?.version || undefined,
+  'tfjs-core': packageCore?.version || undefined,
+  'tfjs-data': packageData?.version || undefined,
+  'tfjs-layers': packageLayers?.version || undefined,
+  'tfjs-converter': packageConverter?.version || undefined,
+  'tfjs-backend-cpu': version_cpu || undefined,
+  'tfjs-backend-webgl': version_webgl || undefined,
+  'tfjs-backend-wasm': version_wasm || undefined,
 };
+// export const version = {};
diff --git a/wiki b/wiki
index 2e665d7f..eaf77ad8 160000
--- a/wiki
+++ b/wiki
@@ -1 +1 @@
-Subproject commit 2e665d7f322cfc79bae842c648feaffa668d883d
+Subproject commit eaf77ad8c8a91df6e63bee662062ff59a0ce987a