face-api/dist/tfjs.esm.js

/*
  Face-API
  homepage: <https://github.com/vladmandic/face-api>
  author: <https://github.com/vladmandic>'
*/

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Buffer shape=${this.shape}`;throw new Error(s)}e++}let n=t[t.length-1];for(let o=0;o<t.length-1;++o)n+=this.strides[o]*t[o];return this.values[n]}locToIndex(t){if(this.rank===0)return 0;if(this.rank===1)return t[0];let e=t[t.length-1];for(let n=0;n<t.length-1;++n)e+=this.strides[n]*t[n];return e}indexToLoc(t){if(this.rank===0)return[];if(this.rank===1)return[t];let e=new Array(this.shape.length);for(let n=0;n<e.length-1;++n)e[n]=Math.floor(t/this.strides[n]),t-=e[n]*this.strides[n];return e[e.length-1]=t,e}get rank(){return this.shape.length}toTensor(){return Ls().makeTensor(this.values,this.shape,this.dtype)}},Ls=null,Wp=null,o4=null;function A1(r){Ls=r}function $1(r){Wp=r}function D1(r){o4=r}var Ft=class{constructor(t,e,n,o){this.kept=!1,this.isDisposedInternal=!1,this.shape=t.slice(),this.dtype=e||"float32",this.size=Zt(t),this.strides=ni(t),this.dataId=n,this.id=o,this.rankType=this.rank<5?this.rank.toString():"higher"}get rank(){return this.shape.length}async buffer(){let t=await this.data();return Wp.buffer(this.shape,this.dtype,t)}bufferSync(){return Wp.buffer(this.shape,this.dtype,this.dataSync())}async array(){let t=await this.data();return Fu(this.shape,t,this.dtype==="complex64")}arraySync(){return Fu(this.shape,this.dataSync(),this.dtype==="complex64")}async data(){this.throwIfDisposed();let t=Ls().read(this.dataId);if(this.dtype==="string"){let e=await t;try{return e.map(n=>Gp(n))}catch(n){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}}return t}dataToGPU(t){return this.throwIfDisposed(),Ls().readToGPU(this.dataId,t)}dataSync(){this.throwIfDisposed();let t=Ls().readSync(this.dataId);if(this.dtype==="string")try{return t.map(e=>Gp(e))}catch(e){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}return t}async bytes(){this.throwIfDisposed();let t=await Ls().read(this.dataId);return this.dtype==="string"?t:new Uint8Array(t.buffer)}dispose(){this.isDisposed||(Ls().disposeTensor(this),this.isDisposedInternal=!0)}get isDisposed(){return this.isDisposedInternal}throwIfDisposed(){if(this.isDisposed)throw new Error("Tensor is disposed.")}print(t=!1){return Wp.print(this,t)}clone(){return this.throwIfDisposed(),Wp.clone(this)}toString(t=!1){let e=this.dataSync();return E1(e,this.shape,this.dtype,t)}cast(t){return this.throwIfDisposed(),Wp.cast(this,t)}variable(t=!0,e,n){return this.throwIfDisposed(),Ls().makeVariable(this,t,e,n)}};Object.defineProperty(Ft,Symbol.hasInstance,{value:r=>!!r&&r.data!=null&&r.dataSync!=null&&r.throwIfDisposed!=null});function O(){return Wd("Tensor",()=>Ft)}O();var Ha=class extends Ft{constructor(t,e,n,o){super(t.shape,t.dtype,t.dataId,o),this.trainable=e,this.name=n}assign(t){if(t.dtype!==this.dtype)throw new Error(`dtype of the new value (${t.dtype}) and previous value (${this.dtype}) must match`);if(!An(t.shape,this.shape))throw new Error(`shape of the new value (${t.shape}) and previous value (${this.shape}) must match`);Ls().disposeTensor(this),this.dataId=t.dataId,Ls().incRef(this,null)}dispose(){Ls().disposeVariable(this),this.isDisposedInternal=!0}};Object.defineProperty(Ha,Symbol.hasInstance,{value:r=>r instanceof Ft&&r.assign!=null&&r.assign instanceof Function});var fo={};Gt(fo,{assertTypesMatch:()=>xS,getTensorsInContainer:()=>Qd,isTensorInList:()=>i4,makeTypesMatch:()=>Wt});var mS;(function(r){r.R0="R0",r.R1="R1",r.R2="R2",r.R3="R3",r.R4="R4",r.R5="R5",r.R6="R6"})(mS||(mS={}));var fS;(function(r){r.float32="float32",r.int32="int32",r.bool="int32",r.complex64="complex64"})(fS||(fS={}));var dS;(function(r){r.float32="float32",r.int32="int32",r.bool="bool",r.complex64="complex64"})(dS||(dS={}));var hS;(function(r){r.float32="float32",r.int32="float32",r.bool="float32",r.complex64="complex64"})(hS||(hS={}));var gS;(function(r){r.float32="complex64",r.int32="complex64",r.bool="complex64",r.complex64="complex64"})(gS||(gS={}));var s4={float32:hS,int32:fS,bool:dS,complex64:gS};function or(r,t){if(r==="string"||t==="string"){if(r==="string"&&t==="string")return"string";throw new Error(`Can not upcast ${r} with ${t}`)}return s4[r][t]}function Gu(r){return or(r,"int32")}function Wt(r,t){if(r.dtype===t.dtype)return[r,t];let e=or(r.dtype,t.dtype);return[r.cast(e),t.cast(e)]}function xS(r,t){E(r.dtype===t.dtype,()=>`The dtypes of the first(${r.dtype}) and second(${t.dtype}) input must match`)}function i4(r,t){return t.some(e=>e.id===r.id)}function Qd(r){let t=[];return R1(r,t,new Set),t}function R1(r,t,e){if(r==null)return;if(r instanceof Ft){t.push(r);return}if(!a4(r))return;let n=r;for(let o in n){let s=n[o];e.has(s)||(e.add(s),R1(s,t,e))}}function a4(r){return Array.isArray(r)||typeof r=="object"}function yS(r){return r.kernelName!=null}var zg=class{constructor(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null,get kernelNames(){return Array.from(new Set(this.kernels.map(t=>t.name)))}}}dispose(){for(let t in this.registeredVariables)this.registeredVariables[t].dispose()}},Ul=class{constructor(t){this.ENV=t,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new zg}async ready(){if(this.pendingBackendInit!=null)return this.pendingBackendInit.then(()=>{});if(this.backendInstance!=null)return;let t=this.getSortedBackends();for(let e=0;e<t.length;e++){let n=t[e];if(await this.initializeBackend(n).success){await this.setBackend(n);return}}throw new Error("Could not initialize any backends, all backend initializations failed.")}get backend(){if(this.pendingBackendInit!=null)throw new Error(`Backend '${this.backendName}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);if(this.backendInstance==null){let{name:t,asyncInit:e}=this.initializeBackendsAndReturnBest();if(e)throw new Error(`The highest priority backend '${t}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);this.setBackend(t)}return this.backendInstance}backendNames(){return Object.keys(this.registryFactory)}findBackend(t){if(!(t in this.registry))if(t in this.registryFactory){let{asyncInit:e}=this.initializeBackend(t);if(e)return null}else return null;return this.registry[t]}findBackendFactory(t){return t in this.registryFactory?this.registryFactory[t].factory:null}registerBackend(t,e,n=1){return t in this.registryFactory?(Ii(`${t} backend was already registered. Reusing existing backend factory.`),!1):(this.registryFactory[t]={factory:e,priority:n},!0)}async setBackend(t){if(this.registryFactory[t]==null)throw new Error(`Backend name '${t}' not found in registry`);if(this.backendName=t,this.registry[t]==null){this.backendInstance=null;let{success:e,asyncInit:n}=this.initializeBackend(t);if(!(n?await e:e))return!1}return this.backendInstance=this.registry[t],this.setupRegisteredKernels(),this.profiler=new Lg(this.backendInstance),!0}setupRegisteredKernels(){Fg(this.backendName).forEach(e=>{e.setupFunc!=null&&e.setupFunc(this.backendInstance)})}disposeRegisteredKernels(t){Fg(t).forEach(n=>{n.disposeFunc!=null&&n.disposeFunc(this.registry[t])})}initializeBackend(t){let e=this.registryFactory[t];if(e==null)throw new Error(`Cannot initialize backend ${t}, no registration found.`);try{let n=e.factory();if(n&&!(n instanceof Mo)&&typeof n.then=="function"){let o=++this.pendingBackendInitId,s=n.then(i=>o<this.pendingBackendInitId?!1:(this.registry[t]=i,this.pendingBackendInit=null,!0)).catch(i=>(o<this.pendingBackendInitId||(this.pendingBackendInit=null,Ii(`Initialization of backend ${t} failed`),Ii(i.stack||i.message)),!1));return this.pendingBackendInit=s,{success:s,asyncInit:!0}}else return this.registry[t]=n,{success:!0,asyncInit:!1}}catch(n){return Ii(`Initialization of backend ${t} failed`),Ii(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(t){if(!(t in this.registryFactory))throw new Error(`${t} backend not found in registry`);this.backendName===t&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,t in this.registry&&(this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t]),delete this.registryFactory[t],this.backendName===t&&(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((t,e)=>this.registryFactory[e].priority-this.registryFactory[t].priority)}initializeBackendsAndReturnBest(){let t=this.getSortedBackends();for(let e=0;e<t.length;e++){let n=t[e],{success:o,asyncInit:s}=this.initializeBackend(n);if(s||o)return{name:n,asyncInit:s}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(t,e){let n=this.state.tensorInfo.get(e),o=n.backend,s=this.readSync(e),i=o.refCount(e);o.disposeData(e,!0),n.backend=t,t.move(e,s,n.shape,n.dtype,i),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(t,e){let n=null;if(e==null){if(typeof t!="function")throw new Error("Please provide a function to tidy()");e=t}else{if(typeof t!="string"&&!(t instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof e!="function")throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");n=t}let o;return this.scopedRun(()=>this.startScope(n),()=>this.endScope(o),()=>(o=e(),o instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),o))}scopedRun(t,e,n){t();try{let o=n();return e(),o}catch(o){throw e(),o}}nextTensorId(){return Ul.nextTensorId++}nextVariableId(){return Ul.nextVariableId++}clone(t){let e=T.runKernel(lo,{x:t}),n={x:t},o=i=>({x:()=>{let a="float32",u={x:i},l={dtype:a};return T.runKernel(io,u,l)}}),s=[];return this.addTapeNode(this.state.activeScope.name,n,[e],o,s,{}),e}runKernel(t,e,n){if(this.backendName==null&&this.backend,!(jd(t,this.backendName)!=null))throw new Error(`Kernel '${t}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:t,inputs:e,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(t,e,n){let o=this.backend.numDataIds(),s=0;n.forEach(u=>{s+=u.dtype==="complex64"?3:1});let i=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],a=o-e-s-i;if(a>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${a} data ids) after running '${t}'`)}runKernelFunc(t){let e,n=[],o=this.isTapeOn(),s=this.state.numBytes,i=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let a;this.backendName==null&&this.backend;let u,l=yS(t)?t.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(yS(t)){let{kernelName:d,inputs:h,attrs:g}=t;this.backendName==null&&this.backend;let x=jd(d,this.backendName);E(x!=null,()=>`Cannot find registered kernel '${d}' for backend '${this.backendName}'`),a=()=>{let b=this.backend.numDataIds();u=x.kernelFunc({inputs:h,attrs:g,backend:this.backend});let w=Array.isArray(u)?u:[u];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(d,b,w);let C=w.map(N=>N.rank!=null?N:this.makeTensorFromTensorInfo(N));if(o){let N=this.getTensorsForGradient(d,h,C);n=this.saveTensorsForBackwardMode(N)}return C}}else{let{forwardFunc:d}=t,h=g=>{!o||(n=g.map(x=>this.keep(this.clone(x))))};a=()=>{let g=this.backend.numDataIds();u=this.tidy(()=>d(this.backend,h));let x=Array.isArray(u)?u:[u];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,g,x),x}}let{inputs:c,attrs:p}=t,m=yS(t)?null:t.backwardsFunc,f;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?e=a():(f=this.profiler.profileKernel(l,c,()=>a()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(f),e=f.outputs)}),o&&this.addTapeNode(l,c,e,m,n,p),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-s,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-i,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(c).map(d=>c[d]!=null?c[d].shape:null),outputShapes:e.map(d=>d.shape),kernelTimeMs:f.timeMs,extraInfo:f.extraInfo}),Array.isArray(u)?e:e[0]}saveTensorsForBackwardMode(t){return t.map(n=>this.keep(this.clone(n)))}getTensorsForGradient(t,e,n){let o=oS(t);if(o!=null){let s=o.inputsToSave||[],i=o.outputsToSave||[],a;o.saveAllInputs?(E(Array.isArray(e),()=>"saveAllInputs is true, expected inputs to be an array."),a=Object.keys(e).map(l=>e[l])):a=s.map(l=>e[l]);let u=n.filter((l,c)=>i[c]);return a.concat(u)}return[]}makeTensor(t,e,n,o){if(t==null)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",o=o||this.backend;let s=t;n==="string"&&Bo(t[0])&&(s=t.map(u=>Wl(u)));let i=o.write(s,e,n),a=new Ft(e,n,i,this.nextTensorId());if(this.trackTensor(a,o),n==="string"){let u=this.state.tensorInfo.get(i),l=tS(s);this.state.numBytes+=l-u.bytes,u.bytes=l}return a}makeTensorFromDataId(t,e,n,o){n=n||"float32";let s={dataId:t,shape:e,dtype:n};return this.makeTensorFromTensorInfo(s,o)}makeTensorFromTensorInfo(t,e){let{dataId:n,shape:o,dtype:s}=t,i=new Ft(o,s,n,this.nextTensorId());return this.trackTensor(i,e),i}makeVariable(t,e=!0,n,o){n=n||this.nextVariableId().toString(),o!=null&&o!==t.dtype&&(t=t.cast(o));let s=new Ha(t,e,n,this.nextTensorId());if(this.state.registeredVariables[s.name]!=null)throw new Error(`Variable with name ${s.name} was already registered`);return this.state.registeredVariables[s.name]=s,this.incRef(s,this.backend),s}trackTensor(t,e){this.state.numTensors++,t.dtype==="string"&&this.state.numStringTensors++;let n=0;t.dtype!=="complex64"&&t.dtype!=="string"&&(n=t.size*Rg(t.dtype)),this.state.numBytes+=n,this.state.tensorInfo.has(t.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(t.dataId,{backend:e||this.backend,dtype:t.dtype,shape:t.shape,bytes:n})),t instanceof Ha||this.track(t)}incRef(t,e){this.trackTensor(t,e),this.backend.incRef(t.dataId)}removeDataId(t,e){this.state.tensorInfo.has(t)&&this.state.tensorInfo.get(t).backend===e&&(this.state.tensorInfo.delete(t),this.state.numDataBuffers--)}disposeTensor(t){if(!this.state.tensorInfo.has(t.dataId))return;let e=this.state.tensorInfo.get(t.dataId);if(this.state.numTensors--,t.dtype==="string"&&(this.state.numStringTensors--,this.state.numBytes-=e.bytes),t.dtype!=="complex64"&&t.dtype!=="string"){let n=t.size*Rg(t.dtype);this.state.numBytes-=n}e.backend.disposeData(t.dataId)&&this.removeDataId(t.dataId,e.backend)}disposeVariables(){for(let t in this.state.registeredVariables){let e=this.state.registeredVariables[t];this.disposeVariable(e)}}disposeVariable(t){this.disposeTensor(t),this.state.registeredVariables[t.name]!=null&&delete this.state.registeredVariables[t.name]}memory(){let t=this.backend.memory();return t.numTensors=this.state.numTensors,t.numDataBuffers=this.state.numDataBuffers,t.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(t.unreliable=!0,t.reasons==null&&(t.reasons=[]),t.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),t}async profile(t){this.state.profiling=!0;let e=this.state.numBytes,n=this.state.numTensors;this.state.activeProfile.kernels=[],this.state.activeProfile.result=await t(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max(...this.state.activeProfile.kernels.map(o=>o.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-e,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let o of this.state.activeProfile.kernels)o.kernelTimeMs=await o.kernelTimeMs,o.extraInfo=await o.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(t,e,n,o,s,i){let a={id:this.state.nextTapeNodeId++,kernelName:t,inputs:e,outputs:n,saved:s},u=oS(t);u!=null&&(o=u.gradFunc),o!=null&&(a.gradient=l=>(l=l.map((c,p)=>{if(c==null){let m=n[p],f=ip(m.size,m.dtype);return this.makeTensor(f,m.shape,m.dtype)}return c}),o(l.length>1?l:l[0],s,i))),this.state.activeTape.push(a)}keep(t){return t.kept=!0,t}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(t){let e={track:[],name:"unnamed scope",id:this.state.nextScopeId++};t&&(e.name=t),this.state.scopeStack.push(e),this.state.activeScope=e}endScope(t){let e=Qd(t),n=new Set(e.map(s=>s.id));for(let s=0;s<this.state.activeScope.track.length;s++){let i=this.state.activeScope.track[s];!i.kept&&!n.has(i.id)&&i.dispose()}let o=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],e.forEach(s=>{!s.kept&&s.scopeId===o.id&&this.track(s)})}gradients(t,e,n,o=!1){if(E(e.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let s=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",t));E(s instanceof Ft,()=>"The result y returned by f() must be a tensor.");let i=N1(this.state.activeTape,e,s);if(!o&&i.length===0&&e.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. 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Ie(r,t,e){if(e!=null){if(typeof t=="string")throw Error(`Error in ${r}: pad must be an integer when using dimRoundingMode ${e} but got pad ${t}.`);if(typeof t=="number")E(ea(t),()=>`Error in ${r}: pad must be an integer when using dimRoundingMode ${e} but got pad ${t}.`);else if(typeof t=="object")t.forEach(n=>{n.forEach(o=>{E(ea(o),()=>`Error in ${r}: pad must be an integer when using dimRoundingMode ${e} but got pad ${o}.`)})});else throw Error(`Error in ${r}: Unknown padding parameter: ${t}`)}}function VH(r,t){let n={x:I(r,"x","reshape","string_or_numeric")},o={shape:t};return T.runKernel(mi,n,o)}var D=k({reshape_:VH});function GH(r,t,e,n,o){let s=I(r,"x","avgPool","float32"),i=1;E(_r(e,i),()=>`Error in avgPool: Either strides or dilations must be 1. 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OE=k({basicLSTMCell_:jH});function XH(r,t,e){let n=I(r,"x","batchToSpaceND"),o=t.reduce((a,u)=>a*u);E(n.rank>=1+t.length,()=>`input rank is ${n.rank} but should be > than blockShape.length ${t.length}`),E(e.length===t.length,()=>`crops.length is ${e.length} but should be equal to blockShape.length  ${t.length}`),E(n.shape[0]%o===0,()=>`input tensor batch is ${n.shape[0]} but is not divisible by the product of the elements of blockShape ${t.join(" * ")} === ${o}`);let s={x:n},i={blockShape:t,crops:e};return T.runKernel(si,s,i)}var Xl=k({batchToSpaceND_:XH});function PE(r){let t;return r.rank===0||r.rank===1?t=D(r,[1,1,1,r.size]):r.rank===2?t=D(r,[1,1,r.shape[0],r.shape[1]]):r.rank===3?t=D(r,[1,r.shape[0],r.shape[1],r.shape[2]]):t=r,t}function YH(r,t,e,n,o,s){s==null&&(s=.001);let i=I(r,"x","batchNorm"),a=I(t,"mean","batchNorm"),u=I(e,"variance","batchNorm"),l;o!=null&&(l=I(o,"scale","batchNorm"));let c;n!=null&&(c=I(n,"offset","batchNorm")),E(a.rank===u.rank,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),E(c==null||a.rank===c.rank,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),E(l==null||a.rank===l.rank,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let m={x:PE(i),scale:l,offset:c,mean:a,variance:u},f={varianceEpsilon:s},d=T.runKernel(ns,m,f);return D(d,i.shape)}var Ai=k({batchNorm_:YH});function ZH(r,t,e,n,o,s){let i=I(r,"x","batchNorm"),a=I(t,"mean","batchNorm"),u=I(e,"variance","batchNorm"),l;o!=null&&(l=I(o,"scale","batchNorm"));let c;return n!=null&&(c=I(n,"offset","batchNorm")),E(i.rank===2,()=>`Error in batchNorm2D: x must be rank 2 but got rank ${i.rank}.`),E(a.rank===2||a.rank===1,()=>`Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank ${a.rank}.`),E(u.rank===2||u.rank===1,()=>`Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank ${u.rank}.`),l!=null&&E(l.rank===2||l.rank===1,()=>`Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank ${l.rank}.`),c!=null&&E(c.rank===2||c.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`),Ai(i,a,u,c,l,s)}var mx=k({batchNorm2d_:ZH});function JH(r,t,e,n,o,s){let i=I(r,"x","batchNorm"),a=I(t,"mean","batchNorm"),u=I(e,"variance","batchNorm"),l;o!=null&&(l=I(o,"scale","batchNorm"));let c;return n!=null&&(c=I(n,"offset","batchNorm")),E(i.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${i.rank}.`),E(a.rank===3||a.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${a.rank}.`),E(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${u.rank}.`),l!=null&&E(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${l.rank}.`),c!=null&&E(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`),Ai(i,a,u,c,l,s)}var fx=k({batchNorm3d_:JH});function QH(r,t,e,n,o,s){let i=I(r,"x","batchNorm"),a=I(t,"mean","batchNorm"),u=I(e,"variance","batchNorm"),l;o!=null&&(l=I(o,"scale","batchNorm"));let c;return n!=null&&(c=I(n,"offset","batchNorm")),E(i.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${i.rank}.`),E(a.rank===4||a.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${a.rank}.`),E(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${u.rank}.`),l!=null&&E(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${l.rank}.`),c!=null&&E(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`),Ai(i,a,u,c,l,s)}var dx=k({batchNorm4d_:QH});function tq(r,t,e){let n=I(r,"x","bincount"),o=I(t,"weights","bincount");E(n.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${n.dtype}`),E(e>=0,()=>`size must be non-negative, but got ${e}.`),E(o.size===n.size||o.size===0,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${n.shape}, weights shape: ${o.shape}.`);let s={x:n,weights:o},i={size:e};return T.runKernel(up,s,i)}var hx=k({bincount_:tq});function eq(r,t){let e=I(r,"s0","broadcastArgs","int32"),n=I(t,"s1","broadcastArgs","int32");if(e.rank!==1)throw new Error(`broadcastArgs(): first input must be a vector (rank=1). Has rank ${e.rank}`);if(n.rank!==1)throw new Error(`broadcastArgs(): second input must be a vector (rank=1). Has rank ${n.rank}`);let o={s0:e,s1:n};return T.runKernel(cp,o)}var LE=k({broadcastArgs_:eq});function rq(r,t){let e=I(r,"broadcastTo","x"),n=e.shape;if(t.some(l=>!(l>0)||l%1!==0))throw new Error(`broadcastTo(): Invalid broadcast shape [${t}].`);if(t.length<e.rank)throw new Error(`broadcastTo(): shape.length=${t.length} < input.rank=${e.rank}.`);if(t.length>e.rank){let l=e.shape.slice();for(;l.length<t.length;)l.unshift(1);e=D(e,l)}let o=e.shape,s=Array.from(t);for(let l=t.length-1;l>=0;l--)if(o[l]===t[l])s[l]=1;else if(e.shape[l]!==1)throw new Error(`broadcastTo(): [${n}] cannot be broadcast to [${t}].`);if(s.map((l,c)=>l>1?c:-1).filter(l=>l>=0).length===0)return sn(e);let a={x:e},u={reps:s};return T.runKernel(Zn,a,u)}var $i=k({broadcastTo_:rq});function nq(r){let e={x:I(r,"x","ceil","float32")};return T.runKernel(Ho,e)}var gx=k({ceil_:nq});function go(r,t,e){let n={shape:r,value:t,dtype:e};return T.runKernel(Al,{},n)}function oq(r,t,e){let n=I(r,"x","clipByValue");if(E(t<=e,()=>`Error in clip: min (${t}) must be less than or equal to max (${e}).`),t===e)return go(n.shape,t,n.dtype);let o={x:n},s={clipValueMin:t,clipValueMax:e};return T.runKernel(ao,o,s)}var Cr=k({clipByValue_:oq});function sq(r){return ne(r,0)}var xx=k({concat1d_:sq});function iq(r,t){return ne(r,t)}var yx=k({concat2d_:iq});function aq(r,t){return ne(r,t)}var bx=k({concat3d_:aq});function lq(r,t){return ne(r,t)}var wx=k({concat4d_:lq});function uq(r,t,e,n,o="NHWC",s=[1,1],i){let a=I(r,"x","conv2d","float32"),u=I(t,"filter","conv2d","float32"),l=a,c=!1;a.rank===3&&(c=!0,l=D(a,[1,a.shape[0],a.shape[1],a.shape[2]])),E(l.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${l.rank}.`),E(u.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${u.rank}.`),Ie("conv2d",n,i);let p=o==="NHWC"?l.shape[3]:l.shape[1];E(p===u.shape[2],()=>`Error in conv2d: depth of input (${p}) must match input depth for filter ${u.shape[2]}.`),E(_r(e,s),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${e} and dilations '${s}'`);let m={x:l,filter:u},f={strides:e,pad:n,dataFormat:o,dilations:s,dimRoundingMode:i},d=T.runKernel(qo,m,f);return c?D(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var Cn=k({conv2d_:uq});function cq(r,t,e,n,o="NWC",s=1,i){let a=I(r,"x","conv1d"),u=I(t,"filter","conv1d"),l=a,c=!1;a.rank===2&&(c=!0,l=D(a,[1,a.shape[0],a.shape[1]])),E(l.rank===3,()=>`Error in conv1d: input must be rank 3, but got rank ${l.rank}.`),E(u.rank===3,()=>`Error in conv1d: filter must be rank 3, but got rank ${u.rank}.`),Ie("conv1d",n,i),E(l.shape[2]===u.shape[1],()=>`Error in conv1d: depth of input (${l.shape[2]}) must match input depth for filter ${u.shape[1]}.`),E(_r(e,s),()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${e} and dilation '${s}'`),E(o==="NWC",()=>`Error in conv1d: got dataFormat of ${o} but only NWC is currently supported.`);let p=D(u,[1,u.shape[0],u.shape[1],u.shape[2]]),m=D(l,[l.shape[0],1,l.shape[1],l.shape[2]]),g=Cn(m,p,[1,e],n,"NHWC",[1,s],i);return c?D(g,[g.shape[2],g.shape[3]]):D(g,[g.shape[0],g.shape[2],g.shape[3]])}var Jp=k({conv1d_:cq});function pq(r,t,e,n,o,s="NHWC",i){E(r.length===t.rank,()=>`Length of inShape (${r.length}) and rank of dy (${t.rank}) must match`);let a=r,u=t,l=!1;t.rank===3&&(l=!0,u=D(t,[1,t.shape[0],t.shape[1],t.shape[2]]),a=[1,r[0],r[1],r[2]]),E(a.length===4,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${a.length}.`),E(u.rank===4,()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${u.rank}`),E(e.rank===4,()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${e.rank}`);let c=s==="NHWC"?a[3]:a[1],p=s==="NHWC"?u.shape[3]:u.shape[1];E(c===e.shape[2],()=>`Error in conv2dDerInput: depth of input (${c}) must match input depth for filter ${e.shape[2]}.`),E(p===e.shape[3],()=>`Error in conv2dDerInput: depth of output (${p}) must match output depth for filter ${e.shape[3]}.`),Ie("conv2dDerInput",o,i);let m={dy:u,filter:e},f={strides:n,pad:o,dataFormat:s,dimRoundingMode:i,inputShape:a},d=T.runKernel(Ko,m,f);return l?D(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var Qp=k({conv2DBackpropInput_:pq});function mq(r,t,e,n,o,s){let i=I(r,"x","conv2dTranspose"),a=I(t,"filter","conv2dTranspose");return Qp(e,i,a,n,o,"NHWC",s)}var tm=k({conv2dTranspose_:mq});function fq(r,t,e,n,o="NDHWC",s=[1,1,1]){let i=I(r,"x","conv3d"),a=I(t,"filter","conv3d"),u=i,l=!1;i.rank===4&&(l=!0,u=D(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),E(u.rank===5,()=>`Error in conv3d: input must be rank 5, but got rank ${u.rank}.`),E(a.rank===5,()=>`Error in conv3d: filter must be rank 5, but got rank ${a.rank}.`),E(u.shape[4]===a.shape[3],()=>`Error in conv3d: depth of input (${u.shape[4]}) must match input depth for filter ${a.shape[3]}.`),E(_r(e,s),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${e} and dilations '${s}'`),E(o==="NDHWC",()=>`Error in conv3d: got dataFormat of ${o} but only NDHWC is currently supported.`);let c={x:u,filter:a},p={strides:e,pad:n,dataFormat:o,dilations:s},m=T.runKernel(El,c,p);return l?D(m,[m.shape[1],m.shape[2],m.shape[3],m.shape[4]]):m}var Cx=k({conv3d_:fq});function dq(r,t,e,n,o){E(r.length===t.rank,()=>`Length of inShape (${r.length}) and rank of dy (${t.rank}) must match`);let s=r,i=t,a=!1;t.rank===4&&(a=!0,i=D(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),s=[1,r[0],r[1],r[2],r[3]]);let u=s[4],l=i.shape[4];E(s.length===5,()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${s.length}.`),E(i.rank===5,()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${i.rank}`),E(e.rank===5,()=>`Error in conv3dDerInput: filter must be rank 5, but got rank ${e.rank}`),E(u===e.shape[3],()=>`Error in conv3dDerInput: depth of input (${u}) must match input depth for filter ${e.shape[3]}.`),E(l===e.shape[4],()=>`Error in conv3dDerInput: depth of output (${l}) must match output depth for filter ${e.shape[4]}.`);let c={dy:i,filter:e},p={pad:o,strides:n,inputShape:s},m=T.runKernel(dp,c,p);return a?D(m,[m.shape[1],m.shape[2],m.shape[3],m.shape[4]]):m}var Ix=k({conv3DBackpropInput_:dq});function hq(r,t,e,n,o){let s=I(r,"x","conv3dTranspose"),i=I(t,"filter","conv3dTranspose");return Ix(e,s,i,n,o)}var vx=k({conv3dTranspose_:hq});function gq(r){let e={x:I(r,"x","cos","float32")};return T.runKernel(jo,e)}var Yl=k({cos_:gq});function xq(r){let e={x:I(r,"x","cosh","float32")};return T.runKernel(Xo,e)}var em=k({cosh_:xq});function yq(r,t=0,e=!1,n=!1){let s={x:I(r,"x","cumprod")},i={axis:t,exclusive:e,reverse:n};return T.runKernel(pa,s,i)}var ju=k({cumprod_:yq});function bq(r,t=0,e=!1,n=!1){let s={x:I(r,"x","cumsum")},i={axis:t,exclusive:e,reverse:n};return T.runKernel(Yo,s,i)}var rm=k({cumsum_:bq});function wq(r,t,e,n=!1){let o=I(r,"x","denseBincount"),s=I(t,"weights","denseBincount");E(o.dtype==="int32",()=>`Error in denseBincount: input dtype must be int32, but got ${o.dtype}`),E(o.rank<=2,()=>`Error in denseBincount: input must be at most rank 2, but got rank ${o.rank}.`),E(e>=0,()=>`size must be non-negative, but got ${e}.`),E(s.size===o.size||s.size===0,()=>`Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${o.shape}, weights shape: ${s.shape}.`);let i={x:o,weights:s},a={size:e,binaryOutput:n};return T.runKernel(hp,i,a)}var ME=k({denseBincount_:wq});function Cq(r,t,e="NHWC"){let n=I(r,"x","depthToSpace","float32"),o=e==="NHWC"?n.shape[1]:n.shape[2],s=e==="NHWC"?n.shape[2]:n.shape[3],i=e==="NHWC"?n.shape[3]:n.shape[1];E(t>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${t}`),E(o*t>=0,()=>`Negative dimension size caused by overflow when multiplying
    ${o} and ${t}  for depthToSpace with input shape
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g=X(R(pt(d,X(ve(h),this.epsilon)),-this.learningRate),a);a.assign(g)}),this.accBeta1.assign(R(this.accBeta1,this.beta1)),this.accBeta2.assign(R(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&St(this.accumulatedFirstMoment.map(t=>t.variable)),this.accumulatedSecondMoment!=null&&St(this.accumulatedSecondMoment.map(t=>t.variable))}async getWeights(){let t=[...this.accumulatedFirstMoment,...this.accumulatedSecondMoment];return[await this.saveIterations()].concat(t.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(t){t=await this.extractIterations(t),B(()=>{this.accBeta1.assign(an(this.beta1,this.iterations_+1)),this.accBeta2.assign(an(this.beta2,this.iterations_+1))});let 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Error("getWeights() is not implemented for Adamax yet.")}async setWeights(t){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(t,e){return new t(e.learningRate,e.beta1,e.beta2,e.epsilon,e.decay)}};mu.className="Adamax";wn(mu);var Mi=class extends Gr{constructor(t){super(),this.learningRate=t,this.setLearningRate(t)}applyGradients(t){(Array.isArray(t)?t.map(n=>n.name):Object.keys(t)).forEach((n,o)=>{let s=Array.isArray(t)?t[o].tensor:t[n];if(s==null)return;let i=T.registeredVariables[n];B(()=>{let a=X(R(this.c,s),i);i.assign(a)})}),this.incrementIterations()}setLearningRate(t){this.learningRate=t,this.c!=null&&this.c.dispose(),this.c=De(mt(-t))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(t){if(t=await this.extractIterations(t),t.length!==0)throw new Error("SGD optimizer does 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e=[],n,o=t.slice(0,this.inputs.length),s=t.slice(this.inputs.length,this.inputs.length+this.outputs.length),i=[];for(let l=0;l<this.inputs.length;++l)i.push({key:this.inputs[l],value:o[l]});let a=new ko(i),u=hc(this.outputs,a);for(let l=0;l<this.lossFunctions.length;++l){let c=this.lossFunctions[l],p=Se(c(s[l],u[l]));l===0?n=p:n=X(n,p),e.push(n)}for(let l=0;l<this.metricsTensors.length;++l){let c=this.metricsTensors[l][0],p=this.metricsTensors[l][1],m=Se(c(s[p],u[p]));e.push(m)}return e})}async fit(t,e,n={}){return sD(this,t,e,n)}async fitDataset(t,e){return nD(this,t,e)}async trainOnBatch(t,e){let n=await this.standardizeUserData(t,e),o=n[0],s=n[1],a=this.makeTrainFunction()(o.concat(s)),u=[];for(let l of a){let c=await l.data();u.push(c[0])}return St(a),To(n[0],t),To(n[1],e),Sr(u)}getNamedWeights(t){let e=[],n=t!=null&&t.trainableOnly,o=n?this.trainableWeights:this.weights,s=this.getWeights(n);for(let i=0;i<o.length;++i)n&&!o[i].trainable||e.push({name:o[i].originalName,tensor:s[i]});return e}set stopTraining(t){this.stopTraining_=t}get stopTraining(){return this.stopTraining_}get optimizer(){return this.optimizer_}set optimizer(t){this.optimizer_!==t&&(this.optimizer_=t,this.isOptimizerOwned=!1)}dispose(){let t=super.dispose();if(t.refCountAfterDispose===0&&this.optimizer!=null&&this.isOptimizerOwned){let e=nh().numTensors;this.optimizer_.dispose(),t.numDisposedVariables+=e-nh().numTensors}return t}getLossIdentifiers(){let t;if(typeof this.loss=="string")t=Io(this.loss);else if(Array.isArray(this.loss)){for(let e of this.loss)if(typeof e!="string")throw new Error("Serialization of non-string loss is not supported.");t=this.loss.map(e=>Io(e))}else{let e=Object.keys(this.loss);t={};let n=this.loss;for(let o of e)if(typeof n[o]=="string")t[o]=Io(n[o]);else throw new Error("Serialization of non-string loss is not supported.")}return t}getMetricIdentifiers(){if(typeof this.metrics=="string"||typeof this.metrics=="function")return[Io(Sh(this.metrics))];if(Array.isArray(this.metrics))return this.metrics.map(t=>Io(Sh(t)));{let t={};for(let e in this.metrics)t[e]=Io(Sh(this.metrics[e]));return t}}getTrainingConfig(){return{loss:this.getLossIdentifiers(),metrics:this.getMetricIdentifiers(),optimizer_config:{class_name:this.optimizer.getClassName(),config:this.optimizer.getConfig()}}}loadTrainingConfig(t){if(t.weighted_metrics!=null)throw new Error("Loading weight_metrics is not supported yet.");if(t.loss_weights!=null)throw new Error("Loading loss_weights is not supported yet.");if(t.sample_weight_mode!=null)throw new Error("Loading sample_weight_mode is not supported yet.");let e=yc(t.optimizer_config),n=hn(e),o;if(typeof t.loss=="string")o=Ja(t.loss);else if(Array.isArray(t.loss))o=t.loss.map(i=>Ja(i));else if(t.loss!=null){o={};for(let i in t.loss)o[i]=Ja(t.loss[i])}let s;if(Array.isArray(t.metrics))s=t.metrics.map(i=>Ja(i));else if(t.metrics!=null){s={};for(let i in t.metrics)s[i]=Ja(t.metrics[i])}this.compile({loss:o,metrics:s,optimizer:n})}async save(t,e){if(typeof t=="string"){let l=Er.getSaveHandlers(t);if(l.length===0)throw new z(`Cannot find any save handlers for URL '${t}'`);if(l.length>1)throw new z(`Found more than one (${l.length}) save handlers for URL '${t}'`);t=l[0]}if(t.save==null)throw new z("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await Er.encodeWeights(this.getNamedWeights(e)),o=!1,s=null,a={modelTopology:this.toJSON(s,o),format:A8,generatedBy:`TensorFlow.js tfjs-layers v${Wm}`,convertedBy:null};if((e==null?!1:e.includeOptimizer)&&this.optimizer!=null){a.trainingConfig=this.getTrainingConfig();let l="optimizer",{data:c,specs:p}=await Er.encodeWeights(await this.optimizer.getWeights(),l);n.specs.push(...p),n.data=Er.concatenateArrayBuffers([n.data,c])}return this.userDefinedMetadata!=null&&(E0(this.userDefinedMetadata,this.name,!0),a.userDefinedMetadata=this.userDefinedMetadata),a.weightData=n.data,a.weightSpecs=n.specs,t.save(a)}setUserDefinedMetadata(t){E0(t,this.name),this.userDefinedMetadata=t}getUserDefinedMetadata(){return this.userDefinedMetadata}};Mn.className="Model";Q.registerClass(Mn);var Ky=class extends Mn{};Ky.className="Functional";Q.registerClass(Ky);async function uD(r,t){"modelTopology"in r||(r={modelTopology:r}),r=r;let e=r.modelTopology;e.model_config!=null&&(e=e.model_config);let n=yc(e),o=hn(n,t);if(r.weightsManifest!=null){let s=await Er.loadWeights(r.weightsManifest,r.pathPrefix,o.weights.map(a=>a.originalName)),i={};for(let a of o.weights)i[a.originalName]=s[a.originalName];o.loadWeights(i),St(s)}return o}async function cD(r,t){if(t==null&&(t={}),typeof r=="string"){let e=Er.getLoadHandlers(r,t);if(e.length===0)e.push(Er.browserHTTPRequest(r,t));else if(e.length>1)throw new z(`Found more than one (${e.length}) load 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compiled before being used.");return this.model.evaluate(t,e,n)}async evaluateDataset(t,e){if(!this.built)throw new Ur("The model needs to be compiled before being used.");return this.model.evaluateDataset(t,e)}predict(t,e={}){return this.model==null&&this.build(),this.model.predict(t,e)}predictOnBatch(t){return this.model==null&&this.build(),this.model.predictOnBatch(t)}compile(t){this.build(),this.model.compile(t),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(t){this.model.optimizer=t}async fit(t,e,n={}){if(!this.built)throw new Ur("The model needs to be compiled before being used.");return this.model.fit(t,e,n)}async fitDataset(t,e){if(!this.built)throw new Ur("The model needs to be compiled before being used.");return this.model.fitDataset(t,e)}async trainOnBatch(t,e){return this.model.trainOnBatch(t,e)}static fromConfig(t,e,n={},o=!1){let s,i={};if(e instanceof Array){if(e[0].className==null||e[0].className==="Merge")throw new z("Legacy serialization format not supported yet.");s=e}else y.assert(e.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=e.layers,delete e.layers,i=e;let a=new t(i);if(!(a instanceof Ui))throw new vt(`Sequential.fromConfig called on non-Sequential input: ${a}`);for(let u of s){let c=hn(u,void 0,o);o&&c.setFastWeightInitDuringBuild(!0),a.add(c)}return a}set stopTraining(t){if(this.model==null)throw new z("Cannot set the stopTraining property of a sequential model before it is compiled.");this.model.stopTraining=t}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 t=[];for(let e of this.layers){let n={};n.className=e.getClassName(),n.config=e.getConfig(),t.push(n)}return{name:this.name,layers:t}}};Ui.className="Sequential";Q.registerClass(Ui);function R8(r){return new Mn(r)}function F8(r){return new Ui(r)}function O8(r,t){return t==null&&(t={}),cD(r,t)}function $0(r){return Ty(r)}function P8(r,t){dn.registerCallbackConstructor(r,t)}var Qr=class extends Q.Serializable{getConfig(){return{}}},jy=class extends Qr{apply(t,e=1){return _$(t,e)}};jy.className="elu";Q.registerClass(jy);var Xy=class extends Qr{apply(t){return cm(t)}};Xy.className="selu";Q.registerClass(Xy);var Yy=class extends Qr{apply(t){return Rr(t)}};Yy.className="relu";Q.registerClass(Yy);var Zy=class extends Qr{apply(t){return B(()=>Pi(6,Rr(t)))}};Zy.className="relu6";Q.registerClass(Zy);var Jy=class extends Qr{apply(t){return t}};Jy.className="linear";Q.registerClass(Jy);var Qy=class extends Qr{apply(t){return 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t={};return t.className="linear",t.config={},D0(t)}if(typeof r=="string"){let t={};return t.className=r,t.config={},D0(t)}else return r instanceof Qr?r:D0(r)}function R0(r){if(r!=null&&typeof r!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${r}`)}var ab=class extends Q.Serializable{},bu=class extends ab{constructor(t){super(),R0(t),this.l1=t==null||t.l1==null?.01:t.l1,this.l2=t==null||t.l2==null?.01:t.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(t){return B(()=>{let e=Ne([1]);return this.hasL1&&(e=X(e,ft(R(this.l1,Ee(t))))),this.hasL2&&(e=X(e,ft(R(this.l2,lc(t))))),D(e,[])})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(t,e){return new t({l1:e.l1,l2:e.l2})}};bu.className="L1L2";Q.registerClass(bu);function fD(r){return R0(r),new bu({l1:r!=null?r.l1:null,l2:0})}function dD(r){return R0(r),new bu({l2:r!=null?r.l2:null,l1:0})}var pD={l1l2:"L1L2"};function me(r){return Im(r)}function mD(r,t={}){return Bi(r,Q.SerializationMap.getMap().classNameMap,t,"regularizer")}function be(r){if(r==null)return null;if(typeof r=="string"){let e={className:r in pD?pD[r]:r,config:{}};return mD(e)}else return r instanceof ab?r:mD(r)}var qm=class extends Rt{constructor(t){super(t==null?{}:t),this.supportsMasking=!0,t!=null&&(this.maxValue=t.maxValue)}call(t,e){t=At(t);let n=Rr(t);return this.maxValue!=null&&(n=Cr(n,0,this.maxValue)),n}computeOutputShape(t){return t}getConfig(){let t={maxValue:this.maxValue},e=super.getConfig();return Object.assign(t,e),t}};qm.className="ReLU";Q.registerClass(qm);var Km=class extends Rt{constructor(t){super(t==null?{}:t),this.DEFAULT_ALPHA=.3,t==null&&(t={}),this.alpha=t.alpha==null?this.DEFAULT_ALPHA:t.alpha}call(t,e){let n=At(t);return Zl(n,this.alpha)}computeOutputShape(t){return t}getConfig(){let t={alpha:this.alpha},e=super.getConfig();return Object.assign(t,e),t}};Km.className="LeakyReLU";Q.registerClass(Km);var jm=class extends 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t={theta:this.theta},e=super.getConfig();return Object.assign(t,e),t}};Ym.className="ThresholdedReLU";Q.registerClass(Ym);var Zm=class extends Rt{constructor(t){super(t==null?{}:t),this.DEFAULT_AXIS=1,t==null&&(t={}),this.softmax=new Hm().apply,this.axis=t.axis==null?this.DEFAULT_AXIS:t.axis}call(t,e){let n=At(t);return this.softmax(n,this.axis)}computeOutputShape(t){return t}getConfig(){let t={axis:this.axis},e=super.getConfig();return Object.assign(t,e),t}};Zm.className="Softmax";Q.registerClass(Zm);function wu(r,t,e){if(typeof r=="number")return Co(r,t);if(r.length!==t)throw new z(`The ${e} argument must be an integer or tuple of ${t} integers. Received: ${r.length} elements.`);for(let n=0;n<t;++n){let o=r[n];if(!N$(o))throw new z(`The ${e} argument must be an integer or tuple of ${t} integers. Received: ${JSON.stringify(r)} including a non-integer number ${o}`)}return r}function Sn(r,t,e,n,o=1){if(r==null)return r;let s=t+(t-1)*(o-1),i;return e==="same"?i=r:i=r-s+1,Math.floor((i+n-1)/n)}function js(r,t,e,n){if(r==null)return null;if(n==="valid")r=r*t+Us([e-t,0]);else if(n==="same")r=r*t;else throw new z(`Unsupport padding mode: ${n}.`);return r}function Nh(r,t){return B(()=>(Re(t),t==="channelsFirst"?Ot(r,[0,2,3,1]):r))}function F0(r,t){return B(()=>(Re(t),t==="channelsFirst"?Ot(r,[0,2,3,4,1]):r))}function M8(r,t,e,n=1,o="valid",s,i=1){return B(()=>{if(s==null&&(s=pn()),Re(s),r.shape.length!==3)throw new z(`The input of a conv1dWithBias operation should be 3, but is ${r.shape.length} instead.`);if(t.shape.length!==3)throw new z(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(e!=null&&e.shape.length!==1)throw new z(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(s==="channelsFirst"&&(r=Ot(r,[0,2,1])),o==="causal")throw new vt("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let a=Jp(r,t,n,o==="same"?"same":"valid","NWC",i);return e!=null&&(a=mn(a,e)),a})}function hD(r,t,e,n=[1,1],o="valid",s,i,a=null){return B(()=>{if(s==null&&(s=pn()),Re(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(t.rank!==3&&t.rank!==4)throw new z(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${r.rank}.`);let u=Nh(r,s);if(o==="causal")throw new vt("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return u=au.conv2d({x:u,filter:t,strides:n,pad:o==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:e,activation:a}),s==="channelsFirst"&&(u=Ot(u,[0,3,1,2])),u})}function z8(r,t,e,n=[1,1,1],o="valid",s,i){return B(()=>{if(s==null&&(s=pn()),Re(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(t.rank!==4&&t.rank!==5)throw new z(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${r.rank}.`);let a=F0(r,s);if(o==="causal")throw new vt("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return a=Cx(a,t,n,o==="same"?"same":"valid","NDHWC",i),e!=null&&(a=mn(a,e)),s==="channelsFirst"&&(a=Ot(a,[0,4,1,2,3])),a})}var bc=class extends Rt{constructor(t,e){if(super(e),this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",bc.verifyArgs(e),this.rank=t,Ze(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new vt(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=wu(e.kernelSize,t,"kernelSize"),this.strides=wu(e.strides==null?1:e.strides,t,"strides"),this.padding=e.padding==null?"valid":e.padding,cn(this.padding),this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Re(this.dataFormat),this.activation=Ks(e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.biasInitializer=de(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=ze(e.biasConstraint),this.biasRegularizer=be(e.biasRegularizer),this.activityRegularizer=be(e.activityRegularizer),this.dilationRate=wu(e.dilationRate==null?1:e.dilationRate,t,"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(t){if(eo("kernelSize"in t,"required key 'kernelSize' not in config"),typeof t.kernelSize!="number"&&!gy(t.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(t.kernelSize)}.`)}getConfig(){let t={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:qs(this.activation),useBias:this.useBias,biasInitializer:ke(this.biasInitializer),biasRegularizer:me(this.biasRegularizer),activityRegularizer:me(this.activityRegularizer),biasConstraint:Me(this.biasConstraint)},e=super.getConfig();return Object.assign(t,e),t}},Cu=class extends bc{constructor(t,e){super(t,e),this.kernel=null,Cu.verifyArgs(e),this.filters=e.filters,Ze(this.filters,"filters"),this.kernelInitializer=de(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=ze(e.kernelConstraint),this.kernelRegularizer=be(e.kernelRegularizer)}build(t){t=Jt(t);let e=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[e]==null)throw new z(`The channel dimension of the input should be defined. Found ${t[e]}`);let n=t[e],o=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",o,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:{[e]:n}}],this.built=!0}call(t,e){return B(()=>{t=At(t);let n,o=this.bias==null?null:this.bias.read(),s=xy(this.activation.getClassName());if(s!=null&&this.rank===2)n=hD(t,this.kernel.read(),o,this.strides,this.padding,this.dataFormat,this.dilationRate,s);else{if(this.rank===1)n=M8(t,this.kernel.read(),o,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=hD(t,this.kernel.read(),o,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=z8(t,this.kernel.read(),o,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new vt("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(t){t=Jt(t);let e=[],n=this.dataFormat==="channelsLast"?t.slice(1,t.length-1):t.slice(2);for(let s=0;s<n.length;++s){let i=Sn(n[s],this.kernelSize[s],this.padding,this.strides[s],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[s]);e.push(i)}let o=[t[0]];return this.dataFormat==="channelsLast"?(o=o.concat(e),o.push(this.filters)):(o.push(this.filters),o=o.concat(e)),o}getConfig(){let t={filters:this.filters,kernelInitializer:ke(this.kernelInitializer),kernelRegularizer:me(this.kernelRegularizer),kernelConstraint:Me(this.kernelConstraint)},e=super.getConfig();return Object.assign(t,e),t}static verifyArgs(t){if(!("filters"in t)||typeof t.filters!="number"||t.filters<1)throw new z(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(t.filters)}`)}},ol=class extends Cu{constructor(t){super(2,t),ol.verifyArgs(t)}getConfig(){let t=super.getConfig();return delete t.rank,t}static verifyArgs(t){if(typeof t.kernelSize!="number"&&!gy(t.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(t.kernelSize)}.`)}};ol.className="Conv2D";Q.registerClass(ol);var sl=class extends Cu{constructor(t){super(3,t),sl.verifyArgs(t)}getConfig(){let t=super.getConfig();return delete t.rank,t}static verifyArgs(t){if(typeof t.kernelSize!="number"&&!(Array.isArray(t.kernelSize)&&(t.kernelSize.length===1||t.kernelSize.length===3)))throw new z(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(t.kernelSize)}.`)}};sl.className="Conv3D";Q.registerClass(sl);var Jm=class extends ol{constructor(t){if(super(t),this.inputSpec=[new ye({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new z(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(t){if(t=Jt(t),t.length!==4)throw new z("Input should have rank 4; Received input shape: "+JSON.stringify(t));let e=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[e]==null)throw new z("The channel dimension of the inputs should be defined. Found `None`.");let n=t[e],o=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",o,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new ye({ndim:4,axes:{[e]:n}})],this.built=!0}call(t,e){return B(()=>{let n=At(t);if(n.shape.length!==4)throw new z(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let o=n.shape,s=o[0],i,a;this.dataFormat==="channelsFirst"?(i=2,a=3):(i=1,a=2);let u=o[i],l=o[a],c=this.kernelSize[0],p=this.kernelSize[1],m=this.strides[0],f=this.strides[1],d=js(u,m,c,this.padding),h=js(l,f,p,this.padding),g=[s,d,h,this.filters];this.dataFormat!=="channelsLast"&&(n=Ot(n,[0,2,3,1]));let x=tm(n,this.kernel.read(),g,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(x=Ot(x,[0,3,1,2])),this.bias!=null&&(x=mn(x,this.bias.read(),this.dataFormat)),this.activation!=null&&(x=this.activation.apply(x)),x})}computeOutputShape(t){t=Jt(t);let e=t.slice(),n,o,s;this.dataFormat==="channelsFirst"?(n=1,o=2,s=3):(n=3,o=1,s=2);let i=this.kernelSize[0],a=this.kernelSize[1],u=this.strides[0],l=this.strides[1];return e[n]=this.filters,e[o]=js(e[o],u,i,this.padding),e[s]=js(e[s],l,a,this.padding),e}getConfig(){let t=super.getConfig();return delete t.dilationRate,t}};Jm.className="Conv2DTranspose";Q.registerClass(Jm);var Qm=class extends sl{constructor(t){if(super(t),this.inputSpec=[new ye({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new z(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(t){if(t=Jt(t),t.length!==5)throw new z("Input should have rank 5; Received input shape: "+JSON.stringify(t));let e=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[e]==null)throw new z("The channel dimension of the inputs should be defined. Found `None`.");let n=t[e],o=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",o,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new ye({ndim:5,axes:{[e]:n}})],this.built=!0}call(t,e){return B(()=>{let n=At(t);if(n.shape.length!==5)throw new z(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let o=n.shape,s=o[0],i,a,u;this.dataFormat==="channelsFirst"?(u=2,i=3,a=4):(u=1,i=2,a=3);let l=o[u],c=o[i],p=o[a],m=this.kernelSize[0],f=this.kernelSize[1],d=this.kernelSize[2],h=this.strides[0],g=this.strides[1],x=this.strides[2],b=js(l,h,m,this.padding),w=js(c,g,f,this.padding),C=js(p,x,d,this.padding),N=[s,b,w,C,this.filters];this.dataFormat!=="channelsLast"&&(n=Ot(n,[0,2,3,4,1]));let _=vx(n,this.kernel.read(),N,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(_=Ot(_,[0,4,1,2,3])),this.bias!==null&&(_=mn(_,this.bias.read(),this.dataFormat)),this.activation!==null&&(_=this.activation.apply(_)),_})}computeOutputShape(t){t=Jt(t);let e=t.slice(),n,o,s,i;this.dataFormat==="channelsFirst"?(n=1,o=2,s=3,i=4):(n=4,o=1,s=2,i=3);let a=this.kernelSize[0],u=this.kernelSize[1],l=this.kernelSize[2],c=this.strides[0],p=this.strides[1],m=this.strides[2];return e[n]=this.filters,e[o]=js(e[o],c,a,this.padding),e[s]=js(e[s],p,u,this.padding),e[i]=js(e[i],m,l,this.padding),e}getConfig(){let t=super.getConfig();return delete t.dilationRate,t}};Qm.className="Conv3DTranspose";Q.registerClass(Qm);var lb=class extends Cu{constructor(t,e){if(super(t,e),this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,e.filters==null)throw new z("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(e.kernelInitializer!=null||e.kernelRegularizer!=null||e.kernelConstraint!=null)throw new z("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(e.padding!=null&&e.padding!=="same"&&e.padding!=="valid")throw new z(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(e.padding)}`);this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=de(e.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=be(e.depthwiseRegularizer),this.depthwiseConstraint=ze(e.depthwiseConstraint),this.pointwiseInitializer=de(e.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=be(e.pointwiseRegularizer),this.pointwiseConstraint=ze(e.pointwiseConstraint)}build(t){if(t=Jt(t),t.length<this.rank+2)throw new z(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(t)}`);let e=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[e]==null||t[e]<0)throw new z(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(t[e])}`);let n=t[e],o=this.kernelSize.concat([n,this.depthMultiplier]),s=[];for(let a=0;a<this.rank;++a)s.push(1);s.push(n*this.depthMultiplier,this.filters);let i=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",o,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,i,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",s,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,i,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,i,this.biasConstraint):this.bias=null,this.inputSpec=[new ye({ndim:this.rank+2,axes:{[e]:n}})],this.built=!0}call(t,e){return B(()=>{t=At(t);let n;if(this.rank===1)throw new vt("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(t=Ot(t,[0,2,3,1])),n=pm(t,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=mn(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=Ot(n,[0,3,1,2])),n})}getConfig(){let t=super.getConfig();return delete t.rank,delete t.kernelInitializer,delete t.kernelRegularizer,delete t.kernelConstraint,t.depthwiseInitializer=ke(this.depthwiseInitializer),t.pointwiseInitializer=ke(this.pointwiseInitializer),t.depthwiseRegularizer=me(this.depthwiseRegularizer),t.pointwiseRegularizer=me(this.pointwiseRegularizer),t.depthwiseConstraint=Me(this.depthwiseConstraint),t.pointwiseConstraint=Me(this.pointwiseConstraint),t}};lb.className="SeparableConv";var tf=class extends lb{constructor(t){super(2,t)}};tf.className="SeparableConv2D";Q.registerClass(tf);var Iu=class extends Cu{constructor(t){super(1,t),Iu.verifyArgs(t),this.inputSpec=[{ndim:3}]}getConfig(){let t=super.getConfig();return delete t.rank,delete t.dataFormat,t}static verifyArgs(t){if(typeof t.kernelSize!="number"&&!gy(t.kernelSize,"number",1,1))throw new z(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(t.kernelSize)}.`)}};Iu.className="Conv1D";Q.registerClass(Iu);var ef=class extends Rt{constructor(t){super(t),typeof t.cropping=="number"?this.cropping=[[t.cropping,t.cropping],[t.cropping,t.cropping]]:typeof t.cropping[0]=="number"?this.cropping=[[t.cropping[0],t.cropping[0]],[t.cropping[1],t.cropping[1]]]:this.cropping=t.cropping,this.dataFormat=t.dataFormat===void 0?"channelsLast":t.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(t){return this.dataFormat==="channelsFirst"?[t[0],t[1],t[2]-this.cropping[0][0]-this.cropping[0][1],t[3]-this.cropping[1][0]-this.cropping[1][1]]:[t[0],t[1]-this.cropping[0][0]-this.cropping[0][1],t[2]-this.cropping[1][0]-this.cropping[1][1],t[3]]}call(t,e){return B(()=>{if(t=At(t),this.dataFormat==="channelsLast"){let n=hh(t,this.cropping[0][0],t.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return hh(n,this.cropping[1][0],t.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=hh(t,this.cropping[0][0],t.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return hh(n,this.cropping[1][0],t.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let t={cropping:this.cropping,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}};ef.className="Cropping2D";Q.registerClass(ef);var rf=class extends Rt{constructor(t){super(t),this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=t.size==null?this.DEFAULT_SIZE:t.size,this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Re(this.dataFormat),this.interpolation=t.interpolation==null?"nearest":t.interpolation,v$(this.interpolation)}computeOutputShape(t){if(this.dataFormat==="channelsFirst"){let e=t[2]==null?null:this.size[0]*t[2],n=t[3]==null?null:this.size[1]*t[3];return[t[0],t[1],e,n]}else{let e=t[1]==null?null:this.size[0]*t[1],n=t[2]==null?null:this.size[1]*t[2];return[t[0],e,n,t[3]]}}call(t,e){return B(()=>{let n=At(t),o=n.shape;if(this.dataFormat==="channelsFirst"){n=Ot(n,[0,2,3,1]);let s=this.size[0]*o[2],i=this.size[1]*o[3],a=this.interpolation==="nearest"?lu.resizeNearestNeighbor(n,[s,i]):lu.resizeBilinear(n,[s,i]);return Ot(a,[0,3,1,2])}else{let s=this.size[0]*o[1],i=this.size[1]*o[2];return this.interpolation==="nearest"?lu.resizeNearestNeighbor(n,[s,i]):lu.resizeBilinear(n,[s,i])}})}getConfig(){let t={size:this.size,dataFormat:this.dataFormat,interpolation:this.interpolation},e=super.getConfig();return Object.assign(t,e),t}};rf.className="UpSampling2D";Q.registerClass(rf);function B8(r,t,e=[1,1],n="valid",o,s){return B(()=>{o==null&&(o=pn()),Re(o);let i=Nh(r,o);if(r.rank!==4)throw new z(`Input for depthwiseConv2d is required to be 4-D, but is instead ${r.rank}-D`);if(t.rank!==4)throw new z(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=Di(i,t,e,n==="same"?"same":"valid","NHWC",s),o==="channelsFirst"&&(i=Ot(i,[0,3,1,2])),i})}var nf=class extends bc{constructor(t){super(2,t),this.depthwiseKernel=null,this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=de(t.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=ze(t.depthwiseConstraint),this.depthwiseRegularizer=be(t.depthwiseRegularizer)}build(t){if(t=Jt(t),t.length<4)throw new z(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(t)}.`);let e=this.dataFormat==="channelsFirst"?1:3;if(t[e]==null||t[e]<0)throw new z(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${t[e]}).`);let n=t[e],o=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",o,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(t,e){return B(()=>{t=At(t);let n=B8(t,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=mn(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(t){t=Jt(t);let e=this.dataFormat==="channelsFirst"?t[2]:t[1],n=this.dataFormat==="channelsFirst"?t[3]:t[2],o=this.dataFormat==="channelsFirst"?t[1]*this.depthMultiplier:t[3]*this.depthMultiplier,s=Sn(e,this.kernelSize[0],this.padding,this.strides[0]),i=Sn(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[t[0],o,s,i]:[t[0],s,i,o]}getConfig(){let t=super.getConfig();return t.depthMultiplier=this.depthMultiplier,t.depthwiseInitializer=ke(this.depthwiseInitializer),t.depthwiseRegularizer=me(this.depthwiseRegularizer),t.depthwiseConstraint=Me(this.depthwiseRegularizer),t}};nf.className="DepthwiseConv2D";Q.registerClass(nf);function O0(r,t,e,n){if(Array.isArray(r)){if(t!=null||e!=null)throw new z("When inputs is an array, neither initialState or constants should be provided");n!=null&&(e=r.slice(r.length-n,r.length),r=r.slice(0,r.length-n)),r.length>1&&(t=r.slice(1,r.length)),r=r[0]}function o(s){return s==null||Array.isArray(s)?s:[s]}return t=o(t),e=o(e),{inputs:r,initialState:t,constants:e}}function P0(r,t,e,n=!1,o,s,i=!1,a=!1){return B(()=>{let u=t.shape.length;if(u<3)throw new z(`Input should be at least 3D, but is ${u}D.`);let l=[1,0].concat(Yr(2,u));if(t=Ot(t,l),s!=null)throw new vt("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),o!=null&&(o=J(J(o,"bool"),"float32"),o.rank===u-1&&(o=gr(o,-1)),o=Ot(o,l)),n&&(t=ur(t,0),o!=null&&(o=ur(o,0)));let c=[],p,m=e,f=t.shape[0],d=vr(t),h;o!=null&&(h=vr(o));for(let x=0;x<f;++x){let b=d[x],w=B(()=>r(b,m));if(o==null)p=w[0],m=w[1];else{let C=B(()=>{let N=h[x],_=ct(xr(N),N),A=X(R(w[0],N),R(m[0],_)),$=m.map((F,P)=>X(R(w[1][P],N),R(F,_)));return{output:A,newStates:$}});p=C.output,m=C.newStates}a&&c.push(p)}let g;return a&&(g=rr(c,1)),[p,g,m]})}var Nn=class extends Rt{constructor(t){super(t);let e;if(t.cell==null)throw new z("cell property is missing for the constructor of RNN.");if(Array.isArray(t.cell)?e=new Ic({cells:t.cell}):e=t.cell,e.stateSize==null)throw new z("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=e,this.returnSequences=t.returnSequences==null?!1:t.returnSequences,this.returnState=t.returnState==null?!1:t.returnState,this.goBackwards=t.goBackwards==null?!1:t.goBackwards,this._stateful=t.stateful==null?!1:t.stateful,this.unroll=t.unroll==null?!1:t.unroll,this.supportsMasking=!0,this.inputSpec=[new ye({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let t=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return Yr(0,t).map(e=>null)}else return this.states_}setStates(t){this.states_=t}computeOutputShape(t){ky(t)&&(t=t[0]),t=t;let e=this.cell.stateSize;Array.isArray(e)||(e=[e]);let n=e[0],o;if(this.returnSequences?o=[t[0],t[1],n]:o=[t[0],n],this.returnState){let s=[];for(let i of e)s.push([t[0],i]);return[o].concat(s)}else return o}computeMask(t,e){return B(()=>{Array.isArray(e)&&(e=e[0]);let n=this.returnSequences?e:null;if(this.returnState){let o=this.states.map(s=>null);return[n].concat(o)}else return n})}get states(){if(this.states_==null){let t=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,e=[];for(let n=0;n<t;++n)e.push(null);return e}else return this.states_}set states(t){this.states_=t}build(t){if(this.numConstants!=null)throw new vt("Constants support is not implemented in RNN yet.");ky(t)&&(t=t[0]),t=t;let n=this.stateful?t[0]:null,o=t.slice(2);this.inputSpec[0]=new ye({shape:[n,null,...o]});let s=[t[0]].concat(t.slice(2));this.cell.build(s);let i;if(Array.isArray(this.cell.stateSize)?i=this.cell.stateSize:i=[this.cell.stateSize],this.stateSpec!=null){if(!y.arraysEqual(this.stateSpec.map(a=>a.shape[a.shape.length-1]),i))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=i.map(a=>new ye({shape:[null,a]}));this.stateful&&this.resetStates()}resetStates(t,e=!1){B(()=>{if(!this.stateful)throw new vn("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==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(o=>Ne([n,o])):this.states_=[Ne([n,this.cell.stateSize])];else if(t==null)St(this.states_),this.keptStates!=null&&(St(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(o=>Ne([n,o])):this.states_[0]=Ne([n,this.cell.stateSize]);else{if(Array.isArray(t)||(t=[t]),t.length!==this.states_.length)throw new z(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${t.length} state value(s). Input received: ${t}`);e===!0?this.keptStates.push(this.states_.slice()):St(this.states_);for(let o=0;o<this.states_.length;++o){let s=t[o],i=Array.isArray(this.cell.stateSize)?this.cell.stateSize[o]:this.cell.stateSize,a=[n,i];if(!y.arraysEqual(s.shape,a))throw new z(`State ${o} is incompatible with layer ${this.name}: expected shape=${a}, received shape=${s.shape}`);this.states_[o]=s}}this.states_=this.states_.map(o=>De(o.clone()))})}apply(t,e){let n=e==null?null:e.initialState,o=e==null?null:e.constants;e==null&&(e={});let s=O0(t,n,o,this.numConstants);t=s.inputs,n=s.initialState,o=s.constants;let i=[],a=[];if(n!=null){e.initialState=n,i=i.concat(n),this.stateSpec=[];for(let l of n)this.stateSpec.push(new ye({shape:l.shape}));a=a.concat(this.stateSpec)}if(o!=null&&(e.constants=o,i=i.concat(o),this.numConstants=o.length),i[0]instanceof Jr){let l=[t].concat(i),c=this.inputSpec.concat(a),p=this.inputSpec;this.inputSpec=c;let m=super.apply(l,e);return this.inputSpec=p,m}else return super.apply(t,e)}call(t,e){return B(()=>{let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;t=At(t),s==null&&(this.stateful?s=this.states_:s=this.getInitialState(t));let i=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(s.length!==i)throw new z(`RNN Layer has ${i} 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 a={training:o},l=P0((d,h)=>{let g=this.cell.call([d].concat(h),a);return[g[0],g.slice(1)]},t,s,this.goBackwards,n,null,this.unroll,this.returnSequences),c=l[0],p=l[1],m=l[2];this.stateful&&this.resetStates(m,o);let f=this.returnSequences?p:c;return this.returnState?[f].concat(m):f})}getInitialState(t){return B(()=>{let e=Ne(t.shape);return e=ft(e,[1,2]),e=el(e),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?vy(e,[1,n]):e):this.cell.stateSize>1?[vy(e,[1,this.cell.stateSize])]:[e]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(t){super.setFastWeightInitDuringBuild(t),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(t)}getConfig(){let t=super.getConfig(),e={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(e.numConstants=this.numConstants);let n=this.cell.getConfig();return this.getClassName()===Nn.className&&(e.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,t,e)}static fromConfig(t,e,n={}){let o=e.cell,s=hn(o,n);return new t(Object.assign(e,{cell:s}))}};Nn.className="RNN";Q.registerClass(Nn);var il=class extends Rt{},wc=class extends il{constructor(t){super(t),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=t.units,Ze(this.units,"units"),this.activation=Ks(t.activation==null?this.DEFAULT_ACTIVATION:t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.kernelInitializer=de(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=de(t.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=de(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=be(t.kernelRegularizer),this.recurrentRegularizer=be(t.recurrentRegularizer),this.biasRegularizer=be(t.biasRegularizer),this.kernelConstraint=ze(t.kernelConstraint),this.recurrentConstraint=ze(t.recurrentConstraint),this.biasConstraint=ze(t.biasConstraint),this.dropout=ac([1,Us([0,t.dropout==null?0:t.dropout])]),this.recurrentDropout=ac([1,Us([0,t.recurrentDropout==null?0:t.recurrentDropout])]),this.dropoutFunc=t.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(t){t=Jt(t),this.kernel=this.addWeight("kernel",[t[t.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(t,e){return B(()=>{if(t=t,t.length!==2)throw new z(`SimpleRNNCell expects 2 input Tensors, got ${t.length}.`);let n=t[1];t=t[0];let o=e.training==null?!1:e.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ll({ones:()=>xr(t),rate:this.dropout,training:o,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ll({ones:()=>xr(n),rate:this.recurrentDropout,training:o,dropoutFunc:this.dropoutFunc}));let s,i=this.dropoutMask,a=this.recurrentDropoutMask;i!=null?s=No(R(t,i),this.kernel.read()):s=No(t,this.kernel.read()),this.bias!=null&&(s=mn(s,this.bias.read())),a!=null&&(n=R(n,a));let u=X(s,No(n,this.recurrentKernel.read()));return this.activation!=null&&(u=this.activation.apply(u)),[u,u]})}getConfig(){let t=super.getConfig(),e={units:this.units,activation:qs(this.activation),useBias:this.useBias,kernelInitializer:ke(this.kernelInitializer),recurrentInitializer:ke(this.recurrentInitializer),biasInitializer:ke(this.biasInitializer),kernelRegularizer:me(this.kernelRegularizer),recurrentRegularizer:me(this.recurrentRegularizer),biasRegularizer:me(this.biasRegularizer),activityRegularizer:me(this.activityRegularizer),kernelConstraint:Me(this.kernelConstraint),recurrentConstraint:Me(this.recurrentConstraint),biasConstraint:Me(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},t,e)}};wc.className="SimpleRNNCell";Q.registerClass(wc);var of=class extends Nn{constructor(t){t.cell=new wc(t),super(t)}call(t,e){return B(()=>{this.cell.dropoutMask!=null&&(St(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(St(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;return super.call(t,{mask:n,training:o,initialState:s})})}static fromConfig(t,e){return new t(e)}};of.className="SimpleRNN";Q.registerClass(of);var Cc=class extends il{constructor(t){if(super(t),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",t.resetAfter)throw new z("GRUCell does not support reset_after parameter set to true.");this.units=t.units,Ze(this.units,"units"),this.activation=Ks(t.activation===void 0?this.DEFAULT_ACTIVATION:t.activation),this.recurrentActivation=Ks(t.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:t.recurrentActivation),this.useBias=t.useBias==null?!0:t.useBias,this.kernelInitializer=de(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=de(t.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=de(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=be(t.kernelRegularizer),this.recurrentRegularizer=be(t.recurrentRegularizer),this.biasRegularizer=be(t.biasRegularizer),this.kernelConstraint=ze(t.kernelConstraint),this.recurrentConstraint=ze(t.recurrentConstraint),this.biasConstraint=ze(t.biasConstraint),this.dropout=ac([1,Us([0,t.dropout==null?0:t.dropout])]),this.recurrentDropout=ac([1,Us([0,t.recurrentDropout==null?0:t.recurrentDropout])]),this.dropoutFunc=t.dropoutFunc,this.implementation=t.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(t){t=Jt(t);let e=t[t.length-1];this.kernel=this.addWeight("kernel",[e,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(t,e){return B(()=>{if(t=t,t.length!==2)throw new z(`GRUCell expects 2 input Tensors (inputs, h, c), got ${t.length}.`);let n=e.training==null?!1:e.training,o=t[1];t=t[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ll({ones:()=>xr(t),rate:this.dropout,training:n,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ll({ones:()=>xr(o),rate:this.recurrentDropout,training:n,count:3,dropoutFunc:this.dropoutFunc}));let s=this.dropoutMask,i=this.recurrentDropoutMask,a,u,l;0<this.dropout&&this.dropout<1&&(t=R(t,s[0]));let c=No(t,this.kernel.read());this.useBias&&(c=mn(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(o=R(o,i[0]));let p=this.recurrentKernel.read(),[m,f]=cr(p,[2*this.units,this.units],p.rank-1),d=No(o,m),[h,g,x]=cr(c,3,c.rank-1),[b,w]=cr(d,2,d.rank-1);a=this.recurrentActivation.apply(X(h,b)),u=this.recurrentActivation.apply(X(g,w));let C=No(R(u,o),f);l=this.activation.apply(X(x,C));let N=X(R(a,o),R(X(1,Ut(a)),l));return[N,N]})}getConfig(){let t=super.getConfig(),e={units:this.units,activation:qs(this.activation),recurrentActivation:qs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:ke(this.kernelInitializer),recurrentInitializer:ke(this.recurrentInitializer),biasInitializer:ke(this.biasInitializer),kernelRegularizer:me(this.kernelRegularizer),recurrentRegularizer:me(this.recurrentRegularizer),biasRegularizer:me(this.biasRegularizer),activityRegularizer:me(this.activityRegularizer),kernelConstraint:Me(this.kernelConstraint),recurrentConstraint:Me(this.recurrentConstraint),biasConstraint:Me(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},t,e)}};Cc.className="GRUCell";Q.registerClass(Cc);var sf=class extends Nn{constructor(t){t.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),t.cell=new Cc(t),super(t)}call(t,e){return B(()=>{this.cell.dropoutMask!=null&&(St(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(St(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;return super.call(t,{mask:n,training:o,initialState:s})})}static fromConfig(t,e){return e.implmentation===0&&(e.implementation=1),new t(e)}};sf.className="GRU";Q.registerClass(sf);var al=class extends il{constructor(t){super(t),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=t.units,Ze(this.units,"units"),this.activation=Ks(t.activation===void 0?this.DEFAULT_ACTIVATION:t.activation),this.recurrentActivation=Ks(t.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:t.recurrentActivation),this.useBias=t.useBias==null?!0:t.useBias,this.kernelInitializer=de(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=de(t.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=de(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=t.unitForgetBias,this.kernelRegularizer=be(t.kernelRegularizer),this.recurrentRegularizer=be(t.recurrentRegularizer),this.biasRegularizer=be(t.biasRegularizer),this.kernelConstraint=ze(t.kernelConstraint),this.recurrentConstraint=ze(t.recurrentConstraint),this.biasConstraint=ze(t.biasConstraint),this.dropout=ac([1,Us([0,t.dropout==null?0:t.dropout])]),this.recurrentDropout=ac([1,Us([0,t.recurrentDropout==null?0:t.recurrentDropout])]),this.dropoutFunc=t.dropoutFunc,this.implementation=t.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(t){var e;t=Jt(t);let n=t[t.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 o;if(this.useBias){if(this.unitForgetBias){let s=this.biasInitializer,i=this.units;o=new(e=class extends fn{apply(u,l){let c=s.apply([i]),p=new xu().apply([i]),m=s.apply([i*2]);return C0(C0(c,p),m)}},e.className="CustomInit",e)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,o,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(t,e){return B(()=>{let n=e.training==null?!1:e.training;if(t=t,t.length!==3)throw new z(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${t.length}.`);let o=t[1],s=t[2];t=t[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ll({ones:()=>xr(t),rate:this.dropout,training:n,count:4,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ll({ones:()=>xr(o),rate:this.recurrentDropout,training:n,count:4,dropoutFunc:this.dropoutFunc}));let i=this.dropoutMask,a=this.recurrentDropoutMask,u,l,c,p;0<this.dropout&&this.dropout<1&&(t=R(t,i[0]));let m=No(t,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(o=R(o,a[0])),m=X(m,No(o,this.recurrentKernel.read())),this.useBias&&(m=mn(m,this.bias.read()));let[f,d,h,g]=cr(m,4,m.rank-1);u=this.recurrentActivation.apply(f),l=this.recurrentActivation.apply(d),c=X(R(l,s),R(u,this.activation.apply(h))),p=this.recurrentActivation.apply(g);let x=R(p,this.activation.apply(c));return[x,x,c]})}getConfig(){let t=super.getConfig(),e={units:this.units,activation:qs(this.activation),recurrentActivation:qs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:ke(this.kernelInitializer),recurrentInitializer:ke(this.recurrentInitializer),biasInitializer:ke(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:me(this.kernelRegularizer),recurrentRegularizer:me(this.recurrentRegularizer),biasRegularizer:me(this.biasRegularizer),activityRegularizer:me(this.activityRegularizer),kernelConstraint:Me(this.kernelConstraint),recurrentConstraint:Me(this.recurrentConstraint),biasConstraint:Me(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},t,e)}};al.className="LSTMCell";Q.registerClass(al);var af=class extends Nn{constructor(t){t.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),t.cell=new al(t),super(t)}call(t,e){return B(()=>{this.cell.dropoutMask!=null&&(St(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(St(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;return super.call(t,{mask:n,training:o,initialState:s})})}static fromConfig(t,e){return e.implmentation===0&&(e.implementation=1),new t(e)}};af.className="LSTM";Q.registerClass(af);var Ic=class extends il{constructor(t){super(t),this.cells=t.cells}get stateSize(){let t=[];for(let e of this.cells.slice().reverse())Array.isArray(e.stateSize)?t.push(...e.stateSize):t.push(e.stateSize);return t}call(t,e){return B(()=>{t=t;let n=t.slice(1),o=[];for(let a of this.cells.slice().reverse())Array.isArray(a.stateSize)?o.push(n.splice(0,a.stateSize.length)):o.push(n.splice(0,1));o.reverse();let s=[],i;for(let a=0;a<this.cells.length;++a){let u=this.cells[a];n=o[a],a===0?i=[t[0]].concat(n):i=[i[0]].concat(n),i=u.call(i,e),s.push(i.slice(1))}n=[];for(let a of s.slice().reverse())n.push(...a);return[i[0]].concat(n)})}build(t){ky(t)&&(t=t[0]),t=t;let e;this.cells.forEach((n,o)=>{Ws(`RNNCell_${o}`,()=>{n.build(t),Array.isArray(n.stateSize)?e=n.stateSize[0]:e=n.stateSize,t=[t[0],e]})}),this.built=!0}getConfig(){let t=super.getConfig(),e=s=>({className:s.getClassName(),config:s.getConfig()}),o={cells:this.cells.map(e)};return Object.assign({},t,o)}static fromConfig(t,e,n={}){let o=[];for(let s of e.cells)o.push(hn(s,n));return new t({cells:o})}get trainableWeights(){if(!this.trainable)return[];let t=[];for(let e of this.cells)t.push(...e.trainableWeights);return t}get nonTrainableWeights(){let t=[];for(let e of this.cells)t.push(...e.nonTrainableWeights);if(!this.trainable){let e=[];for(let n of this.cells)e.push(...n.trainableWeights);return e.concat(t)}return t}getWeights(){let t=[];for(let e of this.cells)t.push(...e.weights);return xh(t)}setWeights(t){let e=[];for(let n of this.cells){let o=n.weights.length,s=t.splice(o);for(let i=0;i<n.weights.length;++i)e.push([n.weights[i],s[i]])}Om(e)}};Ic.className="StackedRNNCells";Q.registerClass(Ic);function ll(r){let{ones:t,rate:e,training:n=!1,count:o=1,dropoutFunc:s}=r,i=()=>s!=null?s(t(),e):Ny(t(),e),a=()=>gu(i,t,n);return!o||o<=1?De(a().clone()):Array(o).fill(void 0).map(a).map(l=>De(l.clone()))}var V8=function(r,t){var e={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&t.indexOf(n)<0&&(e[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var o=0,n=Object.getOwnPropertySymbols(r);o<n.length;o++)t.indexOf(n[o])<0&&Object.prototype.propertyIsEnumerable.call(r,n[o])&&(e[n[o]]=r[n[o]]);return e};var ub=class extends Nn{constructor(t){if(t.unroll)throw new vt("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(t.cell))throw new vt("It is not possible at the moment to stack convolutional cells.");super(t),this.inputSpec=[new ye({ndim:5})]}call(t,e){return B(()=>{if(this.cell.dropoutMask!=null&&(St(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(St(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),e&&e.constants)throw new z("ConvRNN2D cell does not support constants");let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;return super.call(t,{mask:n,training:o,initialState:s})})}computeOutputShape(t){let e=this.computeSingleOutputShape(t);return this.returnSequences||(e=[e[0],...e.slice(2)]),this.returnState&&(e=[e,...Array(2).fill([t[0],...e.slice(-3)])]),e}getInitialState(t){return B(()=>{let{stateSize:e}=this.cell,n=t.shape,o=this.computeSingleOutputShape(n),s=[o[0],...o.slice(2)],i=Ne(s);return Array.isArray(e)?Array(e.length).fill(i):[i]})}resetStates(t,e=!1){B(()=>{if(!this.stateful)throw new vn("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,o=this.computeSingleOutputShape(n),s=[o[0],...o.slice(2)];if(n[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(()=>Ne(s)):this.states_=[Ne(s)];else if(t==null)St(this.states_),this.keptStates!=null&&(St(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ne(s)):this.states_[0]=Ne(s);else{if(Array.isArray(t)||(t=[t]),t.length!==this.states_.length)throw new z(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${t.length} state value(s). Input received: ${t}`);e?this.keptStates.push(this.states_.slice()):St(this.states_);for(let a=0;a<this.states_.length;++a){let u=t[a],l=s;if(!y.arraysEqual(u.shape,l))throw new z(`State ${a} is incompatible with layer ${this.name}: expected shape=${l}, received shape=${u.shape}`);this.states_[a]=u}}this.states_=this.states_.map(a=>De(a.clone()))})}computeSingleOutputShape(t){let{dataFormat:e,filters:n,kernelSize:o,padding:s,strides:i,dilationRate:a}=this.cell,u=e==="channelsFirst",l=t[u?3:2],c=t[u?4:3],p=Sn(l,o[0],s,i[0],a[0]),m=Sn(c,o[1],s,i[1],a[1]);return[...t.slice(0,2),...u?[n,p,m]:[p,m,n]]}};ub.className="ConvRNN2D";var vc=class extends al{constructor(t){let{filters:e,kernelSize:n,strides:o,padding:s,dataFormat:i,dilationRate:a}=t;super(Object.assign({},t,{units:e})),this.filters=e,Ze(this.filters,"filters"),this.kernelSize=wu(n,2,"kernelSize"),this.kernelSize.forEach(u=>Ze(u,"kernelSize")),this.strides=wu(o||1,2,"strides"),this.strides.forEach(u=>Ze(u,"strides")),this.padding=s||"valid",cn(this.padding),this.dataFormat=i||"channelsLast",Re(this.dataFormat),this.dilationRate=wu(a||1,2,"dilationRate"),this.dilationRate.forEach(u=>Ze(u,"dilationRate"))}build(t){var e;t=Jt(t);let n=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[n]==null)throw new z(`The channel dimension of the input should be defined. Found ${t[n]}`);let o=t[n],s=4,i=this.kernelSize.concat([o,this.filters*s]);this.kernel=this.addWeight("kernel",i,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let a=this.kernelSize.concat([this.filters,this.filters*s]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",a,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let u;if(this.unitForgetBias){let l=this.biasInitializer,c=this.filters;u=new(e=class extends fn{apply(m,f){let d=l.apply([c]),h=lr([c]),g=l.apply([c*2]);return Sm([d,h,g])}},e.className="CustomInit",e)}else u=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*s],null,u,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(t,e){return B(()=>{if(t.length!==3)throw new z(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${t.length}.`);let n=e.training||!1,o=t[0],s=t[1],i=t[2],a=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ll({ones:()=>xr(o),rate:this.dropout,training:n,count:a,dropoutFunc:this.dropoutFunc}));let u=this.dropoutMask,l=(rt,ot,at)=>!ot||!ot[at]?rt:R(ot[at],rt),c=l(o,u,0),p=l(o,u,1),m=l(o,u,2),f=l(o,u,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ll({ones:()=>xr(s),rate:this.recurrentDropout,training:n,count:a,dropoutFunc:this.dropoutFunc}));let d=this.recurrentDropoutMask,h=l(s,d,0),g=l(s,d,1),x=l(s,d,2),b=l(s,d,3),w=3,[C,N,_,A]=cr(this.kernel.read(),a,w),[$,F,P,V]=this.useBias?cr(this.bias.read(),a):[null,null,null,null];c=this.inputConv(c,C,$,this.padding),p=this.inputConv(p,N,F,this.padding),m=this.inputConv(m,_,P,this.padding),f=this.inputConv(f,A,V,this.padding);let[G,W,q,H]=cr(this.recurrentKernel.read(),a,w);h=this.recurrentConv(h,G),g=this.recurrentConv(g,W),x=this.recurrentConv(x,q),b=this.recurrentConv(b,H);let j=this.recurrentActivation.apply(X(c,h)),Y=this.recurrentActivation.apply(X(p,g)),Z=X(R(Y,i),R(j,this.activation.apply(X(m,x)))),et=R(this.recurrentActivation.apply(X(f,b)),this.activation.apply(Z));return[et,et,Z]})}getConfig(){let t=super.getConfig(),{units:e}=t,n=V8(t,["units"]),o={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,o)}inputConv(t,e,n,o){let s=Cn(t,e,this.strides,o||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?mn(s,n,this.dataFormat):s}recurrentConv(t,e){return Cn(t,e,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};vc.className="ConvLSTM2DCell";Q.registerClass(vc);var lf=class extends ub{constructor(t){let e=new vc(t);super(Object.assign({},t,{cell:e}))}static fromConfig(t,e){return new t(e)}};lf.className="ConvLSTM2D";Q.registerClass(lf);var Sc=class extends Rt{constructor(t){super(t),this.rate=Math.max(Math.min(t.rate,1),0),this.noiseShape=t.noiseShape,this.seed=t.seed,this.supportsMasking=!0}getNoiseShape(t){if(this.noiseShape==null)return this.noiseShape;let e=t.shape,n=[];for(let o=0;o<this.noiseShape.length;++o)n.push(this.noiseShape[o]==null?e[o]:this.noiseShape[o]);return n}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=At(t);if(0<this.rate&&this.rate<1){let o=e.training==null?!1:e.training,s=this.getNoiseShape(n);return gu(()=>Ny(n,this.rate,s,this.seed),()=>n,o)}return t})}getConfig(){let t={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},e=super.getConfig();return Object.assign(t,e),t}dispose(){return super.dispose()}};Sc.className="Dropout";Q.registerClass(Sc);var uf=class extends Sc{constructor(t){super(t),this.inputSpec=[{ndim:3}]}getNoiseShape(t){let e=t.shape;return[e[0],1,e[2]]}};uf.className="SpatialDropout1D";Q.registerClass(uf);var cf=class extends Rt{constructor(t){if(super(t),this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",t.batchInputShape==null&&t.inputShape==null&&t.inputDim!=null){let e=null;t.batchSize!=null&&(e=t.batchSize),this.batchInputShape=[e,t.inputDim]}this.units=t.units,Ze(this.units,"units"),this.activation=Ks(t.activation),t.useBias!=null&&(this.useBias=t.useBias),this.kernelInitializer=de(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=de(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=ze(t.kernelConstraint),this.biasConstraint=ze(t.biasConstraint),this.kernelRegularizer=be(t.kernelRegularizer),this.biasRegularizer=be(t.biasRegularizer),this.activityRegularizer=be(t.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(t){t=Jt(t);let e=t[t.length-1];this.kernel==null&&(this.kernel=this.addWeight("kernel",[e,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]:e}}],this.built=!0}computeOutputShape(t){t=Jt(t);let e=t.slice();return e[e.length-1]=this.units,e}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=At(t),o=xy(this.activation.getClassName()),s;return o!=null?s=No(n,this.kernel.read(),o,this.bias?this.bias.read():null):(s=No(n,this.kernel.read()),this.bias!=null&&(s=mn(s,this.bias.read())),this.activation!=null&&(s=this.activation.apply(s))),s})}getConfig(){let t={units:this.units,activation:qs(this.activation),useBias:this.useBias,kernelInitializer:ke(this.kernelInitializer),biasInitializer:ke(this.biasInitializer),kernelRegularizer:me(this.kernelRegularizer),biasRegularizer:me(this.biasRegularizer),activityRegularizer:me(this.activityRegularizer),kernelConstraint:Me(this.kernelConstraint),biasConstraint:Me(this.biasConstraint)},e=super.getConfig();return Object.assign(t,e),t}};cf.className="Dense";Q.registerClass(cf);var pf=class extends Rt{constructor(t){t=t||{},super(t),this.inputSpec=[{minNDim:3}],this.dataFormat=t.dataFormat}computeOutputShape(t){t=Jt(t);for(let e of t.slice(1))if(e==null)throw new z(`The shape of the input to "Flatten" is not fully defined (got ${t.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[t[0],So(t,1)]}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=At(t);if(this.dataFormat==="channelsFirst"&&n.rank>1){let o=[0];for(let s=2;s<n.rank;++s)o.push(s);o.push(1),n=Ot(n,o)}return E$(n)})}getConfig(){let t={};this.dataFormat!=null&&(t.dataFormat=this.dataFormat);let e=super.getConfig();return Object.assign(t,e),t}};pf.className="Flatten";Q.registerClass(pf);var mf=class extends Rt{constructor(t){super(t),this.supportsMasking=!0,this.activation=Ks(t.activation)}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=At(t);return this.activation.apply(n)})}getConfig(){let t={activation:qs(this.activation)},e=super.getConfig();return Object.assign(t,e),t}};mf.className="Activation";Q.registerClass(mf);var ff=class extends Rt{constructor(t){super(t),this.n=t.n,this.inputSpec=[{ndim:2}]}computeOutputShape(t){return[t[0],this.n,t[1]]}call(t,e){return B(()=>(t=At(t),k$(t,this.n)))}getConfig(){let t={n:this.n},e=super.getConfig();return Object.assign(t,e),t}};ff.className="RepeatVector";Q.registerClass(ff);var df=class extends Rt{constructor(t){super(t),this.targetShape=t.targetShape;for(let e=0;e<this.targetShape.length;++e)this.isUnknown(this.targetShape[e])&&(this.targetShape[e]=null)}isUnknown(t){return t<0||t==null}fixUnknownDimension(t,e){let n="Total size of new array must be unchanged.",o=e.slice(),s=1,i=null;for(let u=0;u<o.length;++u){let l=o[u];if(this.isUnknown(l))if(i===null)i=u;else throw new z("Can only specifiy one unknown dimension.");else s*=l}let a=So(t);if(i!==null){if(s===0||a%s!==0)throw new z(n);o[i]=a/s}else if(a!==s)throw new z(n);return o}computeOutputShape(t){let e=!1;for(let n=0;n<t.length;++n)if(this.isUnknown(t[n])){e=!0;break}return e?t.slice(0,1).concat(this.targetShape):t.slice(0,1).concat(this.fixUnknownDimension(t.slice(1),this.targetShape))}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=At(t),o=n.shape,s=o.slice(0,1).concat(this.fixUnknownDimension(o.slice(1),this.targetShape));return D(n,s)})}getConfig(){let t={targetShape:this.targetShape},e=super.getConfig();return Object.assign(t,e),t}};df.className="Reshape";Q.registerClass(df);var hf=class extends Rt{constructor(t){if(super(t),t.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(t.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${t.dims} instead.`);let e=Yr(1,t.dims.length+1);if(!y.arraysEqual(t.dims.slice().sort(),e))throw new Error("Invalid permutation `dims`: "+JSON.stringify(t.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=t.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new ye({ndim:this.dims.length+1})]}computeOutputShape(t){t=Jt(t);let e=t.slice();return this.dims.forEach((n,o)=>{e[o+1]=t[n]}),e}call(t,e){return 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ul=class extends Rt{constructor(t){super(t||{}),this.supportsMasking=!0}mergeFunction(t){throw new vt}computeElementwiseOpOutputShape(t,e){if(t==null||e==null)return null;if(t.length<e.length)return this.computeElementwiseOpOutputShape(e,t);if(e.length===0)return t;let n=t.slice(0,t.length-e.length);for(let o=0;o<e.length;++o){let s=t[t.length-e.length+o],i=e[o];if(s==null||i==null||s<0||i<0)n.push(null);else if(s===1)n.push(i);else if(i===1)n.push(s);else{if(s!==i)throw new z("Operands could not be broadcast together with shapes "+JSON.stringify(t)+" "+JSON.stringify(e));n.push(s)}}return n}build(t){if(Array.isArray(t)&&!Array.isArray(t[0])&&(t=[Jt(t)]),t=t,t.length<2)throw new z(`A merge layer should be called on an Array of at least 2 inputs. 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t={axis:this.axis},e=super.getConfig();return Object.assign(t,e),t}};vf.className="Concatenate";Q.registerClass(vf);function kh(r,t){for(;r<0;)r+=t;return r}function G8(r,t,e){if(r.shape.length>3||t.shape.length>3)throw new vt("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 ${t.shape.length}`),typeof e=="number"&&(e=[e,e]),r.dtype==="complex64"||t.dtype==="complex64")throw new vt("batchDot is not implemented for complex64-type Tensors yet.");let n=r.shape.length,o=t.shape.length;e==null&&(e=[n-1,o-2]);let s=e;return B(()=>{let i;if(n>o){i=n-o;let u=[];for(let l=0;l<i;++l)u.push(1);t=D(t,t.shape.concat(u))}else if(o>n){i=o-n;let u=[];for(let l=0;l<i;++l)u.push(1);r=D(r,r.shape.concat(u))}else i=0;let a;if(r.shape.length===2&&t.shape.length===2)s[0]===s[1]?a=ft(R(r,t),s[0]):a=ft(R(Ot(r,[1,0]),t),s[1]);else{let u=s[0]!==r.shape.length-1,l=s[1]===t.shape.length-1;a=Lt(r,t,u,l)}if(i>0){let u;n>o?u=n+o-3:u=n-1;let l=[];for(let c=u;c<u+i;++c)l.push(c);a=Pn(a,l)}return a.shape.length===1&&(a=gr(a,1)),a})}var Sf=class extends ul{constructor(t){super(t),this.axes=t.axes,this.normalize=t.normalize==null?!1:t.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(t){y.assert(Array.isArray(t)&&t.length===2&&Array.isArray(t[0])&&Array.isArray(t[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let e=t[0],n=t[1];if(e.length>3||n.length>3)throw new vt("Dot layer does not support tensors of 4D or higher rank yet.");let o=this.interpretAxes(e,n);if(e[o[0]]!==n[o[1]])throw new z(`Dimension incompatibility: ${e[o[0]]} !== ${n[o[1]]}`)}mergeFunction(t){if(t.length!==2)throw new z(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${t.length} 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Rt{constructor(t){super(t),this.supportsMasking=!0,this.stddev=t.stddev}computeOutputShape(t){return t}getConfig(){let t=super.getConfig(),e={stddev:this.stddev};return Object.assign(e,t),e}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=At(t);return gu(()=>X(Nm(n.shape,0,this.stddev),n),()=>n,e.training||!1)})}};Nf.className="GaussianNoise";Q.registerClass(Nf);var kf=class extends Rt{constructor(t){super(t),this.supportsMasking=!0,this.rate=t.rate}computeOutputShape(t){return t}getConfig(){let t=super.getConfig(),e={rate:this.rate};return Object.assign(e,t),e}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=At(t);return this.rate>0&&this.rate<1?gu(()=>{let s=Math.sqrt(this.rate/(1-this.rate));return R(n,Nm(n.shape,1,s))},()=>n,e.training||!1):n})}};kf.className="GaussianDropout";Q.registerClass(kf);var Tf=class extends Rt{constructor(t){super(t),this.supportsMasking=!0,this.rate=t.rate,this.noiseShape=t.noiseShape}_getNoiseShape(t){return this.noiseShape||At(t).shape}computeOutputShape(t){return t}getConfig(){let t=super.getConfig(),e={rate:this.rate};return Object.assign(e,t),e}call(t,e){return B(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(t);return gu(()=>{let s=At(t),i=1.6732632423543772,a=1.0507009873554805,u=-i*a,l=Fn(Li(n),this.rate);l=tl(l,"float32");let c=((1-this.rate)*(1+this.rate*u**2))**-.5,p=-c*u*this.rate,m=X(R(s,l),R(X(l,-1),u));return X(R(m,c),p)},()=>At(t),e.training||!1)}return t})}};Tf.className="AlphaDropout";Q.registerClass(Tf);function Th(r,t,e,n,o,s=.001){let i;if(r.rank===2)i=mx(r,t,e,n,o,s);else if(r.rank===3)i=fx(r,t,e,n,o,s);else if(r.rank===4)i=dx(r,t,e,n,o,s);else throw new vt(`batchNormalization is not implemented for array of rank ${r.rank} yet`);return i}function W8(r,t,e,n,o=.001){return B(()=>{let s=Zu(r,n),i=s.mean,a=s.variance;return[Th(r,i,a,e,t,o),i,a]})}function U8(r,t,e,n,o=.001){return B(()=>{let s=Zu(r,n),i=s.mean,a=s.variance,u=[];for(let d of 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e=this.axis>=0?this.axis:this.axis+t.length,n=t[e];if(n==null)throw new z(`Axis ${e} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(t)}.`);this.inputSpec=[new ye({ndim:t.length,axes:{[e]:n}})];let o=[n];this.scale&&(this.gamma=this.addWeight("gamma",o,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",o,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",o,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",o,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(t,e){return B(()=>{let n=e.training==null?!1:e.training,o=At(t),s=o.shape,i=s.length,a=Yr(0,i),u=this.axis>=0?this.axis:this.axis+i;a.splice(u,1);let l=Co(1,i);l[u]=s[u];let c=a.slice();c.sort();let p=!y.arraysEqual(c,Yr(0,i).slice(0,i-1)),m=()=>{if(p){let 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t={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:ke(this.betaInitializer),gammaInitializer:ke(this.gammaInitializer),movingMeanInitializer:ke(this.movingMeanInitializer),movingVarianceInitializer:ke(this.movingVarianceInitializer),betaRegularizer:me(this.betaRegularizer),gammaRegularizer:me(this.gammaRegularizer),betaConstraint:Me(this.betaConstraint),gammaConstraint:Me(this.gammaConstraint)},e=super.getConfig();return Object.assign(t,e),t}};Ef.className="BatchNormalization";Q.registerClass(Ef);var _f=class extends Rt{constructor(t){if(t==null&&(t={}),super(t),this.axis=t.axis==null?-1:t.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 e of this.axis)if(!Number.isInteger(e))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=t.epsilon==null?.001:t.epsilon,this.center=t.center==null?!0:t.center,this.scale=t.scale==null?!0:t.scale,this.betaInitializer=de(t.betaInitializer||"zeros"),this.gammaInitializer=de(t.gammaInitializer||"ones"),this.betaRegularizer=be(t.betaRegularizer),this.gammaRegularizer=be(t.gammaRegularizer),this.supportsMasking=!0}build(t){t=Jt(t);let e=t.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]+=e);for(let s of this.axis)if(s<0||s>=e)throw new Error(`Invalid axis: ${s}`);if(this.axis.length!==vo(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(s=>t[s]),o=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,o):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,o):this.beta=null,this.built=!0}call(t,e){let n=At(t),o=n.shape,s=o.length;return B(()=>{let{mean:a,variance:u}=Zu(n,this.axis,!0),l=Co(1,s);for(let h of this.axis)l[h]=o[h];let c=h=>h!=null&&h.shape.length!==s?D(h,l):h,p=this.scale?c(this.gamma.read()):null,m=this.center?c(this.beta.read()):null,f=[],d=[];for(let h=0;h<s;++h)this.axis.indexOf(h)!==-1?(f.push(o[h]),d.push(1)):(f.push(1),d.push(o[h]));return a=$r(a,f),u=$r(u,f),p!=null&&(p=$r(p,d)),m!=null&&(m=$r(m,d)),Th(n,a,u,m,p,this.epsilon)})}getConfig(){let t={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:ke(this.betaInitializer),gammaInitializer:ke(this.gammaInitializer),betaRegularizer:me(this.betaRegularizer),gammaRegularizer:me(this.gammaRegularizer)},e=super.getConfig();return Object.assign(t,e),t}};_f.className="LayerNormalization";Q.registerClass(_f);function q8(r,t,e){return B(()=>{if(r.rank!==4)throw new z(`temporalPadding expects input tensor to be 4-D, but received a ${r.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[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(e==null&&(e=pn()),e!=="channelsLast"&&e!=="channelsFirst")throw new z(`Unknown data format: ${e}. 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s==="max"?i=tu(r,t,e,a):i=jl(r,t,e,a),o==="channelsFirst"&&(i=Ot(i,[0,3,1,2])),i})}function gD(r,t,e,n,o,s){return B(()=>{Re(o),x0(s),cn(n),e==null&&(e=[1,1,1]),n==null&&(n="valid"),o==null&&(o=pn()),s==null&&(s="max"),r=F0(r,o);let i,a=n==="same"?"same":"valid";return s==="max"?i=Bx(r,t,e,a):i=px(r,t,e,a),o==="channelsFirst"&&(i=Ot(i,[0,4,1,2,3])),i})}var cb=class extends Rt{constructor(t){if(t.poolSize==null&&(t.poolSize=2),super(t),typeof t.poolSize=="number")this.poolSize=[t.poolSize];else if(Array.isArray(t.poolSize)&&t.poolSize.length===1&&typeof t.poolSize[0]=="number")this.poolSize=t.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(t.poolSize)}`);if(Ze(this.poolSize,"poolSize"),t.strides==null)this.strides=this.poolSize;else if(typeof t.strides=="number")this.strides=[t.strides];else if(Array.isArray(t.strides)&&t.strides.length===1&&typeof 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Re(s),cn(o),hb(t,e,n,o,s,"avg")}};Df.className="AveragePooling1D";Q.registerClass(Df);var pb=class extends Rt{constructor(t){if(t.poolSize==null&&(t.poolSize=[2,2]),super(t),this.poolSize=Array.isArray(t.poolSize)?t.poolSize:[t.poolSize,t.poolSize],t.strides==null)this.strides=this.poolSize;else if(Array.isArray(t.strides)){if(t.strides.length!==2)throw new z(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${t.strides.length}.`);this.strides=t.strides}else this.strides=[t.strides,t.strides];Ze(this.poolSize,"poolSize"),Ze(this.strides,"strides"),this.padding=t.padding==null?"valid":t.padding,this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Re(this.dataFormat),cn(this.padding),this.inputSpec=[new ye({ndim:4})]}computeOutputShape(t){t=Jt(t);let e=this.dataFormat==="channelsFirst"?t[2]:t[1],n=this.dataFormat==="channelsFirst"?t[3]:t[2];return e=Sn(e,this.poolSize[0],this.padding,this.strides[0]),n=Sn(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[t[0],t[1],e,n]:[t[0],e,n,t[3]]}call(t,e){return B(()=>(this.invokeCallHook(t,e),this.poolingFunction(At(t),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let t={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}},Rf=class extends pb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Re(s),cn(o),hb(t,e,n,o,s,"max")}};Rf.className="MaxPooling2D";Q.registerClass(Rf);var Ff=class extends pb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Re(s),cn(o),hb(t,e,n,o,s,"avg")}};Ff.className="AveragePooling2D";Q.registerClass(Ff);var mb=class extends Rt{constructor(t){if(t.poolSize==null&&(t.poolSize=[2,2,2]),super(t),this.poolSize=Array.isArray(t.poolSize)?t.poolSize:[t.poolSize,t.poolSize,t.poolSize],t.strides==null)this.strides=this.poolSize;else if(Array.isArray(t.strides)){if(t.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 ${t.strides.length}.`);this.strides=t.strides}else this.strides=[t.strides,t.strides,t.strides];Ze(this.poolSize,"poolSize"),Ze(this.strides,"strides"),this.padding=t.padding==null?"valid":t.padding,this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Re(this.dataFormat),cn(this.padding),this.inputSpec=[new ye({ndim:5})]}computeOutputShape(t){t=Jt(t);let e=this.dataFormat==="channelsFirst"?t[2]:t[1],n=this.dataFormat==="channelsFirst"?t[3]:t[2],o=this.dataFormat==="channelsFirst"?t[4]:t[3];return e=Sn(e,this.poolSize[0],this.padding,this.strides[0]),n=Sn(n,this.poolSize[1],this.padding,this.strides[1]),o=Sn(o,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[t[0],t[1],e,n,o]:[t[0],e,n,o,t[4]]}call(t,e){return B(()=>(this.invokeCallHook(t,e),this.poolingFunction(At(t),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let t={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}},Of=class extends mb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Re(s),cn(o),gD(t,e,n,o,s,"max")}};Of.className="MaxPooling3D";Q.registerClass(Of);var Pf=class extends mb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Re(s),cn(o),gD(t,e,n,o,s,"avg")}};Pf.className="AveragePooling3D";Q.registerClass(Pf);var fb=class extends Rt{constructor(t){super(t),this.inputSpec=[new ye({ndim:3})]}computeOutputShape(t){return[t[0],t[2]]}call(t,e){throw new vt}},Lf=class extends fb{constructor(t){super(t||{})}call(t,e){return B(()=>{let n=At(t);return Se(n,1)})}};Lf.className="GlobalAveragePooling1D";Q.registerClass(Lf);var Mf=class extends fb{constructor(t){super(t||{})}call(t,e){return B(()=>{let n=At(t);return Br(n,1)})}};Mf.className="GlobalMaxPooling1D";Q.registerClass(Mf);var db=class extends Rt{constructor(t){super(t),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Re(this.dataFormat),this.inputSpec=[new ye({ndim:4})]}computeOutputShape(t){return t=t,this.dataFormat==="channelsLast"?[t[0],t[3]]:[t[0],t[1]]}call(t,e){throw new vt}getConfig(){let t={dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}},zf=class extends db{call(t,e){return B(()=>{let n=At(t);return this.dataFormat==="channelsLast"?Se(n,[1,2]):Se(n,[2,3])})}};zf.className="GlobalAveragePooling2D";Q.registerClass(zf);var Bf=class extends db{call(t,e){return B(()=>{let n=At(t);return 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t(i)}},Vf=class extends gb{constructor(t){super(t),this.supportsMasking=!0}build(t){if(t=Jt(t),t.length<3)throw new z(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(t)}`);this.inputSpec=[{shape:t}];let e=[t[0]].concat(t.slice(2));this.layer.built||(this.layer.build(e),this.layer.built=!0),super.build(t)}computeOutputShape(t){t=Jt(t);let e=[t[0]].concat(t.slice(2)),n=this.layer.computeOutputShape(e),o=t[1];return[n[0],o].concat(n.slice(1))}call(t,e){return B(()=>(t=At(t),P0((i,a)=>[At(this.layer.call(i,e)),[]],t,[],!1,null,null,!1,!0)[1]))}};Vf.className="TimeDistributed";Q.registerClass(Vf);function K8(r){Vi(C$,"BidirectionalMergeMode",r)}var j8="concat",Gf=class extends gb{constructor(t){super(t);let e=t.layer.getConfig(),n={};n.className=t.layer.getClassName(),n.config=e,this.forwardLayer=hn(n),e.goBackwards=e.goBackwards!==!0;let o={};if(o.className=t.layer.getClassName(),o.config=e,this.backwardLayer=hn(o),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=t.mergeMode===void 0?j8:t.mergeMode,K8(this.mergeMode),t.weights)throw new vt("weights support is not implemented for Bidirectional layer yet.");this._stateful=t.layer.stateful,this.returnSequences=t.layer.returnSequences,this.returnState=t.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=t.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(t){this._trainable=t,this.forwardLayer!=null&&(this.forwardLayer.trainable=t),this.backwardLayer!=null&&(this.backwardLayer.trainable=t)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(t){let 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a;return this.mergeMode==="concat"?a=Sm([o,s]):this.mergeMode==="sum"?a=X(o,s):this.mergeMode==="ave"?a=R(.5,X(o,s)):this.mergeMode==="mul"?a=R(o,s):this.mergeMode==null&&(a=[o,s]),this.returnState?this.mergeMode==null?a.concat(i):[a].concat(i):a})}resetStates(t){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(t){Ws(this.forwardLayer.name,()=>{this.forwardLayer.build(t)}),Ws(this.backwardLayer.name,()=>{this.backwardLayer.build(t)}),this.built=!0}computeMask(t,e){Array.isArray(e)&&(e=e[0]);let n;if(this.returnSequences?this.mergeMode==null?n=[e,e]:n=e:this.mergeMode==null?n=[null,null]:n=null,this.returnState){let s=this.forwardLayer.states.map(i=>null);return Array.isArray(n)?n.concat(s).concat(s):[n].concat(s).concat(s)}else return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return 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n=v("size",r,t,e),o=v("dtype",r,t,e),s=v("elementShape",r,t,e),i=v("dynamicSize",r,t,e),a=v("clearAfterRead",r,t,e),u=v("identicalElementShapes",r,t,e),l=v("name",r,t,e),c=new Fb(l,o,n,s,u,i,a);return e.addTensorArray(c),[c.idTensor,mt(1)]}case"TensorArrayWriteV3":{let n=v("tensorArrayId",r,t,e),o=v("index",r,t,e),s=v("tensor",r,t,e),i=e.getTensorArray(n.id);return i.write(o,s),[i.idTensor]}case"TensorArrayReadV3":{let n=v("tensorArrayId",r,t,e),o=v("index",r,t,e);return[e.getTensorArray(n.id).read(o)]}case"TensorArrayGatherV3":{let n=v("tensorArrayId",r,t,e),o=v("indices",r,t,e),s=v("dtype",r,t,e);return[e.getTensorArray(n.id).gather(o,s)]}case"TensorArrayScatterV3":{let n=v("tensorArrayId",r,t,e),o=v("indices",r,t,e),s=v("tensor",r,t,e),i=e.getTensorArray(n.id);return i.scatter(o,s),[i.idTensor]}case"TensorArrayConcatV3":{let n=v("tensorArrayId",r,t,e),o=e.getTensorArray(n.id),s=v("dtype",r,t,e);return[o.concat(s)]}case"TensorArraySplitV3":{let n=v("tensorArrayId",r,t,e),o=v("tensor",r,t,e),s=v("lengths",r,t,e),i=e.getTensorArray(n.id);return i.split(s,o),[i.idTensor]}case"TensorArraySizeV3":{let n=v("tensorArrayId",r,t,e),o=e.getTensorArray(n.id);return[mt(o.size(),"int32")]}case"TensorArrayCloseV3":{let n=v("tensorArrayId",r,t,e),o=e.getTensorArray(n.id);return o.clearAndClose(),[o.idTensor]}case"TensorListSetItem":{let n=v("tensorListId",r,t,e),o=v("index",r,t,e),s=v("tensor",r,t,e),i=e.getTensorList(n.id);return i.setItem(o,s),[i.idTensor]}case"TensorListGetItem":{let n=v("tensorListId",r,t,e),o=v("index",r,t,e),s=v("elementShape",r,t,e),i=v("elementDType",r,t,e);return[e.getTensorList(n.id).getItem(o,s,i)]}case"TensorListScatterV2":case"TensorListScatter":{let n=v("indices",r,t,e),o=v("tensor",r,t,e),s=v("elementShape",r,t,e),i=v("numElements",r,t,e),a=PD(o,n,s,i);return e.addTensorList(a),[a.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let n=v("elementShape",r,t,e),o=v("elementDType",r,t,e),s;r.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=v(s,r,t,e),a=r.op==="TensorListReserve"?-1:i,u=OD(n,o,i,a);return e.addTensorList(u),[u.idTensor]}case"TensorListGather":{let n=v("tensorListId",r,t,e),o=v("indices",r,t,e),s=v("elementShape",r,t,e),i=v("elementDType",r,t,e);return[e.getTensorList(n.id).gather(o,i,s)]}case"TensorListStack":{let n=v("tensorListId",r,t,e),o=v("elementShape",r,t,e),s=v("elementDType",r,t,e),i=v("numElements",r,t,e);return[e.getTensorList(n.id).stack(o,s,i)]}case"TensorListFromTensor":{let n=v("tensor",r,t,e),o=v("elementShape",r,t,e),s=v("elementDType",r,t,e),i=FD(n,o,s);return e.addTensorList(i),[i.idTensor]}case"TensorListConcat":case"TensorListConcatV2":{let n=v("tensorListId",r,t,e),o=e.getTensorList(n.id),s=v("dtype",r,t,e),i=v("elementShape",r,t,e);return[o.concat(s,i)]}case"TensorListPushBack":{let n=v("tensorListId",r,t,e),o=v("tensor",r,t,e),s=e.getTensorList(n.id);return s.pushBack(o),[s.idTensor]}case"TensorListPopBack":{let n=v("tensorListId",r,t,e),o=v("elementShape",r,t,e),s=v("elementDType",r,t,e);return[e.getTensorList(n.id).popBack(o,s)]}case"TensorListSplit":{let n=v("tensor",r,t,e),o=v("elementShape",r,t,e),s=v("lengths",r,t,e),i=LD(n,s,o);return e.addTensorList(i),[i.idTensor]}case"TensorListLength":{let n=v("tensorListId",r,t,e),o=e.getTensorList(n.id);return[mt(o.size(),"int32")]}case"TensorListResize":{let n=v("tensorListId",r,t,e),o=v("size",r,t,e),i=e.getTensorList(n.id).resize(o);return e.addTensorList(i),[i.idTensor]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};function zD(r,t,e){let[n,o]=v("fusedOps",r,t,e),s=n==="biasadd",i=!s,a=o==="prelu",u=n==="fusedbatchnorm",l=v("numArgs",r,t,e);if(s){if(a&&l!==2)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!a&&s&&l!==1)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd must have one 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o=v("strides",r,t,e),s=Eh(r,t,e),i=v("dataFormat",r,t,e).toUpperCase(),a=v("dilations",r,t,e);return[n.conv2d(v("x",r,t,e),v("filter",r,t,e),[o[1],o[2]],s,i,[a[1],a[2]])]}case"_FusedConv2D":{let{stride:o,pad:s,dataFormat:i,dilations:a,biasArg:u,preluArg:l,activationFunc:c,leakyreluAlpha:p}=zD(r,t,e);return[n.fused.conv2d({x:v("x",r,t,e),filter:v("filter",r,t,e),strides:[o[1],o[2]],pad:s,dataFormat:i,dilations:[a[1],a[2]],bias:u,activation:c,preluActivationWeights:l,leakyreluAlpha:p})]}case"FusedDepthwiseConv2dNative":{let{stride:o,pad:s,dataFormat:i,dilations:a,biasArg:u,preluArg:l,activationFunc:c,leakyreluAlpha:p}=zD(r,t,e);return[n.fused.depthwiseConv2d({x:v("x",r,t,e),filter:v("filter",r,t,e),strides:[o[1],o[2]],pad:s,dataFormat:i,dilations:[a[1],a[2]],bias:u,activation:c,preluActivationWeights:l,leakyreluAlpha:p})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{let 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o=v("strides",r,t,e),s=v("pad",r,t,e),i=v("kernelSize",r,t,e),a=v("includeBatchInIndex",r,t,e),{result:u,indexes:l}=n.maxPoolWithArgmax(v("x",r,t,e),[i[1],i[2]],[o[1],o[2]],s,a);return[u,l]}case"AvgPool3D":{let o=v("strides",r,t,e),s=v("pad",r,t,e),i=v("kernelSize",r,t,e);return[n.avgPool3d(v("x",r,t,e),[i[1],i[2],i[3]],[o[1],o[2],o[3]],s)]}case"MaxPool3D":{let o=v("strides",r,t,e),s=v("pad",r,t,e),i=v("kernelSize",r,t,e);return[n.maxPool3d(v("x",r,t,e),[i[1],i[2],i[3]],[o[1],o[2],o[3]],s)]}case"Dilation2D":{let o=v("strides",r,t,e),s=v("pad",r,t,e),i=v("dilations",r,t,e),a=o[1],u=o[2],l=i[1],c=i[2];return[n.dilation2d(v("x",r,t,e),v("filter",r,t,e),[a,u],s,[l,c],"NHWC")]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var VD=(r,t,e,n=ae)=>{switch(r.op){case"Fill":{let o=v("shape",r,t,e),s=v("dtype",r,t,e),i=v("value",r,t,e);return[n.fill(o,i,s)]}case"LinSpace":{let o=v("start",r,t,e),s=v("stop",r,t,e),i=v("num",r,t,e);return[n.linspace(o,s,i)]}case"Multinomial":{let 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s=o.cast(v("condition",r,t,e),"bool"),i=[await o.whereAsync(s)];return s.dispose(),i}case"ListDiff":return o.setdiff1dAsync(v("x",r,t,e),v("y",r,t,e));default:throw TypeError(`Node type ${r.op} is not implemented`)}};var WD=(r,t,e,n=ae)=>{switch(r.op){case"LowerBound":{let o=v("sortedSequence",r,t,e),s=v("values",r,t,e);return[n.lowerBound(o,s)]}case"TopKV2":{let o=v("x",r,t,e),s=v("k",r,t,e),i=v("sorted",r,t,e),a=n.topk(o,s,i);return[a.values,a.indices]}case"UpperBound":{let o=v("sortedSequence",r,t,e),s=v("values",r,t,e);return[n.upperBound(o,s)]}case"Unique":{let o=v("x",r,t,e),s=n.unique(o);return[s.values,s.indices]}case"UniqueV2":{let o=v("x",r,t,e),s=v("axis",r,t,e),i=n.unique(o,s);return[i.values,i.indices]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var UD=(r,t,e,n=ae)=>{switch(r.op){case"Const":return t[r.name];case"PlaceholderWithDefault":let o=v("default",r,t,e);return[yr(r.name,t,e)||o];case"Placeholder":return[yr(r.name,t,e)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":{let c=v("x",r,t,e);return[Xs(c)]}case"IdentityN":return v("x",r,t,e).map(c=>Xs(c));case"Snapshot":let s=v("x",r,t,e);return[Xs(s)];case"Shape":return[n.tensor1d(v("x",r,t,e).shape,"int32")];case"ShapeN":return v("x",r,t,e).map(c=>n.tensor1d(c.shape));case"Size":return[n.scalar(v("x",r,t,e).size,"int32")];case"Rank":return[n.scalar(v("x",r,t,e).rank,"int32")];case"NoOp":return[n.scalar(1)];case"Print":let i=v("x",r,t,e),a=v("data",r,t,e),u=v("message",r,t,e),l=v("summarize",r,t,e);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(u);for(let c=0;c<a.length;c++)console.log(Array.prototype.slice.call(a[c].dataSync()).slice(0,l));return[i];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var Ob=class{constructor(t,e){this.keyDType=t,this.valueDType=e,this.handle=mt(0),this.tensorMap=new Map,De(this.handle)}get id(){return this.handle.id}clearAndClose(){this.tensorMap.forEach(t=>t.dispose()),this.tensorMap.clear(),this.handle.dispose()}size(){return this.tensorMap.size}tensorSize(){return mt(this.size(),"int32")}async import(t,e){this.checkKeyAndValueTensor(t,e);let n=await t.data();return this.tensorMap.forEach(o=>o.dispose()),this.tensorMap.clear(),B(()=>{let o=vr(e),s=n.length,i=o.length;y.assert(s===i,()=>`The number of elements doesn't match, keys has ${s} elements, the values has ${i} elements.`);for(let a=0;a<s;a++){let u=n[a],l=o[a];De(l),this.tensorMap.set(u,l)}return this.handle})}async find(t,e){this.checkKeyAndValueTensor(t,e);let n=await t.data();return B(()=>{let o=[];for(let s=0;s<n.length;s++){let i=n[s],a=this.findWithDefault(i,e);o.push(a)}return rr(o)})}findWithDefault(t,e){let n=this.tensorMap.get(t);return 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qD=(r,t,e,n=ae)=>{switch(r.op){case"ResizeBilinear":{let o=v("images",r,t,e),s=v("size",r,t,e),i=v("alignCorners",r,t,e),a=v("halfPixelCenters",r,t,e);return[n.image.resizeBilinear(o,[s[0],s[1]],i,a)]}case"ResizeNearestNeighbor":{let o=v("images",r,t,e),s=v("size",r,t,e),i=v("alignCorners",r,t,e),a=v("halfPixelCenters",r,t,e);return[n.image.resizeNearestNeighbor(o,[s[0],s[1]],i,a)]}case"CropAndResize":{let o=v("image",r,t,e),s=v("boxes",r,t,e),i=v("boxInd",r,t,e),a=v("cropSize",r,t,e),u=v("method",r,t,e),l=v("extrapolationValue",r,t,e);return[n.image.cropAndResize(o,s,i,a,u,l)]}case"ImageProjectiveTransformV3":{let o=v("images",r,t,e),s=v("transforms",r,t,e),i=v("outputShape",r,t,e),a=v("fillValue",r,t,e),u=v("interpolation",r,t,e),l=v("fillMode",r,t,e);return[n.image.transform(o,s,u.toLowerCase(),l.toLowerCase(),a,i)]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var KD=(r,t,e,n=ae)=>{switch(r.op){case"Equal":return[n.equal(v("a",r,t,e),v("b",r,t,e))];case"NotEqual":return[n.notEqual(v("a",r,t,e),v("b",r,t,e))];case"Greater":return[n.greater(v("a",r,t,e),v("b",r,t,e))];case"GreaterEqual":return[n.greaterEqual(v("a",r,t,e),v("b",r,t,e))];case"Less":return[n.less(v("a",r,t,e),v("b",r,t,e))];case"LessEqual":return[n.lessEqual(v("a",r,t,e),v("b",r,t,e))];case"LogicalAnd":return[n.logicalAnd(v("a",r,t,e),v("b",r,t,e))];case"LogicalNot":return[n.logicalNot(v("a",r,t,e))];case"LogicalOr":return[n.logicalOr(v("a",r,t,e),v("b",r,t,e))];case"Select":case"SelectV2":return[n.where(v("condition",r,t,e),v("a",r,t,e),v("b",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var jD=(r,t,e,n=ae)=>{switch(r.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[n.matMul(v("a",r,t,e),v("b",r,t,e),v("transposeA",r,t,e),v("transposeB",r,t,e))];case"Einsum":return[n.einsum(v("equation",r,t,e),...v("tensors",r,t,e))];case"Transpose":return[n.transpose(v("x",r,t,e),v("perm",r,t,e))];case"_FusedMatMul":let[o,s]=v("fusedOps",r,t,e),i=o==="biasadd",a=s==="prelu",u=v("numArgs",r,t,e),l=v("leakyreluAlpha",r,t,e);if(i){if(a&&u!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!a&&u!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[c,p]=v("args",r,t,e);return[n.fused.matMul({a:v("a",r,t,e),b:v("b",r,t,e),transposeA:v("transposeA",r,t,e),transposeB:v("transposeB",r,t,e),bias:c,activation:s,preluActivationWeights:p,leakyreluAlpha:l})];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var XD=(r,t,e,n=ae)=>{switch(r.op){case"EuclideanNorm":return[n.euclideanNorm(v("x",r,t,e),v("axis",r,t,e),v("keepDims",r,t,e))];case"FusedBatchNorm":case"FusedBatchNormV2":return[n.batchNorm(v("x",r,t,e),v("mean",r,t,e),v("variance",r,t,e),v("offset",r,t,e),v("scale",r,t,e),v("epsilon",r,t,e))];case"FusedBatchNormV3":return[n.batchNorm(v("x",r,t,e),v("mean",r,t,e),v("variance",r,t,e),v("offset",r,t,e),v("scale",r,t,e),v("epsilon",r,t,e))];case"LRN":return[n.localResponseNormalization(v("x",r,t,e),v("radius",r,t,e),v("bias",r,t,e),v("alpha",r,t,e),v("beta",r,t,e))];case"Softmax":return[n.softmax(v("x",r,t,e))];case"LogSoftmax":return[n.logSoftmax(v("x",r,t,e))];case"SparseToDense":return[n.sparseToDense(v("sparseIndices",r,t,e),v("outputShape",r,t,e),v("sparseValues",r,t,e),v("defaultValue",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var YD=(r,t,e,n=ae)=>{switch(r.op){case"Max":{let 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o=v("x",r,t,e),s=v("weights",r,t,e),i=v("size",r,t,e);return[n.bincount(o,s,i)];case"DenseBincount":{let a=v("x",r,t,e),u=v("weights",r,t,e),l=v("size",r,t,e),c=v("binaryOutput",r,t,e);return[n.denseBincount(a,u,l,c)]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var ZD=(r,t,e,n=ae)=>{switch(r.op){case"ConcatV2":case"Concat":{let o=v("n",r,t,e),s=v("axis",r,t,e),i=v("tensors",r,t,e);return i=i.slice(0,o),[n.concat(i,s)]}case"Gather":{let o=v("x",r,t,e),s=v("indices",r,t,e);return[n.gather(o,n.cast(s,"int32"),0)]}case"GatherV2":{let o=v("axis",r,t,e),s=v("batchDims",r,t,e),i=v("x",r,t,e),a=v("indices",r,t,e);return[n.gather(i,n.cast(a,"int32"),o,s)]}case"Reverse":{let o=v("dims",r,t,e),s=[];for(let a=0;a<o.length;a++)o[a]&&s.push(a);let i=v("x",r,t,e);return[n.reverse(i,s)]}case"ReverseV2":{let o=v("axis",r,t,e),s=v("x",r,t,e);return[n.reverse(s,o)]}case"Slice":{let o=v("begin",r,t,e),s=v("size",r,t,e);return[n.slice(v("x",r,t,e),o,s)]}case"StridedSlice":{let 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o=v("x",r,t,e),s=v("indices",r,t,e);return[n.gatherND(o,s)]}case"SparseToDense":{let o=v("sparseIndices",r,t,e),s=v("outputShape",r,t,e),i=v("sparseValues",r,t,e),a=v("defaultValue",r,t,e);return[n.sparseToDense(o,i,s,i.dtype===a.dtype?a:n.cast(a,i.dtype))]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var JD=(r,t,e,n=ae)=>{switch(r.op){case"SparseFillEmptyRows":{let{outputIndices:o,outputValues:s,emptyRowIndicator:i,reverseIndexMap:a}=n.sparse.sparseFillEmptyRows(v("indices",r,t,e),v("values",r,t,e),v("denseShape",r,t,e),v("defaultValue",r,t,e));return[o,s,i,a]}case"SparseReshape":{let{outputIndices:o,outputShape:s}=n.sparse.sparseReshape(v("inputIndices",r,t,e),v("inputShape",r,t,e),v("newShape",r,t,e));return[o,s]}case"SparseSegmentMean":return[n.sparse.sparseSegmentMean(v("data",r,t,e),v("indices",r,t,e),v("segmentIds",r,t,e))];case"SparseSegmentSum":return[n.sparse.sparseSegmentSum(v("data",r,t,e),v("indices",r,t,e),v("segmentIds",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var QD=(r,t,e,n=ae)=>{switch(r.op){case"FFT":return[n.fft(v("x",r,t,e))];case"IFFT":return[n.ifft(v("x",r,t,e))];case"RFFT":return[n.rfft(v("x",r,t,e))];case"IRFFT":return[n.irfft(v("x",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var tR=(r,t,e,n=ae)=>{switch(r.op){case"StringNGrams":{let{nGrams:o,nGramsSplits:s}=n.string.stringNGrams(v("data",r,t,e),v("dataSplits",r,t,e),v("separator",r,t,e),v("nGramWidths",r,t,e),v("leftPad",r,t,e),v("rightPad",r,t,e),v("padWidth",r,t,e),v("preserveShortSequences",r,t,e));return[o,s]}case"StringSplit":{let{indices:o,values:s,shape:i}=n.string.stringSplit(v("input",r,t,e),v("delimiter",r,t,e),v("skipEmpty",r,t,e));return[o,s,i]}case"StringToHashBucketFast":return[n.string.stringToHashBucketFast(v("input",r,t,e),v("numBuckets",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var eR=(r,t,e,n=ae)=>{switch(r.op){case"Cast":return[n.cast(v("x",r,t,e),v("dtype",r,t,e))];case"ExpandDims":{let o=v("axis",r,t,e);return[n.expandDims(v("x",r,t,e),o)]}case"Squeeze":{let o=v("axis",r,t,e);return[n.squeeze(v("x",r,t,e),o)]}case"Reshape":return[n.reshape(v("x",r,t,e),v("shape",r,t,e))];case"MirrorPad":return[n.mirrorPad(v("x",r,t,e),v("padding",r,t,e),v("mode",r,t,e))];case"PadV2":case"Pad":return[n.pad(v("x",r,t,e),v("padding",r,t,e),v("constantValue",r,t,e))];case"SpaceToBatchND":{let o=v("blockShape",r,t,e),s=v("paddings",r,t,e);return[n.spaceToBatchND(v("x",r,t,e),o,s)]}case"BatchToSpaceND":{let o=v("blockShape",r,t,e),s=v("crops",r,t,e);return[n.batchToSpaceND(v("x",r,t,e),o,s)]}case"DepthToSpace":{let o=v("blockSize",r,t,e),s=v("dataFormat",r,t,e).toUpperCase();return[n.depthToSpace(v("x",r,t,e),o,s)]}case"BroadcastTo":return[n.broadcastTo(v("x",r,t,e),v("shape",r,t,e))];case"BroadcastArgs":return[n.broadcastArgs(v("s0",r,t,e),v("s1",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};function lN(r,t,e,n,o=B){let s=((i,a,u)=>{switch(i.category){case"arithmetic":return o(()=>$D(i,a,u));case"basic_math":return o(()=>DD(i,a,u));case"control":return MD(i,a,u);case"convolution":return o(()=>BD(i,a,u));case"creation":return o(()=>VD(i,a,u));case"dynamic":return GD(i,a,u);case"evaluation":return o(()=>WD(i,a,u));case"image":return o(()=>qD(i,a,u));case"graph":return o(()=>UD(i,a,u));case"logical":return o(()=>KD(i,a,u));case"matrices":return o(()=>jD(i,a,u));case"normalization":return o(()=>XD(i,a,u));case"reduction":return o(()=>YD(i,a,u));case"slice_join":return o(()=>ZD(i,a,u));case"sparse":return o(()=>JD(i,a,u));case"spectral":return o(()=>QD(i,a,u));case"string":return o(()=>tR(i,a,u));case"transformation":return o(()=>eR(i,a,u));case"hash_table":return HD(i,a,u,n);case"custom":let l=wb(i.op);if(l&&l.customExecutor)return l.customExecutor(new Db(i,a,u));throw TypeError(`Custom op ${i.op} is not registered.`);default:throw TypeError(`Unknown op '${i.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,t,e);return y.isPromise(s)?s.then(i=>[].concat(i)):[].concat(s)}var Ah=class{constructor(t={},e={},n={},o={}){this.weightMap=t,this.tensorArrayMap=e,this.tensorListMap=n,this.functionMap=o,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}newFrame(t,e){return{id:t,frameName:e,iterationId:0}}set currentContext(t){this.contexts!==t&&(this.contexts=t,this.generateCurrentContextIds())}get currentContext(){return this.contexts}get currentContextId(){return this._currentContextIds[0]}get currentContextIds(){return this._currentContextIds}generateCurrentContextIds(){let t=[];for(let e=0;e<this.contexts.length-1;e++){let n=this.contexts.slice(0,this.contexts.length-e);t.push(this.contextIdforContexts(n))}t.push(""),this._currentContextIds=t}contextIdforContexts(t){return t?t.map(e=>e.id===0&&e.iterationId===0?"":`${e.frameName}-${e.iterationId}`).join("/"):""}enterFrame(t){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,t)),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 t=Object.assign({},this.contexts[this.contexts.length-1]);t.iterationId+=1,t.id=this.lastId,this.contexts.splice(-1,1,t),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}else throw new Error("Cannot increase frame iteration, the context is empty")}getWeight(t){return this.weightMap[t]}addTensorArray(t){this.tensorArrayMap[t.id]=t}getTensorArray(t){return this.tensorArrayMap[t]}addTensorList(t){this.tensorListMap[t.id]=t}getTensorList(t){return this.tensorListMap[t]}dispose(t){for(let e in this.tensorArrayMap)this.tensorArrayMap[e].clearAndClose(t);for(let e in this.tensorListMap)this.tensorListMap[e].clearAndClose(t)}};function uN(r,t,e,n){let o=new Set,s=[],i=null,a=null,u=new Set,l=Object.keys(r).map(m=>gn(m)[0]),c=[];n!=null&&(c=n.map(m=>gn(m.name)[0]));let p=[...t];for(;p.length>0;){let m=p.pop();if((cN(m)||y7(m)||b7(m))&&i==null&&(i=m,a=i.children.map(f=>f.name).filter(f=>o.has(f))),o.add(m.name),e[m.name]==null&&l.indexOf(m.name)===-1&&c.indexOf(m.name)===-1){if(m.inputs.length===0){s.push(m.name);continue}m.inputs.forEach(f=>{u.has(f.name)||(u.add(f.name),p.push(f))})}}return{inputs:r,outputs:t,usedNodes:o,missingInputs:s,dynamicNode:i,syncInputs:a}}function rR(r,t,e){let{usedNodes:n,inputs:o}=e,s=[],i=Object.keys(o).map(c=>gn(c)[0]).map(c=>r.nodes[c]),a=r.initNodes;i.forEach(c=>{n.has(c.name)&&s.push(c)}),r.weights.forEach(c=>{n.has(c.name)&&s.push(c)}),a!=null&&a.forEach(c=>{n.has(c.name)&&s.push(c)});let u=new Set,l=[];for(;s.length>0;){let c=s.pop();u.add(c.name),t[c.name]||l.push(c),c.children.forEach(p=>{!u.has(p.name)&&n.has(p.name)&&p.inputs.every(m=>u.has(m.name))&&s.push(p)})}return l}var h7=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],g7=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],x7=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function cN(r){return h7.indexOf(r.op)>=0}function y7(r){return g7.indexOf(r.op)>=0}function b7(r){return x7.indexOf(r.op)>=0}var Nc=class{constructor(t,e){this.graph=t,this.parent=e,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this.intermediateTensors={},this.keepTensorForDebug=!1,this._outputs=t.outputs,this._inputs=t.inputs,this._initNodes=t.initNodes,this._signature=t.signature,this._functions=t.functions,t.functions!=null&&Object.keys(t.functions).forEach(n=>{this._functionExecutorMap[n]=new Nc(t.functions[n],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(t){let e=Object.keys(t).map(n=>t[n].map(o=>o.id));this._weightIds=[].concat(...e),this._weightMap=t}set resourceManager(t){this._resourceManager=t}get inputs(){return this._inputs.map(t=>({name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(t=>({name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(t=>t.signatureKey||t.name)}get outputNodes(){return this._outputs.map(t=>{let e=t.signatureKey||t.name;return t.defaultOutput?`${e}:${t.defaultOutput}`:e})}get functions(){return Object.keys(this._functions).reduce((t,e)=>(t[e]=this._functions[e].signature,t),{})}getCompilationKey(t,e){let n=t.map(s=>s.name).sort(),o=e.map(s=>s.name).sort();return n.join(this.SEPERATOR)+"--"+o.join(this.SEPERATOR)}compile(t,e){let n=uN(t,e,this.weightMap,this._initNodes),{missingInputs:o,dynamicNode:s,syncInputs:i}=n;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 [${i}]`);if(o.length>0){let a=e.map(l=>l.name),u=Object.keys(t);throw new Error(`Cannot compute the outputs [${a}] from the provided inputs [${u}]. Missing the following inputs: [${o}]`)}return rR(this.graph,this.weightMap,n)}execute(t,e){t=this.mapInputs(t);let n=Object.keys(t).sort();this.checkInputs(t),this.checkInputShapeAndType(t),e=this.mapOutputs(e),this.checkOutputs(e);let o=n.map(p=>this.graph.nodes[gn(p)[0]]),s=e.map(p=>gn(p)[0]),i=s.map(p=>this.graph.nodes[p]);this.resetIntermediateTensors(),i.length===0&&(i=this._outputs);let a=this.getCompilationKey(o,i),u=this.compiledMap.get(a);u==null&&(u=this.compile(t,i),this.compiledMap.set(a,u));let l={},c={};return B(()=>{let p=new Ah(this.weightMap,l,c,this.functionExecutorMap),m=Object.assign({},this.weightMap);Object.keys(t).forEach(h=>{let[g,x]=gn(h),b=[];b[x]=t[h],m[g]=b});let f=this.getFrozenTensorIds(m),d={};for(let h=0;h<u.length;h++){let g=u[h];if(!m[g.name]){let x=lN(g,m,p,this._resourceManager);if(y.isPromise(x))throw new Error(`The execution of the op '${g.op}' returned a promise. Please use model.executeAsync() instead.`);m[g.name]=x,this.checkTensorForDisposal(g.name,g,m,p,f,s,d)}}return this.parent==null&&p.dispose(f),e.map(h=>yr(h,m,p))})}getFrozenTensorIds(t){let e=[].concat.apply([],Object.keys(t).map(n=>t[n]).map(n=>n.map(o=>o.id)));return new Set(e)}checkTensorForDisposal(t,e,n,o,s,i,a){e.category==="control"||i.indexOf(t)!==-1||(n[t].forEach(u=>{u!=null&&(a[u.id]=(a[u.id]||0)+e.children.length)}),e.inputs.forEach(u=>{if(u.category!=="control"){let l=TD(u.name,n,o);l!=null&&l.forEach(c=>{if(c&&!c.kept&&!s.has(c.id)){let p=a[c.id];if(p===1){if(!this.keepTensorForDebug)c.dispose();else{let[m,f]=Eo(e.name,o);this.intermediateTensors[m]?this.intermediateTensors[m][f]=c:(this.intermediateTensors[m]=[],this.intermediateTensors[m][f]=c)}delete a[c.id]}else p!=null&&a[c.id]--}})}}))}async executeAsync(t,e){return this._executeAsync(t,e)}disposeIntermediateTensors(){!this.intermediateTensors||(Object.keys(this.intermediateTensors).forEach(t=>this.intermediateTensors[t].forEach(e=>e.dispose())),this.disposeTensorsMap())}disposeTensorsMap(){!this.tensorsMap||Object.keys(this.tensorsMap).forEach(t=>{this.tensorsMap[t].forEach(n=>{n&&!n.kept&&!n.isDisposed&&!this.keepIds.has(n.id)&&n.dispose()})})}getIntermediateTensors(){return this.tensorsMap}resetIntermediateTensors(){for(let t in this.intermediateTensors)this.intermediateTensors[t].forEach(e=>e.dispose()),delete this.intermediateTensors[t]}async _executeAsync(t,e,n=!1,o={},s={}){n||(t=this.mapInputs(t),this.checkInputs(t),this.checkInputShapeAndType(t),e=this.mapOutputs(e),this.checkOutputs(e));try{this.keepTensorForDebug=M().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(c){console.warn(c.message)}this.resetIntermediateTensors();let i=new Ah(this.weightMap,o,s,this.functionExecutorMap);this.tensorsMap=await this.executeWithControlFlow(t,i,e,n);let a=e.map(c=>yr(c,this.tensorsMap,i)),u=a.map(c=>c.id),l=Object.keys(t).map(c=>t[c].id);return this.keepIds=new Set([...u,...l,...this.weightIds]),this.keepTensorForDebug||this.disposeTensorsMap(),this.parent==null&&i.dispose(this.keepIds),a}async executeFunctionAsync(t,e,n){let o=t.reduce((s,i,a)=>(s[this.inputs[a].name]=i,s),{});return this._executeAsync(o,this.outputNodes,!0,e,n)}async executeWithControlFlow(t,e,n,o){let s=Object.keys(t),i=s.map(w=>this.graph.nodes[gn(w)[0]]),a=n.map(w=>gn(w)[0]),u=a.map(w=>this.graph.nodes[w]);u.length===0&&(u=this._outputs);let{usedNodes:l,missingInputs:c,dynamicNode:p,syncInputs:m}=uN(t,u,this.weightMap,this._initNodes),f=[...i,...this.graph.weights,...this._initNodes||[]].map(w=>({node:w,contexts:e.currentContext})),d=Object.assign({},this.weightMap);Object.keys(t).forEach(w=>{let[C,N]=gn(w),_=[];_[N]=t[w],d[C]=_});let h={},g=this.getFrozenTensorIds(d),x={};for(;f.length>0;){let w=this.processStack(i,f,e,d,x,g,a,h,l);await Promise.all(w)}p==null&&!o&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let b=u.filter(w=>!cN(w)&&!yr(w.name,d,e)).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}]. ${w}`)}return d}processStack(t,e,n,o,s,i,a,u,l){let c=[];for(;e.length>0;){let p=e.pop();n.currentContext=p.contexts;let m="";if(p.node.op==="Enter"&&v("isConstant",p.node,o,n)&&([m]=Eo(p.node.name,n)),o[p.node.name]==null){let f=lN(p.node,o,n,this._resourceManager);m||([m]=Eo(p.node.name,n));let d=n.currentContext;y.isPromise(f)?c.push(f.then(h=>(o[m]=h,n.currentContext=d,this.checkTensorForDisposal(m,p.node,o,n,i,a,u),this.processChildNodes(p.node,e,n,o,s,l),h))):(o[m]=f,this.checkTensorForDisposal(m,p.node,o,n,i,a,u),this.processChildNodes(p.node,e,n,o,s,l))}else this.processChildNodes(p.node,e,n,o,s,l)}return c}processChildNodes(t,e,n,o,s,i){t.children.forEach(a=>{let[u]=Eo(a.name,n);s[u]||!i.has(a.name)||(a.op==="Merge"?a.inputNames.some(l=>!!yr(l,o,n))&&(s[u]=!0,e.push({contexts:n.currentContext,node:a})):a.inputNames.every(l=>!!yr(l,o,n))&&(s[u]=!0,e.push({contexts:n.currentContext,node:a})))})}dispose(){Object.keys(this.weightMap).forEach(t=>this.weightMap[t].forEach(e=>e.dispose()))}checkInputShapeAndType(t){Object.keys(t).forEach(e=>{let n=t[e],[o]=gn(e),s=this.graph.nodes[o];if(s.attrParams.shape&&s.attrParams.shape.value){let i=s.attrParams.shape.value,a=i.length===n.shape.length&&n.shape.every((u,l)=>i[l]===-1||i[l]===u);y.assert(a,()=>`The shape of dict['${s.name}'] provided in model.execute(dict) must be [${i}], but was [${n.shape}]`)}s.attrParams.dtype&&s.attrParams.dtype.value&&y.assert(n.dtype===s.attrParams.dtype.value,()=>`The dtype of dict['${s.name}'] provided in model.execute(dict) must be ${s.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(t){let e={};for(let n in t)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let o=this._signature.inputs[n];e[o.name]=t[n]}else e[n]=t[n];return e}checkInputs(t){let e=Object.keys(t).filter(n=>{let[o]=gn(n);return this.graph.nodes[o]==null});if(e.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${e}] that are not part of graph`)}mapOutputs(t){return t.map(e=>this._signature!=null&&this._signature.outputs!=null&&this._signature.outputs[e]!=null?this._signature.outputs[e].name:e,{})}checkOutputs(t){t.forEach(e=>{let[n]=gn(e);if(!this.graph.nodes[n])throw new Error(`The output '${e}' is not found in the graph`)})}};var Pb=class{constructor(t={},e={}){this.hashTableNameToHandle=t,this.hashTableMap=e}addHashTable(t,e){this.hashTableNameToHandle[t]=e.handle,this.hashTableMap[e.id]=e}getHashTableHandleByName(t){return this.hashTableNameToHandle[t]}getHashTableById(t){return this.hashTableMap[t]}dispose(){for(let t in this.hashTableMap)this.hashTableMap[t].clearAndClose(),delete this.hashTableMap[t];for(let t in this.hashTableNameToHandle)this.hashTableNameToHandle[t].dispose(),delete this.hashTableNameToHandle[t]}};var w7="?tfjs-format=file",C7="model.json",$h=class{constructor(t,e={},n=Er){this.modelUrl=t,this.loadOptions=e,this.version="n/a",this.io=n,e==null&&(this.loadOptions={}),this.resourceManager=new Pb}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}findIOHandler(){let t=this.modelUrl;if(t.load!=null)this.handler=t;else if(this.loadOptions.requestInit!=null)this.handler=this.io.browserHTTPRequest(t,this.loadOptions);else{let e=this.io.getLoadHandlers(t,this.loadOptions);if(e.length===0)e.push(this.io.browserHTTPRequest(t,this.loadOptions));else if(e.length>1)throw new Error(`Found more than one (${e.length}) load handlers for URL '${[t]}'`);this.handler=e[0]}}load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let t=this.handler.load();return y.isPromise(t)?t.then(e=>this.loadSync(e)):this.loadSync(t)}loadSync(t){this.artifacts=t;let e=this.artifacts.modelTopology,n=this.artifacts.signature;if(this.artifacts.userDefinedMetadata!=null){let s=this.artifacts.userDefinedMetadata;s.signature!=null&&(n=s.signature),s.structuredOutputKeys!=null&&(this.structuredOutputKeys=s.structuredOutputKeys)}this.signature=n,this.version=`${e.versions.producer}.${e.versions.minConsumer}`;let o=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new Nc(_h.Instance.transformGraph(e,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(o),this.executor.resourceManager=this.resourceManager,t.modelInitializer!=null&&t.modelInitializer.node!=null){let s=_h.Instance.transformGraph(t.modelInitializer);this.initializer=new Nc(s),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(t,e){if(typeof t=="string"){let n=this.io.getSaveHandlers(t);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${t}'`);if(n.length>1)throw new Error(`Found more than one (${n.length}) save handlers for URL '${t}'`);t=n[0]}if(t.save==null)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return t.save(this.artifacts)}predict(t,e){let n=this.execute(t,this.outputNodes);if(this.structuredOutputKeys){let o=n instanceof Ft?[n]:n,s={};return o.forEach((i,a)=>s[this.structuredOutputKeys[a]]=i),s}return n}normalizeInputs(t){if(!(t instanceof Ft)&&!Array.isArray(t))return t;if(t=Array.isArray(t)?t:[t],t.length!==this.inputNodes.length)throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${t.length} input tensors.`);return this.inputNodes.reduce((e,n,o)=>(e[n]=t[o],e),{})}normalizeOutputs(t){return t=t||this.outputNodes,Array.isArray(t)?t:[t]}execute(t,e){t=this.normalizeInputs(t),e=this.normalizeOutputs(e);let n=this.executor.execute(t,e);return n.length>1?n:n[0]}async executeAsync(t,e){t=this.normalizeInputs(t),e=this.normalizeOutputs(e);let n=await this.executor.executeAsync(t,e);return n.length>1?n:n[0]}getIntermediateTensors(){return 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Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}};var jf=class extends Je{constructor(t){super(),this.microphoneConfig=t,this.isClosed=!1,this.fftSize=t.fftSize||1024;let e=Math.log2(this.fftSize);if(this.fftSize<0||e<4||e>14||!Number.isInteger(e))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=t.numFramesPerSpectrogram||43,this.sampleRateHz=t.sampleRateHz,this.columnTruncateLength=t.columnTruncateLength||this.fftSize,this.audioTrackConstraints=t.audioTrackConstraints,this.smoothingTimeConstant=t.smoothingTimeConstant||0,this.includeSpectrogram=t.includeSpectrogram!==!1,this.includeWaveform=t.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(t={}){if(!M().get("IS_BROWSER"))throw new Error("microphone API is only supported in browser environment.");let e=new jf(t);return await e.start(),e}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 t=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new t,!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 e=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,e.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 t,e,n=await this.getAudioData();if(this.includeSpectrogram){let o=this.flattenQueue(n.freqDataQueue);t=this.getTensorFromAudioDataArray(o,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let o=this.flattenQueue(n.timeDataQueue);e=this.getTensorFromAudioDataArray(o,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:t,waveform:e},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let t=[],e=[],n=0;return new Promise(o=>{let s=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&o({freqDataQueue:t,timeDataQueue:e}),t.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),e.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(s),o({freqDataQueue:t,timeDataQueue:e}))},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(t){let e=t[0].length,n=new Float32Array(t.length*e);return t.forEach((o,s)=>n.set(o,s*e)),n}getTensorFromAudioDataArray(t,e){let n=new Float32Array(y.sizeFromShape(e));return n.set(t,n.length-t.length),wr(n,e)}};var Xf=class extends Je{constructor(t,e){if(super(),this.webcamVideoElement=t,this.webcamConfig=e,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=Le([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,o=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,s=(1-n)/2,i=(1-o)/2,a=s+n,u=o+i;this.cropBox=Bs([i,s,u,a],[1,4])}else this.cropBox=Bs([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(t,e={}){if(!M().get("IS_BROWSER"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!t){if(t=document.createElement("video"),!e.resizeWidth||!e.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");t.width=e.resizeWidth,t.height=e.resizeHeight}let n=new Xf(t,e);return await n.start(),n}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(t){throw t.message=`Error thrown while initializing video stream: ${t.message}`,t}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(t){console.log(t),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(t=>{this.webcamVideoElement.onloadedmetadata=()=>{t()}})}async next(){if(this.isClosed)return{value:null,done:!0};let t;try{t=Jg.fromPixels(this.webcamVideoElement)}catch(e){throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(e)}`)}if(this.resize)try{return{value:this.cropAndResizeFrame(t),done:!1}}catch(e){throw new Error(`Error thrown cropping the video: ${e.message}`)}finally{t.dispose()}else return{value:t,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(t){return B(()=>{let e=gr(J(t,"float32"),0),n;n=lu.cropAndResize(e,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let o=n.shape;return D(n,o.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}};var Yf=class{};var Fh=class extends Je{split(t){return new TN(this,t)}},TN=class extends Fh{constructor(t,e){super(),this.upstream=t,this.impl=new EN(t,e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},EN=class extends Tc{constructor(t,e){super(),this.upstream=t,this.separator=e,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let t=await this.upstream.next();if(t.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let e=t.value.split(this.separator);e[0]=this.carryover+e[0];for(let n of e.slice(0,-1))this.outputQueue.push(n);return this.carryover=e[e.length-1],!0}};var Ub=class extends Je{decodeUTF8(){return new _N(this)}},_N=class extends Fh{constructor(t){super(),this.upstream=t,this.impl=new AN(t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},AN=class extends Tc{constructor(t){if(super(),this.upstream=t,M().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:e}=pN();this.decoder=new e("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let t=await this.upstream.next(),e;if(t.done)return!1;e=t.value;let n;return M().get("IS_BROWSER")?n=this.decoder.decode(e,{stream:!0}):n=this.decoder.write(Buffer.from(e.buffer)),this.outputQueue.push(n),!0}};var Zf=class extends Ub{constructor(t,e={}){super(),this.file=t,this.options=e,y.assert(t instanceof Uint8Array||(M().get("IS_BROWSER")?t instanceof File||t instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=e.offset||0,this.chunkSize=e.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,n)=>{let o=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,o)));else{let s=new FileReader;s.onload=a=>{let u=s.result;if(u instanceof 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Yf{constructor(t,e={}){super(),this.url=t,this.fileOptions=e}async iterator(){return Hb(this.url)?new Jf(this.url,this.fileOptions).iterator():xR(this.url,this.fileOptions)}};function yR(r,t={}){return new Kf(new Qf(r),t)}function bR(r){let t=Dh(r);return kn(async()=>t)}function wR(r){return kn(async()=>{let t=await r();return Dh(()=>t.next())})}async function CR(r,t){return Xf.create(r,t)}async function IR(r){return jf.create(r)}var $N="3.21.0";function tt(r,t){Array.isArray(r)||(r=[r]),r.forEach(e=>{e!=null&&y.assert(e.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}var A7=Wr.whereImpl,Su=class extends Mo{constructor(){super(),this.blockSize=48,this.firstUse=!0,this.data=new ta(this,ho())}nextDataId(){return Su.nextDataId++}write(t,e,n){this.firstUse&&(this.firstUse=!1,M().get("IS_NODE")&&S.warn(`
============================
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Do=S.RowPartitionType,od=class{constructor(t,e,n,o,s,i,a,u,l,c){this.shape=t,this.shapeShape=e,this.values=n,this.valuesShape=o,this.valuesDType=s,this.defaultValue=i,this.defaultValueShape=a,this.rowPartitionValues=u,this.rowPartitionValuesShapes=l,this.rowPartitionTypes=S.getRowPartitionTypesHelper(c),this.raggedRank=S.getRaggedRank(this.rowPartitionTypes)}getRowPartitionTypeByDimension(t){return this.rowPartitionTypes[0]===Do.FIRST_DIM_SIZE?this.rowPartitionTypes[t+1]:this.rowPartitionTypes[t]}getRowPartitionTensor(t){return this.rowPartitionTypes[0]===Do.FIRST_DIM_SIZE?this.rowPartitionValues[t+1]:this.rowPartitionValues[t]}getMaxWidth(t){let e=this.getRowPartitionTensor(t-1);switch(this.getRowPartitionTypeByDimension(t-1)){case Do.VALUE_ROWIDS:return od.getMaxWidthValueRowID(e);case Do.ROW_SPLITS:return od.getMaxWidthRowSplit(e);default:throw new Error(`Cannot handle partition type ${Do[this.getRowPartitionTypeByDimension(t-1)]}`)}}static getMaxWidthRowSplit(t){let e=t.length;if(e===0||e===1)return 0;let n=0;for(let o=0;o<e-1;++o){let s=t[o+1]-t[o];s>n&&(n=s)}return n}static getMaxWidthValueRowID(t){let e=t.length;if(e===0)return 0;let n=0,o=t[0],s=0;for(let i=1;i<e;++i){let a=t[i];a!==o&&(o=a,s=Math.max(i-n,s),n=i)}return Math.max(e-n,s)}tensorShapeFromTensor(t,e,n=!0){if(e.length===0){if(t[0]===-1)return[];throw new Error("The only valid scalar shape tensor is the fully unknown shape specified as -1.")}return XR(t,n)}calculateOutputSize(t){let e=this.valuesShape,n=this.defaultValueShape;S.validateDefaultValueShape(n,e);let o=this.tensorShapeFromTensor(this.shape,this.shapeShape),i=S.combineRaggedTensorToTensorShapes(this.raggedRank,o,e);i[0]<0&&(i[0]=t);for(let a=1;a<=this.raggedRank;++a)i[a]<0&&(i[a]=this.getMaxWidth(a));return i}calculateFirstParentOutputIndex(t,e,n){let o=Math.min(t,n),s=[],i=0;for(let a=0;a<o;++a,i+=e)s.push(i);for(let a=o;a<t;++a)s.push(-1);return y.assert(s.length===t,()=>"Final length of result must be equal to firstDimension."),s}calculateOutputIndexRowSplit(t,e,n,o){let s=t.length,i=[];for(let a=0;a<s-1;++a){let u=t[a+1]-t[a],l=Math.min(o,u),c=e[a];c===-1&&(l=0);for(let p=0;p<l;++p)i.push(c),c+=n;for(let p=0;p<u-l;++p)i.push(-1)}if(s>0&&i.length!==t[s-1])throw new Error("Invalid row split size.");return i}calculateOutputIndexValueRowID(t,e,n,o){let s=t.length,i=[];if(s===0)return[];let a=0,u=t[0];if(u>=e.length)throw new Error(`Got currentValueRowId=${u}, which is not less than ${e.length}`);let l=e[u];i.push(l);for(let c=1;c<s;++c){let p=t[c];if(p===u)l>=0&&(++a,a<o?l+=n:l=-1);else{if(a=0,u=p,p>=e.length)throw new Error(`Got nextValueRowId=${p} which is not less than ${e.length}`);l=e[p]}i.push(l)}if(i.length!==t.length)throw new Error("Invalid row ids.");return i}calculateOutputIndex(t,e,n,o){let s=this.getRowPartitionTensor(t),i=this.getRowPartitionTypeByDimension(t);switch(i){case Do.VALUE_ROWIDS:return this.calculateOutputIndexValueRowID(s,e,n,o);case Do.ROW_SPLITS:if(s.length-1>e.length)throw new Error(`Row partition size is greater than output size: ${s.length-1} > ${e.length}`);return this.calculateOutputIndexRowSplit(s,e,n,o);default:throw new Error(`Unsupported partition type: ${Do[i]}`)}}getFirstDimensionSize(){let t=this.rowPartitionValues[0];if(this.rowPartitionTypes.length===0)throw new Error("No row_partition_types given.");let e=this.rowPartitionTypes[0];switch(e){case Do.FIRST_DIM_SIZE:return t[0];case Do.VALUE_ROWIDS:throw new Error("Cannot handle VALUE_ROWIDS in first dimension.");case Do.ROW_SPLITS:return this.rowPartitionValuesShapes[0][0]-1;default:throw new Error(`Cannot handle type ${Do[e]}`)}}compute(){if(this.rowPartitionValues[0].length<=0)throw new Error("Invalid first partition input. 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Ro(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{begin:s,size:i}=n;tt(o,"slice");let[a,u]=Pe.parseSliceParams(o,s,i);Pe.assertParamsValid(o,a,u);let l=e.data.get(o.dataId).values,c=$c(l,a,u,o.shape,o.dtype);return e.makeTensorInfo(u,o.dtype,c)}var QR={kernelName:di,backendName:"cpu",kernelFunc:Ro};function tw(r,t,e,n,o,s,i){let a=t[0],u=s[0],l=new Array(u),c=new Array(a),p=t[1];if(u===0){if(a!==0)throw new Error(S.getSparseFillEmptyRowsIndicesDenseShapeMismatch(a));let g=y.getArrayFromDType(e,0),x=y.getArrayFromDType(o,0);return[g,[0,p],x,l,c]}let m=!0,f=0,d=new Array(u).fill(0);for(let g=0;g<a;++g){let x=r[g*p];if(x<0)throw new Error(S.getSparseFillEmptyRowsNegativeIndexErrorMessage(g,x));if(x>=u)throw new Error(S.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(g,x,u));++d[x],m=m&&x>=f,f=x}let h=!0;for(let g=0;g<u;++g){let x=d[g]===0;l[g]=x,h=h&&!x,d[g]=Math.max(d[g],1),g>0&&(d[g]+=d[g-1])}if(h&&m){let g=r,x=n;for(let b=0;b<a;++b)c[b]=b;return[g,[a,p],x,l,c]}else{let 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e.makeTensorInfo(o.shape,o.dtype,h)}var AF={kernelName:ns,backendName:"cpu",kernelFunc:SJ};function NJ(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockShape:s,crops:i}=n;tt([o],"batchToSpaceND");let a=s.reduce((x,b)=>x*b),u=S.getReshaped(o.shape,s,a),l=S.getPermuted(u.length,s.length),c=S.getReshapedPermuted(o.shape,s,a),p=S.getSliceBeginCoords(i,s.length),m=S.getSliceSize(c,i,s.length),f=Xt({inputs:{x:o},backend:e,attrs:{shape:u}}),d=Be({inputs:{x:f},backend:e,attrs:{perm:l}}),h=Xt({inputs:{x:d},backend:e,attrs:{shape:c}}),g=Ro({inputs:{x:h},backend:e,attrs:{begin:p,size:m}});return e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(d),e.disposeIntermediateTensorInfo(h),g}var $F={kernelName:si,backendName:"cpu",kernelFunc:NJ};function kJ(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,weights:s}=t,{size:i}=n,a=e.data.get(o.dataId).values,u=e.data.get(s.dataId).values,l=rd(a,u,s.dtype,s.shape,i);return e.makeTensorInfo([i],s.dtype,l)}var 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qi(r){let{inputs:t,backend:e}=r,{input:n}=t,o=e.data.get(n.dataId).complexTensorInfos.imag,s=e.data.get(o.dataId).values;return e.makeTensorInfo(o.shape,o.dtype,s)}var PF={kernelName:vp,backendName:"cpu",kernelFunc:qi};function Nu(r){let{inputs:t,backend:e,attrs:n}=r,{axis:o}=n,s=y.parseAxisParam(o,t[0].shape)[0],i=t.map(h=>h.shape);S.assertParamsConsistent(i,s);let a=S.computeOutShape(t.map(h=>h.shape),s);if(y.sizeFromShape(a)===0)return e.makeTensorInfo(a,t[0].dtype,[]);let u=t.filter(h=>y.sizeFromShape(h.shape)>0);if(u.length===1)return qr({inputs:{x:u[0]},backend:e});if(u[0].dtype==="complex64"){let h=u.map(C=>_o({inputs:{input:C},backend:e})),g=u.map(C=>qi({inputs:{input:C},backend:e})),x=Nu({inputs:h,backend:e,attrs:{axis:s}}),b=Nu({inputs:g,backend:e,attrs:{axis:s}}),w=br({inputs:{real:x,imag:b},backend:e});return 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AJ(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,pad:a,dataFormat:u,dimRoundingMode:l,filterShape:c}=n;tt([o,s],"conv2dBackpropFilter");let p=S.convertConv2DDataFormat(u),m=S.computeConv2DInfo(o.shape,c,i,1,a,l,!1,p),{strideHeight:f,strideWidth:d,filterHeight:h,filterWidth:g}=m,x=m.dataFormat==="channelsLast",b=new pe(m.filterShape,"float32"),w=m.padInfo.left,C=m.padInfo.top,N=e.data.get(o.dataId).values,_=e.data.get(s.dataId).values,A=new pe(o.shape,o.dtype,N),$=new pe(s.shape,s.dtype,_);for(let F=0;F<h;++F){let P=Math.max(0,Math.ceil((C-F)/f)),V=Math.min(m.outHeight,(m.inHeight+C-F)/f);for(let G=0;G<g;++G){let W=Math.max(0,Math.ceil((w-G)/d)),q=Math.min(m.outWidth,(m.inWidth+w-G)/d);for(let H=0;H<m.inChannels;++H)for(let j=0;j<m.outChannels;++j){let Y=0;for(let Z=0;Z<m.batchSize;++Z)for(let et=P;et<V;++et){let rt=F+et*f-C;for(let ot=W;ot<q;++ot){let at=G+ot*d-w;x?Y+=A.get(Z,rt,at,H)*$.get(Z,et,ot,j):Y+=A.get(Z,H,rt,at)*$.get(Z,j,et,ot)}}b.set(Y,F,G,H,j)}}}return e.makeTensorInfo(b.shape,b.dtype,b.values)}var zF={kernelName:mp,backendName:"cpu",kernelFunc:AJ};function $J(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{inputShape:i,strides:a,pad:u,dataFormat:l,dimRoundingMode:c}=n;tt([o,s],"conv2dBackpropInput");let p=y.computeStrides(s.shape),m=y.computeStrides(o.shape),f=S.convertConv2DDataFormat(l),d=S.computeConv2DInfo(i,s.shape,a,1,u,c,!1,f),h=new pe(d.inShape,"float32"),g=h.values,x=e.data.get(o.dataId).values,b=e.data.get(s.dataId).values,[w,C,N]=p,{batchSize:_,filterHeight:A,filterWidth:$,inChannels:F,inHeight:P,inWidth:V,outChannels:G,outHeight:W,outWidth:q,strideHeight:H,strideWidth:j}=d;f=d.dataFormat;let Y=A-1-d.padInfo.top,Z=$-1-d.padInfo.left,et=f==="channelsLast",rt=h.strides[0],ot=et?h.strides[1]:h.strides[2],at=et?h.strides[2]:1,nt=et?1:h.strides[1],it=m[0],dt=et?m[1]:m[2],ht=et?m[2]:1,bt=et?1:m[1];for(let Tt=0;Tt<_;++Tt)for(let _t=0;_t<F;++_t)for(let Bt=0;Bt<P;++Bt){let 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l=y.computeStrides(o.shape),c=y.computeStrides(s.shape),p=S.computeConv3DInfo(o.shape,u,i,1,a),m=p.strideDepth,f=p.strideHeight,d=p.strideWidth,h=p.filterDepth,g=p.filterHeight,x=p.filterWidth,b=new pe(p.filterShape,"float32"),w=b.values,[C,N,_,A]=b.strides,$=e.data.get(s.dataId).values,[F,P,V,G]=c,W=e.data.get(o.dataId).values,[q,H,j,Y]=l,Z=p.padInfo.front,et=p.padInfo.left,rt=p.padInfo.top;for(let ot=0;ot<h;++ot){let at=Math.max(0,Math.ceil((Z-ot)/m)),nt=Math.min(p.outDepth,(p.inDepth+Z-ot)/m),it=ot*C;for(let dt=0;dt<g;++dt){let ht=Math.max(0,Math.ceil((rt-dt)/f)),bt=Math.min(p.outHeight,(p.inHeight+rt-dt)/f),Tt=dt*N+it;for(let _t=0;_t<x;++_t){let Bt=Math.max(0,Math.ceil((et-_t)/d)),Yt=Math.min(p.outWidth,(p.inWidth+et-_t)/d),ce=_t*_+Tt;for(let he=0;he<p.inChannels;++he){let Kt=he*A+ce;for(let Te=0;Te<p.outChannels;++Te){let fe=0;for(let Ae=0;Ae<p.batchSize;++Ae){let Ge=Ae*q,En=Ae*F;for(let nr=at;nr<nt;++nr){let Or=(ot+nr*m-Z)*H+Ge,qe=nr*P+En;for(let Pr=ht;Pr<bt;++Pr){let 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denseBincount: input must be at most rank 2, but got rank${o.shape.length}.`)}var XF={kernelName:hp,backendName:"cpu",kernelFunc:BJ};function VJ(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockSize:s,dataFormat:i}=n;y.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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GJ(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,dilations:a,pad:u,dimRoundingMode:l,filterShape:c}=n;tt([o,s],"depthwiseConv2dNativeBackpropFilter");let p=S.computeConv2DInfo(o.shape,c,i,a,u,l,!0),{strideHeight:m,strideWidth:f,filterHeight:d,filterWidth:h}=p,g=new pe(p.filterShape,"float32"),x=p.padInfo.left,b=p.padInfo.top,w=p.outChannels/p.inChannels,C=e.data.get(o.dataId).values,N=new pe(o.shape,o.dtype,C),_=e.data.get(s.dataId).values,A=new pe(s.shape,s.dtype,_);for(let $=0;$<d;++$){let F=Math.max(0,Math.ceil((b-$)/m)),P=Math.min(p.outHeight,(p.inHeight+b-$)/m);for(let V=0;V<h;++V){let G=Math.max(0,Math.ceil((x-V)/f)),W=Math.min(p.outWidth,(p.inWidth+x-V)/f);for(let q=0;q<p.outChannels;++q){let H=Math.trunc(q/w),j=q%w,Y=0;for(let Z=0;Z<p.batchSize;++Z)for(let et=F;et<P;++et){let rt=$+et*m-b;for(let ot=G;ot<W;++ot){let at=V+ot*f-x;Y+=N.get(Z,rt,at,H)*A.get(Z,et,ot,q)}}g.set(Y,$,V,H,j)}}}return e.makeTensorInfo(g.shape,g.dtype,g.values)}var JF={kernelName:gp,backendName:"cpu",kernelFunc:GJ};function WJ(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{strides:i,dilations:a,pad:u,dimRoundingMode:l,inputShape:c}=n;tt([o,s],"depthwiseConv2DNativeBackpropInput");let p=y.computeStrides(o.shape),m=y.computeStrides(s.shape),f=S.computeConv2DInfo(c,s.shape,i,a,u,l,!0),d=new pe(f.inShape,"float32"),h=d.values,[g,x,b]=d.strides,w=e.data.get(o.dataId).values,[C,N,_]=p,A=e.data.get(s.dataId).values,[$,F,P]=m,{batchSize:V,filterHeight:G,filterWidth:W,inChannels:q,inHeight:H,inWidth:j,outChannels:Y,outHeight:Z,outWidth:et,strideHeight:rt,strideWidth:ot}=f,at=G-1-f.padInfo.top,nt=W-1-f.padInfo.left,it=Y/q;for(let dt=0;dt<V;++dt)for(let ht=0;ht<q;++ht)for(let bt=0;bt<H;++bt){let Tt=bt-at,_t=Math.max(0,Math.ceil(Tt/rt)),Bt=Math.min(Z,(G+Tt)/rt);for(let Yt=0;Yt<j;++Yt){let ce=Yt-nt,he=Math.max(0,Math.ceil(ce/ot)),Kt=Math.min(et,(W+ce)/ot),Te=0;for(let fe=_t;fe<Bt;++fe){let Ae=fe*rt-Tt;for(let Ge=he;Ge<Kt;++Ge){let 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eO={kernelName:_l,backendName:"cpu",kernelFunc:({inputs:r,backend:t,attrs:e})=>{let{x:n,filter:o}=r,{strides:s,pad:i,dilations:a}=e,u=t,l=u.data.get(n.dataId).values,c=n.shape.length,p=u.data.get(o.dataId).values,m=o.shape.length,{batchSize:f,inHeight:d,inWidth:h,inChannels:g,outHeight:x,outWidth:b,padInfo:w,strideHeight:C,strideWidth:N,filterHeight:_,filterWidth:A,dilationHeight:$,dilationWidth:F,outShape:P}=S.computeDilation2DInfo(n.shape,o.shape,s,i,"NHWC",a),V=y.sizeFromShape(P),G=P.length,W=y.getArrayFromDType(n.dtype,V);for(let H=0;H<f;++H)for(let j=0;j<x;++j){let Y=j*C-w.top;for(let Z=0;Z<b;++Z){let et=Z*N-w.left;for(let rt=0;rt<g;++rt){let ot=Number.MIN_SAFE_INTEGER;for(let nt=0;nt<_;++nt){let it=Y+nt*$;if(it>=0&&it<d)for(let dt=0;dt<A;++dt){let ht=et+dt*F;if(ht>=0&&ht<h){let bt=y.locToIndex([H,it,ht,rt],c,y.computeStrides(n.shape)),Tt=y.locToIndex([nt,dt,rt],m,y.computeStrides(o.shape)),_t=l[bt]+p[Tt];_t>ot&&(ot=_t)}}}let at=y.locToIndex([H,j,Z,rt],G,y.computeStrides(P));W[at]=ot}}}return{dataId:u.write(y.toTypedArray(W,n.dtype),P,n.dtype),shape:P,dtype:n.dtype}}};var rO={kernelName:Hd,backendName:"cpu",kernelFunc:({inputs:r,backend:t,attrs:e})=>{let{x:n,filter:o,dy:s}=r,{strides:i,pad:a,dilations:u}=e,l=t,c=y.toNestedArray(n.shape,l.data.get(n.dataId).values),p=y.toNestedArray(o.shape,l.data.get(o.dataId).values),{batchSize:m,inHeight:f,inWidth:d,inChannels:h,outHeight:g,outWidth:x,padInfo:b,strideHeight:w,strideWidth:C,filterHeight:N,filterWidth:_,dilationHeight:A,dilationWidth:$,outShape:F}=S.computeDilation2DInfo(n.shape,o.shape,i,a,"NHWC",u);y.assert(s.rank===F.length,()=>`Error in ${Hd}, dy must have the same rank as output ${F.length}, but got ${s.rank}`);let P=y.toNestedArray(F,l.data.get(s.dataId).values),V=y.makeZerosNestedTypedArray(o.shape,o.dtype);for(let W=0;W<m;++W)for(let q=0;q<g;++q){let H=q*w-b.top;for(let j=0;j<x;++j){let Y=j*C-b.left;for(let Z=0;Z<h;++Z){let et=Number.MIN_SAFE_INTEGER,rt=0,ot=0;for(let at=0;at<N;++at){let nt=H+at*A;if(nt>=0&&nt<f)for(let it=0;it<_;++it){let dt=Y+it*$;if(dt>=0&&dt<d){let ht=c[W][nt][dt][Z]+p[at][it][Z];ht>et&&(et=ht,rt=at,ot=it)}}}V[rt][ot][Z]+=P[W][q][j][Z]}}}return{dataId:l.write(y.toTypedArray(V,n.dtype),o.shape,o.dtype),shape:o.shape,dtype:o.dtype}}};var nO={kernelName:Ud,backendName:"cpu",kernelFunc:({inputs:r,backend:t,attrs:e})=>{let{x:n,filter:o,dy:s}=r,{strides:i,pad:a,dilations:u}=e,l=t,c=y.toNestedArray(n.shape,l.data.get(n.dataId).values),p=y.toNestedArray(o.shape,l.data.get(o.dataId).values),{batchSize:m,inHeight:f,inWidth:d,inChannels:h,outHeight:g,outWidth:x,padInfo:b,strideHeight:w,strideWidth:C,filterHeight:N,filterWidth:_,dilationHeight:A,dilationWidth:$,outShape:F}=S.computeDilation2DInfo(n.shape,o.shape,i,a,"NHWC",u);y.assert(s.rank===F.length,()=>`Error in ${Ud}, dy must have the same rank as output ${F.length}, but got ${s.rank}`);let P=y.toNestedArray(F,l.data.get(s.dataId).values),V=y.makeZerosNestedTypedArray(n.shape,n.dtype);for(let W=0;W<m;++W)for(let q=0;q<g;++q){let H=q*w-b.top;for(let j=0;j<x;++j){let Y=j*C-b.left;for(let Z=0;Z<h;++Z){let et=Number.MIN_SAFE_INTEGER,rt=H<0?0:H,ot=Y<0?0:Y;for(let at=0;at<N;++at){let nt=H+at*A;if(nt>=0&&nt<f)for(let it=0;it<_;++it){let dt=Y+it*$;if(dt>=0&&dt<d){let ht=c[W][nt][dt][Z]+p[at][it][Z];ht>et&&(et=ht,rt=nt,ot=dt)}}}V[W][rt][ot][Z]+=P[W][q][j][Z]}}}return{dataId:l.write(y.toTypedArray(V,n.dtype),n.shape,n.dtype),shape:n.shape,dtype:n.dtype}}};function fl(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n;tt(o,"sum");let a;o.dtype==="bool"?a=Ao({inputs:{x:o},backend:e,attrs:{dtype:"int32"}}):a=qr({inputs:{x:o},backend:e});let 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Nt=M();Nt.registerFlag("HAS_WEBGL",()=>Nt.getNumber("WEBGL_VERSION")>0);Nt.registerFlag("WEBGL_VERSION",()=>yw(2)?2:yw(1)?1:0);Nt.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Nt.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Nt.get("WEBGL_VERSION")===2);Nt.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Nt.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Nt.registerFlag("WEBGL_PACK",()=>Nt.getBool("HAS_WEBGL"));Nt.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_CLIP",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_REDUCE",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_LAZILY_UNPACK",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_CONV_IM2COL",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>Dk(Nt.getNumber("WEBGL_VERSION")));Nt.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>Rk(Nt.getNumber("WEBGL_VERSION")));Nt.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let r=Nt.getNumber("WEBGL_VERSION");return r===0?0:Fk(r)});Nt.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Nt.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!Hl.isMobile());Nt.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>Ok(Nt.getNumber("WEBGL_VERSION")));Nt.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Nt.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Nt.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Nt.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>Pk(Nt.getNumber("WEBGL_VERSION")));Nt.registerFlag("WEBGL_FENCE_API_ENABLED",()=>Lk(Nt.getNumber("WEBGL_VERSION")));Nt.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Nt.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Nt.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}.`)});Nt.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>Hl.isMobile()?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}.`)});Nt.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);Nt.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);Nt.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);Nt.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);Nt.registerFlag("WEBGL_EXP_CONV",()=>!1);Nt.registerFlag("SOFTWARE_WEBGL_ENABLED",()=>Nt.getBool("IS_TEST"));Nt.registerFlag("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE",()=>1/0);Nt.registerFlag("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE",()=>!1);Nt.registerFlag("WEBGL2_ISNAN_CUSTOM",()=>!1);function Ve(){let r,t,e,n,o,s,i,a,u,l;return M().getNumber("WEBGL_VERSION")===2?(r="#version 300 es",t="in",e="out",n="in",o="texture",s="outputColor",i="out vec4 outputColor;",a=M().getBool("WEBGL2_ISNAN_CUSTOM")?`
      bool isnan_custom(float val) {
        uint floatToUint = floatBitsToUint(val);
        return (floatToUint & 0x7fffffffu) > 0x7f800000u;
      }

      bvec4 isnan_custom(vec4 val) {
        return bvec4(isnan_custom(val.x),
          isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));
      }

      #define isnan(value) isnan_custom(value)
    `:"",u="",l=`
      #define round(value) newRound(value)
      int newRound(float value) {
        return int(floor(value + 0.5));
      }

      ivec4 newRound(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `):(r="",t="attribute",e="varying",n="varying",o="texture2D",s="gl_FragColor",i="",a=`
      #define isnan(value) isnan_custom(value)
      bool isnan_custom(float val) {
        return (val > 0. || val < 1. || val == 0.) ? false : true;
      }
      bvec4 isnan_custom(vec4 val) {
        return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
      }
    `,u=`
      uniform float INFINITY;

      bool isinf(float val) {
        return abs(val) == INFINITY;
      }
      bvec4 isinf(vec4 val) {
        return equal(abs(val), vec4(INFINITY));
      }
    `,l=`
      int round(float value) {
        return int(floor(value + 0.5));
      }

      ivec4 round(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `),{version:r,attribute:t,varyingVs:e,varyingFs:n,texture2D:o,output:s,defineOutput:i,defineSpecialNaN:a,defineSpecialInf:u,defineRound:l}}function Js(r,t,e="index"){let n=y.computeStrides(t);return n.map((o,s)=>{let i=`int ${r[s]} = ${e} / ${o}`,a=s===n.length-1?`int ${r[s+1]} = ${e} - ${r[s]} * ${o}`:`index -= ${r[s]} * ${o}`;return`${i}; ${a};`}).join("")}function Mc(r,t,e="index"){let n=y.computeStrides(t);return n.map((o,s)=>{let i=`int ${r[s]} = ${e} / outShapeStrides[${s}]`,a=s===n.length-1?`int ${r[s+1]} = ${e} - ${r[s]} * outShapeStrides[${s}]`:`index -= ${r[s]} * outShapeStrides[${s}]`;return`${i}; ${a};`}).join("")}function Q9(r,t){let e=r.length,n=r.map(s=>`${t}[${s}]`),o=new Array(e-1);o[e-2]=n[e-1];for(let s=e-3;s>=0;--s)o[s]=`(${o[s+1]} * ${n[s+1]})`;return o}function qP(r,t,e="index"){let n=r.map((s,i)=>i),o=Q9(n,t);return o.map((s,i)=>{let a=`int ${r[i]} = ${e} / ${o[i]}`,u=i===o.length-1?`int ${r[i+1]} = ${e} - ${r[i]} * ${o[i]}`:`index -= ${r[i]} * ${o[i]}`;return`${a}; ${u};`}).join("")}function pd(r){let t=y.computeStrides(r).map(e=>e.toString());return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
  }
`}function md(){return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
  }
`}var bw=`
  const float FLOAT_MAX = 1.70141184e38;
  const float FLOAT_MIN = 1.17549435e-38;

  lowp vec4 encode_float(highp float v) {
    if (isnan(v)) {
      return vec4(255, 255, 255, 255);
    }

    highp float av = abs(v);

    if(av < FLOAT_MIN) {
      return vec4(0.0, 0.0, 0.0, 0.0);
    } else if(v > FLOAT_MAX) {
      return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;
    } else if(v < -FLOAT_MAX) {
      return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;
    }

    highp vec4 c = vec4(0,0,0,0);

    highp float e = floor(log2(av));
    highp float m = exp2(fract(log2(av))) - 1.0;

    c[2] = floor(128.0 * m);
    m -= c[2] / 128.0;
    c[1] = floor(32768.0 * m);
    m -= c[1] / 32768.0;
    c[0] = floor(8388608.0 * m);

    highp float ebias = e + 127.0;
    c[3] = floor(ebias / 2.0);
    ebias -= c[3] * 2.0;
    c[2] += floor(ebias) * 128.0;

    c[3] += 128.0 * step(0.0, -v);

    return c / 255.0;
  }
`;var{getBroadcastDims:KP}=S;function jP(r,t,e){let n=[];if(r.forEach(f=>{let d=y.sizeFromShape(f.shapeInfo.logicalShape);if(f.shapeInfo.isUniform?n.push(`uniform float ${f.name}${d>1?`[${d}]`:""};`):(n.push(`uniform sampler2D ${f.name};`),n.push(`uniform int offset${f.name};`)),e.enableShapeUniforms){let{uniformShape:h}=ww(e.packedInputs,f.shapeInfo.logicalShape,f.shapeInfo.texShape);switch(h.length){case 1:n.push(`uniform int ${f.name}Shape;`);break;case 2:n.push(`uniform ivec2 ${f.name}Shape;`);break;case 3:n.push(`uniform ivec3 ${f.name}Shape;`);break;case 4:n.push(`uniform ivec4 ${f.name}Shape;`);break;default:break}n.push(`uniform ivec2 ${f.name}TexShape;`)}}),e.enableShapeUniforms){switch(t.logicalShape.length){case 1:n.push("uniform int outShape;");break;case 2:n.push("uniform ivec2 outShape;"),n.push("uniform int outShapeStrides;");break;case 3:n.push("uniform ivec3 outShape;"),n.push("uniform ivec2 outShapeStrides;");break;case 4:n.push("uniform ivec4 outShape;"),n.push("uniform ivec3 outShapeStrides;");break;default:break}n.push("uniform ivec2 outTexShape;")}e.customUniforms&&e.customUniforms.forEach(f=>{n.push(`uniform ${f.type} ${f.name}${f.arrayIndex?`[${f.arrayIndex}]`:""};`)});let o=n.join(`
`),s=r.map(f=>ttt(f,t,e.packedInputs,e.enableShapeUniforms)).join(`
`),i=t.texShape,a=Ve(),u=ntt(a),l,c,p=itt(a);return t.isPacked?(l=ett(t.logicalShape,i,e.enableShapeUniforms),c=stt(a)):(l=rtt(t.logicalShape,i,e.enableShapeUniforms),c=ott(a)),e.packedInputs&&(p+=ctt),[p,u,c,o,l,s,e.userCode].join(`
`)}function dd(r,t=!1){let e=r.shapeInfo.logicalShape;switch(e.length){case 0:return Itt(r,t);case 1:return Stt(r,t);case 2:return ktt(r,t);case 3:return Ett(r,t);case 4:return Att(r,t);case 5:return $tt(r);case 6:return Dtt(r);default:throw new Error(`${e.length}-D input sampling is not yet supported`)}}function XP(r,t){switch(r.shapeInfo.logicalShape.length){case 0:return Ctt(r);case 1:return vtt(r,t);case 2:return Ntt(r,t);case 3:return Ttt(r,t);default:return _tt(r,t)}}function ttt(r,t,e=!1,n){let o="";e?o+=XP(r,n):o+=dd(r,n);let s=r.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(e?o+=Rtt(r,t):o+=Ftt(r,t)),o}function ett(r,t,e){switch(r.length){case 0:return YP();case 1:return ptt(r,t,e);case 2:return btt(r,t,e);case 3:return ftt(r,t,e);default:return htt(r,t,e)}}function rtt(r,t,e){switch(r.length){case 0:return YP();case 1:return mtt(r,t,e);case 2:return wtt(r,t,e);case 3:return dtt(r,t,e);case 4:return gtt(r,t,e);case 5:return xtt(r,t);case 6:return ytt(r,t);default:throw new Error(`${r.length}-D output sampling is not yet supported`)}}function ntt(r){return`
    float sampleTexture(sampler2D textureSampler, vec2 uv) {
      return ${r.texture2D}(textureSampler, uv).r;
    }
  `}function ott(r){return`
    void setOutput(float val) {
      ${r.output} = vec4(val, 0, 0, 0);
    }
  `}function stt(r){return`
    void setOutput(vec4 val) {
      ${r.output} = val;
    }
  `}function itt(r){return`${r.version}
    precision highp float;
    precision highp int;
    precision highp sampler2D;
    ${r.varyingFs} vec2 resultUV;
    ${r.defineOutput}
    const vec2 halfCR = vec2(0.5, 0.5);

    struct ivec5
    {
      int x;
      int y;
      int z;
      int w;
      int u;
    };

    struct ivec6
    {
      int x;
      int y;
      int z;
      int w;
      int u;
      int v;
    };

    uniform float NAN;
    ${r.defineSpecialNaN}
    ${r.defineSpecialInf}
    ${r.defineRound}

    int imod(int x, int y) {
      return x - y * (x / y);
    }

    int idiv(int a, int b, float sign) {
      int res = a / b;
      int mod = imod(a, b);
      if (sign < 0. && mod != 0) {
        res -= 1;
      }
      return res;
    }

    //Based on the work of Dave Hoskins
    //https://www.shadertoy.com/view/4djSRW
    #define HASHSCALE1 443.8975
    float random(float seed){
      vec2 p = resultUV * seed;
      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);
      p3 += dot(p3, p3.yzx + 19.19);
      return fract((p3.x + p3.y) * p3.z);
    }

    ${att}
    ${ltt}
    ${utt}
  `}var att=`
vec2 uvFromFlat(int texNumR, int texNumC, int index) {
  int texR = index / texNumC;
  int texC = index - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
  int texelIndex = index / 2;
  int texR = texelIndex / texNumC;
  int texC = texelIndex - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
`,ltt=`
vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
  int texNumC, int row, int col) {
  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
  int texR = texelIndex / texNumC;
  int texC = texelIndex - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
`,utt=`
vec2 packedUVfrom3D(int texNumR, int texNumC,
    int texelsInBatch, int texelsInLogicalRow, int b,
    int row, int col) {
  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);
  int texR = index / texNumC;
  int texC = index - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
`,ctt=`
  float getChannel(vec4 frag, vec2 innerDims) {
    vec2 modCoord = mod(innerDims, 2.);
    return modCoord.x == 0. ?
      (modCoord.y == 0. ? frag.r : frag.g) :
      (modCoord.y == 0. ? frag.b : frag.a);
  }
  float getChannel(vec4 frag, int dim) {
    float modCoord = mod(float(dim), 2.);
    return modCoord == 0. ? frag.r : frag.g;
  }
`;function YP(){return`
    int getOutputCoords() {
      return 0;
    }
  `}function ptt(r,t,e){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?e?`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
      }
    `:`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ${n[1]}.0);
      }
    `:n[1]===1?e?`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
      }
    `:`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ${n[0]}.0);
      }
    `:e?`
    int getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
    }
  `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));
      return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
    }
  `}function mtt(r,t,e){return t[0]===1?e?`
      int getOutputCoords() {
        return int(resultUV.x * float(outTexShape[1]));
      }
    `:`
      int getOutputCoords() {
        return int(resultUV.x * ${t[1]}.0);
      }
    `:t[1]===1?e?`
      int getOutputCoords() {
        return int(resultUV.y * float(outTexShape[0]));
      }
    `:`
      int getOutputCoords() {
        return int(resultUV.y * ${t[0]}.0);
      }
    `:e?`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(outTexShape[0], outTexShape[1]));
      return resTexRC.x * outTexShape[1] + resTexRC.y;
    }
  `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      return resTexRC.x * ${t[1]} + resTexRC.y;
    }
  `}function ftt(r,t,e){if(e)return`
    ivec3 getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;

      int b = index / texelsInBatch;
      index -= b * texelsInBatch;

      int r = 2 * (index / texelsInLogicalRow);
      int c = imod(index, texelsInLogicalRow) * 2;

      return ivec3(b, r, c);
    }
  `;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],o=Math.ceil(r[2]/2),s=o*Math.ceil(r[1]/2);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));
      int index = resTexRC.x * ${n[1]} + resTexRC.y;

      int b = index / ${s};
      index -= b * ${s};

      int r = 2 * (index / ${o});
      int c = imod(index, ${o}) * 2;

      return ivec3(b, r, c);
    }
  `}function dtt(r,t,e){if(e)return`
  ivec3 getOutputCoords() {
    ivec2 resTexRC = ivec2(resultUV.yx *
                           vec2(outTexShape[0], outTexShape[1]));
    int index = resTexRC.x * outTexShape[1] + resTexRC.y;
    ${Mc(["r","c","d"],r)}
    return ivec3(r, c, d);
  }
`;let n=Js(["r","c","d"],r);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      ${n}
      return ivec3(r, c, d);
    }
  `}function htt(r,t,e){if(e)return`
    ivec4 getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;

      int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
      int texelsInBatchN = texelsInBatch * outShape[1];

      int b2 = index / texelsInBatchN;
      index -= b2 * texelsInBatchN;

      int b = index / texelsInBatch;
      index -= b * texelsInBatch;

      int r = 2 * (index / texelsInLogicalRow);
      int c = imod(index, texelsInLogicalRow) * 2;

      return ivec4(b2, b, r, c);
    }
  `;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],o=Math.ceil(r[r.length-1]/2),s=o*Math.ceil(r[r.length-2]/2),i=s,a="",u="b, r, c";for(let l=2;l<r.length-1;l++)i*=r[r.length-l-1],a=`
      int b${l} = index / ${i};
      index -= b${l} * ${i};
    `+a,u=`b${l}, `+u;return`
    ivec${r.length} getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));
      int index = resTexRC.x * ${n[1]} + resTexRC.y;

      ${a}

      int b = index / ${s};
      index -= b * ${s};

      int r = 2 * (index / ${o});
      int c = imod(index, ${o}) * 2;

      return ivec${r.length}(${u});
    }
  `}function gtt(r,t,e){if(e)return`
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(outTexShape[0], outTexShape[1]));
      int index = resTexRC.x * outTexShape[1] + resTexRC.y;
      ${Mc(["r","c","d","d2"],r)}
      return ivec4(r, c, d, d2);
    }
  `;let n=Js(["r","c","d","d2"],r);return`
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      ${n}
      return ivec4(r, c, d, d2);
    }
  `}function xtt(r,t){let e=Js(["r","c","d","d2","d3"],r);return`
    ivec5 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
                             ${t[1]}));

      int index = resTexRC.x * ${t[1]} + resTexRC.y;

      ${e}

      ivec5 outShape = ivec5(r, c, d, d2, d3);
      return outShape;
    }
  `}function ytt(r,t){let e=Js(["r","c","d","d2","d3","d4"],r);return`
    ivec6 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;

      ${e}

      ivec6 result = ivec6(r, c, d, d2, d3, d4);
      return result;
    }
  `}function btt(r,t,e){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(y.arraysEqual(r,t))return e?`
      ivec2 getOutputCoords() {
        ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
        return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
      }
    `:`
      ivec2 getOutputCoords() {
        return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
      }
    `;let o=Math.ceil(r[1]/2);return e?`
    ivec2 getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));

      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
      int r = 2 * (index / texelsInLogicalRow);
      int c = imod(index, texelsInLogicalRow) * 2;

      return ivec2(r, c);
    }
  `:`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));

      int index = resTexRC.x * ${n[1]} + resTexRC.y;
      int r = 2 * (index / ${o});
      int c = imod(index, ${o}) * 2;

      return ivec2(r, c);
    }
  `}function wtt(r,t,e){return y.arraysEqual(r,t)?e?`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
      }
    `:`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
      }
    `:r[1]===1?e?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(outTexShape[0], outTexShape[1]));
        int index = resTexRC.x * outTexShape[1] + resTexRC.y;
        return ivec2(index, 0);
      }
    `:`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${t[0]}, ${t[1]}));
        int index = resTexRC.x * ${t[1]} + resTexRC.y;
        return ivec2(index, 0);
      }
    `:r[0]===1?e?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(outTexShape[0], outTexShape[1]));
        int index = resTexRC.x * outTexShape[1] + resTexRC.y;
        return ivec2(0, index);
      }
    `:`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${t[0]}, ${t[1]}));
        int index = resTexRC.x * ${t[1]} + resTexRC.y;
        return ivec2(0, index);
      }
    `:e?`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(outTexShape[0], outTexShape[1]));
      int index = resTexRC.x * outTexShape[1] + resTexRC.y;
      int r = index / outShape[1];
      int c = index - r * outShape[1];
      return ivec2(r, c);
    }
  `:`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      int r = index / ${r[1]};
      int c = index - r * ${r[1]};
      return ivec2(r, c);
    }
  `}function zc(r){return`offset${r}`}function Ctt(r){let t=r.name,e="get"+t.charAt(0).toUpperCase()+t.slice(1),n=Ve();return`
    vec4 ${e}() {
      return ${n.texture2D}(${t}, halfCR);
    }
  `}function Itt(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`float ${n}() {return ${e};}`;let[o,s]=r.shapeInfo.texShape;if(o===1&&s===1)return`
      float ${n}() {
        return sampleTexture(${e}, halfCR);
      }
    `;let i=zc(e);if(t)return`
    float ${n}() {
      vec2 uv = uvFromFlat(${e}TexShape[0], ${e}TexShape[1], ${i});
      return sampleTexture(${e}, uv);
    }
  `;let[a,u]=r.shapeInfo.texShape;return`
    float ${n}() {
      vec2 uv = uvFromFlat(${a}, ${u}, ${i});
      return sampleTexture(${e}, uv);
    }
  `}function vtt(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),o=r.shapeInfo.texShape,s=Ve();if(t)return`
    vec4 ${n}(int index) {
      ivec2 packedTexShape = ivec2(ceil(float(${e}TexShape[0]) / 2.0), ceil(float(${e}TexShape[1]) / 2.0));
      vec2 uv = packedUVfrom1D(
        packedTexShape[0], packedTexShape[1], index);
      return ${s.texture2D}(${e}, uv);
    }
  `;let i=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)];return`
    vec4 ${n}(int index) {
      vec2 uv = packedUVfrom1D(
        ${i[0]}, ${i[1]}, index);
      return ${s.texture2D}(${e}, uv);
    }
  `}function Stt(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`
      float ${n}(int index) {
        ${hd(r)}
      }
    `;let o=r.shapeInfo.texShape,s=o[0],i=o[1];if(i===1&&s===1)return`
      float ${n}(int index) {
        return sampleTexture(${e}, halfCR);
      }
    `;let a=zc(e);return i===1?t?`
      float ${n}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${a}) + 0.5) / float(${e}TexShape[0]));
        return sampleTexture(${e}, uv);
      }
    `:`
      float ${n}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${a}) + 0.5) / ${s}.0);
        return sampleTexture(${e}, uv);
      }
    `:s===1?t?`
      float ${n}(int index) {
        vec2 uv = vec2((float(index + ${a}) + 0.5) / float(${e}TexShape[1]), 0.5);
        return sampleTexture(${e}, uv);
      }
    `:`
      float ${n}(int index) {
        vec2 uv = vec2((float(index + ${a}) + 0.5) / ${i}.0, 0.5);
        return sampleTexture(${e}, uv);
      }
    `:t?`
    float ${n}(int index) {
      vec2 uv = uvFromFlat(${e}TexShape[0], ${e}TexShape[1], index + ${a});
      return sampleTexture(${e}, uv);
    }
  `:`
    float ${n}(int index) {
      vec2 uv = uvFromFlat(${s}, ${i}, index + ${a});
      return sampleTexture(${e}, uv);
    }
  `}function Ntt(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r.shapeInfo.texShape,i=s[0],a=s[1],u=Ve();if(s!=null&&y.arraysEqual(e,s))return t?`
      vec4 ${o}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);

        return ${u.texture2D}(${n}, uv);
      }
    `:`
      vec4 ${o}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${a}.0, ${i}.0);

        return ${u.texture2D}(${n}, uv);
      }
    `;if(t)return`
    vec4 ${o}(int row, int col) {
      ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
      int valuesPerRow = int(ceil(float(${n}Shape[1]) / 2.0));
      vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);
      return ${u.texture2D}(${n}, uv);
    }
  `;let l=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],c=Math.ceil(e[1]/2);return`
    vec4 ${o}(int row, int col) {
      vec2 uv = packedUVfrom2D(${c}, ${l[0]}, ${l[1]}, row, col);
      return ${u.texture2D}(${n}, uv);
    }
  `}function ktt(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r.shapeInfo.texShape;if(s!=null&&y.arraysEqual(e,s)){if(t)return`
      float ${o}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `;let m=s[0],f=s[1];return`
    float ${o}(int row, int col) {
      vec2 uv = (vec2(col, row) + halfCR) / vec2(${f}.0, ${m}.0);
      return sampleTexture(${n}, uv);
    }
  `}let{newShape:i,keptDims:a}=y.squeezeShape(e),u=i;if(u.length<e.length){let m=gd(r,u),f=["row","col"];return`
      ${dd(m,t)}
      float ${o}(int row, int col) {
        return ${o}(${xd(f,a)});
      }
    `}if(r.shapeInfo.isUniform)return`
      float ${o}(int row, int col) {
        int index = round(dot(vec2(row, col), vec2(${e[1]}, 1)));
        ${hd(r)}
      }
    `;let l=s[0],c=s[1],p=zc(n);return c===1?t?`
      float ${o}(int row, int col) {
        float index = dot(vec3(row, col, ${p}), vec3(${n}Shape[1], 1, 1));
        vec2 uv = vec2(0.5, (index + 0.5) / float(${n}TexShape[0]));
        return sampleTexture(${n}, uv);
      }
    `:`
    float ${o}(int row, int col) {
      float index = dot(vec3(row, col, ${p}), vec3(${e[1]}, 1, 1));
      vec2 uv = vec2(0.5, (index + 0.5) / ${l}.0);
      return sampleTexture(${n}, uv);
    }
  `:l===1?t?`
      float ${o}(int row, int col) {
        float index = dot(vec3(row, col, ${p}), vec3(${n}Shape[1], 1, 1));
        vec2 uv = vec2((index + 0.5) / float(${n}TexShape[1]), 0.5);
        return sampleTexture(${n}, uv);
      }
    `:`
    float ${o}(int row, int col) {
      float index = dot(vec3(row, col, ${p}), vec3(${e[1]}, 1, 1));
      vec2 uv = vec2((index + 0.5) / ${c}.0, 0.5);
      return sampleTexture(${n}, uv);
    }
  `:t?`
      float ${o}(int row, int col) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${n}Shape[1] + col + ${p};
        vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
        return sampleTexture(${n}, uv);
      }
    `:`
  float ${o}(int row, int col) {
    // Explicitly use integer operations as dot() only works on floats.
    int index = row * ${e[1]} + col + ${p};
    vec2 uv = uvFromFlat(${l}, ${c}, index);
    return sampleTexture(${n}, uv);
  }
`}function Ttt(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];if(e[0]===1){let m=e.slice(1),f=[1,2],d=gd(r,m),h=["b","row","col"];return`
        ${XP(d,t)}
        vec4 ${o}(int b, int row, int col) {
          return ${o}(${xd(h,f)});
        }
      `}let a=Ve();if(t)return`
    vec4 ${o}(int b, int row, int col) {
      ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
      int valuesPerRow = int(ceil(float(${n}Shape[2]) / 2.0));
      int texelsInBatch = valuesPerRow * int(ceil(float(${n}Shape[1]) / 2.0));
      vec2 uv = packedUVfrom3D(
        packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);
      return ${a.texture2D}(${n}, uv);
    }
  `;let u=i[0],l=i[1],c=Math.ceil(e[2]/2),p=c*Math.ceil(e[1]/2);return`
    vec4 ${o}(int b, int row, int col) {
      vec2 uv = packedUVfrom3D(
        ${u}, ${l}, ${p}, ${c}, b, row, col);
      return ${a.texture2D}(${n}, uv);
    }
  `}function Ett(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e[1]*e[2],i=e[2],{newShape:a,keptDims:u}=y.squeezeShape(e),l=a;if(l.length<e.length){let h=gd(r,l),g=["row","col","depth"];return`
        ${dd(h,t)}
        float ${o}(int row, int col, int depth) {
          return ${o}(${xd(g,u)});
        }
      `}if(r.shapeInfo.isUniform)return`
      float ${o}(int row, int col, int depth) {
        int index = round(dot(vec3(row, col, depth),
                          vec3(${s}, ${i}, 1)));
        ${hd(r)}
      }
    `;let c=r.shapeInfo.texShape,p=c[0],m=c[1],f=r.shapeInfo.flatOffset;if(m===s&&f==null)return t?`
      float ${o}(int row, int col, int depth) {
        int stride1 = ${n}Shape[2];
        float texR = float(row);
        float texC = dot(vec2(col, depth), vec2(stride1, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `:`
        float ${o}(int row, int col, int depth) {
          float texR = float(row);
          float texC = dot(vec2(col, depth), vec2(${i}, 1));
          vec2 uv = (vec2(texC, texR) + halfCR) /
                     vec2(${m}.0, ${p}.0);
          return sampleTexture(${n}, uv);
        }
      `;if(m===i&&f==null)return t?`
      float ${o}(int row, int col, int depth) {
        float texR = dot(vec2(row, col), vec2(${n}Shape[1], 1));
        float texC = float(depth);
        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `:`
    float ${o}(int row, int col, int depth) {
      float texR = dot(vec2(row, col), vec2(${e[1]}, 1));
      float texC = float(depth);
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${m}.0, ${p}.0);
      return sampleTexture(${n}, uv);
    }
  `;let d=zc(n);return t?`
    float ${o}(int row, int col, int depth) {
      // Explicitly use integer operations as dot() only works on floats.
      int stride0 = ${n}Shape[1] * ${n}Shape[2];
      int stride1 = ${n}Shape[2];
      int index = row * stride0 + col * stride1 + depth + ${d};
      vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
      return sampleTexture(${n}, uv);
    }
    `:`
      float ${o}(int row, int col, int depth) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${s} + col * ${i} + depth + ${d};
        vec2 uv = uvFromFlat(${p}, ${m}, index);
        return sampleTexture(${n}, uv);
      }
  `}function _tt(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),o=Ve();if(t)return`
    vec4 ${n}(int b2, int b, int row, int col) {
      int valuesPerRow = int(ceil(float(${e}Shape[3]) / 2.0));
      int texelsInBatch = valuesPerRow * int(ceil(float(${e}Shape[2]) / 2.0));
      int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);
      texelsInBatch *= ${e}Shape[1];
      index = b2 * texelsInBatch + index;
      ivec2 packedTexShape = ivec2(ceil(float(${e}TexShape[0]) / 2.0), ceil(float(${e}TexShape[1]) / 2.0));
      int texR = index / packedTexShape[1];
      int texC = index - texR * packedTexShape[1];
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return ${o.texture2D}(${e}, uv);
    }
  `;let s=r.shapeInfo.logicalShape,i=s.length,a=r.shapeInfo.texShape,u=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],l=u[0],c=u[1],p=Math.ceil(s[i-1]/2),m=p*Math.ceil(s[i-2]/2),f="int b, int row, int col",d=`b * ${m} + (row / 2) * ${p} + (col / 2)`;for(let h=2;h<i-1;h++)f=`int b${h}, `+f,m*=s[i-h-1],d=`b${h} * ${m} + `+d;return`
    vec4 ${n}(${f}) {
      int index = ${d};
      int texR = index / ${c};
      int texC = index - texR * ${c};
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${c}, ${l});
      return ${o.texture2D}(${e}, uv);
    }
  `}function Att(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e[3],i=e[2]*s,a=e[1]*i,{newShape:u,keptDims:l}=y.squeezeShape(e);if(u.length<e.length){let b=gd(r,u),w=["row","col","depth","depth2"];return`
      ${dd(b,t)}
      float ${o}(int row, int col, int depth, int depth2) {
        return ${o}(${xd(w,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}, ${i}, ${s}, 1)));
        ${hd(r)}
      }
    `;let c=r.shapeInfo.flatOffset,p=r.shapeInfo.texShape,m=p[0],f=p[1],d=`int stride2 = ${n}Shape[3];`,h=`int stride1 = ${n}Shape[2] * stride2;`,g=`int stride0 = ${n}Shape[1] * stride1;`;if(f===a&&c==null)return t?`
      float ${o}(int row, int col, int depth, int depth2) {
        ${d}
        ${h}
        float texR = float(row);
        float texC =
            dot(vec3(col, depth, depth2),
                vec3(stride1, stride2, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `:`
      float ${o}(int row, int col, int depth, int depth2) {
        float texR = float(row);
        float texC =
            dot(vec3(col, depth, depth2),
                vec3(${i}, ${s}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${f}.0, ${m}.0);
        return sampleTexture(${n}, uv);
      }
    `;if(f===s&&c==null)return t?`
      float ${o}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${n}Shape[1] * ${n}Shape[2], ${n}Shape[2], 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `:`
      float ${o}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${e[1]*e[2]}, ${e[2]}, 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${f}.0, ${m}.0);
        return sampleTexture(${n}, uv);
      }
    `;let x=zc(n);return t?`
    float ${o}(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
      ${d}
      ${h}
      ${g}
      int index = row * stride0 + col * stride1 +
          depth * stride2 + depth2;
      vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index + ${x});
      return sampleTexture(${n}, uv);
    }
  `:`
    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 * ${i} +
          depth * ${s} + depth2;
      vec2 uv = uvFromFlat(${m}, ${f}, index + ${x});
      return sampleTexture(${n}, uv);
    }
  `}function $tt(r){let t=r.shapeInfo.logicalShape,e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),o=t[4],s=t[3]*o,i=t[2]*s,a=t[1]*i,{newShape:u,keptDims:l}=y.squeezeShape(t);if(u.length<t.length){let h=gd(r,u),g=["row","col","depth","depth2","depth3"];return`
      ${dd(h)}
      float ${n}(int row, int col, int depth, int depth2, int depth3) {
        return ${n}(${xd(g,l)});
      }
    `}if(r.shapeInfo.isUniform)return`
      float ${n}(int row, int col, int depth, int depth2, int depth3) {
        float index = dot(
          vec4(row, col, depth, depth2),
          vec4(${a}, ${i}, ${s}, ${o})) +
          depth3;
        ${hd(r)}
      }
    `;let c=r.shapeInfo.flatOffset,p=r.shapeInfo.texShape,m=p[0],f=p[1];if(f===a&&c==null)return`
      float ${n}(int row, int col, int depth, int depth2, int depth3) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
                         vec4(${i}, ${s}, ${o}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${f}.0, ${m}.0);
        return sampleTexture(${e}, uv);
      }
    `;if(f===o&&c==null)return`
      float ${n}(int row, int col, int depth, int depth2, int depth3) {
        float texR = dot(
          vec4(row, col, depth, depth2),
          vec4(${t[1]*t[2]*t[3]},
               ${t[2]*t[3]}, ${t[3]}, 1));
        int texC = depth3;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${f}.0, ${m}.0);
        return sampleTexture(${e}, uv);
      }
    `;let d=zc(e);return`
    float ${n}(int row, int col, int depth, int depth2, int depth3) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${a} + col * ${i} + depth * ${s} +
          depth2 * ${o} + depth3 + ${d};
      vec2 uv = uvFromFlat(${m}, ${f}, index);
      return sampleTexture(${e}, uv);
    }
  `}function Dtt(r){let t=r.shapeInfo.logicalShape,e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),{newShape:o,keptDims:s}=y.squeezeShape(t);if(o.length<t.length){let g=gd(r,o),x=["row","col","depth","depth2","depth3","depth4"];return`
      ${dd(g)}
      float ${n}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        return ${n}(${xd(x,s)});
      }
    `}let i=t[5],a=t[4]*i,u=t[3]*a,l=t[2]*u,c=t[1]*l;if(r.shapeInfo.isUniform)return`
      float ${n}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
        int index = round(dot(
          vec4(row, col, depth, depth2),
          vec4(${c}, ${l}, ${u}, ${a})) +
          dot(
            vec2(depth3, depth4),
            vec2(${i}, 1)));
        ${hd(r)}
      }
    `;let p=r.shapeInfo.flatOffset,m=r.shapeInfo.texShape,f=m[0],d=m[1];if(d===c&&p==null)return`
      float ${n}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
          vec4(${l}, ${u}, ${a}, ${i})) +
               float(depth4);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${d}.0, ${f}.0);
        return sampleTexture(${e}, uv);
      }
    `;if(d===i&&p==null)return`
      float ${n}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        float texR = dot(vec4(row, col, depth, depth2),
          vec4(${t[1]*t[2]*t[3]*t[4]},
               ${t[2]*t[3]*t[4]},
               ${t[3]*t[4]},
               ${t[4]})) + float(depth3);
        int texC = depth4;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${d}.0, ${f}.0);
        return sampleTexture(${e}, uv);
      }
    `;let h=zc(e);return`
    float ${n}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${c} + col * ${l} + depth * ${u} +
          depth2 * ${a} + depth3 * ${i} + depth4 + ${h};
      vec2 uv = uvFromFlat(${f}, ${d}, index);
      return sampleTexture(${e}, uv);
    }
  `}function hd(r){let t=r.name,e=y.sizeFromShape(r.shapeInfo.logicalShape);return e<2?`return ${t};`:`
    for (int i = 0; i < ${e}; i++) {
      if (i == index) {
        return ${t}[i];
      }
    }
  `}function Rtt(r,t){let e=r.name,n=e.charAt(0).toUpperCase()+e.slice(1),o="get"+n+"AtOutCoords",s=r.shapeInfo.logicalShape.length,i=t.logicalShape.length,a=KP(r.shapeInfo.logicalShape,t.logicalShape),u=zt(i),l=i-s,c,p=["x","y","z","w","u","v"];s===0?c="":i<2&&a.length>=1?c="coords = 0;":c=a.map(b=>`coords.${p[b+l]} = 0;`).join(`
`);let m="";i<2&&s>0?m="coords":m=r.shapeInfo.logicalShape.map((b,w)=>`coords.${p[w+l]}`).join(", ");let f="return outputValue;",h=y.sizeFromShape(r.shapeInfo.logicalShape)===1,x=y.sizeFromShape(t.logicalShape)===1;if(s===1&&!h&&!x)f=`
      return vec4(outputValue.xy, outputValue.xy);
    `;else if(h&&!x)i===1?f=`
        return vec4(outputValue.x, outputValue.x, 0., 0.);
      `:f=`
        return vec4(outputValue.x);
      `;else if(a.length){let b=s-2,w=s-1;a.indexOf(b)>-1&&a.indexOf(w)>-1?f="return vec4(outputValue.x);":a.indexOf(b)>-1?f="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":a.indexOf(w)>-1&&(f="return vec4(outputValue.xx, outputValue.zz);")}return`
    vec4 ${o}() {
      ${u} coords = getOutputCoords();
      ${c}
      vec4 outputValue = get${n}(${m});
      ${f}
    }
  `}function Ftt(r,t){let e=r.name,n=e.charAt(0).toUpperCase()+e.slice(1),o="get"+n+"AtOutCoords",s=t.texShape,i=r.shapeInfo.texShape,a=r.shapeInfo.logicalShape.length,u=t.logicalShape.length;if(!r.shapeInfo.isUniform&&a===u&&r.shapeInfo.flatOffset==null&&y.arraysEqual(i,s))return`
      float ${o}() {
        return sampleTexture(${e}, resultUV);
      }
    `;let l=zt(u),c=KP(r.shapeInfo.logicalShape,t.logicalShape),p=u-a,m,f=["x","y","z","w","u","v"];a===0?m="":u<2&&c.length>=1?m="coords = 0;":m=c.map(h=>`coords.${f[h+p]} = 0;`).join(`
`);let d="";return u<2&&a>0?d="coords":d=r.shapeInfo.logicalShape.map((h,g)=>`coords.${f[g+p]}`).join(", "),`
    float ${o}() {
      ${l} coords = getOutputCoords();
      ${m}
      return get${n}(${d});
    }
  `}function zt(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 ${r} is not yet supported`)}function ww(r,t,e){let{newShape:n,keptDims:o}=y.squeezeShape(t),s=t.length,i=r&&s===3&&t[0]===1,a=i?t.slice(1):n,u=!r&&s>1&&!y.arraysEqual(t,e)&&n.length<s||i;return{useSqueezeShape:u,uniformShape:u?a:t,keptDims:o}}function gd(r,t){let e=JSON.parse(JSON.stringify(r));return e.shapeInfo.logicalShape=t,e}function xd(r,t){return t.map(e=>r[e]).join(", ")}function JP(r,t,e,n){let o=e.map((c,p)=>{let m={logicalShape:c.shape,texShape:c.isUniform?null:c.texData.texShape,isUniform:c.isUniform,isPacked:c.isUniform?!1:c.texData.isPacked,flatOffset:null};return c.texData!=null&&c.texData.slice!=null&&c.texData.slice.flatOffset>0&&(m.flatOffset=c.texData.slice.flatOffset),{name:t.variableNames[p],shapeInfo:m}}),s=o.map(c=>c.shapeInfo),i={logicalShape:n.shape,texShape:n.texData.texShape,isUniform:!1,isPacked:n.texData.isPacked,flatOffset:null},a=jP(o,i,t),u=wk(r.gl,a),l=r.createProgram(u);return M().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:u,source:a,webGLProgram:l,inShapeInfos:s,outShapeInfo:i,uniformLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,inShapesLocations:null,inTexShapesLocations:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:Object.assign({program:t,fragmentShader:u,source:a,webGLProgram:l,inShapeInfos:s,outShapeInfo:i},Mk(r,t,l))}function Mk(r,t,e){let n={},o={},s={},i=[],a,u,l,c=null,p=null;p=r.getUniformLocation(e,"NAN",!1),M().getNumber("WEBGL_VERSION")===1&&(c=r.getUniformLocation(e,"INFINITY",!1));let m=!1;for(let f=0;f<t.variableNames.length;f++){let d=t.variableNames[f];n[d]=r.getUniformLocation(e,d,m),n[`offset${d}`]=r.getUniformLocation(e,`offset${d}`,m),t.enableShapeUniforms&&(o[`${d}Shape`]=r.getUniformLocation(e,`${d}Shape`,m),s[`${d}TexShape`]=r.getUniformLocation(e,`${d}TexShape`,m))}return t.enableShapeUniforms&&(a=r.getUniformLocation(e,"outShape",m),l=r.getUniformLocation(e,"outShapeStrides",m),u=r.getUniformLocation(e,"outTexShape",m)),t.customUniforms&&t.customUniforms.forEach((f,d)=>{i[d]=r.getUniformLocation(e,f.name,m)}),{uniformLocations:n,customUniformLocations:i,infLoc:c,nanLoc:p,inShapesLocations:o,inTexShapesLocations:s,outShapeLocation:a,outShapeStridesLocation:l,outTexShapeLocation:u}}function ZP(r,t){if(r.length!==t.length)throw Error(`Binary was compiled with ${r.length} inputs, but was executed with ${t.length} inputs`);r.forEach((e,n)=>{let o=e.logicalShape,s=t[n],i=s.shape;if(!y.arraysEqual(o,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${o} and ${i} must match`);if(e.isUniform&&s.isUniform)return;let a=e.texShape,u=s.isUniform?null:s.texData.texShape;if(!y.arraysEqual(a,u))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${a} and ${u} must match`)})}function QP(r,t,e,n,o){t.program.enableShapeUniforms||(ZP(t.inShapeInfos,e),ZP([t.outShapeInfo],[n]));let s=n.texData.texture,i=n.texData.texShape;n.texData.isPacked?r.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):r.setOutputMatrixTexture(s.texture,i[0],i[1]),r.setProgram(t.webGLProgram),M().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&r.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&r.gl.uniform1f(t.nanLoc,NaN),e.forEach((u,l)=>{let c=t.program.variableNames[l],p=t.uniformLocations[c],m=t.uniformLocations[`offset${c}`],f=t.inShapesLocations[`${c}Shape`],d=t.inTexShapesLocations[`${c}TexShape`];if(f){let{uniformShape:h}=ww(t.program.packedInputs,u.shape,u.texData.texShape);switch(h.length){case 1:r.gl.uniform1iv(f,new Int32Array(h));break;case 2:r.gl.uniform2iv(f,new Int32Array(h));break;case 3:r.gl.uniform3iv(f,new Int32Array(h));break;case 4:r.gl.uniform4iv(f,new Int32Array(h));break;default:break}}if(d&&r.gl.uniform2i(d,u.texData.texShape[0],u.texData.texShape[1]),p!=null){if(u.isUniform){if(y.sizeFromShape(u.shape)<2)r.gl.uniform1f(p,u.uniformValues[0]);else{let h=u.uniformValues;h instanceof Float32Array||(h=new Float32Array(h)),r.gl.uniform1fv(p,h)}return}u.texData.slice!=null&&m!=null&&r.gl.uniform1i(m,u.texData.slice.flatOffset),r.setInputMatrixTexture(u.texData.texture.texture,p,l)}});let a=t.outShapeLocation;if(a)switch(n.shape.length){case 1:r.gl.uniform1iv(a,new Int32Array(n.shape));break;case 2:r.gl.uniform2iv(a,new Int32Array(n.shape));break;case 3:r.gl.uniform3iv(a,new Int32Array(n.shape));break;case 4:r.gl.uniform4iv(a,new Int32Array(n.shape));break;default:break}if(t.outShapeStridesLocation){let u=y.computeStrides(n.shape);switch(n.shape.length){case 2:r.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(u));break;case 3:r.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(u));break;case 4:r.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(u));break;default:break}}t.outTexShapeLocation&&r.gl.uniform2i(t.outTexShapeLocation,n.texData.texShape[0],n.texData.texShape[1]),t.program.customUniforms&&o&&t.program.customUniforms.forEach((u,l)=>{let c=t.customUniformLocations[l],p=o[l];if(u.type==="float")r.gl.uniform1fv(c,p);else if(u.type==="vec2")r.gl.uniform2fv(c,p);else if(u.type==="vec3")r.gl.uniform3fv(c,p);else if(u.type==="vec4")r.gl.uniform4fv(c,p);else if(u.type==="int")r.gl.uniform1iv(c,p);else if(u.type==="ivec2")r.gl.uniform2iv(c,p);else if(u.type==="ivec3")r.gl.uniform3iv(c,p);else if(u.type==="ivec4")r.gl.uniform4iv(c,p);else throw Error(`uniform type ${u.type} is not supported yet.`)}),r.executeProgram()}function tL(r,t,e){let n="";t.concat(e).forEach(i=>{let a=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(r.enableShapeUniforms&&!i.isUniform){let u=i.texData.texShape,{useSqueezeShape:l,uniformShape:c,keptDims:p}=ww(r.packedInputs,i.shape,u),m="",f="",d="";if(c.length===1&&r.packedInputs){let N=[Math.ceil(u[0]/2),Math.ceil(u[1]/2)];m=`${N[0]>1}_${N[1]>1}`}else if(c.length===2&&!r.packedInputs)f=`${c[0]>1}_${c[1]>1}`;else if(c.length>2&&!r.packedInputs){let N=y.computeStrides(c);d=`${N[0]===u[1]}_${N[N.length-1]===u[1]}`}let h=i.shape.length,g=c.length===2&&y.arraysEqual(i.shape,u),x=y.sizeFromShape(i.shape)===1,b=S.getBroadcastDims(i.shape,e.shape),w=!r.packedInputs&&h===e.shape.length&&y.arraysEqual(u,e.texData.texShape),C=r.packedInputs||c.length>2?"":`${u[0]>1}_${u[1]>1}`;n+=`${h}_${w}_${l?p:""}_${c.length}_${x}_${b}_${g}_${m}_${f}_${d}_${C}_${a}`}else{let u=i.isUniform?"uniform":i.texData.texShape;n+=`${i.shape}_${u}_${a}`}});let o=r.userCode,s=r.constructor.name;return s+="_"+n+"_"+o+`${M().getNumber("WEBGL_VERSION")}`,s}function we(r){return M().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&r<=4}var Cw=class{constructor(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=ku.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let e=Ve();this.outputShape=t,this.enableShapeUniforms=we(this.outputShape.length),this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${this.enableShapeUniforms?Mc(["r","c","d"],t):Js(["r","c","d"],t)}
        return ivec3(r, c, d);
      }

      void main() {
        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);

        vec4 result = vec4(0.);

        for (int i=0; i<4; i++) {
          int flatIndex = index + i;
          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
          result[i] = getA(rc.x, rc.y, rc.z);
        }

        ${e.output} = result;
      }
    `}};var Iw=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=ku.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let e=Ve();this.outputShape=t,this.enableShapeUniforms=we(this.outputShape.length),this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${this.enableShapeUniforms?Mc(["r","c","d"],t):Js(["r","c","d"],t)}
        return ivec3(r, c, d);
      }

      void main() {
        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);

        vec4 result = vec4(0.);

        for (int i=0; i<4; i++) {
          int flatIndex = index + i;
          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));
        }

        ${e.output} = result;
      }
    `}};var vw=class{constructor(t){this.variableNames=["A"],this.outTexUsage=Kr.DOWNLOAD;let e=Ve();this.outputShape=t,this.userCode=`
      ${bw}

      void main() {
        float x = getAAtOutCoords();
        ${e.output} = encode_float(x);
      }
    `}};var Sw=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Kr.DOWNLOAD;let e=Ve();this.outputShape=t,this.userCode=`
      ${bw}

      void main() {
        ivec3 coords = getOutputCoords();
        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
        ${e.output} = encode_float(x);
      }
    `}};var Nw=class{constructor(t,e=!1){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=Ve();this.outputShape=t,this.enableShapeUniforms=we(this.outputShape.length);let o="result";e&&(o="floor(result * 255. + 0.5)"),this.userCode=`
      ${this.enableShapeUniforms?md():pd(t)}

      void main() {
        ivec3 coords = getOutputCoords();

        int flatIndex = getFlatIndex(coords);
        int offset = imod(flatIndex, 4);

        flatIndex = idiv(flatIndex, 4, 1.);

        int r = flatIndex / texShape[1];
        int c = imod(flatIndex, texShape[1]);
        vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
        vec4 values = ${n.texture2D}(A, uv);

        float result;

        if(offset == 0) {
          result = values[0];
        } else if(offset == 1) {
          result = values[1];
        } else if(offset == 2) {
          result = values[2];
        } else {
          result = values[3];
        }

        ${n.output} = vec4(${o}, 0., 0., 0.);
      }
    `}};var kw=class{constructor(t,e=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=Ve();this.outputShape=t,this.enableShapeUniforms=we(this.outputShape.length);let o="",s="result";e&&(s="floor(result * 255. + 0.5)");for(let i=0;i<=1;i++)for(let a=0;a<=1;a++){let u=i*2+a;o+=`
          localCoords = coords;
          if(localCoords[2] + ${a} < ${this.enableShapeUniforms?"outShape[2]":`${t[2]}`}) {
          localCoords[2] += ${a};
          if (localCoords[1] + ${i} < ${this.enableShapeUniforms?"outShape[1]":`${t[1]}`}) {
            localCoords[1] += ${i};

            flatIndex = getFlatIndex(localCoords);
            offset = imod(flatIndex, 4);

            flatIndex = idiv(flatIndex, 4, 1.);

            int r = flatIndex / texShape[1];
            int c = imod(flatIndex, texShape[1]);
            vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
            values = ${n.texture2D}(A, uv);

            if (offset == 0) {
              result[${u}] = values[0];
            } else if (offset == 1) {
              result[${u}] = values[1];
            } else if (offset == 2) {
              result[${u}] = values[2];
            } else {
              result[${u}] = values[3];
            }
          }
        }
        `}this.userCode=`
        ${this.enableShapeUniforms?md():pd(t)}

        void main() {
          ivec3 coords = getOutputCoords();

          vec4 result = vec4(0.);
          int flatIndex, r, c, offset;
          ivec3 localCoords;
          vec2 uv;
          vec4 values;

          ${o}

          ${n.output} = ${s};
        }
    `}};var eT={};Gt(eT,{bindVertexProgramAttributeStreams:()=>Kk,createBufferFromOutputTexture:()=>Yk,createFloat16MatrixTexture:()=>Wk,createFloat16PackedMatrixTexture:()=>qk,createFloat32MatrixTexture:()=>Gk,createIndexBuffer:()=>Vk,createPackedMatrixTexture:()=>Hk,createUnsignedBytesMatrixTexture:()=>Uk,createVertexBuffer:()=>Bk,createVertexShader:()=>zk,downloadByteEncodedFloatMatrixFromOutputTexture:()=>Jk,downloadFloat32MatrixFromBuffer:()=>Zk,downloadMatrixFromPackedOutputTexture:()=>tT,downloadPackedMatrixFromBuffer:()=>Qk,getInternalFormatForFloat16MatrixTexture:()=>Ew,getInternalFormatForFloat16PackedMatrixTexture:()=>$w,getInternalFormatForFloat32MatrixTexture:()=>Tw,getInternalFormatForPackedMatrixTexture:()=>Aw,getInternalFormatForUnsignedBytesMatrixTexture:()=>_w,uploadDenseMatrixToTexture:()=>jk,uploadPixelDataToTexture:()=>Xk});function zk(r){let t=Ve(),e=`${t.version}
    precision highp float;
    ${t.attribute} vec3 clipSpacePos;
    ${t.attribute} vec2 uv;
    ${t.varyingVs} vec2 resultUV;

    void main() {
      gl_Position = vec4(clipSpacePos, 1);
      resultUV = uv;
    }`;return bk(r,e)}function Bk(r){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 vk(r,t)}function Vk(r){let t=new Uint16Array([0,1,2,2,1,3]);return Sk(r,t)}function jh(r,t,e,n,o,s){kk(t,e);let i=Nk(r),a=r.TEXTURE_2D;return yt(r,()=>r.bindTexture(a,i)),yt(r,()=>r.texParameteri(a,r.TEXTURE_WRAP_S,r.CLAMP_TO_EDGE)),yt(r,()=>r.texParameteri(a,r.TEXTURE_WRAP_T,r.CLAMP_TO_EDGE)),yt(r,()=>r.texParameteri(a,r.TEXTURE_MIN_FILTER,r.NEAREST)),yt(r,()=>r.texParameteri(a,r.TEXTURE_MAG_FILTER,r.NEAREST)),M().getNumber("WEBGL_VERSION")===1?yt(r,()=>r.texImage2D(a,0,n,t,e,0,o,s,null)):yt(r,()=>r.texStorage2D(a,1,n,t,e)),yt(r,()=>r.bindTexture(r.TEXTURE_2D,null)),{texture:i,texShape:[e,t]}}function Tw(r){return r.internalFormatFloat}function Gk(r,t,e,n){let[o,s]=Lc(t,e);return jh(r,o,s,Tw(n),n.textureFormatFloat,r.FLOAT)}function Ew(r){return r.internalFormatHalfFloat}function Wk(r,t,e,n){let[o,s]=Lc(t,e);return jh(r,o,s,Ew(n),n.textureFormatFloat,n.textureTypeHalfFloat)}function _w(r){return r.downloadTextureFormat}function Uk(r,t,e,n){let[o,s]=Lc(t,e);return jh(r,o,s,_w(n),r.RGBA,r.UNSIGNED_BYTE)}function Aw(r){return r.internalFormatPackedFloat}function Hk(r,t,e,n){let[o,s]=Ki(t,e);return jh(r,o,s,Aw(n),r.RGBA,r.FLOAT)}function $w(r){return r.internalFormatPackedHalfFloat}function qk(r,t,e,n){let[o,s]=Ki(t,e);return jh(r,o,s,$w(n),r.RGBA,n.textureTypeHalfFloat)}function Kk(r,t,e){return yt(r,()=>r.bindBuffer(r.ARRAY_BUFFER,e)),gw(r,t,"clipSpacePos",e,3,20,0)&&gw(r,t,"uv",e,2,20,12)}function jk(r,t,e,n,o,s){yt(r,()=>r.bindTexture(r.TEXTURE_2D,t));let i,a,u;o instanceof Uint8Array?(i=new Uint8Array(e*n*4),a=r.UNSIGNED_BYTE,u=r.RGBA):(i=new 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yt(r,()=>r.bufferData(r.PIXEL_PACK_BUFFER,a,r.STREAM_READ)),yt(r,()=>r.readPixels(0,0,e,t,r.RGBA,r.FLOAT,0)),yt(r,()=>r.bindBuffer(r.PIXEL_PACK_BUFFER,null)),o}function Zk(r,t,e){let n=r,o=new Float32Array(e);return n.bindBuffer(n.PIXEL_PACK_BUFFER,t),n.getBufferSubData(n.PIXEL_PACK_BUFFER,0,o),n.bindBuffer(n.PIXEL_PACK_BUFFER,null),o}function Jk(r,t,e,n){let[o,s]=Lc(t,e),i=4,a=new Uint8Array(BP(t*e,i));return yt(r,()=>r.readPixels(0,0,o,s,n.downloadTextureFormat,r.UNSIGNED_BYTE,a)),new Float32Array(a.buffer)}function Qk(r,t,e,n,o,s,i,a){let u=r,l=new Float32Array(VP(s,i));return u.bindBuffer(u.PIXEL_PACK_BUFFER,t),u.getBufferSubData(u.PIXEL_PACK_BUFFER,0,l),u.bindBuffer(u.PIXEL_PACK_BUFFER,null),l}function tT(r,t,e){let n=new Float32Array(t*e*4);return yt(r,()=>r.readPixels(0,0,e,t,r.RGBA,r.FLOAT,n)),n}var Bc=class{constructor(t){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let e=M().getNumber("WEBGL_VERSION");t!=null?(this.gl=t,hk(e,t)):this.gl=Bn(e);let n="WEBGL_color_buffer_float",o="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),M().getNumber("WEBGL_VERSION")===1){let s="OES_texture_float",i="OES_texture_half_float";if(this.textureFloatExtension=ld(this.gl,s),Vn(this.gl,i))this.textureHalfFloatExtension=ld(this.gl,i);else if(M().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),Vn(this.gl,o))this.colorBufferHalfFloatExtension=ld(this.gl,o);else if(M().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",Vn(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(Vn(this.gl,o))this.colorBufferHalfFloatExtension=this.gl.getExtension(o);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=Bk(this.gl),this.indexBuffer=Vk(this.gl),this.framebuffer=Tk(this.gl),this.textureConfig=Uh(this.gl,this.textureHalfFloatExtension)}get debug(){return M().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 t=this.gl;yt(t,()=>t.finish()),yt(t,()=>t.bindFramebuffer(t.FRAMEBUFFER,null)),yt(t,()=>t.deleteFramebuffer(this.framebuffer)),yt(t,()=>t.bindBuffer(t.ARRAY_BUFFER,null)),yt(t,()=>t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,null)),yt(t,()=>t.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(t,e){return this.throwIfDisposed(),Gk(this.gl,t,e,this.textureConfig)}createFloat16MatrixTexture(t,e){return this.throwIfDisposed(),Wk(this.gl,t,e,this.textureConfig)}createUnsignedBytesMatrixTexture(t,e){return this.throwIfDisposed(),Uk(this.gl,t,e,this.textureConfig)}uploadPixelDataToTexture(t,e){this.throwIfDisposed(),Xk(this.gl,t,e)}uploadDenseMatrixToTexture(t,e,n,o){this.throwIfDisposed(),jk(this.gl,t,e,n,o,this.textureConfig)}createFloat16PackedMatrixTexture(t,e){return this.throwIfDisposed(),qk(this.gl,t,e,this.textureConfig)}createPackedMatrixTexture(t,e){return this.throwIfDisposed(),Hk(this.gl,t,e,this.textureConfig)}deleteMatrixTexture(t){this.throwIfDisposed(),this.outputTexture===t&&(xw(this.gl,this.framebuffer),this.outputTexture=null),yt(this.gl,()=>this.gl.deleteTexture(t))}downloadByteEncodedFloatMatrixFromOutputTexture(t,e,n){return this.downloadMatrixDriver(t,()=>Jk(this.gl,e,n,this.textureConfig))}downloadPackedMatrixFromBuffer(t,e,n,o,s,i){return Qk(this.gl,t,e,n,o,s,i,this.textureConfig)}downloadFloat32MatrixFromBuffer(t,e){return Zk(this.gl,t,e)}createBufferFromTexture(t,e,n){this.bindTextureToFrameBuffer(t);let o=Yk(this.gl,e,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),o}createAndWaitForFence(){let t=this.createFence(this.gl);return this.pollFence(t)}createFence(t){let e,n;if(M().getBool("WEBGL_FENCE_API_ENABLED")){let o=t,s=o.fenceSync(o.SYNC_GPU_COMMANDS_COMPLETE,0);t.flush(),n=()=>{let 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yt(e,()=>e.attachShader(n,this.vertexShader)),yt(e,()=>e.attachShader(n,t)),Ik(e,n),this.debug&&Hh(e,n),this.vertexAttrsAreBound||(this.setProgram(n),this.vertexAttrsAreBound=Kk(e,this.program,this.vertexBuffer)),n}deleteProgram(t){this.throwIfDisposed(),t===this.program&&(this.program=null),t!=null&&yt(this.gl,()=>this.gl.deleteProgram(t))}setProgram(t){this.throwIfDisposed(),this.program=t,this.program!=null&&this.debug&&Hh(this.gl,this.program),yt(this.gl,()=>this.gl.useProgram(t))}getUniformLocation(t,e,n=!0){return this.throwIfDisposed(),n?Ek(this.gl,t,e):_k(this.gl,t,e)}getAttributeLocation(t,e){return this.throwIfDisposed(),yt(this.gl,()=>this.gl.getAttribLocation(t,e))}getUniformLocationNoThrow(t,e){return this.throwIfDisposed(),this.gl.getUniformLocation(t,e)}setInputMatrixTexture(t,e,n){this.throwIfDisposed(),this.throwIfNoProgram(),Ak(this.gl,t,e,n)}setOutputMatrixTexture(t,e,n){this.setOutputMatrixTextureDriver(t,n,e)}setOutputPackedMatrixTexture(t,e,n){this.throwIfDisposed();let[o,s]=Ki(e,n);this.setOutputMatrixTextureDriver(t,o,s)}setOutputMatrixWriteRegion(t,e,n,o){this.setOutputMatrixWriteRegionDriver(n,t,o,e)}setOutputPackedMatrixWriteRegion(t,e,n,o){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&Hh(this.gl,this.program),ud(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let t=this.gl;this.debug&&this.debugValidate(),yt(t,()=>t.drawElements(t.TRIANGLES,6,t.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),yt(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=ld(this.gl,M().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(M().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,o=this.getQueryTimerExtensionWebGL2(),s=n.createQuery();return n.beginQuery(o.TIME_ELAPSED_EXT,s),s}let t=this.getQueryTimerExtensionWebGL1(),e=t.createQueryEXT();return t.beginQueryEXT(t.TIME_ELAPSED_EXT,e),e}endQuery(){if(M().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let e=this.gl,n=this.getQueryTimerExtensionWebGL2();e.endQuery(n.TIME_ELAPSED_EXT);return}let t=this.getQueryTimerExtensionWebGL1();t.endQueryEXT(t.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(t){return await y.repeatedTry(()=>this.disposed||this.isQueryAvailable(t,M().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(t,M().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(t,e){if(e===0)return null;if(e===2){let n=this.gl;return n.getQueryParameter(t,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(t,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(t,e){if(e===0)return!0;if(e===2){let n=this.gl,o=this.getQueryTimerExtensionWebGL2(),s=n.getQueryParameter(t,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(o.GPU_DISJOINT_EXT)),s&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),o=n.getQueryObjectEXT(t,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),o&&!this.disjoint}}pollFence(t){return new Promise(e=>{this.addItemToPoll(()=>t.isFencePassed(),()=>e())})}pollItems(){let t=Ltt(this.itemsToPoll.map(e=>e.isDoneFn));for(let e=0;e<=t;++e){let{resolveFn:n}=this.itemsToPoll[e];n()}this.itemsToPoll=this.itemsToPoll.slice(t+1)}addItemToPoll(t,e){if(this.itemsToPoll.push({isDoneFn:t,resolveFn:e}),this.itemsToPoll.length>1)return;let n;"setTimeoutCustom"in M().platform&&(n=M().platform.setTimeoutCustom.bind(M().platform)),y.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0),()=>0,null,n)}bindTextureToFrameBuffer(t){this.throwIfDisposed(),qh(this.gl,t,this.framebuffer),this.debug&&ud(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(qh(this.gl,this.outputTexture,this.framebuffer),this.debug&&ud(this.gl)):xw(this.gl,this.framebuffer)}downloadMatrixDriver(t,e){this.bindTextureToFrameBuffer(t);let n=e();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(t,e,n){this.throwIfDisposed();let o=this.gl;qh(o,t,this.framebuffer),this.debug&&ud(o),this.outputTexture=t,yt(o,()=>o.viewport(0,0,e,n)),yt(o,()=>o.scissor(0,0,e,n))}setOutputMatrixWriteRegionDriver(t,e,n,o){this.throwIfDisposed(),yt(this.gl,()=>this.gl.scissor(t,e,n,o))}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 Ltt(r){let t=0;for(;t<r.length&&r[t]();++t);return t-1}var{addImpl:eL,bincountImpl:Dw,bincountReduceImpl:rL,castImpl:nL,ceilImpl:oL,concatImpl:sL,equalImpl:iL,expImpl:aL,expm1Impl:lL,floorImpl:uL,gatherNdImpl:cL,gatherV2Impl:pL,greaterImpl:mL,greaterEqualImpl:fL,lessImpl:dL,lessEqualImpl:hL,linSpaceImpl:gL,logImpl:xL,maxImpl:yL,maximumImpl:bL,minimumImpl:wL,multiplyImpl:CL,negImpl:IL,notEqualImpl:vL,prodImpl:SL,raggedGatherImpl:NL,raggedTensorToTensorImpl:kL,rangeImpl:TL,rsqrtImpl:EL,scatterImpl:_L,sigmoidImpl:AL,simpleAbsImpl:Rw,sliceImpl:$L,sparseFillEmptyRowsImpl:DL,sparseReshapeImpl:RL,sparseSegmentReductionImpl:Fw,sqrtImpl:FL,stridedSliceImpl:OL,stringNGramsImpl:PL,stringSplitImpl:LL,stringToHashBucketFastImpl:ML,subImpl:zL,tileImpl:BL,topKImpl:VL,transposeImpl:Vc,uniqueImpl:GL}=iw;function rT(r,t){return["x","y","z","w","u","v"].slice(0,t).map(e=>`${r}.${e}`)}function Qe(r,t){return t===1?[r]:rT(r,t)}function WL(r,t){if(r===1)return"rc";let e="";for(let n=0;n<r;n++)e+=t[n],n<r-1&&(e+=",");return e}var Ow=class{constructor(t){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=t,this.rank=t.length,this.enableShapeUniforms=we(this.outputShape.length),this.rank===0)this.userCode=`
        void main() {
          setOutput(vec4(getA(), 0., 0., 0.));
        }
      `;else{let e=Qe("rc",this.rank),n=zt(this.rank),o=this.getOutOfBoundsCondition(e),s=this.getSetup(e),i=this.getOutput(e);this.userCode=`
        void main() {
          ${n} rc = getOutputCoords();

          if(${o}) {
            setOutput(vec4(0));
          } else {
            ${s}

            setOutput(vec4(${i}));
          }
        }
      `}}getSourceCoordsArr(t){let e=[];for(let n=0;n<=1;n++)for(let o=0;o<=1;o++){let s=`${n===0?"r":"rp1"}, ${o===0?"c":"cp1"}`;for(let i=2;i<this.rank;i++)s=`${t[t.length-1-i]},`+s;e.push(s)}return e}getOutOfBoundsCondition(t){if(this.rank===1)return`rc > ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let e="";for(let n=this.rank-2;n<this.rank;n++)e+=`${t[n]} >= ${this.enableShapeUniforms?`outShape[${n}]`:this.outputShape[n]}`,n<this.rank-1&&(e+="||");return e}getSetup(t){if(this.rank===1)return"";let e=t.slice(-2),n=this.enableShapeUniforms?`outShape[${this.rank} - 1]`:this.outputShape[this.rank-1],o=this.enableShapeUniforms?`outShape[${this.rank} - 2]`:this.outputShape[this.rank-2];return`
      int r = ${e[0]};
      int c = ${e[1]};
      int rp1 = r + 1;
      int cp1 = c + 1;

      bool cEdge = cp1 >= ${n};
      bool rEdge = rp1 >= ${o};
    `}getOutput(t){let e=this.getSourceCoordsArr(t);return this.rank===1?`getA(rc), (rc + 1 >= ${this.enableShapeUniforms?"outShape":this.outputShape[0]} ? 0. : getA(rc + 1)), 0, 0`:`getA(${e[0]}),
            cEdge ? 0. : getA(${e[1]}),
            rEdge ? 0. : getA(${e[2]}),
            rEdge || cEdge ? 0. : getA(${e[3]})`}};var yd=class{constructor(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=t,this.enableShapeUniforms=we(this.outputShape.length);let n="";for(let o=0;o<4;o++){let s="thisRC = rc;";o%2===1&&(s+="thisRC.z += 1;"),o>1&&(s+="thisRC.y += 1;"),n+=`
        ${s}
        ${o>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
          int flatIndex = getFlatIndex(thisRC);

          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));

          result[${o}] =
            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
        ${o>0?"}":""}
      `}this.userCode=`
      ${Mtt(e,this.enableShapeUniforms)}
      ${this.enableShapeUniforms?md():pd(t)}

      void main() {
        ivec3 rc = getOutputCoords();

        vec4 result = vec4(0.);

        ivec3 thisRC;
        int rows = ${this.enableShapeUniforms?"outShape[1]":t[1]};
        int cols = ${this.enableShapeUniforms?"outShape[2]":t[2]};

        ${n}

        setOutput(result);
      }
    `}};function Mtt(r,t){return`
    ivec3 inputCoordsFromReshapedOutCoords(int index) {
      ${t?qP(["r","c","d"],"inputShape"):Js(["r","c","d"],r)}
      return ivec3(r, c, d);
    }
  `}var Pw=class{constructor(t){this.gpgpu=t,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(t,e,n){let o=HL(e,n),s=qL(t,o,n);s in this.freeTextures||(this.freeTextures[s]=[]),s in this.usedTextures||(this.usedTextures[s]=[]);let i=UL(t,o,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[s].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=i,this.log();let u=this.freeTextures[s].shift();return this.usedTextures[s].push(u),u}let a;return o===Fr.PACKED_2X2_FLOAT32?a=this.gpgpu.createPackedMatrixTexture(t[0],t[1]):o===Fr.PACKED_2X2_FLOAT16?a=this.gpgpu.createFloat16PackedMatrixTexture(t[0],t[1]):o===Fr.UNPACKED_FLOAT32?a=this.gpgpu.createFloat32MatrixTexture(t[0],t[1]):o===Fr.UNPACKED_FLOAT16?a=this.gpgpu.createFloat16MatrixTexture(t[0],t[1]):o===Fr.PACKED_4X1_UNSIGNED_BYTE&&(a=this.gpgpu.createUnsignedBytesMatrixTexture(t[0],t[1])),this.usedTextures[s].push(a),this.numUsedTextures++,this._numBytesAllocated+=i,this.log(),a}releaseTexture(t,e,n,o){if(this.freeTextures==null)return;let s=HL(n,o),i=qL(e,s,o);i in this.freeTextures||(this.freeTextures[i]=[]);let a=UL(e,s,this.gpgpu.gl,this.gpgpu.textureConfig,o),u=M().get("WEBGL_DELETE_TEXTURE_THRESHOLD");u!==-1&&this._numBytesAllocated>u?(this.gpgpu.deleteMatrixTexture(t.texture),this._numBytesAllocated-=a):(this.freeTextures[i].push(t),this.numFreeTextures++,this._numBytesFree+=a),this.numUsedTextures--;let l=this.usedTextures[i],c=l.indexOf(t);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let t=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${t})`);let e=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*e)}%)`)}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 t in this.freeTextures)this.freeTextures[t].forEach(e=>{this.gpgpu.deleteMatrixTexture(e.texture)});for(let t in this.usedTextures)this.usedTextures[t].forEach(e=>{this.gpgpu.deleteMatrixTexture(e.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function ztt(r,t){let e=r;if(t===e.R32F)return 4;if(t===e.R16F)return 2;if(t===e.RGBA32F)return 16;if(t===r.RGBA)return 16;if(t===e.RGBA16F)return 8;if(t===e.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function UL(r,t,e,n,o){let s=Btt(t,n),i;if(o){let[u,l]=Ki(r[0],r[1]);i=u*l}else{let[u,l]=Lc(r[0],r[1]);i=u*l}let a=ztt(e,s);return i*a}function Btt(r,t){switch(r){case Fr.PACKED_2X2_FLOAT32:return Aw(t);case Fr.PACKED_2X2_FLOAT16:return $w(t);case Fr.UNPACKED_FLOAT32:return Tw(t);case Fr.UNPACKED_FLOAT16:return Ew(t);case Fr.PACKED_4X1_UNSIGNED_BYTE:return _w(t);default:throw new Error(`Unknown physical texture type ${r}`)}}function Vtt(r){return M().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?r?Fr.PACKED_2X2_FLOAT32:Fr.UNPACKED_FLOAT32:r?Fr.PACKED_2X2_FLOAT16:Fr.UNPACKED_FLOAT16}function HL(r,t){if(r===Kr.UPLOAD)return Fr.PACKED_2X2_FLOAT32;if(r===Kr.RENDER||r==null)return Vtt(t);if(r===Kr.DOWNLOAD||r===Kr.PIXELS)return Fr.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${r}`)}function qL(r,t,e){return`${r[0]}_${r[1]}_${t}_${e}`}var tn=class{constructor(t,e){this.variableNames=["A"],this.outputShape=t,this.enableShapeUniforms=we(this.outputShape.length),this.userCode=`
      float unaryOperation(float x) {
        ${e}
      }

      void main() {
        float x = getAAtOutCoords();
        float y = unaryOperation(x);

        setOutput(y);
      }
    `}},pr="if (isnan(x)) return x;",KL="return x;",nT="return abs(x);";var jL="return (x >= 0.0) ? x : (exp(x) - 1.0);",XL=pr+`
  return (x < 0.0) ? 0.0 : x;
`,YL=pr+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,Gc="return x;",ZL="return 1.0 / (1.0 + exp(-1.0 * x));";var QL="return x;",tM=`
  vec4 result;

  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);
  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);

  return result;
`,eM=`
  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,rM=`
  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,nM="return 1.0 / (1.0 + exp(-1.0 * x));",no=class{constructor(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.enableShapeUniforms=we(this.outputShape.length),this.userCode=`
      vec4 unaryOperation(vec4 x) {
        ${e}
      }

      void main() {
        vec4 x = getAAtOutCoords();
        vec4 y = unaryOperation(x);

        setOutput(y);
      }
    `}};var Lw=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=t,this.enableShapeUniforms=we(this.outputShape.length);let e=t.length,n=Qe("rc",e),o=zt(e),s=WL(e,n),i=n.slice(-2),a=e<=1?"rc":`vec2(${i.join(",")})`;this.userCode=`
      void main() {
        ${o} rc = getOutputCoords();
        vec4 packedInput = getA(${s});

        setOutput(getChannel(packedInput, ${a}));
      }
    `}};var Wtt=Wr.whereImpl,Utt=1e-7,Htt=1e-4,Mw={};function qtt(r){return r in Mw||(Mw[r]={}),Mw[r]}var Ktt=M().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),jtt=600;function Xtt(){return M().global.screen==null?1024:M().global.screen.height*M().global.screen.width*window.devicePixelRatio*jtt/1024/1024}var Eu=class extends Mo{constructor(t){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!M().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let e;if(t!=null){if(t instanceof Bc)e=t;else{let n=Bn(M().getNumber("WEBGL_VERSION"),t);e=new Bc(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Bn(M().getNumber("WEBGL_VERSION"));e=new Bc(n),this.binaryCache=qtt(M().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=e,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new Pw(this.gpgpu),this.numMBBeforeWarning=Xtt(),this.texData=new ta(this,ho())}nextDataId(){return Eu.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}write(t,e,n){if((M().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||M().getBool("DEBUG"))&&this.checkNumericalProblems(t),n==="complex64"&&t!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let o={id:this.nextDataId()};return this.texData.set(o,{shape:e,dtype:n,values:t,usage:Kr.UPLOAD,refCount:1}),o}refCount(t){return this.texData.has(t)?this.texData.get(t).refCount:0}incRef(t){let e=this.texData.get(t);e.refCount++}decRef(t){if(this.texData.has(t)){let e=this.texData.get(t);e.refCount--}}move(t,e,n,o,s){if(M().getBool("DEBUG")&&this.checkNumericalProblems(e),o==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(t,{shape:n,dtype:o,values:e,usage:Kr.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(t){this.disposeData(t.dataId)}readSync(t){let e=this.texData.get(t),{values:n,dtype:o,complexTensorInfos:s,slice:i,shape:a,isPacked:u}=e;if(i!=null){let m;u?m=new no(a,Gc):m=new tn(a,Gc);let f=this.runWebGLProgram(m,[{dataId:t,shape:a,dtype:o}],o),d=this.readSync(f.dataId);return this.disposeIntermediateTensorInfo(f),d}if(n!=null)return this.convertAndCacheOnCPU(t);if(o==="string")return n;let l=this.activeTimers!=null,c;l&&(c=y.now());let p;if(o==="complex64"){let m=this.readSync(s.real.dataId),f=this.readSync(s.imag.dataId);p=S.mergeRealAndImagArrays(m,f)}else p=this.getValuesFromTexture(t);return l&&(this.downloadWaitMs+=y.now()-c),this.convertAndCacheOnCPU(t,p)}async read(t){if(this.pendingRead.has(t)){let d=this.pendingRead.get(t);return new Promise(h=>d.push(h))}let e=this.texData.get(t),{values:n,shape:o,slice:s,dtype:i,complexTensorInfos:a,isPacked:u}=e;if(s!=null){let d;u?d=new no(o,Gc):d=new tn(o,Gc);let h=this.runWebGLProgram(d,[{dataId:t,shape:o,dtype:i}],i),g=this.read(h.dataId);return this.disposeIntermediateTensorInfo(h),g}if(n!=null)return this.convertAndCacheOnCPU(t);if(M().getBool("DEBUG")&&!M().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&M().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(i!=="complex64"&&M().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(t);let d=this.texData.get(c.dataId);l=this.gpgpu.createBufferFromTexture(d.texture.texture,...Wh(o))}this.pendingRead.set(t,[]),i!=="complex64"&&await this.gpgpu.createAndWaitForFence();let p;if(i==="complex64"){let d=await Promise.all([this.read(a.real.dataId),this.read(a.imag.dataId)]),h=d[0],g=d[1];p=S.mergeRealAndImagArrays(h,g)}else if(l==null)p=this.getValuesFromTexture(t);else{let d=y.sizeFromShape(o);p=this.gpgpu.downloadFloat32MatrixFromBuffer(l,d)}if(c!=null&&this.disposeIntermediateTensorInfo(c),l!=null){let d=this.gpgpu.gl;yt(d,()=>d.deleteBuffer(l))}let m=this.convertAndCacheOnCPU(t,p),f=this.pendingRead.get(t);return this.pendingRead.delete(t),f.forEach(d=>d(m)),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t)&&ho().removeDataId(t,this),this.pendingDeletes--),m}readToGPU(t,e={}){let n=this.texData.get(t),{values:o,shape:s,slice:i,dtype:a,isPacked:u,texture:l}=n;if(a==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(i!=null){let f;u?f=new no(s,Gc):f=new tn(s,Gc);let d=this.runWebGLProgram(f,[{dataId:t,shape:s,dtype:a}],a),h=this.readToGPU(d,e);return this.disposeIntermediateTensorInfo(d),h}if(l==null)throw o!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let c=this.decode(t,e.customTexShape),p=ho().makeTensorFromTensorInfo(c),m=this.texData.get(c.dataId);return Object.assign({tensorRef:p},m.texture)}bufferSync(t){let e=this.readSync(t.dataId);if(t.dtype==="string")try{let n=e.map(o=>y.decodeString(o));return wt(t.shape,t.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return wt(t.shape,t.dtype,e)}checkNumericalProblems(t){if(t!=null)for(let e=0;e<t.length;e++){let n=t[e];if(!yk(n))throw M().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 ${n} cannot be represented on this device.`)}}getValuesFromTexture(t){let{shape:e,dtype:n,isPacked:o}=this.texData.get(t),s=y.sizeFromShape(e);if(M().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let m=this.decode(t),f=this.texData.get(m.dataId),d=this.gpgpu.downloadMatrixFromPackedTexture(f.texture.texture,...Wh(e)).subarray(0,s);return this.disposeIntermediateTensorInfo(m),d}let i=M().getBool("WEBGL_PACK")&&o===!0,a=i?Kh(e):e,u=i?new Sw(a):new vw(a),l=this.runWebGLProgram(u,[{shape:a,dtype:n,dataId:t}],"float32"),c=this.texData.get(l.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture.texture,c.texShape[0],c.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(l),p}timerAvailable(){return M().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(t){let e=this.activeTimers,n=[],o=!1;this.programTimersStack==null?(this.programTimersStack=n,o=!0):this.activeTimers.push(n),this.activeTimers=n,t();let s=y.flatten(this.activeTimers.map(u=>u.query)).filter(u=>u!=null),i=y.flatten(this.activeTimers.map(u=>u.name)).filter(u=>u!=null);this.activeTimers=e,o&&(this.programTimersStack=null);let a={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(M().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let u=await Promise.all(s);a.kernelMs=y.sum(u),a.getExtraProfileInfo=()=>u.map((l,c)=>({name:i[c],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else a.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,a})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return M().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:y.now(),endMs:null}}endTimer(t){return M().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),t):(t.endMs=y.now(),t)}async getQueryTime(t){if(M().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(t);let e=t;return e.endMs-e.startMs}disposeData(t,e=!1){if(this.pendingDisposal.has(t))return!1;if(!this.texData.has(t))return!0;if(e?this.texData.get(t).refCount=0:this.texData.get(t).refCount--,!e&&this.texData.get(t).refCount>0)return!1;if(this.pendingRead.has(t))return this.pendingDisposal.add(t),this.pendingDeletes++,!1;this.releaseGPUData(t);let{complexTensorInfos:n}=this.texData.get(t);return n!=null&&(this.disposeData(n.real.dataId,e),this.disposeData(n.imag.dataId,e)),this.texData.delete(t),!0}releaseGPUData(t){let{texture:e,dtype:n,texShape:o,usage:s,isPacked:i,slice:a}=this.texData.get(t),u=a&&a.origDataId||t,l=this.dataRefCount.get(u);l>1?this.dataRefCount.set(u,l-1):(this.dataRefCount.delete(u),e!=null&&(this.numBytesInGPU-=this.computeBytes(o,n),this.textureManager.releaseTexture(e,o,s,i)));let c=this.texData.get(t);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(t){return this.uploadToGPU(t),this.texData.get(t).texture.texture}getDataInfo(t){return this.texData.get(t)}shouldExecuteOnCPU(t,e=Ktt){return M().getBool("WEBGL_CPU_FORWARD")&&t.every(n=>this.texData.get(n.dataId).texture==null&&y.sizeFromShape(n.shape)<e)}getGPGPUContext(){return this.gpgpu}where(t){S.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let e=t.dataSync();return Wtt(t.shape,e)}packedUnaryOp(t,e,n){let o=new no(t.shape,e),s=this.compileAndRun(o,[t],n);return ho().makeTensorFromTensorInfo(s)}abs(t){if(this.shouldExecuteOnCPU([t])&&t.dtype!=="complex64"){let o=Rw(this.texData.get(t.dataId).values);return this.makeOutput(t.shape,t.dtype,o)}if(M().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,nT,t.dtype);let e=new tn(t.shape,nT),n=this.compileAndRun(e,[t]);return ho().makeTensorFromTensorInfo(n)}makeTensorInfo(t,e,n){let o;if(e==="string"&&n!=null&&n.length>0&&y.isString(n[0])){let s=n.map(i=>y.encodeString(i));o=this.write(s,t,e)}else o=this.write(n,t,e);return this.texData.get(o).usage=null,{dataId:o,shape:t,dtype:e}}makeOutput(t,e,n){return ho().makeTensorFromTensorInfo(this.makeTensorInfo(t,e,n),this)}unpackTensor(t){let e=new Lw(t.shape);return this.runWebGLProgram(e,[t],t.dtype)}packTensor(t){let e=new Ow(t.shape),n=!0;return this.runWebGLProgram(e,[t],t.dtype,null,n)}packedReshape(t,e){let n=[hl(t.shape),...gl(t.shape)],o={dtype:t.dtype,shape:n,dataId:t.dataId},s=[hl(e),...gl(e)],i=new yd(s,n),a=!0,u=[n],l=this.runWebGLProgram(i,[o],t.dtype,u,a);return{dataId:l.dataId,shape:e,dtype:l.dtype}}decode(t,e){let n=this.texData.get(t),{isPacked:o,shape:s,dtype:i}=n;if(e!=null){let m=y.sizeFromShape(s),f=e[0]*e[1]*4;y.assert(m<=f,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let a=Kh(s),u;o?u=new Iw(a):u=new Cw(a);let l=!0,c=[e!=null?e:Wh(a)],p=this.runWebGLProgram(u,[{shape:a,dtype:i,dataId:t}],i,c,l,e);return{dtype:i,shape:s,dataId:p.dataId}}runWebGLProgram(t,e,n,o,s=!1,i){let a=this.makeTensorInfo(t.outputShape,n),u=this.texData.get(a.dataId);if(t.packedOutput&&(u.isPacked=!0),t.outPackingScheme===ku.DENSE){let x=i!=null?i:Wh(t.outputShape);u.texShape=x.map(b=>b*2)}if(t.outTexUsage!=null&&(u.usage=t.outTexUsage),y.sizeFromShape(a.shape)===0)return u.values=y.getTypedArrayFromDType(a.dtype,0),a;let l=[],c=e.map(x=>{if(x.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let b=this.texData.get(x.dataId);if(b.texture==null){if(!t.packedInputs&&y.sizeFromShape(x.shape)<=M().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:x.shape,texData:null,isUniform:!0,uniformValues:b.values};t.packedInputs&&(b.isPacked=!0,b.shape=x.shape)}if(this.uploadToGPU(x.dataId),!!b.isPacked!=!!t.packedInputs)x=b.isPacked?this.unpackTensor(x):this.packTensor(x),l.push(x),b=this.texData.get(x.dataId);else if(b.isPacked&&!Tu(b.shape,x.shape)){let w=x,C=x.shape;x.shape=b.shape,x=this.packedReshape(x,C),l.push(x),b=this.texData.get(x.dataId),w.shape=C}return{shape:x.shape,texData:b,isUniform:!1}});this.uploadToGPU(a.dataId);let p={shape:a.shape,texData:u,isUniform:!1},m=tL(t,c,p),f=this.getAndSaveBinary(m,()=>JP(this.gpgpu,t,c,p)),d=this.activeTimers!=null,h;d&&(h=this.startTimer()),M().get("ENGINE_COMPILE_ONLY")||QP(this.gpgpu,f,c,p,o),l.forEach(x=>this.disposeIntermediateTensorInfo(x)),d&&(h=this.endTimer(h),this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime(h)}));let g=M().get("WEBGL_FLUSH_THRESHOLD");if(g>0){let x=y.now();x-this.lastGlFlushTime>g&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=x)}if(!M().getBool("WEBGL_LAZILY_UNPACK")&&u.isPacked&&s===!1){let x=this.unpackTensor(a);return this.disposeIntermediateTensorInfo(a),x}return a}compileAndRun(t,e,n,o,s=!1){return n=n||e[0].dtype,this.runWebGLProgram(t,e,n,o,s)}getAndSaveBinary(t,e){return t in this.binaryCache||(this.binaryCache[t]=e()),this.binaryCache[t]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(M().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=B(()=>{if(!M().get("WEBGL_RENDER_FLOAT32_ENABLED")){let t=M().getBool("DEBUG");M().set("DEBUG",!1);let e=this.abs(mt(1e-8)).dataSync()[0];if(M().set("DEBUG",t),e>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?Utt:Htt}uploadToGPU(t){let e=this.texData.get(t),{shape:n,dtype:o,values:s,texture:i,usage:a,isPacked:u}=e;if(i!=null)return;let l=this.activeTimers!=null,c;l&&(c=y.now());let p=e.texShape;if(p==null&&(p=$k(n,u),e.texShape=p),s!=null){let m=Kh(n),f,d=p[1],h=p[0],g=s instanceof Uint8Array||s instanceof Uint8ClampedArray;(u||!g)&&([d,h]=Ki(p[0],p[1])),u?f=new kw(m,g):f=new Nw(m,g);let x=g?[h,d]:p,b=this.makeTensorInfo(x,o),w=this.texData.get(b.dataId);g?w.usage=Kr.PIXELS:w.usage=Kr.UPLOAD,w.texShape=x,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(b.dataId),d,h,s);let C=[[h,d]],N=!0,_=this.runWebGLProgram(f,[b],o,C,N),A=this.texData.get(_.dataId);e.texShape=A.texShape,e.isPacked=A.isPacked,e.usage=A.usage,M().get("ENGINE_COMPILE_ONLY")?this.disposeData(_.dataId):(e.texture=A.texture,e.values=null,this.texData.delete(_.dataId)),this.disposeIntermediateTensorInfo(b),l&&(this.uploadWaitMs+=y.now()-c)}else{let m=this.acquireTexture(p,a,o,u);e.texture=m}}convertAndCacheOnCPU(t,e){let n=this.texData.get(t),{dtype:o}=n;return this.releaseGPUData(t),e!=null&&(n.values=Ytt(e,o)),n.values}acquireTexture(t,e,n,o){if(this.numBytesInGPU+=this.computeBytes(t,n),!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(t,e,o)}computeBytes(t,e){return t[0]*t[1]*y.bytesPerElement(e)}checkCompileCompletion(){for(let[,t]of Object.entries(this.binaryCache))this.checkCompletion_(t)}async checkCompileCompletionAsync(){let t=[];if(this.gpgpu.parallelCompilationExtension){for(let[,e]of Object.entries(this.binaryCache))t.push(this.checkCompletionAsync_(e));return Promise.all(t)}else{for(let[,e]of Object.entries(this.binaryCache)){let n=new Promise(o=>{try{this.checkCompletion_(e),o(!0)}catch(s){throw s}});t.push(n)}return Promise.all(t)}}async checkCompletionAsync_(t){return this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(t):(await ph(),this.checkCompletionAsync_(t))}checkCompletion_(t){if(this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(t.webGLProgram)),this.gpgpu.gl.getShaderParameter(t.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(hw(t.source,this.gpgpu.gl.getShaderInfoLog(t.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let[,t]of Object.entries(this.binaryCache)){let{uniformLocations:e,customUniformLocations:n,infLoc:o,nanLoc:s,inShapesLocations:i,inTexShapesLocations:a,outShapeLocation:u,outShapeStridesLocation:l,outTexShapeLocation:c}=Mk(this.gpgpu,t.program,t.webGLProgram);t.uniformLocations=e,t.customUniformLocations=n,t.infLoc=o,t.nanLoc=s,t.inShapesLocations=i,t.inTexShapesLocations=a,t.outShapeLocation=u,t.outShapeStridesLocation=l,t.outTexShapeLocation=c}}};Eu.nextDataId=0;function Ytt(r,t){if(t==="float32"||t==="complex64")return r;if(t==="int32"||t==="bool"){let e=t==="int32"?new Int32Array(r.length):new Uint8Array(r.length);for(let n=0;n<e.length;++n)e[n]=Math.round(r[n]);return e}else throw new Error(`Unknown dtype ${t}`)}var oM="3.21.0";function sM(){M().set("WEBGL_FORCE_F16_TEXTURES",!0)}Hl.isBrowser()&&jp("webgl",()=>new Eu,2);var oTe={forceHalfFloat:sM};var bd=`
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`;var oo=class{constructor(t,e,n){this.variableNames=["A","B"],this.outputShape=S.assertAndGetBroadcastShape(e,n),this.enableShapeUniforms=we(this.outputShape.length),this.userCode=`
      float binaryOperation(float a, float b) {
        ${t}
      }

      void main() {
        float a = getAAtOutCoords();
        float b = getBAtOutCoords();
        setOutput(binaryOperation(a, b));
      }
    `}};var ji=`
  result.r = isNaN.r ? NAN : result.r;
  result.g = isNaN.g ? NAN : result.g;
  result.b = isNaN.b ? NAN : result.b;
  result.a = isNaN.a ? NAN : result.a;
`;var Fo=class{constructor(t,e,n,o=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=S.assertAndGetBroadcastShape(e,n);let s=this.outputShape.length;this.enableShapeUniforms=we(s);let i="";if(o)if(s===0||y.sizeFromShape(this.outputShape)===1)i=`
          result.y = 0.;
          result.z = 0.;
          result.w = 0.;
        `;else if(i=`
          ${zt(s)} coords = getOutputCoords();
        `,s===1)this.enableShapeUniforms?i+=`
            result.y = (coords + 1) >= outShape ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `:i+=`
            result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `;else{let u=Qe("coords",s);this.enableShapeUniforms?i+=`
            bool nextRowOutOfBounds =
              (${u[s-2]} + 1) >= outShape[${s} - 2];
            bool nextColOutOfBounds =
              (${u[s-1]} + 1) >= outShape[${s} - 1];
            result.y = nextColOutOfBounds ? 0. : result.y;
            result.z = nextRowOutOfBounds ? 0. : result.z;
            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
          `:i+=`
            bool nextRowOutOfBounds =
              (${u[s-2]} + 1) >= ${this.outputShape[s-2]};
            bool nextColOutOfBounds =
              (${u[s-1]} + 1) >= ${this.outputShape[s-1]};
            result.y = nextColOutOfBounds ? 0. : result.y;
            result.z = nextRowOutOfBounds ? 0. : result.z;
            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
          `}this.userCode=`
      vec4 binaryOperation(vec4 a, vec4 b) {
        ${t}
      }

      void main() {
        vec4 a = getAAtOutCoords();
        vec4 b = getBAtOutCoords();

        vec4 result = binaryOperation(a, b);
        ${i}

        setOutput(result);
      }
    `}};function tr(r){let{inputs:t,backend:e}=r,{x:n}=t;return e.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var iM={kernelName:lo,backendName:"webgl",kernelFunc:tr};function Tn(r){let{inputs:t,backend:e}=r,{real:n,imag:o}=t,s=e.makeTensorInfo(n.shape,"complex64"),i=e.texData.get(s.dataId),a=tr({inputs:{x:n},backend:e}),u=tr({inputs:{x:o},backend:e});return i.complexTensorInfos={real:a,imag:u},s}var aM={kernelName:pp,backendName:"webgl",kernelFunc:Tn};var oT="return (a < 0.) ? b * a : a;",sT=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function Ztt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{alpha:s}=n,i=e.makeTensorInfo([],"float32",y.createScalarValue(s,"float32")),a=M().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Fo(sT,o.shape,i.shape):new oo(oT,o.shape,i.shape),u=e.runWebGLProgram(a,[o,i],"float32");return e.disposeIntermediateTensorInfo(i),u}var lM={kernelName:ss,backendName:"webgl",kernelFunc:Ztt};var iT="return (a < 0.) ? b * a : a;",aT=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function Jtt(r){let{inputs:t,backend:e}=r,{x:n,alpha:o}=t,s=M().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Fo(aT,n.shape,o.shape):new oo(iT,n.shape,o.shape);return e.runWebGLProgram(s,[n,o],"float32")}var uM={kernelName:ys,backendName:"webgl",kernelFunc:Jtt};var Oo="if (isnan(x)) return x;";function Ct({opSnippet:r,packedOpSnippet:t,cpuKernelImpl:e,dtype:n}){return({inputs:o,backend:s})=>{let{x:i}=o,a=s,u=n||i.dtype;if(a.shouldExecuteOnCPU([i])&&e!=null){let p=a.texData.get(i.dataId),m=e(p.values,u);return a.makeTensorInfo(i.shape,u,m)}let l=M().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return l?c=new no(i.shape,t):c=new tn(i.shape,r),a.runWebGLProgram(c,[i],u)}}function le({opSnippet:r,packedOpSnippet:t,checkOutOfBounds:e=!1,supportsComplex:n=!1,cpuKernelImpl:o,dtype:s}){return({inputs:i,backend:a})=>{let{a:u,b:l}=i,c=a;if(n&&u.dtype==="complex64"){let d=c.texData.get(u.dataId),h=c.texData.get(l.dataId),[g,x]=[[d.complexTensorInfos.real,h.complexTensorInfos.real],[d.complexTensorInfos.imag,h.complexTensorInfos.imag]].map(w=>{let[C,N]=w,_={dataId:C.dataId,dtype:C.dtype,shape:u.shape},A={dataId:N.dataId,dtype:N.dtype,shape:l.shape},$=new oo(r,u.shape,l.shape);return c.runWebGLProgram($,[_,A],or(C.dtype,N.dtype))}),b=Tn({inputs:{real:g,imag:x},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(x),b}let p=s||or(u.dtype,l.dtype);if((u.dtype==="string"||l.dtype==="string"||c.shouldExecuteOnCPU([u,l]))&&o!=null){let d=c.texData.get(u.dataId).values,h=c.texData.get(l.dataId).values,g=u.dtype==="string"?S.fromUint8ToStringArray(d):d,x=u.dtype==="string"?S.fromUint8ToStringArray(h):h,[b,w]=o(u.shape,l.shape,g,x,p),C=c.makeTensorInfo(w,p),N=c.texData.get(C.dataId);return N.values=b,C}let m=M().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,f;return m?f=new Fo(t,u.shape,l.shape,e):f=new oo(r,u.shape,l.shape),c.runWebGLProgram(f,[u,l],p)}}function xl(r,t=!1){if(r==="linear")return t?QL:KL;if(r==="relu")return t?eM:XL;if(r==="elu")return t?tM:jL;if(r==="relu6")return t?rM:YL;if(r==="prelu")return t?aT:iT;if(r==="leakyrelu")return t?sT:oT;if(r==="sigmoid")return t?nM:ZL;throw new Error(`Activation ${r} has not been implemented for the WebGL backend.`)}var wd=class{constructor(t,e,n,o=!1,s=!1,i=!1,a=null,u=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n,this.enableShapeUniforms=we(this.outputShape.length);let c=o?t[1]:t[2],p=Math.ceil(c/2),m=o?"i * 2, rc.y":"rc.y, i * 2",f=s?"rc.z, i * 2":"i * 2, rc.z",d=o?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],h=s?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],g="",x="";a&&(u?g=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${a}
        }`:l?g=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${a}
        }`:g=`vec4 activation(vec4 x) {
          ${a}
        }`,x="result = activation(result);");let b=i?"result += getBiasAtOutCoords();":"";i&&this.variableNames.push("bias"),u&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let w="rc.x",C="rc.x";t[0]<e[0]?w=`int(min(float(rc.x), ${t[0]-1}.))`:e[0]<t[0]&&(C=`int(min(float(rc.x), ${e[0]-1}.))`),this.userCode=`
      ${g}
      // Don't use uniform for sharedDimensionPacked for performance.
      const float sharedDimension = ${p}.0;

      vec4 dot2x2ARowBCol(ivec3 rc) {
        vec4 result = vec4(0);
        for (int i = 0; i < ${p}; i++) {
          int batchA = ${w};
          int batchB = ${C};
          vec4 a = getMatrixA(batchA, ${m});
          vec4 b = getMatrixB(batchB, ${f});

          // These swizzled products need to be separately added.
          // See: https://github.com/tensorflow/tfjs/issues/1735
          result += (${d[0]} * ${h[0]});
          result += (${d[1]} * ${h[1]});
        }
        return result;
      }

      void main() {
        ivec3 rc = getOutputCoords();
        vec4 result = dot2x2ARowBCol(rc);

        ${b}

        ${x}

        setOutput(result);
      }
    `}};var lT={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},Xh=class{constructor(t,e,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=S.assertAndGetBroadcastShape(e,n),this.userCode=`
      float binaryOpComplex(
          float areal, float aimag, float breal, float bimag) {
        ${t}
      }

      void main() {
        float areal = getARealAtOutCoords();
        float aimag = getAImagAtOutCoords();
        float breal = getBRealAtOutCoords();
        float bimag = getBImagAtOutCoords();
        setOutput(binaryOpComplex(areal, aimag, breal, bimag));
      }
    `}};var cM="return a * b;";function Yh(r){let{inputs:t,backend:e}=r,{a:n,b:o}=t,s=S.upcastType(n.dtype,o.dtype);if(n.dtype==="complex64"){let a=e.texData.get(n.dataId),u=e.texData.get(o.dataId),l=new Xh(lT.REAL,n.shape,o.shape),c=new Xh(lT.IMAG,n.shape,o.shape),p=[{dataId:a.complexTensorInfos.real.dataId,dtype:a.complexTensorInfos.real.dtype,shape:n.shape},{dataId:a.complexTensorInfos.imag.dataId,dtype:a.complexTensorInfos.imag.dtype,shape:n.shape},{dataId:u.complexTensorInfos.real.dataId,dtype:u.complexTensorInfos.real.dtype,shape:o.shape},{dataId:u.complexTensorInfos.imag.dataId,dtype:u.complexTensorInfos.imag.dtype,shape:o.shape}],m=e.runWebGLProgram(l,p,"float32"),f=e.runWebGLProgram(c,p,"float32"),d=Tn({inputs:{real:m,imag:f},backend:e});return e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f),d}if(e.shouldExecuteOnCPU([n,o])){let a=e.texData.get(n.dataId),u=e.texData.get(o.dataId),[l,c]=CL(n.shape,o.shape,a.values,u.values,s),p=e.makeTensorInfo(c,s),m=e.texData.get(p.dataId);return m.values=l,p}let i;return M().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new Fo(cM,n.shape,o.shape):i=new oo(cM,n.shape,o.shape),e.runWebGLProgram(i,[n,o],s)}var pM={kernelName:ds,backendName:"webgl",kernelFunc:Yh};function mM(r,t,e){let n=[hl(r.shape),...gl(r.shape)],o={dtype:r.dtype,shape:n,dataId:r.dataId},s=[hl(t),...gl(t)],i=new yd(s,n),a=!0,u=[n],l=e.runWebGLProgram(i,[o],r.dtype,u,a);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function st(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{shape:s}=n,i=e,a=y.sizeFromShape(o.shape),u=y.inferFromImplicitShape(s,a),l=y.sizeFromShape(u);y.assert(a===l,()=>`The new shape (${u}) has ${l} elements and the old shape (${o.shape}) has ${a} elements. The new shape and old shape must have the same number of elements.`);let c=i.texData.get(o.dataId);return c.isPacked&&!Tu(o.shape,u)&&!(c.texture!==null&&Tu(c.shape,u))?mM(o,u,i):(i.incRef(o.dataId),{dataId:o.dataId,shape:u,dtype:o.dtype})}var fM={kernelName:mi,backendName:"webgl",kernelFunc:st};var Zh=class{constructor(t,e){this.variableNames=["x"];let{windowSize:n,batchSize:o,inSize:s,outSize:i}=t;this.outputShape=[o,i];let a=Math.floor(n/4)*4,u=n%4,l="sumValue += dot(values, ones);";if(e!=null){let p=1/e;l=`sumValue += dot(values * ${y.isInt(p)?p.toPrecision(2):p}, ones);`}let c="";s%n>0&&(c=`
        if (inIdx < 0 || inIdx >= ${s}) {
          return 0.0;
        }
      `),this.userCode=`
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float getValue(int batch, int inIdx) {
        ${c}
        return getX(batch, inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ${n};

        float sumValue = 0.0;

        for (int i = 0; i < ${a}; i += 4) {
          int inIdx = inOffset + i;
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          ${l}
        }

        int inIdx = inOffset + ${a};
        if (${u===1}) {
          vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);

          ${l}
        } else if (${u===2}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1), 0.0, 0.0);

          ${l}
        } else if (${u===3}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2), 0.0);

          ${l}
        }
        setOutput(sumValue);
      }
    `}};var zw=class{constructor(t,e){this.variableNames=["x"];let{windowSize:n,batchSize:o,inSize:s,outSize:i}=t;this.outputShape=[o,i];let a="0.0",u="";e==="prod"?a="1.0":e==="min"?(a="1.0 / 1e-20",u="min"):e==="max"&&(a="-1.0 / 1e-20",u="max");let l=`${e}(${e}(${e}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;e==="sum"?l="sumValue":e==="prod"?l="prodValue":e==="all"?l="allValue":e==="any"&&(l="anyValue");let c=Math.floor(n/4)*4,p=n%4,m=`
      if (${e==="sum"}) {
        sumValue += dot(values, ones);
      } else if (${e==="prod"}) {
        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
        prodValue *= tmp[0] * tmp[1];
      } else {
        minMaxValue = ${u}(values, minMaxValue);
        if (${e==="min"} || ${e==="max"}) {
          minMaxValue = ${u}(values, minMaxValue);
          bvec4 isNaN = isnan(values);
          if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {
            minMaxValue = vec4(NAN);
          }
        }
      }
    `,f="vec4";e==="all"?(a="1.0",m=`
        bool reducedAllValue = all(values);
        float floatedReducedAllValue = float(reducedAllValue);
        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
      `,f="bvec4"):e==="any"&&(a="0.0",m=`
        bool reducedAnyValue = any(values);
        float floatedReducedAnyValue = float(reducedAnyValue);
        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
      `,f="bvec4");let d="";s%n>0&&(d=`
        if (inIdx < 0 || inIdx >= ${s}) {
          return initializationValue;
        }
      `),this.userCode=`
      const float initializationValue = ${a};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float getValue(int batch, int inIdx) {
        ${d}
        return getX(batch, inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ${n};

        vec4 minMaxValue = vec4(${a});
        float prodValue = 1.0;
        float sumValue = 0.0;
        float allValue = 1.0;
        float anyValue = 0.0;

        for (int i = 0; i < ${c}; i += 4) {
          int inIdx = inOffset + i;
          ${f} values = ${f}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          ${m}
        }

        int inIdx = inOffset + ${c};
        if (${p===1}) {
          ${f} values = ${f}(
            getValue(batch, inIdx),
            initializationValue,
            initializationValue,
            initializationValue
          );

          ${m}
        } else if (${p===2}) {
          ${f} values = ${f}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            initializationValue,
            initializationValue
          );

          ${m}
        } else if (${p===3}) {
          ${f} values = ${f}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            initializationValue
          );

          ${m}
        }
        setOutput(${l});
      }
    `}};function tet(r){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let e=t.length?t[t.length-1].outSize:r[1],n=S.computeOptimalWindowSize(e);t.push({inSize:e,windowSize:n,outSize:Math.ceil(e/n)})}return t}function Gn(r,t,e,n){let o=tet(r.shape),s=r;for(let i=0;i<o.length;i++){let{inSize:a,windowSize:u,outSize:l}=o[i],c,p;e==="mean"?c=i===0?new Zh({windowSize:u,inSize:a,batchSize:r.shape[0],outSize:l},a):new Zh({windowSize:u,inSize:a,batchSize:r.shape[0],outSize:l}):c=new zw({windowSize:u,inSize:a,batchSize:r.shape[0],outSize:l},e),p=s,s=n.runWebGLProgram(c,[s],t),p.dataId!==r.dataId&&n.disposeIntermediateTensorInfo(p)}return s}var Bw=class{constructor(t,e){this.variableNames=["A"];let n=new Array(t.length);for(let i=0;i<n.length;i++)n[i]=t[e[i]];this.outputShape=n,this.rank=n.length;let o=zt(this.rank),s=eet(e);this.userCode=`
    void main() {
      ${o} resRC = getOutputCoords();
      setOutput(getA(${s}));
    }
    `}};function eet(r){let t=r.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let e=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],n=new Array(t);for(let o=0;o<r.length;o++)n[r[o]]=e[o];return n.join()}var Vw=class{constructor(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(t.length);for(let c=0;c<n.length;c++)n[c]=t[e[c]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let o=zt(this.rank),s=rT("rc",this.rank),i=new Array(this.rank);for(let c=0;c<e.length;c++)i[e[c]]=s[c];let a=`vec2(${i.slice(-2).join()})`,u=`++${s[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${i.join()}), ${a})`;this.userCode=`
    void main() {
      ${o} rc = getOutputCoords();
      vec4 result = vec4(0.);
      result[0] = ${l};
      if(${u}) {
        result[1] = ${l};
      }
      --${s[this.rank-1]};
      if(++${s[this.rank-2]} < ${n[this.rank-2]}) {
        result[2] = ${l};
        if(${u}) {
          result[3] = ${l};
        }
      }
      setOutput(result);
    }
    `}};function _u(r,t,e){let n=M().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Vw(r.shape,t):new Bw(r.shape,t);return e.runWebGLProgram(n,[r],r.dtype)}function dM(r,t,e,n){let o=t,s=r.shape.length,i=y.parseAxisParam(o,r.shape),a=i,u=S.getAxesPermutation(a,s),l=u!=null,c=r;l&&(c=_u(r,u,n),a=S.getInnerMostAxes(a.length,s)),S.assertAxesAreInnerMostDims("sum",a,s);let[p,m]=S.computeOutAndReduceShapes(c.shape,a),f=p;e&&(f=S.expandShapeToKeepDim(p,i));let d=y.sizeFromShape(m),g=y.sizeFromShape(r.shape)/d,x=st({inputs:{x:c},attrs:{shape:[g,d]},backend:n}),b=Gu(r.dtype),w=Gn(x,b,"sum",n),C=st({inputs:{x:w},attrs:{shape:f},backend:n});return n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(w),l&&n.disposeIntermediateTensorInfo(c),C}function Wc(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n;return dM(o,s,i,e)}var hM={kernelName:As,backendName:"webgl",kernelFunc:Wc};function Fe(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{perm:s}=n,i=e,a=o.shape.length,u=new Array(a);for(let c=0;c<u.length;c++)u[c]=o.shape[s[c]];let l;if(i.shouldExecuteOnCPU([o])){let p=i.texData.get(o.dataId).values,m=Vc(p,o.shape,o.dtype,s,u);l=i.makeTensorInfo(u,o.dtype);let f=i.texData.get(l.dataId);f.values=m}else l=_u(o,s,i);return l}var gM={kernelName:Jn,backendName:"webgl",kernelFunc:Fe};var uT=1e3;function Uc({a:r,b:t,transposeA:e,transposeB:n,backend:o,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:a=0,activation:u=null}){let l=r.shape.length,c=t.shape.length,p=e?r.shape[l-2]:r.shape[l-1],m=n?t.shape[c-1]:t.shape[c-2],f=e?r.shape[l-1]:r.shape[l-2],d=n?t.shape[c-2]:t.shape[c-1],h=r.shape.slice(0,-2),g=t.shape.slice(0,-2),x=y.sizeFromShape(h),b=y.sizeFromShape(g),C=zr.assertAndGetBroadcastShape(r.shape.slice(0,-2),t.shape.slice(0,-2)).concat([f,d]);y.assert(p===m,()=>`Error in matMul: inner shapes (${p}) and (${m}) of Tensors with shapes ${r.shape} and ${t.shape} and transposeA=${e} and transposeB=${n} must match.`);let N=e?[x,p,f]:[x,f,p],_=n?[b,d,m]:[b,m,d],A=st({inputs:{x:r},backend:o,attrs:{shape:N}}),$=st({inputs:{x:t},backend:o,attrs:{shape:_}}),F=[A,$],P=Math.max(x,b),V=e?A.shape[1]:A.shape[2],G=s!=null,W=i!=null,q=u==="leakyrelu",H=u!=null?xl(u,!0):null,j=G||W||q||H!=null,Y;if((f===1||d===1)&&V>uT&&j===!1){let et=A,rt=$;e&&(et=Fe({inputs:{x:A},backend:o,attrs:{perm:[0,2,1]}}),F.push(et)),n&&(rt=Fe({inputs:{x:$},backend:o,attrs:{perm:[0,2,1]}}),F.push(rt));let ot=d!==1,at=d===1,nt=et;ot&&(nt=st({inputs:{x:et},backend:o,attrs:{shape:[P,V,1]}}),F.push(nt));let it=d===1?2:1,dt=rt;at&&(dt=st({inputs:{x:rt},backend:o,attrs:{shape:[P,1,V]}}),F.push(dt));let ht=Yh({inputs:{a:nt,b:dt},backend:o});Y=Wc({inputs:{x:ht},backend:o,attrs:{axis:it,keepDims:!0}}),F.push(ht)}else{let et=or(r.dtype,t.dtype),rt=new wd(N,_,[P,f,d],e,n,G,H,W,q),ot=[A,$];if(s!=null&&ot.push(s),W&&ot.push(i),q){let at=o.makeTensorInfo([],"float32",y.createScalarValue(a,"float32"));ot.push(at),F.push(at)}Y=o.runWebGLProgram(rt,ot,et)}let Z=st({inputs:{x:Y},backend:o,attrs:{shape:C}});F.push(Y);for(let et of F)o.disposeIntermediateTensorInfo(et);return Z}function ret(r){let{inputs:t,backend:e,attrs:n}=r,{a:o,b:s,bias:i,preluActivationWeights:a}=t,{transposeA:u,transposeB:l,activation:c,leakyreluAlpha:p}=n;return Uc({a:o,b:s,transposeA:u,transposeB:l,backend:e,bias:i,preluActivationWeights:a,leakyreluAlpha:p,activation:c})}var xM={kernelName:bi,backendName:"webgl",kernelFunc:ret};var yM="return abs(x);";function net(r){let{inputs:t,backend:e}=r,{x:n}=t;if(e.shouldExecuteOnCPU([n])&&n.dtype!=="complex64"){let s=e.texData.get(n.dataId),i=Rw(s.values);return e.makeTensorInfo(n.shape,n.dtype,i)}let o;return M().getBool("WEBGL_PACK_UNARY_OPERATIONS")?o=new no(n.shape,yM):o=new tn(n.shape,yM),e.runWebGLProgram(o,[n],n.dtype)}var bM={kernelName:oi,backendName:"webgl",kernelFunc:net};var oet=pr+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return acos(x);
`,set=Ct({opSnippet:oet}),wM={kernelName:ra,backendName:"webgl",kernelFunc:set};var iet=pr+`
  if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,aet=Ct({opSnippet:iet}),CM={kernelName:na,backendName:"webgl",kernelFunc:aet};var IM="return a + b;",uet=le({opSnippet:IM,packedOpSnippet:IM,supportsComplex:!0,cpuKernelImpl:eL}),vM={kernelName:Yn,backendName:"webgl",kernelFunc:uet};var Gw=class{constructor(t,e){this.outputShape=[],this.outputShape=t,this.variableNames=e.map((s,i)=>`T${i}`);let n=[];this.variableNames.forEach(s=>{n.push(`float v${s} = get${s}AtOutCoords();`)});let o=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
      void main() {
        ${n.join(`
        `)}

        float result = ${o};
        setOutput(result);
      }
    `}};var Ww=class{constructor(t,e){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.variableNames=e.map((s,i)=>`T${i}`);let n=[];this.variableNames.forEach(s=>{n.push(`vec4 v${s} = get${s}AtOutCoords();`)});let o=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
      void main() {
        ${n.join(`
        `)}

        vec4 result = ${o};
        setOutput(result);
      }
    `}};function Uw(r){let{inputs:t,backend:e}=r,n=t;if(n.length===1)return tr({inputs:{x:n[0]},backend:e});if(n.length>M().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let u=Math.floor(n.length/2),l=Uw({inputs:n.slice(0,u),backend:e}),c=Uw({inputs:n.slice(u),backend:e});return Uw({inputs:[l,c],backend:e})}let o=n.map(u=>u.dtype).reduce((u,l)=>or(u,l)),s=n.map(u=>u.shape),a=M().getBool("WEBGL_PACK")?new Ww(n[0].shape,s):new Gw(n[0].shape,s);return e.runWebGLProgram(a,n,o)}var SM={kernelName:Vo,backendName:"webgl",kernelFunc:Uw};function cet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=y.parseAxisParam(s,o.shape),l=u,c=S.getAxesPermutation(l,a),p=o;c!=null&&(p=Fe({inputs:{x:o},backend:e,attrs:{perm:c}}),l=S.getInnerMostAxes(l.length,a)),S.assertAxesAreInnerMostDims("all",l,a);let[m,f]=S.computeOutAndReduceShapes(p.shape,l),d=y.sizeFromShape(f),h=st({inputs:{x:p},backend:e,attrs:{shape:[-1,d]}}),g=Gn(h,h.dtype,"all",e),x;if(i){let b=S.expandShapeToKeepDim(m,u);x=st({inputs:{x:g},backend:e,attrs:{shape:b}})}else x=st({inputs:{x:g},backend:e,attrs:{shape:m}});return e.disposeIntermediateTensorInfo(h),e.disposeIntermediateTensorInfo(g),c!=null&&e.disposeIntermediateTensorInfo(p),x}var NM={kernelName:oa,backendName:"webgl",kernelFunc:cet};function pet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=y.parseAxisParam(s,o.shape),l=u,c=S.getAxesPermutation(l,a),p=o;c!=null&&(p=Fe({inputs:{x:o},backend:e,attrs:{perm:c}}),l=S.getInnerMostAxes(l.length,a)),S.assertAxesAreInnerMostDims("any",l,a);let[m,f]=S.computeOutAndReduceShapes(p.shape,l),d=y.sizeFromShape(f),h=st({inputs:{x:p},backend:e,attrs:{shape:[-1,d]}}),g=Gn(h,h.dtype,"any",e),x;if(i){let b=S.expandShapeToKeepDim(m,u);x=st({inputs:{x:g},backend:e,attrs:{shape:b}})}else x=st({inputs:{x:g},backend:e,attrs:{shape:m}});return e.disposeIntermediateTensorInfo(h),e.disposeIntermediateTensorInfo(g),c!=null&&e.disposeIntermediateTensorInfo(p),x}var kM={kernelName:sa,backendName:"webgl",kernelFunc:pet};var Hw=class{constructor(t,e,n){this.variableNames=["A"];let{windowSize:o,batchSize:s,outSize:i}=t;n||this.variableNames.push("bestIndicesA"),this.outputShape=[s,i];let a=e==="max"?">":"<",u=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ${o};

        int bestIndex = inOffset;
        float bestValue = getA(batch, bestIndex);

        for (int i = 0; i < ${o}; i++) {
          int inIdx = ${u};
          float candidate = getA(batch, inIdx);
          if (candidate ${a} bestValue) {
            bestValue = candidate;
            bestIndex = inIdx;
          }
        }
        setOutput(float(bestIndex));
      }
    `}};var qw=class{constructor(t,e,n,o){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,y.assert(t.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let s=t[t.length-1],i=Math.ceil(s/e);this.outputShape=t.slice(0,-1),i>1&&this.outputShape.push(i),o||this.variableNames.push("bestIndicesA");let a=this.outputShape,u=a.length,l=zt(u),c=Qe("coords",u),p,m;if(i===1){m=u+1;let $=zt(m);p=`
        ${$} sourceLocR = ${$}(${c.join()}, 0);
        ++${c[u-1]};
        ${$} sourceLocG = ${$}(${c.join()}, 0);
        ++${c[u-2]};
        ${$} sourceLocA = ${$}(${c.join()}, 0);
        --${c[u-1]};
        ${$} sourceLocB = ${$}(${c.join()}, 0);
        --${c[u-2]};`}else m=u,p=`
        ${l} sourceLocR = coords;
        ++${c[u-1]};
        ${l} sourceLocG = coords;
        ++${c[u-2]};
        ${l} sourceLocA = coords;
        --${c[u-1]};
        ${l} sourceLocB = coords;
        --${c[u-2]};`;let f=["x","y","z","w","u","v"].slice(0,m),d="."+f[m-1],h=f.map($=>"int "+$),g=Qe("sourceLocR",m-1).concat("inIdx.r"),x=Qe("sourceLocG",m-1).concat("inIdx.g"),b=Qe("sourceLocB",m-1).concat("inIdx.b"),w=Qe("sourceLocA",m-1).concat("inIdx.a"),C=n==="max"?"greaterThan":"lessThan",N=o?"":`
          inIdx = round(vec4(getBestIndicesAChannel(${g.join()}),
                             getBestIndicesAChannel(${x.join()}),
                             getBestIndicesAChannel(${b.join()}),
                             getBestIndicesAChannel(${w.join()})));`,_=`vec4(
            getAChannel(${g.join()}),
            hasNextCol ? getAChannel(${x.join()}) : 0.,
            hasNextRow ? getAChannel(${b.join()}) : 0.,
            hasNextRow && hasNextCol ? getAChannel(${w.join()}) : 0.)`,A=o?"":`
      float getBestIndicesAChannel(${h.join()}) {
        return getChannel(getBestIndicesA(${f.join()}),
                                          vec2(${f.slice(-2).join()}));
      }`;this.userCode=`
      float getAChannel(${h.join()}) {
        return getChannel(getA(${f.join()}),
                               vec2(${f.slice(-2).join()}));
      }
      ${A}
      void main() {
        ${l} coords = getOutputCoords();
        bool hasNextCol = ${c[u-1]} < ${a[u-1]-1};
        bool hasNextRow = ${c[u-2]} < ${a[u-2]-1};
        ${p}
        ivec4 srcIdx = ivec4(sourceLocR${d}, sourceLocG${d},
          sourceLocB${d}, sourceLocA${d}) * ${e};
        ivec4 inIdx = srcIdx;
        vec4 bestIndex = vec4(inIdx);
        vec4 bestValue = ${_};

        for (int i = 0; i < ${e}; i++) {
          inIdx = srcIdx;
          ${N}
          vec4 candidate = ${_};
          bvec4 nan = isnan(candidate);
          bvec4 replace = bvec4(
            vec4(${C}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));

          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,
                           replace.y  ? candidate.y : bestValue.y,
                           replace.z  ? candidate.z : bestValue.z,
                           replace.w  ? candidate.w : bestValue.w);
          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));
          srcIdx++;
        }
        setOutput(bestIndex);
      }
    `}};function TM(r,t,e,n=null){let o=t.shape[0],s=t.shape[1];n!=null&&(o=n.shape[0],s=n.shape[1]);let i=S.computeOptimalWindowSize(s),a={windowSize:i,inSize:s,batchSize:o,outSize:Math.ceil(s/i)},u=new Hw(a,e,n==null),l=[t];n!=null&&l.push(n);let c=r.runWebGLProgram(u,l,"int32");if(c.shape[1]===1)return c;let p=TM(r,t,e,c);return r.disposeIntermediateTensorInfo(c),p}function EM(r,t,e,n=null){let o=n!=null?n.shape:t.shape,s=o[o.length-1],i=S.computeOptimalWindowSize(s),a=new qw(o,i,e,n==null),u=n==null?[t]:[t,n],l=r.runWebGLProgram(a,u,"int32");if(l.shape.length===t.shape.length){let c=EM(r,t,e,l);return r.disposeIntermediateTensorInfo(l),c}return l}function Kw(r,t,e,n){let o=[e];if(S.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),o,t.shape.length),!M().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],i=r.texData.get(t.dataId),a=i!==null&&i.isPacked,u=t;a&&(u=r.unpackTensor(t),s.push(u));let[l,c]=S.computeOutAndReduceShapes(u.shape,o),p=y.sizeFromShape(c),m=st({inputs:{x:u},backend:r,attrs:{shape:[-1,p]}});s.push(m);let f=TM(r,m,n);s.push(f);let d=st({inputs:{x:f},backend:r,attrs:{shape:l}});return s.forEach(h=>r.disposeIntermediateTensorInfo(h)),d}return EM(r,t,n)}function met(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s}=n,i=y.parseAxisParam(s,o.shape),a=S.getAxesPermutation(i,o.shape.length),u=o,l=[];a!=null&&(u=Fe({inputs:{x:o},backend:e,attrs:{perm:a}}),l.push(u),i=S.getInnerMostAxes(i.length,u.shape.length)),S.assertAxesAreInnerMostDims("argMax",[i[0]],u.shape.length);let c=Kw(e,u,i[0],"max");return l.forEach(p=>e.disposeIntermediateTensorInfo(p)),c}var _M={kernelName:Go,backendName:"webgl",kernelFunc:met};function fet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s}=n,i=y.parseAxisParam(s,o.shape),a=S.getAxesPermutation(i,o.shape.length),u=o,l=[];a!=null&&(u=Fe({inputs:{x:o},backend:e,attrs:{perm:a}}),l.push(u),i=S.getInnerMostAxes(i.length,u.shape.length)),S.assertAxesAreInnerMostDims("argMin",[i[0]],u.shape.length);let c=Kw(e,u,i[0],"min");return l.forEach(p=>e.disposeIntermediateTensorInfo(p)),c}var AM={kernelName:Nl,backendName:"webgl",kernelFunc:fet};var det=pr+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return asin(x);
`,het=Ct({opSnippet:det}),$M={kernelName:ia,backendName:"webgl",kernelFunc:het};var get=pr+"return log(x + sqrt(x * x + 1.0));",xet=Ct({opSnippet:get}),DM={kernelName:aa,backendName:"webgl",kernelFunc:xet};var yet=pr+`
  return atan(x);
`,bet=Ct({opSnippet:yet}),RM={kernelName:la,backendName:"webgl",kernelFunc:bet};var wet=bd+`
  return atan(a, b);
`,Cet=`
  vec4 result = atan(a, b);
  bvec4 isNaNA = isnan(a);
  bvec4 isNaNB = isnan(b);
  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
  `+ji+`
  return result;
`,Iet=le({opSnippet:wet,packedOpSnippet:Cet}),FM={kernelName:ca,backendName:"webgl",kernelFunc:Iet};var vet=pr+`
  if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,Net=Ct({opSnippet:vet}),OM={kernelName:ua,backendName:"webgl",kernelFunc:Net};var Qs=class{constructor(t,e,n,o=!1,s=!1){if(this.variableNames=["x"],e==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let i=t.filterWidth,a=t.strideHeight,u=t.strideWidth,l=t.dilationHeight,c=t.dilationWidth,p=t.effectiveFilterHeight,m=t.effectiveFilterWidth,f=t.padInfo.top,d=t.padInfo.left;this.outputShape=t.outShape;let h=e==="avg",g=`((batch  * ${t.inHeight} + xR) * ${t.inWidth} + xC) * ${t.inChannels} + d`,x=`(xR * ${t.inWidth} + xC) * ${t.inChannels} + d`,b="0.0";if(h||(b="-1.0 / 1e-20"),n){let $=">=";this.userCode=`
        const ivec2 strides = ivec2(${a}, ${u});
        const ivec2 pads = ivec2(${f}, ${d});

        void main() {
          ivec4 coords = getOutputCoords();
          int batch = coords[0];
          int d = coords[3];

          ivec2 xRCCorner = coords.yz * strides - pads;
          int xRCorner = xRCCorner.x;
          int xCCorner = xRCCorner.y;

          // max/min x(?, ?, d) to get y(yR, yC, d).
          // ? = to be determined
          float minMaxValue = 0.0;
          float minMaxValueFound = 0.0;
          int minMaxPosition = 0;
          float avgValue = 0.0;

          for (int wR = 0; wR < ${p};
              wR += ${l}) {
            int xR = xRCorner + wR;

            if (xR < 0 || xR >= ${t.inHeight}) {
              continue;
            }

            for (int wC = 0; wC < ${m};
                wC += ${c}) {
              int xC = xCCorner + wC;

              if (xC < 0 || xC >= ${t.inWidth}) {
                continue;
              }

              float value = getX(batch, xR, xC, d);

              // If a min / max value has already been found, use it. If not,
              // use the current value.
              float currMinMaxValue = mix(
                  value, minMaxValue, minMaxValueFound);
              if (value ${$} currMinMaxValue) {
                minMaxValue = value;
                minMaxValueFound = 1.0;
                minMaxPosition = ${o?s?g:x:`wR * ${m} + wC`};
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let w="max",C=`${e}(${e}(${e}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;e==="avg"&&(C="avgValue / count");let N=Math.floor(i/4)*4,_=i%4,A=`
      if (${h}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${w}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec2 strides = ivec2(${a}, ${u});
      const ivec2 pads = ivec2(${f}, ${d});
      const float initializationValue = ${b};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float count = 0.0;

      float getValue(int batch, int xR, int xC, int d) {
        if (xC < 0 || xC >= ${t.inWidth}) {
          return initializationValue;
        }
        count += 1.0;
        return getX(batch, xR, xC, d);
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d = coords[3];

        ivec2 xRCCorner = coords.yz * strides - pads;
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // max/min x(?, ?, d) to get y(yR, yC, d).
        // ? = to be determined
        vec4 minMaxValue = vec4(${b});
        float avgValue = 0.0;
        count = 0.0;

        for (int wR = 0; wR < ${p};
            wR += ${l}) {
          int xR = xRCorner + wR;

          if (xR < 0 || xR >= ${t.inHeight}) {
            continue;
          }

          for (int wC = 0; wC < ${N}; wC += 4) {
            int xC = xCCorner + wC * ${c};

            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${c}, d),
              getValue(batch, xR, xC + 2 * ${c}, d),
              getValue(batch, xR, xC + 3 * ${c}, d)
            );

            ${A}
          }

          int xC = xCCorner + ${N};
          if (${_===1}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              initializationValue,
              initializationValue,
              initializationValue
            );

            ${A}
          } else if (${_===2}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${c}, d),
              initializationValue,
              initializationValue
            );

            ${A}
          } else if (${_===3}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${c}, d),
              getValue(batch, xR, xC + 2 * ${c}, d),
              initializationValue
            );

            ${A}
          }
        }
        setOutput(${C});
      }
    `}},Au=class{constructor(t,e,n,o=!1,s=!1){if(this.variableNames=["x"],e==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let i=t.filterWidth,a=t.strideDepth,u=t.strideHeight,l=t.strideWidth,c=t.dilationDepth,p=t.dilationHeight,m=t.dilationWidth,f=t.effectiveFilterDepth,d=t.effectiveFilterHeight,h=t.effectiveFilterWidth,g=t.padInfo.front,x=t.padInfo.top,b=t.padInfo.left;this.outputShape=t.outShape;let w=e==="avg",C="0.0";if(w||(C="-1.0 / 1e-20"),n){let P=">=";this.userCode=`
        const ivec3 strides =
            ivec3(${a}, ${u}, ${l});
        const ivec3 pads = ivec3(${g}, ${x}, ${b});

        void main() {
          ivec5 coords = getOutputCoords();
          int batch = coords.x;
          int ch = coords.u;

          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
          int xDCorner = xCorner.x;
          int xRCorner = xCorner.y;
          int xCCorner = xCorner.z;

          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).
          // ? = to be determined
          float minMaxValue = 0.0;
          float minMaxValueFound = 0.0;
          int minMaxPosition = 0;

          for (int wD = 0; wD < ${f};
              wD += ${c}) {
            int xD = xDCorner + wD;

            if (xD < 0 || xD >= ${t.inDepth}) {
              continue;
            }

            for (int wR = 0; wR < ${d};
                wR += ${p}) {
              int xR = xRCorner + wR;

              if (xR < 0 || xR >= ${t.inHeight}) {
                continue;
              }

              for (int wC = 0; wC < ${h};
                  wC += ${m}) {
                int xC = xCCorner + wC;

                if (xC < 0 || xC >= ${t.inWidth}) {
                  continue;
                }

                float value = getX(batch, xD, xR, xC, ch);

                // If a min / max value has already been found, use it. If not,
                // use the current value.
                float currMinMaxValue = mix(
                    value, minMaxValue, minMaxValueFound);
                if (value ${P} currMinMaxValue) {
                  minMaxValue = value;
                  minMaxValueFound = 1.0;
                  minMaxPosition = ${o?s?`(((batch * ${t.inDepth} + xD) * ${t.inHeight} + xR) * ${t.inWidth} + xC) * ${t.inChannels} + ch`:`((xD * ${t.inHeight} + xR) * ${t.inWidth} + xC) * ${t.inChannels} + ch`:`wD * ${d} * ${h} +
                      wR * ${h} + wC`};
                }
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let N="max",_=`${e}(${e}(${e}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;e==="avg"&&(_="avgValue / count");let A=Math.floor(i/4)*4,$=i%4,F=`
      if (${w}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${N}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec3 strides =
        ivec3(${a}, ${u}, ${l});
      const ivec3 pads = ivec3(${g}, ${x}, ${b});
      const float initializationValue = ${C};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float count = 0.0;

      float getValue(int batch, int xD, int xR, int xC, int ch) {
        if (xC < 0 || xC >= ${t.inWidth}) {
          return initializationValue;
        }
        count += 1.0;
        return getX(batch, xD, xR, xC, ch);
      }

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
        int xDCorner = xCorner.x;
        int xRCorner = xCorner.y;
        int xCCorner = xCorner.z;

        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
        // ? = to be determined
        vec4 minMaxValue = vec4(${C});
        float avgValue = 0.0;
        count = 0.0;

        for (int wD = 0; wD < ${f};
            wD += ${c}) {
          int xD = xDCorner + wD;

          if (xD < 0 || xD >= ${t.inDepth}) {
            continue;
          }

          for (int wR = 0; wR < ${d};
            wR += ${p}) {
            int xR = xRCorner + wR;

            if (xR < 0 || xR >= ${t.inHeight}) {
              continue;
            }

            for (int wC = 0; wC < ${A}; wC += 4) {
              int xC = xCCorner + wC * ${m};

              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${m}, ch),
                getValue(batch, xD, xR, xC + 2 * ${m}, ch),
                getValue(batch, xD, xR, xC + 3 * ${m}, ch)
              );

              ${F}
            }

            int xC = xCCorner + ${A};
            if (${$===1}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                initializationValue,
                initializationValue,
                initializationValue
              );

              ${F}
            } else if (${$===2}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${m}, ch),
                initializationValue,
                initializationValue
              );

              ${F}
            } else if (${$===3}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${m}, ch),
                getValue(batch, xD, xR, xC + 2 * ${m}, ch),
                initializationValue
              );

              ${F}
            }
          }
          setOutput(${_});
        }
      }
    `}};function ket(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t;Zs(o,"avgPool");let{filterSize:s,strides:i,pad:a,dimRoundingMode:u}=n,l=1;y.assert(S.eitherStridesOrDilationsAreOne(i,l),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${l}'`);let c=S.computePool2DInfo(o.shape,s,i,l,a,u);if(c.filterWidth===1&&c.filterHeight===1&&y.arraysEqual(c.inShape,c.outShape))return tr({inputs:{x:o},backend:e});let p=new Qs(c,"avg",!1);return e.runWebGLProgram(p,[o],"float32")}var PM={kernelName:Wo,backendName:"webgl",kernelFunc:ket};function Tet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{filterSize:s,strides:i,pad:a,dimRoundingMode:u,dataFormat:l}=n,c=[1,1,1],p=S.computePool3DInfo(o.shape,s,i,c,a,u,l),m=new Au(p,"avg",!1);return e.runWebGLProgram(m,[o],"float32")}var LM={kernelName:kl,backendName:"webgl",kernelFunc:Tet};var jw=class{constructor(t){this.variableNames=["dy"],this.outputShape=t.inShape;let e=t.filterHeight,n=t.filterWidth,o=t.strideHeight,s=t.strideWidth,i=t.dilationHeight,a=t.dilationWidth,u=t.effectiveFilterHeight,l=t.effectiveFilterWidth,c=u-1-t.padInfo.top,p=l-1-t.padInfo.left,m=1/(e*n);this.userCode=`
      const ivec2 pads = ivec2(${c}, ${p});
      const float avgMultiplier = float(${m});

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];

        ivec2 dyRCCorner = coords.yz - pads;
        int dyRCorner = dyRCCorner.x;
        int dyCCorner = dyRCCorner.y;

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${u};
            wR += ${i}) {
          float dyR = float(dyRCorner + wR) / ${o}.0;

          if (dyR < 0.0 || dyR >= ${t.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          for (int wC = 0; wC < ${l};
            wC+= ${a}) {
            float dyC = float(dyCCorner + wC) / ${s}.0;

            if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            float dyValue = getDy(b, idyR, idyC, d);

            dotProd += dyValue * avgMultiplier;
          }
        }
        setOutput(dotProd);
      }
    `}},Xw=class{constructor(t){this.variableNames=["dy"],this.outputShape=t.inShape;let e=t.filterDepth,n=t.filterHeight,o=t.filterWidth,s=t.strideDepth,i=t.strideHeight,a=t.strideWidth,u=t.dilationDepth,l=t.dilationHeight,c=t.dilationWidth,p=t.effectiveFilterDepth,m=t.effectiveFilterHeight,f=t.effectiveFilterWidth,d=p-1-t.padInfo.front,h=m-1-t.padInfo.top,g=f-1-t.padInfo.left,x=1/(e*n*o);this.userCode=`
      const ivec3 pads = ivec3(${d}, ${h}, ${g});
      const float avgMultiplier = float(${x});

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyDCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get
        // dx(xD, xR, xC, ch).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int wD = 0; wD < ${p};
            wD += ${u}) {
          float dyD = float(dyDCorner + wD) / ${s}.0;

          if (dyD < 0.0 || dyD >= ${t.outDepth}.0 || fract(dyD) > 0.0) {
            continue;
          }
          int idyD = int(dyD);

          for (int wR = 0; wR < ${m};
              wR += ${l}) {
            float dyR = float(dyRCorner + wR) / ${i}.0;

            if (dyR < 0.0 || dyR >= ${t.outHeight}.0 ||
                fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            for (int wC = 0; wC < ${f};
                wC += ${c}) {
              float dyC = float(dyCCorner + wC) / ${a}.0;

              if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              float dyValue = getDy(batch, idyD, idyR, idyC, ch);

              dotProd += dyValue * avgMultiplier;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function Eet(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s,{filterSize:a,strides:u,pad:l,dimRoundingMode:c}=n,p=[1,1,1],m=S.computePool3DInfo(i.shape,a,u,p,l,c),f=new Xw(m);return e.runWebGLProgram(f,[o],i.dtype)}var MM={kernelName:lp,backendName:"webgl",kernelFunc:Eet};function _et(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s;Zs([o,s],"avgPoolGrad");let{filterSize:a,strides:u,pad:l}=n,c=S.computePool2DInfo(i.shape,a,u,1,l),p=new jw(c);return e.runWebGLProgram(p,[o],i.dtype)}var zM={kernelName:ap,backendName:"webgl",kernelFunc:_et};function Aet(r){let{inputs:t,backend:e,attrs:n}=r,{a:o,b:s}=t,{transposeA:i,transposeB:a}=n;return Uc({a:o,b:s,transposeA:i,transposeB:a,backend:e})}var BM={kernelName:Uo,backendName:"webgl",kernelFunc:Aet};var Yw=class{constructor(t,e,n,o,s,i){this.outputShape=[],this.variableNames=["x","mean","variance"],S.assertAndGetBroadcastShape(t,e),S.assertAndGetBroadcastShape(t,n);let a="0.0";o!=null&&(S.assertAndGetBroadcastShape(t,o),this.variableNames.push("offset"),a="getOffsetAtOutCoords()");let u="1.0";s!=null&&(S.assertAndGetBroadcastShape(t,s),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=t,this.userCode=`
      void main() {
        float x = getXAtOutCoords();
        float mean = getMeanAtOutCoords();
        float variance = getVarianceAtOutCoords();
        float offset = ${a};
        float scale = ${u};
        float inv = scale * inversesqrt(variance + float(${i}));
        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
      }
    `}};var Zw=class{constructor(t,e,n,o,s,i){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],S.assertAndGetBroadcastShape(t,e),S.assertAndGetBroadcastShape(t,n);let a="vec4(0.0)";o!=null&&(S.assertAndGetBroadcastShape(t,o),this.variableNames.push("offset"),a="getOffsetAtOutCoords()");let u="vec4(1.0)";s!=null&&(S.assertAndGetBroadcastShape(t,s),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=t,this.userCode=`
      void main() {
        vec4 offset = ${a};
        vec4 scale = ${u};

        vec4 x = getXAtOutCoords();
        vec4 mean = getMeanAtOutCoords();
        vec4 variance = getVarianceAtOutCoords();

        vec4 inv = scale * inversesqrt(variance + vec4(${i}));

        setOutput((x - mean) * inv + offset);
      }
    `}};var $et=({inputs:r,backend:t,attrs:e})=>{let{x:n,mean:o,variance:s,offset:i,scale:a}=r;y.assert(o.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),y.assert(i==null||o.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),y.assert(a==null||o.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:u}=e;u==null&&(u=.001);let l=[n,o,s],c=null;i!=null&&(c=i.shape,l.push(i));let p=null;a!=null&&(p=a.shape,l.push(a));let m=M().getBool("WEBGL_PACK_NORMALIZATION")?new Zw(n.shape,o.shape,s.shape,c,p,u):new Yw(n.shape,o.shape,s.shape,c,p,u);return t.runWebGLProgram(m,l,l[0].dtype)},VM={kernelName:ns,backendName:"webgl",kernelFunc:$et};var Jw=class{constructor(t){this.variableNames=["source"],this.outputShape=t,this.rank=t.length;let e=zt(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=Det(this.rank),o,s=t.map((i,a)=>`sourceLoc.${cT[a]} = start[${a}] + coords.${cT[a]};`);o=`
        ${e} sourceLoc;
        ${e} coords = getOutputCoords();
        ${s.join(`
`)}
      `,this.userCode=`
      void main() {
        ${o}
        setOutput(getSource(${n}));
      }
    `}},cT=["x","y","z","w","u","v"];function Det(r){if(r===1)return"sourceLoc";if(r<=6)return cT.slice(0,r).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${r} is not yet supported`)}var Qw=class{constructor(t){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.rank=t.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let e=zt(this.rank),n=Qe("coords",this.rank),o=Qe("sourceLoc",this.rank),s=this.rank===1?"sourceLoc":`vec2(${o.slice(-2).join()})`,i=`getChannel(getSource(${o.join()}), ${s})`,a=`
      result.x = ${i};
      if (++${n[this.rank-1]} < ${t[this.rank-1]}) {
        ++${o[this.rank-1]};
        result.y = ${i};
        --${o[this.rank-1]};
      }
    `,u=this.rank===1?"":`
      --${n[this.rank-1]};
      if (++${n[this.rank-2]} < ${t[this.rank-2]}) {
        ++${o[this.rank-2]};
        result.z = ${i};
        if (++${n[this.rank-1]} < ${t[this.rank-1]}) {
          ++${o[this.rank-1]};
          result.w = ${i};
        }
      }
    `,l=this.rank<=4?`sourceLoc = coords +
            ${e}(${t.map((c,p)=>`start[${p}]`).join()});`:t.map((c,p)=>`${o[p]} = ${n[p]} + start[${p}];`).join(`
`);this.userCode=`
      void main() {
        ${e} coords = getOutputCoords();
        ${e} sourceLoc;
        ${l}
        vec4 result = vec4(0.);
        ${a}
        ${u}
        setOutput(result);
      }
    `}};function Ret(r,t,e,n){let o=n.texData.get(r.dataId),s=n.makeTensorInfo(e,r.dtype),i=n.texData.get(s.dataId);Object.assign(i,o),i.refCount=1,i.shape=e,i.dtype=r.dtype;let a=Pe.computeFlatOffset(t,y.computeStrides(r.shape));o.slice&&(a+=o.slice.flatOffset),i.slice={flatOffset:a,origDataId:o.slice&&o.slice.origDataId||r.dataId};let u=n.dataRefCount.get(i.slice.origDataId)||1;return n.dataRefCount.set(i.slice.origDataId,u+1),s}function ti(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{begin:s,size:i}=n,[a,u]=Pe.parseSliceParams(o,s,i);if(Pe.assertParamsValid(o,a,u),y.sizeFromShape(u)===0)return e.makeTensorInfo(u,o.dtype,[]);if(e.shouldExecuteOnCPU([o])||o.dtype==="string"){let p=e.texData.get(o.dataId),m=$L(p.values,a,u,o.shape,o.dtype);return e.makeTensorInfo(u,o.dtype,m)}let{isPacked:l}=e.texData.get(o.dataId),c=Pe.isSliceContinous(o.shape,a,u);if(l||!c){let p=M().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Qw(u):new Jw(u),m=[a];return e.runWebGLProgram(p,[o],o.dtype,m)}return e.uploadToGPU(o.dataId),Ret(o,a,u,e)}var GM={kernelName:di,backendName:"webgl",kernelFunc:ti};var Fet=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockShape:s,crops:i}=n;y.assert(o.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let a=s.reduce((b,w)=>b*w),u=S.getReshaped(o.shape,s,a),l=S.getPermuted(u.length,s.length),c=S.getReshapedPermuted(o.shape,s,a),p=S.getSliceBeginCoords(i,s.length),m=S.getSliceSize(c,i,s.length),f=[],d=st({inputs:{x:o},backend:e,attrs:{shape:u}}),h=Fe({inputs:{x:d},backend:e,attrs:{perm:l}}),g=st({inputs:{x:h},backend:e,attrs:{shape:c}}),x=ti({inputs:{x:g},backend:e,attrs:{begin:p,size:m}});return f.push(d),f.push(h),f.push(g),f.forEach(b=>e.disposeIntermediateTensorInfo(b)),x},WM={kernelName:si,backendName:"webgl",kernelFunc:Fet};function Oet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,weights:s}=t,{size:i}=n,a=e.readSync(o.dataId),u=e.readSync(s.dataId),l=Dw(a,u,s.dtype,s.shape,i);return e.makeTensorInfo([i],s.dtype,l)}var UM={kernelName:up,backendName:"webgl",kernelFunc:Oet};function Pet(r){let{inputs:t,backend:e}=r,{s0:n,s1:o}=t,s=e.readSync(n.dataId),i=e.readSync(o.dataId),a=S.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return e.makeTensorInfo([a.length],"int32",Int32Array.from(a))}var HM={kernelName:cp,backendName:"webgl",kernelFunc:Pet};var Let="return float(a != b);",pT=le({opSnippet:Let,cpuKernelImpl:vL,dtype:"bool"}),qM={kernelName:Aa,backendName:"webgl",kernelFunc:pT};function yl(r){let{inputs:t,backend:e}=r,{input:n}=t,o=e.texData.get(n.dataId);return tr({inputs:{x:o.complexTensorInfos.real},backend:e})}var KM={kernelName:Dp,backendName:"webgl",kernelFunc:yl};var Met="return float(int(x));";function jM(r,t){let e=new tn(r.shape,Met),n=t.runWebGLProgram(e,[r],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function mT(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{dtype:s}=n;if(s==="complex64"){if(o.dtype==="complex64")return tr({inputs:{x:o},backend:e});let i=Ne(o.shape),a=mT({inputs:{x:o},backend:e,attrs:{dtype:"float32"}}),u=Tn({inputs:{real:a,imag:i},backend:e});return i.dispose(),e.disposeIntermediateTensorInfo(a),u}if(o.dtype==="complex64"){let i=yl({inputs:{input:o},backend:e}),a=mT({inputs:{x:i},backend:e,attrs:{dtype:s}});return e.disposeIntermediateTensorInfo(i),a}if(!y.hasEncodingLoss(o.dtype,s)){let i=tr({inputs:{x:o},backend:e});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(e.shouldExecuteOnCPU([o])){let i=e.texData.get(o.dataId).values,[a,u,l]=nL(i,o.shape,o.dtype,s);return e.makeTensorInfo(a,u,l)}if(s==="int32")return jM(o,e);if(s==="bool"){let i=e.makeTensorInfo([],"bool",y.getTypedArrayFromDType("bool",1)),u=pT({inputs:{a:o,b:i},backend:e});return e.disposeIntermediateTensorInfo(i),u}throw new Error(`Error in Cast: failed to cast ${o.dtype} to ${s}`)}var XM={kernelName:io,backendName:"webgl",kernelFunc:mT};var YM="return ceil(x);",zet=Ct({opSnippet:YM,packedOpSnippet:YM,cpuKernelImpl:oL}),ZM={kernelName:Ho,backendName:"webgl",kernelFunc:zet};var tC=class{constructor(t){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=t,this.userCode=`

      void main() {
        float value = getAAtOutCoords();
        if (isnan(value)) {
          setOutput(value);
          return;
        }

        setOutput(clamp(value, minVal, maxVal));
      }
    `}};var eC=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=t,this.userCode=`
      void main() {
        vec4 value = getAAtOutCoords();

        if (any(isnan(value))) {
          setOutput(value);
          return;
        }

        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
      }
    `}};function Bet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{clipValueMin:s,clipValueMax:i}=n,a;M().getBool("WEBGL_PACK_CLIP")?a=new eC(o.shape):a=new tC(o.shape);let u=[[s],[i]];return e.runWebGLProgram(a,[o],o.dtype,u)}var JM={kernelName:ao,backendName:"webgl",kernelFunc:Bet};var rC=class{constructor(t){this.variableNames=["real","imag"],this.outputShape=t,this.userCode=`
      void main() {
        float re = abs(getRealAtOutCoords());
        float im = abs(getImagAtOutCoords());
        float mx = max(re, im);

        // sadly the length function in glsl is not underflow-safe
        // (at least not on Intel GPUs). So the safe solution is
        // to ensure underflow-safety in all cases.
        setOutput(
          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
        );
      }
    `}};function QM(r,t){return{dataId:t.dataId,dtype:t.dtype,shape:r.shape}}function Vet(r){let{inputs:t,backend:e}=r,{x:n}=t,o=e.texData.get(n.dataId),s=new rC(n.shape),i=[QM(n,o.complexTensorInfos.real),QM(n,o.complexTensorInfos.imag)];return e.runWebGLProgram(s,i,i[0].dtype)}var tz={kernelName:Tl,backendName:"webgl",kernelFunc:Vet};var nC=class{constructor(t){this.outputShape=[],this.outputShape=S.computeOutShape(t,1),this.variableNames=t.map((i,a)=>`T${a}`);let e=new Array(t.length-1);e[0]=t[0][1];for(let i=1;i<e.length;i++)e[i]=e[i-1]+t[i][1];let n=[`if (yC < ${e[0]}) setOutput(getT0(yR, yC));`];for(let i=1;i<e.length;i++){let a=e[i-1];n.push(`else if (yC < ${e[i]}) setOutput(getT${i}(yR, yC-${a}));`)}let o=e.length,s=e[e.length-1];n.push(`else setOutput(getT${o}(yR, yC-${s}));`),this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int yR = coords.x;
        int yC = coords.y;

        ${n.join(`
        `)}
      }
    `}};var sC=class{constructor(t,e){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=S.computeOutShape(t,e);let n=this.outputShape,o=n.length,s=zt(o),i=Qe("coords",o),a=["x","y","z","w","u","v"].slice(0,o);this.variableNames=t.map((h,g)=>`T${g}`);let u=new Array(t.length-1);u[0]=t[0][e];for(let h=1;h<u.length;h++)u[h]=u[h-1]+t[h][e];let l=a[e],c=a.slice(-2),p=a.join(),m=`if (${l} < ${u[0]}) {
        return getChannel(
            getT0(${p}), vec2(${c.join()}));
        }`;for(let h=1;h<u.length;h++){let g=u[h-1];m+=`
        if (${l} < ${u[h]}  && ${l} >= ${u[h-1]}) {
          return getChannel(
            getT${h}(${oC(a,l,g)}),
            vec2(${oC(c,l,g)}));
        }`}let f=u.length,d=u[u.length-1];m+=`
        return getChannel(
          getT${f}(${oC(a,l,d)}),
          vec2(${oC(c,l,d)}));`,this.userCode=`
      float getValue(${a.map(h=>"int "+h)}) {
        ${m}
      }

      void main() {
        ${s} coords = getOutputCoords();
        vec4 result = vec4(getValue(${i}), 0., 0., 0.);

        ${i[o-1]} = ${i[o-1]} + 1;
        if (${i[o-1]} < ${n[o-1]}) {
          result.g = getValue(${i});
        }

        ${i[o-2]} = ${i[o-2]} + 1;
        if (${i[o-2]} < ${n[o-2]}) {
          result.a = getValue(${i});
        }

        ${i[o-1]} = ${i[o-1]} - 1;
        if (${i[o-2]} < ${n[o-2]} &&
            ${i[o-1]} < ${n[o-1]}) {
          result.b = getValue(${i});
        }
        setOutput(result);
      }
    `}};function oC(r,t,e){let n=r.indexOf(t);return r.map((s,i)=>i===n?`${s} - ${e}`:s).join()}function Hc(r){let{inputs:t,backend:e}=r,{input:n}=t,o=e.texData.get(n.dataId);return tr({inputs:{x:o.complexTensorInfos.imag},backend:e})}var ez={kernelName:vp,backendName:"webgl",kernelFunc:Hc};function Cd(r,t,e){let n=r[0].dtype;if(n==="complex64"){let p=r.map(g=>yl({inputs:{input:g},backend:e})),m=r.map(g=>Hc({inputs:{input:g},backend:e})),f=Cd(p,t,e),d=Cd(m,t,e),h=Tn({inputs:{real:f,imag:d},backend:e});return p.forEach(g=>e.disposeIntermediateTensorInfo(g)),m.forEach(g=>e.disposeIntermediateTensorInfo(g)),e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(d),h}let o=e.shouldExecuteOnCPU(r);if(n==="string"&&(o=!0),o){let p=r.map(b=>{let w=y.sizeFromShape(b.shape.slice(t));return st({inputs:{x:b},backend:e,attrs:{shape:[-1,w]}})}),m=p.map(b=>({vals:e.readSync(b.dataId),shape:b.shape})),f=S.computeOutShape(p.map(b=>b.shape),1),d=p[0].shape[0]===1,h=sL(m,f,n,d),g=S.computeOutShape(r.map(b=>b.shape),t),x=e.makeTensorInfo(g,n,h);return p.forEach(b=>e.disposeIntermediateTensorInfo(b)),x}let s=M().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(r.length>s){let p=[];for(let f=0;f<r.length;f+=s){let d=r.slice(f,f+s);p.push(Cd(d,t,e))}let m=Cd(p,t,e);for(let f of p)e.disposeIntermediateTensorInfo(f);return m}if(M().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&r[0].shape.length>1){let p=new sC(r.map(m=>m.shape),t);return e.runWebGLProgram(p,r,n)}let{tensors2D:i,outShape:a}=Get(r,t,e),u=new nC(i.map(p=>p.shape)),l=e.runWebGLProgram(u,i,n);i.forEach(p=>e.disposeIntermediateTensorInfo(p));let c=st({inputs:{x:l},attrs:{shape:a},backend:e});return e.disposeIntermediateTensorInfo(l),c}function Get(r,t,e){let n=S.computeOutShape(r.map(s=>s.shape),t);return{tensors2D:r.map(s=>st({inputs:{x:s},attrs:{shape:[-1,y.sizeFromShape(s.shape.slice(t))]},backend:e})),outShape:n}}function fT(r){let{inputs:t,backend:e,attrs:n}=r,{axis:o}=n,s=y.parseAxisParam(o,t[0].shape)[0],i=t.map(l=>l.shape);S.assertParamsConsistent(i,s);let a=S.computeOutShape(t.map(l=>l.shape),s);if(y.sizeFromShape(a)===0)return e.makeTensorInfo(a,t[0].dtype,[]);let u=t.filter(l=>y.sizeFromShape(l.shape)>0);return u.length===1?tr({inputs:{x:u[0]},backend:e}):Cd(u,s,e)}var rz={kernelName:ii,backendName:"webgl",kernelFunc:fT};var Id=class{constructor(t,e=!1,n=null,o=!1,s=!1){this.variableNames=["x","W"],this.outputShape=t.outShape;let i=t.padInfo.top,a=t.padInfo.left,u=t.strideHeight,l=t.strideWidth,c=t.dilationHeight,p=t.dilationWidth,m=t.filterHeight,f=t.filterWidth,d=Math.floor(t.inChannels/4)*4,h=t.inChannels%4,g=t.dataFormat==="channelsLast",x=g?1:2,b=g?2:3,w=g?3:1,C="",N="";n&&(o?C=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:s?C=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:C=`
          float activation(float x) {
            ${n}
          }
        `,N="result = activation(result);");let _=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${C}

      const ivec2 strides = ivec2(${u}, ${l});
      const ivec2 pads = ivec2(${i}, ${a});

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d2 = coords[${w}];

        ivec2 xRCCorner =
            ivec2(coords[${x}], coords[${b}]) * strides - pads;
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${m}; wR++) {
          int xR = xRCorner + wR * ${c};

          if (xR < 0 || xR >= ${t.inHeight}) {
            continue;
          }

          for (int wC = 0; wC < ${f}; wC++) {
            int xC = xCCorner + wC * ${p};

            if (xC < 0 || xC >= ${t.inWidth}) {
              continue;
            }

            for (int d1 = 0; d1 < ${d}; d1 += 4) {
              vec4 wValues = vec4(
                getW(wR, wC, d1, d2),
                getW(wR, wC, d1 + 1, d2),
                getW(wR, wC, d1 + 2, d2),
                getW(wR, wC, d1 + 3, d2)
              );

              if (${g}) {
                vec4 xValues = vec4(
                  getX(batch, xR, xC, d1),
                  getX(batch, xR, xC, d1 + 1),
                  getX(batch, xR, xC, d1 + 2),
                  getX(batch, xR, xC, d1 + 3)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec4 xValues = vec4(
                  getX(batch, d1, xR, xC),
                  getX(batch, d1 + 1, xR, xC),
                  getX(batch, d1 + 2, xR, xC),
                  getX(batch, d1 + 3, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }
            }

            if (${h===1}) {

              if (${g}) {
                dotProd +=
                    getX(batch, xR, xC, ${d}) *
                    getW(wR, wC, ${d}, d2);
              } else {
                dotProd +=
                    getX(batch, ${d}, xR, xC) *
                    getW(wR, wC, ${d}, d2);
              }

            } else if (${h===2}) {
              vec2 wValues = vec2(
                getW(wR, wC, ${d}, d2),
                getW(wR, wC, ${d} + 1, d2)
              );

              if (${g}) {
                vec2 xValues = vec2(
                  getX(batch, xR, xC, ${d}),
                  getX(batch, xR, xC, ${d} + 1)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec2 xValues = vec2(
                  getX(batch, ${d}, xR, xC),
                  getX(batch, ${d} + 1, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }

            } else if (${h===3}) {
              vec3 wValues = vec3(
                getW(wR, wC, ${d}, d2),
                getW(wR, wC, ${d} + 1, d2),
                getW(wR, wC, ${d} + 2, d2)
              );

              if (${g}) {
                vec3 xValues = vec3(
                  getX(batch, xR, xC, ${d}),
                  getX(batch, xR, xC, ${d} + 1),
                  getX(batch, xR, xC, ${d} + 2)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec3 xValues = vec3(
                  getX(batch, ${d}, xR, xC),
                  getX(batch, ${d} + 1, xR, xC),
                  getX(batch, ${d} + 2, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }

            }
          }
        }

        float result = dotProd;
        ${_}
        ${N}
        setOutput(result);
      }
    `}},iC=class{constructor(t){this.variableNames=["x","W"],this.outputShape=t.outShape;let e=t.padInfo.front,n=t.padInfo.top,o=t.padInfo.left,s=t.strideDepth,i=t.strideHeight,a=t.strideWidth,u=t.dilationDepth,l=t.dilationHeight,c=t.dilationWidth,p=t.filterDepth,m=t.filterHeight,f=t.filterWidth,d=Math.floor(t.inChannels/4)*4,h=t.inChannels%4;this.userCode=`
      const ivec3 strides = ivec3(${s}, ${i}, ${a});
      const ivec3 pads = ivec3(${e}, ${n}, ${o});

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int d2 = coords.u;

        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
        int xFCorner = xFRCCorner.x;
        int xRCorner = xFRCCorner.y;
        int xCCorner = xFRCCorner.z;

        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get
        // y(yF, yR, yC, d2). ? = to be determined. : = across all
        // values in that axis.
        float dotProd = 0.0;
        for (int wF = 0; wF < ${p}; wF++) {
          int xF = xFCorner + wF * ${u};

          if (xF < 0 || xF >= ${t.inDepth}) {
            continue;
          }

          for (int wR = 0; wR < ${m}; wR++) {
            int xR = xRCorner + wR * ${l};

            if (xR < 0 || xR >= ${t.inHeight}) {
              continue;
            }

            for (int wC = 0; wC < ${f}; wC++) {
              int xC = xCCorner + wC * ${c};

              if (xC < 0 || xC >= ${t.inWidth}) {
                continue;
              }

              for (int d1 = 0; d1 < ${d}; d1 += 4) {
                vec4 xValues = vec4(
                  getX(batch, xF, xR, xC, d1),
                  getX(batch, xF, xR, xC, d1 + 1),
                  getX(batch, xF, xR, xC, d1 + 2),
                  getX(batch, xF, xR, xC, d1 + 3)
                );
                vec4 wValues = vec4(
                  getW(wF, wR, wC, d1, d2),
                  getW(wF, wR, wC, d1 + 1, d2),
                  getW(wF, wR, wC, d1 + 2, d2),
                  getW(wF, wR, wC, d1 + 3, d2)
                );

                dotProd += dot(xValues, wValues);
              }

              if (${h===1}) {
                dotProd +=
                  getX(batch, xF, xR, xC, ${d}) *
                  getW(wF, wR, wC, ${d}, d2);
              } else if (${h===2}) {
                vec2 xValues = vec2(
                  getX(batch, xF, xR, xC, ${d}),
                  getX(batch, xF, xR, xC, ${d} + 1)
                );
                vec2 wValues = vec2(
                  getW(wF, wR, wC, ${d}, d2),
                  getW(wF, wR, wC, ${d} + 1, d2)
                );
                dotProd += dot(xValues, wValues);
              } else if (${h===3}) {
                vec3 xValues = vec3(
                  getX(batch, xF, xR, xC, ${d}),
                  getX(batch, xF, xR, xC, ${d} + 1),
                  getX(batch, xF, xR, xC, ${d} + 2)
                );
                vec3 wValues = vec3(
                  getW(wF, wR, wC, ${d}, d2),
                  getW(wF, wR, wC, ${d} + 1, d2),
                  getW(wF, wR, wC, ${d} + 2, d2)
                );
                dotProd += dot(xValues, wValues);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}};var vd=class{constructor(t,e=!1,n=null,o=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=t.outShape,this.enableShapeUniforms=we(this.outputShape.length);let i=t.padInfo.left,a=t.strideWidth,u=t.dilationWidth,l=t.filterHeight,c=t.filterWidth,p=c,m=`
       int xR; int xC; int xCOffset;
       vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g<c;g++)m+=`
           vec4 xTexelC${g*2};
           int xTexelC${g*2}Ready;
           vec4 xTexelC${g*2+1};
           int xTexelC${g*2+1}Ready;
           vec4 xC${g};`;m+=`
     for (int r = 0; r < ${l}; r++) {
      for (int d1 = 0; d1 < ${t.inChannels}; d1 += 2) {
       `;for(let g=0;g<c;g++)m+=`
           xTexelC${g*2} = vec4(0.0);
           xTexelC${g*2}Ready = 0;
           xTexelC${g*2+1} = vec4(0.0);
           xTexelC${g*2+1}Ready = 0;
           xC${g} = vec4(0.0);`;m+=`
         xR = xRCorner + r * dilations[0];
         if (xR >=0 && xR < inDims[0]) {
       `;for(let g=0;g<(p+1)/2;g++){let x=g*2;if(m+=`
           xC = xCCorner + ${x*u};
           `,a===1){if(x<c&&(i%2===1?(m+=`
                 xCOffset = xC + 1;
                 if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${x}Ready == 0) {
                   xTexelC${x} = getX(batch, xR, xCOffset, d1);

                   // Need to manually clear unused channels in case
                   // we're reading from recycled texture.
                   if (xCOffset + 1 >= inDims[1]) {
                     xTexelC${x}.zw = vec2(0.0);
                   }
                   xTexelC${x}Ready = 1;
                 }
               `,u===1&&x>0?m+=`
                 xC${x} = vec4(xTexelC${x-2}.zw, xTexelC${x}.xy);
                 `:m+=`
                   xCOffset = xC + 1 - 2;

                   if (xCOffset >= 0 && xCOffset < inDims[1]) {
                     previous = getX(batch, xR, xCOffset, d1);

                     // Need to manually clear unused channels in case
                     // we're reading from recycled texture.
                     if (xCOffset + 1 >= inDims[1]) {
                       previous.zw = vec2(0.0);
                     }

                     xC${x} = vec4(previous.zw, xTexelC${x}.xy);
                   } else {
                     xC${x} = vec4(0.0, 0.0, xTexelC${x}.xy);
                   }
                   `):m+=`
                 if (xC >= 0 && xC < inDims[1] && xTexelC${x}Ready == 0) {
                   xTexelC${x} = getX(batch, xR, xC, d1);
                   if (xC + 1 >= inDims[1]) {
                     xTexelC${x}.zw = vec2(0.0);
                   }
                   xTexelC${x}Ready = 1;
                 }

                 xC${x} = xTexelC${x};
                 `,x+1<c)){let b=i%2===0?y.nearestLargerEven(u):u;u%2===0&&i%2===1||u%2!==0&&i%2!==1?(m+=`
                   xCOffset = xC + imod(pads[1], 2) + ${b};

                   if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${x+1}Ready == 0) {
                     xTexelC${x+1} = getX(batch, xR, xCOffset, d1);

                     // Need to manually clear unused channels in case
                     // we're reading from recycled texture.
                     if (xCOffset + 1 >= inDims[1]) {
                       xTexelC${x+1}.zw = vec2(0.0);
                     }
                     xTexelC${x+1}Ready = 1;
                   }
                   `,u>1?m+=`
                     xCOffset -= 2;
                     if (xCOffset >= 0 && xCOffset < inDims[1]) {
                      previous = getX(batch, xR, xCOffset, d1);
                      xC${x+1} = vec4(previous.zw, xTexelC${x+1}.xy);
                     } else {
                      xC${x+1} = vec4(0.0, 0.0, xTexelC${x+1}.xy);
                     }
                     `:m+=`
                     xC${x+1} = vec4(xTexelC${x}.zw, xTexelC${x+1}.xy);
                     `):b===1?m+=`
                     xC${x+1} = xTexelC${x};
                     `:m+=`
                     xCOffset = xC + ${b};

                     if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${x+1}Ready == 0) {
                       xTexelC${x+1} = getX(batch, xR, xCOffset, d1);
                       if (xCOffset + 1 >= inDims[1]) {
                         xTexelC${x+1}.zw = vec2(0.0);
                       }
                       xTexelC${x+1}Ready = 1;
                     }

                     xC${x+1} = xTexelC${x+1};
                     `}}else x<c&&(i%2===1?(m+=`
                 xCOffset = xC + 1 - strides[1];
                 if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${x}Ready == 0) {
                   xTexelC${x} = getX(batch, xR, xCOffset, d1);
                   // Need to manually clear unused channels in case
                   // we're reading from recycled texture.
                   if (xCOffset + 1 >= inDims[1]) {
                     xTexelC${x}.zw = vec2(0.0);
                   }
                   xTexelC${x}Ready = 1;
                 }

                 if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${x+1}Ready == 0) {
                   xTexelC${x+1} = getX(batch, xR, xC + 1, d1);
                   // Need to manually clear unused channels in case
                   // we're reading from recycled texture.
                   if (xC + 2 >= inDims[1]) {
                     xTexelC${x+1}.zw = vec2(0.0);
                   }
                   xTexelC${x+1}Ready = 1;
                 }

                 xC${x} = vec4(xTexelC${x}.zw, xTexelC${x+1}.zw);
               `,x+1<c&&(m+=`
                   final = vec4(0.0);
                   xCOffset = xC + 1 + strides[1];
                   if(xCOffset >= 0 && xCOffset < inDims[1]) {
                     final = getX(batch, xR, xCOffset, d1);
                   }
                   xC${x+1} = vec4(xTexelC${x+1}.xy, final.xy);
                 `)):(m+=`
                 if(xC >= 0 && xC < inDims[1] && xTexelC${x}Ready == 0) {
                   xTexelC${x} = getX(batch, xR, xC, d1);
                   if (xC + 1 >= inDims[1]) {
                     xTexelC${x}.zw = vec2(0.0);
                   }
                   xTexelC${x}Ready = 1;
                 }

                 xCOffset = xC + strides[1];
                 if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${x+1}Ready == 0) {
                   xTexelC${x+1} = getX(batch, xR, xCOffset, d1);
                   if (xCOffset + 1 >= inDims[1]) {
                     xTexelC${x+1}.zw = vec2(0.);
                   }
                   xTexelC${x+1}Ready = 1;
                 }

                 xC${x} = vec4(
                   xTexelC${x}.xy, xTexelC${x+1}.xy);
               `,x+1<c&&(m+=`
                   xC${x+1} = vec4(xTexelC${x}.zw, xTexelC${x+1}.zw);
                 `)));x<c&&(m+=`
             wTexel = getW(r, ${x}, d1, d2);
             dotProd += xC${x}.xxzz * vec4(wTexel.xy, wTexel.xy);
             if(d1 + 1 < ${t.inChannels}) {
               dotProd += xC${x}.yyww * vec4(wTexel.zw, wTexel.zw);
             }
           `,x+1<c&&(m+=`
               wTexel = getW(r, ${x+1}, d1, d2);
               dotProd += xC${x+1}.xxzz * vec4(wTexel.xy, wTexel.xy);
               if(d1 + 1 < ${t.inChannels}) {
                 dotProd += xC${x+1}.yyww * vec4(wTexel.zw, wTexel.zw);
               }
             `))}m+=`
     }
   `,m+=`
     }
   `,m+=`
     }
   `;let f="",d="";n&&(o?f=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:s?f=`vec4 activation(vec4 a) {
           vec4 b = getLeakyreluAlphaAtOutCoords();
           ${n}
         }`:f=`vec4 activation(vec4 x) {
           ${n}
         }`,d="result = activation(result);");let h=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
       ${f}

       void main() {
         ivec4 coords = getOutputCoords();
         int batch = coords.x;
         ivec2 xRCCorner = coords.yz * strides - pads;
         int d2 = coords.w;
         int xRCorner = xRCCorner.x;
         int xCCorner = xRCCorner.y;

         //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
         vec4 dotProd = vec4(0.000000000000001);

         ${m}

         vec4 result = dotProd - vec4(0.000000000000001);
         ${h}
         ${d}
         setOutput(result);
       }
     `}};var aC=class{constructor(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec4"},{name:"pad",type:"ivec2"},{name:"stride",type:"ivec2"},{name:"dilation",type:"ivec2"},{name:"inChannels",type:"int"},{name:"itemsPerBlockRow",type:"int"},{name:"outWidth",type:"int"}],this.outputShape=t,this.enableShapeUniforms=we(this.outputShape.length);let{dataFormat:n}=e,o=Ve(),s=n==="channelsLast",i=s?1:2,a=s?2:3,u=this.enableShapeUniforms?"if(blockIndex < outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${t[2]} && pos < ${t[1]}) {`,l="";for(let c=0;c<=1;c++)for(let p=0;p<=1;p++)l+=`
          blockIndex = rc.z + ${p};
          pos = rc.y + ${c};

          ${u}
            offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];
            d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);

            if(d0 < inputShape[${i}] && d0 >= 0) {
              // Use custom imod instead mod. On Intel GPU, mod may generate
              // unexpected value.
              // https://github.com/tensorflow/tfjs/issues/5447
              offsetX = imod(blockIndex, outWidth) * stride[1] - pad[1];
              d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) /
                  inChannels);

              if(d1 < inputShape[${a}] && d1 >= 0) {

                ch = imod(pos, inChannels);

                if (${s}) {
                  innerDims = vec2(d1, ch);
                  result[${c*2+p}] = getChannel(
                    getA(rc.x, d0, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                } else {
                  innerDims = vec2(d0, d1);
                  result[${c*2+p}] = getChannel(
                    getA(rc.x, ch, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                }
              }
            }
          }
        `;this.userCode=`
      void main() {
        ivec3 rc = getOutputCoords();

        vec4 result = vec4(0);

        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
        vec2 innerDims;

        ${l}

        ${o.output} = result;
      }
    `}};function lC(r,t){let e=r.length;return e>=3?t?[...r.slice(0,-3),r[e-3]*r[e-2],r[e-1]]:[...r.slice(0,-3),r[e-3],r[e-2]*r[e-1]]:!t&&e===1&&r[0]>1?[r[0],1]:null}function uC({x:r,filter:t,convInfo:e,backend:n,bias:o=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:a=null}){let u=r.shape,l=n.texData.get(r.dataId),c=e.inChannels,p=u[0]*u[1]*u[2],m=e.outChannels,f=e.dataFormat==="channelsLast",d=!1,h=!1,g,x=[];if(s!=null){let C=lC(s.shape,f);C!=null&&(s=st({inputs:{x:s},backend:n,attrs:{shape:C}}),x.push(s))}if(o!=null){let C=lC(o.shape,f);C!=null&&(o=st({inputs:{x:o},backend:n,attrs:{shape:C}}),x.push(o))}if(!((p===1||m===1)&&c>uT)&&l.isPacked&&f&&l.texture!=null&&u[2]%2!==0&&y.arraysEqual(l.shape.slice(-3),u.slice(-3))){let C=u[0]*u[1]*(u[2]+1),N={dataId:r.dataId,shape:[1,C,e.inChannels],dtype:r.dtype},_=l.shape;l.shape=l.shape.slice(),l.shape[l.shape.length-2]++,y.assert(Tu(l.shape,N.shape),()=>`packed reshape ${l.shape} to ${N.shape} isn't free`);let A=st({inputs:{x:t},backend:n,attrs:{shape:[1,e.inChannels,e.outChannels]}});x.push(A);let $=Uc({a:N,b:A,backend:n,transposeA:d,transposeB:h,bias:o,activation:a,preluActivationWeights:s,leakyreluAlpha:i}),F=n.texData.get($.dataId);y.assert(F.isPacked,()=>"batchMatMul result is expected to be packed"),l.shape=_,F.shape=e.outShape,g=tr({inputs:{x:$},backend:n}),g.shape=e.outShape,x.push($)}else{let C=e.outHeight*e.outWidth,N=st({inputs:{x:r},backend:n,attrs:{shape:f?[e.batchSize,C,e.inChannels]:[e.batchSize,e.inChannels,C]}}),_=st({inputs:{x:t},backend:n,attrs:{shape:[1,e.inChannels,e.outChannels]}}),A=Uc({a:f?N:_,b:f?_:N,transposeA:!f,transposeB:h,backend:n,bias:o,activation:a,preluActivationWeights:s,leakyreluAlpha:i});g=st({inputs:{x:A},backend:n,attrs:{shape:e.outShape}}),x.push(N),x.push(_),x.push(A)}for(let C of x)n.disposeIntermediateTensorInfo(C);return g}function cC({x:r,filter:t,convInfo:e,backend:n,bias:o=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:a=null}){let{filterWidth:u,filterHeight:l,inChannels:c,outWidth:p,outHeight:m,dataFormat:f}=e,d=f==="channelsLast",h=u*l*c,g=m*p,x=[e.batchSize,h,g],b=!0,w=!1,C=[];if(s!=null){let Z=lC(s.shape,d);Z!=null&&(s=st({inputs:{x:s},backend:n,attrs:{shape:Z}}),C.push(s))}if(o!=null){let Z=lC(o.shape,d);Z!=null&&(o=st({inputs:{x:o},backend:n,attrs:{shape:Z}}),C.push(o))}let N=st({inputs:{x:t},backend:n,attrs:{shape:[1,h,y.sizeFromShape(t.shape)/h]}});C.push(N);let _=new aC(x,e),A=[r.shape,[e.padInfo.top,e.padInfo.left],[e.strideHeight,e.strideWidth],[e.dilationHeight,e.dilationWidth],[e.inChannels],[e.filterWidth*e.inChannels],[e.outWidth]],$=n.runWebGLProgram(_,[r],"float32",A),F=st({inputs:{x:$},backend:n,attrs:{shape:x}});C.push($),C.push(F);let P=o!=null,V=s!=null,G=a==="leakyrelu",W=a?xl(a,!0):null,q=new wd(d?F.shape:N.shape,d?N.shape:F.shape,d?[e.batchSize,g,e.outChannels]:[e.batchSize,e.outChannels,g],b,w,P,W,V,G),H=d?[F,N]:[N,F];if(o&&H.push(o),V&&H.push(s),G){let Z=n.makeTensorInfo([],"float32",y.createScalarValue(i,"float32"));H.push(Z),C.push(Z)}let j=n.runWebGLProgram(q,H,"float32"),Y=st({inputs:{x:j},backend:n,attrs:{shape:e.outShape}});C.push(j);for(let Z of C)n.disposeIntermediateTensorInfo(Z);return Y}function Wet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dataFormat:u,dilations:l,dimRoundingMode:c}=n,p=S.convertConv2DDataFormat(u),m=S.computeConv2DInfo(o.shape,s.shape,i,l,a,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=uC({x:o,filter:s,convInfo:m,backend:e});else if(m.strideWidth<=2&&p==="channelsLast"&&M().getBool("WEBGL_EXP_CONV")){let h=new vd(m),g=[[m.padInfo.top,m.padInfo.left],[m.strideHeight,m.strideWidth],[m.dilationHeight,m.dilationWidth],[m.inHeight,m.inWidth]];f=e.runWebGLProgram(h,[o,s],"float32",g)}else if(M().getBool("WEBGL_CONV_IM2COL"))f=cC({x:o,filter:s,convInfo:m,backend:e});else{let h=new Id(m);f=e.runWebGLProgram(h,[o,s],"float32")}let d=st({inputs:{x:f},backend:e,attrs:{shape:m.outShape}});return e.disposeIntermediateTensorInfo(f),d}var nz={kernelName:qo,backendName:"webgl",kernelFunc:Wet};var pC=class{constructor(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;let e=t.strideHeight,n=t.strideWidth,o=t.padInfo.top,s=t.padInfo.left,i=t.dataFormat==="channelsLast";this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int wR = coords.x;
        int wC = coords.y;
        int d1 = coords.z;
        int d2 = coords.w;

        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int b = 0; b < ${t.batchSize}; b++) {
          for (int yR = 0; yR < ${t.outHeight}; yR++) {
            int xR = wR + yR * ${e} - ${o};

            if (xR < 0 || xR >= ${t.inHeight}) {
              continue;
            }

            for (int yC = 0; yC < ${t.outWidth}; yC++) {
              int xC = wC + yC * ${n} - ${s};

              if (xC < 0 || xC >= ${t.inWidth}) {
                continue;
              }

              if (${i}) {
                float dyValue = getDy(b, yR, yC, d2);
                float xValue = getX(b, xR, xC, d1);
                dotProd += (xValue * dyValue);
              } else {
                float dyValue = getDy(b, d2, yR, yC);
                float xValue = getX(b, d1, xR, xC);
                dotProd += (xValue * dyValue);
              }

            }
          }
        }
        setOutput(dotProd);
      }
    `}},mC=class{constructor(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;let e=t.filterHeight,n=t.filterWidth,o=t.strideHeight,s=t.strideWidth,i=t.dataFormat==="channelsLast",a=e-1-t.padInfo.top,u=n-1-t.padInfo.left,l=i?1:2,c=i?2:3,p=i?3:1;this.userCode=`
      const ivec2 pads = ivec2(${a}, ${u});

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d1 = coords[${p}];

        ivec2 dyCorner = ivec2(coords[${l}], coords[${c}]) - pads;
        int dyRCorner = dyCorner.x;
        int dyCCorner = dyCorner.y;

        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${e}; wR++) {
          float dyR = float(dyRCorner + wR) / ${o}.0;

          if (dyR < 0.0 || dyR >= ${t.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          int wRPerm = ${e} - 1 - wR;

          for (int wC = 0; wC < ${n}; wC++) {
            float dyC = float(dyCCorner + wC) / ${s}.0;

            if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            int wCPerm = ${n} - 1 - wC;

            for (int d2 = 0; d2 < ${t.outChannels}; d2++) {

              if (${i}) {
                float xValue = getDy(batch, idyR, idyC, d2);
                float wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              } else {
                float xValue = getDy(batch, d2, idyR, idyC);
                float wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }

            }
          }
        }
        setOutput(dotProd);
      }
    `}},fC=class{constructor(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;let e=t.strideDepth,n=t.strideHeight,o=t.strideWidth,s=t.padInfo.front,i=t.padInfo.top,a=t.padInfo.left;this.userCode=`
      void main() {
        ivec5 coords = getOutputCoords();
        int wF = coords.x;
        int wR = coords.y;
        int wC = coords.z;
        int d1 = coords.w;
        int d2 = coords.u;

        float dotProd = 0.0;

        for (int b = 0; b < ${t.batchSize}; b++) {
          for (int yF = 0; yF < ${t.outDepth}; yF++) {
            int xF = wF + yF * ${e} - ${s};

            if (xF < 0 || xF >= ${t.inDepth}) {
              continue;
            }

            for (int yR = 0; yR < ${t.outHeight}; yR++) {
              int xR = wR + yR * ${n} - ${i};

              if (xR < 0 || xR >= ${t.inHeight}) {
                continue;
              }

              for (int yC = 0; yC < ${t.outWidth}; yC++) {
                int xC = wC + yC * ${o} - ${a};

                if (xC < 0 || xC >= ${t.inWidth}) {
                  continue;
                }

                float dyValue = getDy(b, yF, yR, yC, d2);
                float xValue = getX(b, xF, xR, xC, d1);
                dotProd += (xValue * dyValue);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}},dC=class{constructor(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;let e=t.filterDepth,n=t.filterHeight,o=t.filterWidth,s=t.strideDepth,i=t.strideHeight,a=t.strideWidth,u=e-1-t.padInfo.front,l=n-1-t.padInfo.top,c=o-1-t.padInfo.left;this.userCode=`
      const ivec3 pads = ivec3(${u}, ${l}, ${c});

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int d1 = coords.u;


        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyFCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        float dotProd = 0.0;
        for (int wF = 0; wF < ${e}; wF++) {
          float dyF = float(dyFCorner + wF) / ${s}.0;

          if (dyF < 0.0 || dyF >= ${t.outDepth}.0 || fract(dyF) > 0.0) {
            continue;
          }
          int idyF = int(dyF);

          int wFPerm = ${e} - 1 - wF;

          for (int wR = 0; wR < ${n}; wR++) {
            float dyR = float(dyRCorner + wR) / ${i}.0;

            if (dyR < 0.0 || dyR >= ${t.outHeight}.0 ||
              fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            int wRPerm = ${n} - 1 - wR;

            for (int wC = 0; wC < ${o}; wC++) {
              float dyC = float(dyCCorner + wC) / ${a}.0;

              if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              int wCPerm = ${o} - 1 - wC;

              for (int d2 = 0; d2 < ${t.outChannels}; d2++) {
                float xValue = getDy(batch, idyF, idyR, idyC, d2);
                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function Uet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,pad:a,dataFormat:u,dimRoundingMode:l,filterShape:c}=n,p=S.convertConv2DDataFormat(u),m=S.computeConv2DInfo(o.shape,c,i,1,a,l,!1,p),f=new pC(m);return e.runWebGLProgram(f,[o,s],"float32")}var oz={kernelName:mp,backendName:"webgl",kernelFunc:Uet};function Het(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{inputShape:i,strides:a,pad:u,dataFormat:l,dimRoundingMode:c}=n,p=S.convertConv2DDataFormat(l),m=S.computeConv2DInfo(i,s.shape,a,1,u,c,!1,p),f=new mC(m);return e.runWebGLProgram(f,[o,s],"float32")}var sz={kernelName:Ko,backendName:"webgl",kernelFunc:Het};function qet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u}=n,l=S.computeConv3DInfo(o.shape,s.shape,i,u,a),c=new iC(l);return e.runWebGLProgram(c,[o,s],"float32")}var iz={kernelName:El,backendName:"webgl",kernelFunc:qet};function Ket(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,pad:a,filterShape:u}=n,l=S.computeConv3DInfo(o.shape,u,i,1,a),c=new fC(l);return e.runWebGLProgram(c,[o,s],"float32")}var az={kernelName:fp,backendName:"webgl",kernelFunc:Ket};function jet(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{pad:i,strides:a,inputShape:u}=n,l=S.computeConv3DInfo(u,s.shape,a,1,i),c=new dC(l);return e.runWebGLProgram(c,[o,s],"float32")}var lz={kernelName:dp,backendName:"webgl",kernelFunc:jet};var Xet=Oo+`
  return cos(x);
`,Yet=Ct({opSnippet:Xet}),uz={kernelName:jo,backendName:"webgl",kernelFunc:Yet};var Zet=`
  float e2x = exp(-x);
  return (e2x + 1.0 / e2x) / 2.0;
`,Jet=Ct({opSnippet:Zet}),cz={kernelName:Xo,backendName:"webgl",kernelFunc:Jet};var hC=class{constructor(t,e,n,o,s){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[i,a,u,l]=t,[c]=e,[p,m]=n;this.outputShape=[c,p,m,l];let f=o==="bilinear"?1:0,[d,h]=[`${a-1}.0`,`${u-1}.0`],[g,x,b]=p>1?[`${(a-1)/(p-1)}`,"(y2-y1) * height_ratio",`y1*${d} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${d}`],[w,C,N]=m>1?[`${(u-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() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int y = coords[1];
        int x = coords[2];
        int d = coords[3];

        // get box vals
        float y1 = getBoxes(b,0);
        float x1 = getBoxes(b,1);
        float y2 = getBoxes(b,2);
        float x2 = getBoxes(b,3);

        // get image in batch index
        int bInd = round(getBoxInd(b));
        if(bInd < 0 || bInd >= ${i}) {
          return;
        }

        float height_scale = ${x};
        float width_scale = ${C};

        float in_y = ${b};
        if( in_y < 0.0 || in_y > ${d} ) {
          setOutput(float(${s}));
          return;
        }
        float in_x = ${N};
        if( in_x < 0.0 || in_x > ${h} ) {
          setOutput(float(${s}));
          return;
        }

        vec2 sourceFracIndexCR = vec2(in_x,in_y);
        if(${f} == 1) {
          // Compute the four integer indices.
          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));

          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);

          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);

          float top = topLeft + (topRight - topLeft) * fracCR.x;
          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
          float newValue = top + (bottom - top) * fracCR.y;
          setOutput(newValue);
        } else {
          // Compute the coordinators of nearest neighbor point.
          ivec2 sourceNearestCR = ivec2(floor(
            sourceFracIndexCR + vec2(0.5,0.5)));
          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
          setOutput(newValue);
        }
      }
    `}};var Qet=r=>{let{inputs:t,backend:e,attrs:n}=r,{image:o,boxes:s,boxInd:i}=t,{cropSize:a,method:u,extrapolationValue:l}=n,c=new hC(o.shape,s.shape,a,u,l);return e.runWebGLProgram(c,[o,s,i],"float32")},pz={kernelName:ma,backendName:"webgl",kernelFunc:Qet};var qc;(function(r){r.Prod="*",r.Sum="+"})(qc||(qc={}));var Jh=class{constructor(t,e,n,o){this.op=t,this.outputShape=e,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let s=this.outputShape.length,i=this.op===qc.Prod?"1.0":"0.0",a=n?i:`getX(${mz(s,"coords",this.op)})`,u=this.outputShape[this.outputShape.length-1],l="",c="";n?(l=o?`end != ${u-1}`:"end != 0",c=o?"end + 1":"end - 1"):(l=o?`end + pow2 < ${u}`:"end >= pow2",c=o?"end + pow2":"end - pow2"),this.userCode=`
      void main() {
        ${zt(s)} coords = getOutputCoords();
        int end = ${fz(s,"coords",this.op)};
        float val = ${a};
        int pow2 = int(pow(2.0, index));
        if (${l}) {
          int idx = ${c};
          ${fz(s,"coords",this.op)} = idx;
          val ${this.op}= getX(${mz(s,"coords",this.op)});
        }
        setOutput(val);
      }
    `}};function mz(r,t,e){if(r===1)return`${t}`;if(r===2)return`${t}.x, ${t}.y`;if(r===3)return`${t}.x, ${t}.y, ${t}.z`;if(r===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw new Error(`Cumulative ${e} for rank ${r} is not yet supported`)}function fz(r,t,e){if(r===1)return`${t}`;if(r===2)return`${t}.y`;if(r===3)return`${t}.z`;if(r===4)return`${t}.w`;throw new Error(`Cumulative ${e} for rank ${r} is not yet supported`)}function gC(r,t,e,n,o,s){let i=t.shape.length,a=S.getAxesPermutation([n],i),u=t;a!=null&&(u=Fe({inputs:{x:t},backend:e,attrs:{perm:a}}));let l=S.getInnerMostAxes(1,i)[0];if(l!==i-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let c=u.shape[l],p=tr({inputs:{x:u},backend:e});for(let m=0;m<=Math.ceil(Math.log2(c))-1;m++){let f=new Jh(r,u.shape,!1,s),d=[[m]],h=p;p=e.runWebGLProgram(f,[p],p.dtype,d),e.disposeIntermediateTensorInfo(h)}if(o){let m=new Jh(r,u.shape,o,s),f=p;p=e.runWebGLProgram(m,[p],p.dtype),e.disposeIntermediateTensorInfo(f)}if(a!=null){let m=S.getUndoAxesPermutation(a),f=Fe({inputs:{x:p},backend:e,attrs:{perm:m}});return e.disposeIntermediateTensorInfo(p),e.disposeIntermediateTensorInfo(u),f}return p}function trt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n;return gC(qc.Prod,o,e,s,i,a)}var dz={kernelName:pa,backendName:"webgl",kernelFunc:trt};function ert(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n;return gC(qc.Sum,o,e,s,i,a)}var hz={kernelName:Yo,backendName:"webgl",kernelFunc:ert};function rrt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,weights:s}=t,{size:i,binaryOutput:a}=n;if(o.shape.length===1){let u=e.readSync(o.dataId),l=e.readSync(s.dataId),c=Dw(u,l,s.dtype,s.shape,i);return e.makeTensorInfo([i],s.dtype,c)}else if(o.shape.length===2){let u=e.bufferSync(o),l=e.bufferSync(s),c=rL(u,l,i,a);return e.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${o.shape.length}.`)}var gz={kernelName:hp,backendName:"webgl",kernelFunc:rrt};var xC=class{constructor(t,e,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=t,this.blockSize=e,this.dataFormat=n,this.userCode=`
    void main() {
      ivec4 coords = getOutputCoords();
      int b = coords[0];
      int h = ${this.getHeightCoordString()};
      int w = ${this.getWidthCoordString()};
      int d = ${this.getDepthCoordString()};

      int in_h = h / ${e};
      int offset_h = imod(h, ${e});
      int in_w = w / ${e};
      int offset_w = imod(w, ${e});
      int offset_d = (offset_h * ${e} + offset_w) *
        ${this.getOutputDepthSize()};
      int in_d = d + offset_d;

      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 nrt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockSize:s,dataFormat:i}=n,a=o.shape[0],u=i==="NHWC"?o.shape[1]:o.shape[2],l=i==="NHWC"?o.shape[2]:o.shape[3],c=i==="NHWC"?o.shape[3]:o.shape[1],p=u*s,m=l*s,f=c/(s*s),d=i==="NHWC"?[a,p,m,f]:[a,f,p,m],h=new xC(d,s,i);return e.runWebGLProgram(h,[o],o.dtype)}var xz={kernelName:fa,backendName:"webgl",kernelFunc:nrt};var Sd=class{constructor(t,e=!1,n=null,o=!1,s=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=t.outShape,this.enableShapeUniforms=we(this.outputShape.length);let i=t.filterHeight,a=t.filterWidth,u=t.outChannels/t.inChannels,l="",c="";n&&(o?l=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:s?l=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:l=`
          float activation(float x) {
            ${n}
          }
        `,c="result = activation(result);");let p=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${l}

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        ivec2 xRCCorner = coords.yz * strides - pads;
        int d2 = coords.w;
        int d1 = d2 / ${u};
        int q = d2 - d1 * ${u};

        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.
        for (int wR = 0; wR < ${i}; wR++) {
          int xR = xRCorner + wR * dilations[0];

          if (xR < 0 || xR >= inDims[0]) {
            continue;
          }

          for (int wC = 0; wC < ${a}; wC++) {
            int xC = xCCorner + wC * dilations[1];

            if (xC < 0 || xC >= inDims[1]) {
              continue;
            }

            float xVal = getX(batch, xR, xC, d1);
            float wVal = getW(wR, wC, d1, q);
            dotProd += xVal * wVal;
          }
        }

        float result = dotProd;
        ${p}
        ${c}
        setOutput(result);
      }
    `}};var Nd=class{constructor(t,e=!1,n=null,o=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=t.outShape,this.enableShapeUniforms=we(this.outputShape.length);let i=t.outChannels/t.inChannels,a=t.padInfo.left,u=t.strideWidth,l=t.dilationWidth,c=t.filterHeight,p=t.filterWidth,m=p,f=`
      int xR; int xC; int xCOffset;
      vec4 wTexel; vec4 previous; vec4 final;`;for(let x=0;x<p;x++)f+=`
          vec4 xTexelC${x*2};
          int xTexelC${x*2}Ready;
          vec4 xTexelC${x*2+1};
          int xTexelC${x*2+1}Ready;
          vec4 xC${x};`;f+=`
    for (int r = 0; r < ${c}; r++) {
      `;for(let x=0;x<p;x++)f+=`
          xTexelC${x*2} = vec4(0.0);
          xTexelC${x*2}Ready = 0;
          xTexelC${x*2+1} = vec4(0.0);
          xTexelC${x*2+1}Ready = 0;
          xC${x} = vec4(0.0);`;f+=`
        xR = xRCorner + r * dilations[0];
        if (xR >=0 && xR < inDims[0]) {
      `;for(let x=0;x<(m+1)/2;x++){let b=x*2;if(f+=`
          xC = xCCorner + ${b*l};
          `,u===1){if(b<p&&(a%2===1?(f+=`
                xCOffset = xC + 1;
                if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b}Ready == 0) {
                  xTexelC${b} = getX(batch, xR, xCOffset, d1);

                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xCOffset + 1 >= inDims[1]) {
                    xTexelC${b}.zw = vec2(0.0);
                  }
                  xTexelC${b}Ready = 1;
                }
              `,l===1&&b>0?f+=`
                xC${b} = vec4(xTexelC${b-2}.zw, xTexelC${b}.xy);
                `:f+=`
                  xCOffset = xC + 1 - 2;

                  if (xCOffset >= 0 && xCOffset < inDims[1]) {
                    previous = getX(batch, xR, xCOffset, d1);

                    // Need to manually clear unused channels in case
                    // we're reading from recycled texture.
                    if (xCOffset + 1 >= inDims[1]) {
                      previous.zw = vec2(0.0);
                    }

                    xC${b} = vec4(previous.zw, xTexelC${b}.xy);
                  } else {
                    xC${b} = vec4(0.0, 0.0, xTexelC${b}.xy);
                  }
                  `):f+=`
                if (xC >= 0 && xC < inDims[1] && xTexelC${b}Ready == 0) {
                  xTexelC${b} = getX(batch, xR, xC, d1);
                  if (xC + 1 >= inDims[1]) {
                    xTexelC${b}.zw = vec2(0.0);
                  }
                  xTexelC${b}Ready = 1;
                }

                xC${b} = xTexelC${b};
                `,b+1<p)){let w=a%2===0?y.nearestLargerEven(l):l;l%2===0&&a%2===1||l%2!==0&&a%2!==1?(f+=`
                  xCOffset = xC + imod(pads[1], 2) + ${w};

                  if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
                    xTexelC${b+1} = getX(batch, xR, xCOffset, d1);

                    // Need to manually clear unused channels in case
                    // we're reading from recycled texture.
                    if (xCOffset + 1 >= inDims[1]) {
                      xTexelC${b+1}.zw = vec2(0.0);
                    }
                    xTexelC${b+1}Ready = 1;
                  }
                  `,l>1?f+=`
                    xCOffset -= 2;
                    if (xCOffset >= 0 && xCOffset < inDims[1]) {
                     previous = getX(batch, xR, xCOffset, d1);
                     xC${b+1} = vec4(previous.zw, xTexelC${b+1}.xy);
                    } else {
                     xC${b+1} = vec4(0.0, 0.0, xTexelC${b+1}.xy);
                    }
                    `:f+=`
                    xC${b+1} = vec4(xTexelC${b}.zw, xTexelC${b+1}.xy);
                    `):w===1?f+=`
                    xC${b+1} = xTexelC${b};
                    `:f+=`
                    xCOffset = xC + ${w};

                    if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
                      xTexelC${b+1} = getX(batch, xR, xCOffset, d1);
                      if (xCOffset + 1 >= inDims[1]) {
                        xTexelC${b+1}.zw = vec2(0.0);
                      }
                      xTexelC${b+1}Ready = 1;
                    }

                    xC${b+1} = xTexelC${b+1};
                    `}}else b<p&&(a%2===1?(f+=`
                xCOffset = xC + 1 - strides[1];
                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b}Ready == 0) {
                  xTexelC${b} = getX(batch, xR, xCOffset, d1);
                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xCOffset + 1 >= inDims[1]) {
                    xTexelC${b}.zw = vec2(0.0);
                  }
                  xTexelC${b}Ready = 1;
                }

                if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${b+1}Ready == 0) {
                  xTexelC${b+1} = getX(batch, xR, xC + 1, d1);
                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xC + 2 >= inDims[1]) {
                    xTexelC${b+1}.zw = vec2(0.0);
                  }
                  xTexelC${b+1}Ready = 1;
                }

                xC${b} = vec4(xTexelC${b}.zw, xTexelC${b+1}.zw);
              `,b+1<p&&(f+=`
                  final = vec4(0.0);
                  xCOffset = xC + 1 + strides[1];
                  if(xCOffset >= 0 && xCOffset < inDims[1]) {
                    final = getX(batch, xR, xCOffset, d1);
                  }
                  xC${b+1} = vec4(xTexelC${b+1}.xy, final.xy);
                `)):(f+=`
                if(xC >= 0 && xC < inDims[1] && xTexelC${b}Ready == 0) {
                  xTexelC${b} = getX(batch, xR, xC, d1);
                  if (xC + 1 >= inDims[1]) {
                    xTexelC${b}.zw = vec2(0.0);
                  }
                  xTexelC${b}Ready = 1;
                }

                xCOffset = xC + strides[1];
                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
                  xTexelC${b+1} = getX(batch, xR, xCOffset, d1);
                  if (xCOffset + 1 >= inDims[1]) {
                    xTexelC${b+1}.zw = vec2(0.);
                  }
                  xTexelC${b+1}Ready = 1;
                }

                xC${b} = vec4(
                  xTexelC${b}.xy, xTexelC${b+1}.xy);
              `,b+1<p&&(f+=`
                  xC${b+1} = vec4(xTexelC${b}.zw, xTexelC${b+1}.zw);
                `)));b<p&&(f+=`
            wTexel = getW(r, ${b}, d1, q);
            dotProd += xC${b} * vec4(wTexel.xz, wTexel.xz);
          `,b+1<p&&(f+=`
              wTexel = getW(r, ${b+1}, d1, q);
              dotProd += xC${b+1} * vec4(wTexel.xz, wTexel.xz);
            `))}f+=`
    }
  `,f+=`
      }
    `;let d="",h="";n&&(o?d=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:s?d=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:d=`vec4 activation(vec4 x) {
          ${n}
        }`,h="result = activation(result);");let g=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${d}

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        ivec2 xRCCorner = coords.yz * strides - pads;
        int d2 = coords.w;
        int d1 = d2 / ${i};
        int q = d2 - d1 * ${i};
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
        vec4 dotProd = vec4(0.000000000000001);

        ${f}

        vec4 result = dotProd - vec4(0.000000000000001);
        ${g}
        ${h}
        setOutput(result);
      }
    `}};function ort(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u,dimRoundingMode:l}=n,c=u;c==null&&(c=[1,1]),y.assert(S.eitherStridesOrDilationsAreOne(i,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let p=S.computeConv2DInfo(o.shape,s.shape,i,c,a,l,!0),m;M().getBool("WEBGL_PACK_DEPTHWISECONV")&&p.strideWidth<=2&&p.outChannels/p.inChannels===1?m=new Nd(p):m=new Sd(p);let f=[[p.padInfo.top,p.padInfo.left],[p.strideHeight,p.strideWidth],[p.dilationHeight,p.dilationWidth],[p.inHeight,p.inWidth]];return e.runWebGLProgram(m,[o,s],"float32",f)}var yz={kernelName:Zo,backendName:"webgl",kernelFunc:ort};var yC=class{constructor(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;let e=t.strideHeight,n=t.strideWidth,o=t.padInfo.top,s=t.padInfo.left,i=t.outChannels/t.inChannels;this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int wR = coords.x;
        int wC = coords.y;
        int d1 = coords.z;
        int dm = coords.w;
        int d2 = d1 * ${i} + dm;

        float dotProd = 0.0;

        // TO DO: Vec4 over the batch size
        for (int b = 0; b < ${t.batchSize}; b++) {
          for (int yR = 0; yR < ${t.outHeight}; yR++) {
            int xR = wR + yR * ${e} - ${o};

            if (xR < 0 || xR >= ${t.inHeight}) {
              continue;
            }

            for (int yC = 0; yC < ${t.outWidth}; yC++) {
              int xC = wC + yC * ${n} - ${s};

              if (xC < 0 || xC >= ${t.inWidth}) {
                continue;
              }

              float dyValue = getDy(b, yR, yC, d2);
              float xValue = getX(b, xR, xC, d1);
              dotProd += (xValue * dyValue);
            }
          }
        }
        setOutput(dotProd);
      }
    `}},bC=class{constructor(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;let e=t.filterHeight,n=t.filterWidth,o=t.strideHeight,s=t.strideWidth,i=e-1-t.padInfo.top,a=n-1-t.padInfo.left,u=t.outChannels/t.inChannels;this.userCode=`
      const ivec2 pads = ivec2(${i}, ${a});

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d1 = coords[3];
        ivec2 dyCorner = coords.yz - pads;
        int dyRCorner = dyCorner.x;
        int dyCCorner = dyCorner.y;

        float dotProd = 0.0;

        for (int wR = 0; wR < ${e}; wR++) {
          float dyR = float(dyRCorner + wR) / ${o}.0;

          if (dyR < 0.0 || dyR >= ${t.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          int wRPerm = ${e} - 1 - wR;

          for (int wC = 0; wC < ${n}; wC++) {
            float dyC = float(dyCCorner + wC) / ${s}.0;

            if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            int wCPerm = ${n} - 1 - wC;

            // TO DO: Vec4 over the channelMul
            for (int dm = 0; dm < ${u}; dm++) {
              int d2 = d1 * ${u} + dm;
              float xValue = getDy(batch, idyR, idyC, d2);
              float wValue = getW(wRPerm, wCPerm, d1, dm);
              dotProd += xValue * wValue;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function srt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,dilations:a,pad:u,dimRoundingMode:l,filterShape:c}=n,p=S.computeConv2DInfo(o.shape,c,i,a,u,l,!0),m=new yC(p);return e.runWebGLProgram(m,[o,s],"float32")}var bz={kernelName:gp,backendName:"webgl",kernelFunc:srt};function irt(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{strides:i,dilations:a,pad:u,dimRoundingMode:l,inputShape:c}=n,p=S.computeConv2DInfo(c,s.shape,i,a,u,l,!0),m=new bC(p);return e.runWebGLProgram(m,[o,s],"float32")}var wz={kernelName:xp,backendName:"webgl",kernelFunc:irt};var wC=class{constructor(t){this.variableNames=["X"],this.outputShape=[t,t],this.userCode=`
      void main() {
          ivec2 coords = getOutputCoords();
          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
          setOutput(val);
      }
    `}};function art(r){let{inputs:t,backend:e}=r,{x:n}=t,o=[...n.shape,...n.shape],s=y.sizeFromShape(n.shape),i=st({inputs:{x:n},backend:e,attrs:{shape:[s]}}),a=new wC(s),u=e.runWebGLProgram(a,[i],i.dtype),l=st({inputs:{x:u},backend:e,attrs:{shape:o}});return e.disposeIntermediateTensorInfo(i),e.disposeIntermediateTensorInfo(u),l}var Cz={kernelName:yp,backendName:"webgl",kernelFunc:art};var CC=class{constructor(t){this.variableNames=["x","W"],this.outputShape=t.outShape;let{inHeight:e,inWidth:n,padInfo:o,strideHeight:s,strideWidth:i,filterHeight:a,filterWidth:u,dilationHeight:l,dilationWidth:c}=t,{top:p,left:m}=o;this.userCode=`
      const ivec2 strides = ivec2(${s}, ${i});
      const ivec2 pads = ivec2(${p}, ${m});
      const float neg_infinity = -3.4e38;

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        int d1 = coords.w;
        ivec2 outTopLeftCorner =
            coords.yz * strides - pads;
        int hBeg = outTopLeftCorner.x;
        int wBeg = outTopLeftCorner.y;

        float curVal = neg_infinity;
        for (int h = 0; h < ${a}; h++) {
          int hIn = hBeg + h * ${l};

          if (hIn >= 0 && hIn < ${e}) {
            for (int w = 0; w < ${u}; w++) {
              int wIn = wBeg + w * ${c};

              if (wIn >= 0 && wIn < ${n}) {
                float xVal = getX(batch, hIn, wIn, d1);
                float wVal = getW(h, w, d1);

                float val = xVal + wVal;
                if (val > curVal) {
                  curVal = val;
                }
              }
            }
          }
        }

        float result = curVal;
        setOutput(result);
      }
    `}};function lrt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u}=n,l=S.computeDilation2DInfo(o.shape,s.shape,i,a,"NHWC",u),c,p=new CC(l);c=e.runWebGLProgram(p,[o,s],"float32");let m=st({inputs:{x:c},backend:e,attrs:{shape:l.outShape}});return e.disposeIntermediateTensorInfo(c),m}var Iz={kernelName:_l,backendName:"webgl",kernelFunc:lrt};function urt(r){let{inputs:t,backend:e,attrs:n}=r,{equation:o}=n,s=t,{allDims:i,summedDims:a,idDims:u}=S.decodeEinsumEquation(o,s.length);S.checkEinsumDimSizes(i.length,u,s);let{path:l,steps:c}=S.getEinsumComputePath(a,u),p=c.length,m=null,f=i.length,d=[];for(let h=0;h<p;++h){for(let g of c[h]){let{permutationIndices:x,expandDims:b}=S.getEinsumPermutation(f,u[g]),w;S.isIdentityPermutation(x)?w=s[g]:(w=Fe({inputs:{x:s[g]},backend:e,attrs:{perm:x}}),d.push(w));let C=w.shape.slice();for(let N=0;N<b.length;++N)C.splice(b[N],0,1);y.arraysEqual(w.shape,C)||(w=st({inputs:{x:w},backend:e,attrs:{shape:C}}),d.push(w)),m===null?m=w:(m=Yh({inputs:{a:w,b:m},backend:e}),d.push(m))}h<p-1&&(l[h]>=0&&(m=Wc({inputs:{x:m},backend:e,attrs:{axis:l[h]-(i.length-f),keepDims:!1}}),d.push(m)),f--)}for(let h of d)h!==m&&e.disposeIntermediateTensorInfo(h);return m}var vz={kernelName:bp,backendName:"webgl",kernelFunc:urt};var crt="return (x >= 0.0) ? x : (exp(x) - 1.0);",prt=`
  vec4 result;

  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);
  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);

  return result;
`,mrt=Ct({opSnippet:crt,packedOpSnippet:prt}),Sz={kernelName:Qo,backendName:"webgl",kernelFunc:mrt};var frt="return (b >= 1.0) ? a : a * (b + 1.0);",drt=`
  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,hrt=r=>{let{inputs:t,backend:e}=r,{dy:n,y:o}=t,s=M().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Fo(drt,n.shape,o.shape):new oo(frt,n.shape,o.shape);return e.runWebGLProgram(s,[n,o],n.dtype)},Nz={kernelName:wp,backendName:"webgl",kernelFunc:hrt};var grt=`
  return vec4(equal(a, b));
`,xrt="return float(a == b);",yrt=le({opSnippet:xrt,packedOpSnippet:grt,dtype:"bool",cpuKernelImpl:iL}),kz={kernelName:ha,backendName:"webgl",kernelFunc:yrt};var brt=`
  // Error function is calculated approximately with elementary function.
  // See "Handbook of Mathematical Functions with Formulas,
  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
  float p = ${S.ERF_P};
  float a1 = ${S.ERF_A1};
  float a2 = ${S.ERF_A2};
  float a3 = ${S.ERF_A3};
  float a4 = ${S.ERF_A4};
  float a5 = ${S.ERF_A5};

  float sign = sign(x);
  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));
`,wrt=Ct({opSnippet:brt}),Tz={kernelName:da,backendName:"webgl",kernelFunc:wrt};var Crt=Oo+`
  return exp(x);
`,Irt=`
  vec4 result = exp(x);
  bvec4 isNaN = isnan(x);
  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,dT=Ct({opSnippet:Crt,packedOpSnippet:Irt,cpuKernelImpl:aL,dtype:"float32"}),Ez={kernelName:ts,backendName:"webgl",kernelFunc:dT};function IC(r){let{inputs:t,attrs:e,backend:n}=r,{dim:o}=e,{input:s}=t,i=s.shape.length,a=s.shape.slice(),u=o;return o<0&&(y.assert(-(i+1)<=o,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),u=i+o+1),a.splice(u,0,1),st({inputs:{x:s},backend:n,attrs:{shape:a}})}var _z={kernelName:ai,backendName:"webgl",kernelFunc:IC};var Az="return exp(x) - 1.0;",vrt=Ct({opSnippet:Az,packedOpSnippet:Az,cpuKernelImpl:lL}),$z={kernelName:ga,backendName:"webgl",kernelFunc:vrt};var Qh=class{constructor(t,e,n){this.variableNames=["real","imag"];let o=e[1];this.outputShape=e;let s=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,i=n?`${o}.0`:"1.0",a;if(t==="real")a="return real * expR - imag * expI;";else if(t==="imag")a="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${t}.`);this.userCode=`
      const float exponentMultiplier = ${s};

      float unaryOpComplex(float real, float expR, float imag, float expI) {
        ${a}
      }

      float mulMatDFT(int batch, int index) {
        float indexRatio = float(index) / float(${o});
        float exponentMultiplierTimesIndexRatio =
            exponentMultiplier * indexRatio;

        float result = 0.0;

        for (int i = 0; i < ${o}; i++) {
          // x = (-2|2 * PI / N) * index * i;
          float x = exponentMultiplierTimesIndexRatio * float(i);
          float expR = cos(x);
          float expI = sin(x);
          float real = getReal(batch, i);
          float imag = getImag(batch, i);

          result +=
              unaryOpComplex(real, expR, imag, expI) / ${i};
        }

        return result;
      }

      void main() {
        ivec2 coords = getOutputCoords();
        setOutput(mulMatDFT(coords[0], coords[1]));
      }
    `}};function vC(r,t,e){let n=e.texData.get(r.dataId),o=y.sizeFromShape(r.shape),s=r.shape[r.shape.length-1],i=o/s,a=st({inputs:{x:r},backend:e,attrs:{shape:[i,s]}}),u=a.shape,l=new Qh("real",u,t),c=new Qh("imag",u,t),p=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:u},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:u}],m=e.runWebGLProgram(l,p,"float32"),f=e.runWebGLProgram(c,p,"float32"),d=Tn({inputs:{real:m,imag:f},backend:e});e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f);let h=st({inputs:{x:d},backend:e,attrs:{shape:r.shape}});return e.disposeIntermediateTensorInfo(a),e.disposeIntermediateTensorInfo(d),h}function Srt(r){let{inputs:t,backend:e}=r,{input:n}=t;return vC(n,!1,e)}var Dz={kernelName:Cp,backendName:"webgl",kernelFunc:Srt};var SC=class{constructor(t,e){this.outputShape=[],this.customUniforms=[{name:"value",type:"float"}],this.variableNames=["x"],this.outputShape=t,this.userCode=`
      void main() {
        // Input can be obtained from uniform value.
        setOutput(value);
      }
    `}};function bl(r){let{backend:t,attrs:e}=r,{shape:n,value:o}=e,{dtype:s}=e;if(s=s||y.inferDtype(o),s==="string"){let i=y.getArrayFromDType(s,y.sizeFromShape(n));return i.fill(o),t.makeTensorInfo(n,s,i)}else{let i=new SC(n,o),a=[[o]];return t.runWebGLProgram(i,[],s,a)}}var Rz={kernelName:Al,backendName:"webgl",kernelFunc:bl};var NC=class{constructor(t){this.variableNames=["Image"],this.outputShape=[];let e=t[2];this.outputShape=t,this.userCode=`
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];

          int coordX = ${e} - x - 1;
          float outputValue;
          if(coordX >= 0 && coordX < ${e}) {
            outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
          } else {
            outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
          }
          setOutput(outputValue);
        }
    `}};var Fz={kernelName:xa,backendName:"webgl",kernelFunc:({inputs:r,backend:t})=>{let{image:e}=r,n=t,o=new NC(e.shape);return n.runWebGLProgram(o,[e],e.dtype)}};var Oz="return floor(x);",Nrt=Ct({opSnippet:Oz,packedOpSnippet:Oz,cpuKernelImpl:uL}),Pz={kernelName:es,backendName:"webgl",kernelFunc:Nrt};var krt=`
  float s = sign(a) * sign(b);
  int ia = round(a);
  int ib = round(b);
  if (ib != 0) {
    // Windows (D3D) wants guaranteed non-zero int division at compile-time.
    return float(idiv(ia, ib, s));
  } else {
    return NAN;
  }
`,Trt=`
  ivec4 ia = round(a);
  ivec4 ib = round(b);
  bvec4 cond = notEqual(ib, ivec4(0));
  ivec4 result = ivec4(0);
  vec4 s = sign(a) * sign(b);

  // Windows (D3D) wants guaranteed non-zero int division at compile-time.
  if (cond[0]) {
    result[0] = idiv(ia[0], ib[0], s[0]);
  }
  if (cond[1]) {
    result[1] = idiv(ia[1], ib[1], s[1]);
  }
  if (cond[2]) {
    result[2] = idiv(ia[2], ib[2], s[2]);
  }
  if (cond[3]) {
    result[3] = idiv(ia[3], ib[3], s[3]);
  }
  return vec4(result);
`,Ert=le({opSnippet:krt,packedOpSnippet:Trt,dtype:"int32"}),Lz={kernelName:rs,backendName:"webgl",kernelFunc:Ert};var kC=class{constructor(t){this.variableNames=["A"];let e=Ve(),[n,o]=t;this.outputShape=t,this.userCode=`
      void main() {
        ivec3 coords = getOutputCoords();
        int texR = coords[0];
        int texC = coords[1];
        int depth = coords[2];
        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${o}.0, ${n}.0);

        vec4 values = ${e.texture2D}(A, uv);
        float value;
        if (depth == 0) {
          value = values.r;
        } else if (depth == 1) {
          value = values.g;
        } else if (depth == 2) {
          value = values.b;
        } else if (depth == 3) {
          value = values.a;
        }

        setOutput(floor(value * 255.0 + 0.5));
      }
    `}};var TC=class{constructor(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let e=Ve(),[n,o]=t;this.outputShape=t,this.userCode=`
      void main() {
        ivec3 coords = getOutputCoords();
        int texR = coords[0];
        int texC = coords[1];
        int depth = coords[2];

        vec4 result = vec4(0.);

        for(int row=0; row<=1; row++) {
          for(int col=0; col<=1; col++) {
            texC = coords[1] + row;
            depth = coords[2] + col;

            vec2 uv = (vec2(texC, texR) + halfCR) /
                       vec2(${o}.0, ${n}.0);
            vec4 values = ${e.texture2D}(A, uv);
            float value;
            if (depth == 0) {
              value = values.r;
            } else if (depth == 1) {
              value = values.g;
            } else if (depth == 2) {
              value = values.b;
            } else if (depth == 3) {
              value = values.a;
            }

            result[row * 2 + col] = floor(value * 255.0 + 0.5);
          }
        }

        ${e.output} = result;
      }
    `}};var Mz={kernelName:qd,backendName:"webgl",kernelFunc:_rt},kd,hT=M().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function _rt(r){let{inputs:t,backend:e,attrs:n}=r,{pixels:o}=t,{numChannels:s}=n,i=typeof HTMLVideoElement!="undefined"&&o instanceof HTMLVideoElement,a=typeof HTMLImageElement!="undefined"&&o instanceof HTMLImageElement,[u,l]=i?[o.videoWidth,o.videoHeight]:[o.width,o.height],c=[l,u],p=[l,u,s];if(a||i){let h=M().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(kd==null||h!==hT)&&(hT=h,kd=document.createElement("canvas").getContext("2d",{willReadFrequently:hT})),kd.canvas.width=u,kd.canvas.height=l,kd.drawImage(o,0,0,u,l),o=kd.canvas}let m=e.makeTensorInfo(c,"int32");e.texData.get(m.dataId).usage=Kr.PIXELS,e.gpgpu.uploadPixelDataToTexture(e.getTexture(m.dataId),o);let f=M().getBool("WEBGL_PACK")?new TC(p):new kC(p),d=e.runWebGLProgram(f,[m],"int32");return e.disposeData(m.dataId),d}function Art(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s,bias:i,preluActivationWeights:a}=t,{strides:u,pad:l,dataFormat:c,dilations:p,dimRoundingMode:m,activation:f,leakyreluAlpha:d}=n,h=S.convertConv2DDataFormat(c),g=S.computeConv2DInfo(o.shape,s.shape,u,p,l,m,!1,h),x,b=[],w=i!=null,C=a!=null,N=f==="leakyrelu",_=()=>{let $=[o,s],F=(P,V)=>{if(V==="NCHW"&&P.shape.length===1&&P.shape[0]!==1){let G=st({inputs:{x:P},backend:e,attrs:{shape:[P.shape[0],1,1]}});return b.push(G),G}return P};if(w&&$.push(F(i,c)),C&&$.push(F(a,c)),N){let P=e.makeTensorInfo([],"float32",y.createScalarValue(d,"float32"));$.push(P),b.push(P)}return $};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=uC({x:o,filter:s,convInfo:g,backend:e,bias:i,activation:f,preluActivationWeights:a,leakyreluAlpha:d});else if(g.strideWidth<=2&&h==="channelsLast"&&M().getBool("WEBGL_EXP_CONV")){let $=f?xl(f,!0):null,F=new vd(g,w,$,C,N),P=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],V=_();x=e.runWebGLProgram(F,V,"float32",P)}else if(M().getBool("WEBGL_CONV_IM2COL"))x=cC({x:o,filter:s,convInfo:g,backend:e,bias:i,activation:f,preluActivationWeights:a,leakyreluAlpha:d});else{let $=f?xl(f,!1):null,F=new Id(g,w,$,C,N),P=_();x=e.runWebGLProgram(F,P,"float32")}let A=st({inputs:{x},backend:e,attrs:{shape:g.outShape}});return b.push(x),b.forEach($=>e.disposeIntermediateTensorInfo($)),A}var zz={kernelName:wi,backendName:"webgl",kernelFunc:Art};function $rt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s,bias:i,preluActivationWeights:a}=t,{strides:u,pad:l,dilations:c,dimRoundingMode:p,activation:m,leakyreluAlpha:f}=n,d=[],h=c;h==null&&(h=[1,1]),y.assert(S.eitherStridesOrDilationsAreOne(u,h),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${u} and dilations '${h}'`);let g=S.computeConv2DInfo(o.shape,s.shape,u,h,l,p,!0),x=M().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,b=m?xl(m,x):null,w=[o,s],C=i!=null,N=a!=null,_=m==="leakyrelu";if(C&&w.push(i),N&&w.push(a),_){let P=e.makeTensorInfo([],"float32",y.createScalarValue(f,"float32"));w.push(P),d.push(P)}let A;x?A=new Nd(g,C,b,N,_):A=new Sd(g,C,b,N,_);let $=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],F=e.runWebGLProgram(A,w,"float32",$);return d.forEach(P=>e.disposeIntermediateTensorInfo(P)),F}var Bz={kernelName:Ci,backendName:"webgl",kernelFunc:$rt};var EC=class{constructor(t,e,n,o){this.sliceDim=t,this.strides=e,this.paramsShape=o,this.variableNames=["x","indices"],this.outputShape=n;let s=zt(n.length),i=`
    int index;`;for(let a=0;a<this.sliceDim;a++)i+=`
          index = round(getIndices(coords[0], ${a}));
          out_of_bounds = out_of_bounds || index < 0;
          out_of_bounds = out_of_bounds || index >= ${this.paramsShape[a]};
          flattenIndex += index * ${this.strides[a]};`;this.userCode=`
         void main() {
          ${s} coords = getOutputCoords();
          int flattenIndex = 0;
          bool out_of_bounds = false;

          ${i}

          setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));
        }
      `}};function Drt(r){let{inputs:t,backend:e}=r,{params:n,indices:o}=t,s=o.shape,i=s[s.length-1],a=y.sizeFromShape(n.shape),[u,l,c,p]=S.prepareAndValidate(n,o),m=st({inputs:{x:o},backend:e,attrs:{shape:[l,i]}}),f=st({inputs:{x:n},backend:e,attrs:{shape:[y.sizeFromShape(n.shape)/c,c]}});if(e.shouldExecuteOnCPU([n,o])||n.dtype==="string"){let x=e.readSync(o.dataId),b=e.bufferSync(n),w=cL(x,b,n.dtype,l,i,c,p,n.shape,a);return e.makeTensorInfo(u,n.dtype,w.values)}let d=new EC(i,p,[l,c],n.shape),h=e.runWebGLProgram(d,[f,m],f.dtype),g=st({inputs:{x:h},backend:e,attrs:{shape:u}});return e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(h),g}var Vz={kernelName:ya,backendName:"webgl",kernelFunc:Drt};var _C=class{constructor(t,e){this.variableNames=["A","indices"],this.outputShape=e,this.rank=e.length;let n=zt(this.rank),o=Rrt(t,2);this.userCode=`
      void main() {
        ${n} resRC = getOutputCoords();
        int index = int(getIndices(resRC.x, resRC.z));
        float inBounds = (index >= 0) && (index < ${t[2]}) ? 1.0 : 0.0;
        setOutput(inBounds * getA(${o}));
      }
    `}};function Rrt(r,t){let e=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let o=0;o<r.length;o++)o===2?n.push("index"):n.push(`${e[o]}`);return n.join()}function gT(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,indices:s}=t,{axis:i,batchDims:a}=n,u=y.parseAxisParam(i,o.shape)[0];if(M().get("DEBUG")){let b=e.readSync(s.dataId),w=o.shape[u];for(let C=0;C<b.length;++C){let N=b[C];y.assert(N<=w-1&&N>=0,()=>`GatherV2: the index value ${N} is not in [0, ${w-1}]`)}}let l=S.segment_util.collectGatherOpShapeInfo(o,s,u,a),c=y.sizeFromShape(s.shape),p=[],m=st({inputs:{x:o},backend:e,attrs:{shape:[l.batchSize,l.outerSize,l.dimSize,l.sliceSize]}}),f=st({inputs:{x:s},backend:e,attrs:{shape:[l.batchSize,c/l.batchSize]}});p.push(m),p.push(f);let d=[l.batchSize,l.outerSize,c/l.batchSize,l.sliceSize];if(e.shouldExecuteOnCPU([o,s])||o.dtype==="string"){let b=e.bufferSync(f),w=e.bufferSync(m),C=pL(w,b,d);return p.forEach(N=>e.disposeIntermediateTensorInfo(N)),e.makeTensorInfo(l.outputShape,C.dtype,C.values)}let h=new _C(m.shape,d),g=e.runWebGLProgram(h,[m,f],m.dtype);p.push(g);let x=st({inputs:{x:g},backend:e,attrs:{shape:l.outputShape}});return p.forEach(b=>e.disposeIntermediateTensorInfo(b)),x}var Gz={kernelName:li,backendName:"webgl",kernelFunc:gT};var Frt="return float(a > b);",Ort=`
  return vec4(greaterThan(a, b));
`,Prt=le({opSnippet:Frt,packedOpSnippet:Ort,cpuKernelImpl:mL,dtype:"bool"}),Wz={kernelName:ba,backendName:"webgl",kernelFunc:Prt};var Lrt="return float(a >= b);",Mrt=`
  return vec4(greaterThanEqual(a, b));
`,zrt=le({opSnippet:Lrt,packedOpSnippet:Mrt,dtype:"bool",cpuKernelImpl:fL}),Uz={kernelName:os,backendName:"webgl",kernelFunc:zrt};function Brt(r){let{inputs:t,backend:e}=r,{input:n}=t;return vC(n,!0,e)}var Hz={kernelName:Ip,backendName:"webgl",kernelFunc:Brt};var Vrt="return float(!isnan(x) && !isinf(x));",Grt=Ct({opSnippet:Vrt,dtype:"bool"}),qz={kernelName:wa,backendName:"webgl",kernelFunc:Grt};var Wrt="return float(isinf(x));",Urt=Ct({opSnippet:Wrt,dtype:"bool"}),Kz={kernelName:Ca,backendName:"webgl",kernelFunc:Urt};var Hrt="return float(isnan(x));",qrt=Ct({opSnippet:Hrt,dtype:"bool"}),jz={kernelName:Ia,backendName:"webgl",kernelFunc:qrt};var Krt="return float(a < b);",jrt=`
  return vec4(lessThan(a, b));
`,Xrt=le({opSnippet:Krt,packedOpSnippet:jrt,cpuKernelImpl:dL,dtype:"bool"}),Xz={kernelName:va,backendName:"webgl",kernelFunc:Xrt};var Yrt="return float(a <= b);",Zrt=`
  return vec4(lessThanEqual(a, b));
`,Jrt=le({opSnippet:Yrt,packedOpSnippet:Zrt,cpuKernelImpl:hL,dtype:"bool"}),Yz={kernelName:Sa,backendName:"webgl",kernelFunc:Jrt};function Qrt(r){let{backend:t,attrs:e}=r,{start:n,stop:o,num:s}=e,i=gL(n,o,s);return t.makeTensorInfo([i.length],"float32",i)}var Zz={kernelName:Sp,backendName:"webgl",kernelFunc:Qrt};var tnt=Oo+`
  return x < 0.0 ? 0./0. : log(x);
`,ent=`
  vec4 result = log(x);
  bvec4 isNaN = isnan(x);
  result.r = isNaN.r ? x.r : (x.r < 0.0 ? 0./0. : result.r);
  result.g = isNaN.g ? x.g : (x.g < 0.0 ? 0./0. : result.g);
  result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);
  result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);
  return result;
`,rnt=Ct({opSnippet:tnt,packedOpSnippet:ent,cpuKernelImpl:xL}),Jz={kernelName:is,backendName:"webgl",kernelFunc:rnt};var nnt=Oo+`
  return log(1.0 + x);
`,ont=Ct({opSnippet:nnt}),Qz={kernelName:Na,backendName:"webgl",kernelFunc:ont};var snt="return float(a >= 1.0 && b >= 1.0);",int=`
  return vec4(
    vec4(greaterThanEqual(a, vec4(1.0))) *
    vec4(greaterThanEqual(b, vec4(1.0))));
`,ant=le({opSnippet:snt,packedOpSnippet:int,dtype:"bool"}),t3={kernelName:ka,backendName:"webgl",kernelFunc:ant};var lnt="return float(!(x >= 1.0));",unt=Ct({opSnippet:lnt}),e3={kernelName:Ta,backendName:"webgl",kernelFunc:unt};var cnt="return float(a >= 1.0 || b >= 1.0);",pnt=`
  return min(
    vec4(greaterThanEqual(a, vec4(1.0))) +
    vec4(greaterThanEqual(b, vec4(1.0))),
    vec4(1.0));
`,mnt=le({opSnippet:cnt,packedOpSnippet:pnt,dtype:"bool"}),r3={kernelName:Ea,backendName:"webgl",kernelFunc:mnt};var AC=class{constructor(t,e,n,o,s){this.variableNames=["x"],this.outputShape=[];let i=e,a=t[3]-1;this.outputShape=t;let u,l=`float(${n}) + float(${o}) * sum`;s===.5?u=`inversesqrt(${l})`:s===1?u=`1.0/(${l})`:u=`exp(log(${l}) * float(-${s}));`,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];
        int d = coords[3];
        float x = getX(b, r, c, d);
        float sum = 0.0;
        for (int j = -${i}; j <= ${i}; j++) {
          int idx = d + j;
          if (idx >= 0 && idx <=  ${a}) {
            float z = getX(b, r, c, idx);
            sum += z * z;
          }
        }
        float val = x * ${u};
        setOutput(val);
      }
    `}};var $C=class{constructor(t,e,n,o,s){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let i=e,a=t[3]-1;this.outputShape=t;let u,l=`float(${n}) + float(${o}) * sum`;s===.5?u=`inversesqrt(${l})`:s===1?u=`1.0/(${l})`:u=`exp(log(${l}) * float(-${s}));`,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords.x;
        int r = coords.y;
        int c = coords.z;
        int d = coords.w;

        bool hasNextCol = d < ${this.outputShape[3]};
        bool hasNextRow = c < ${this.outputShape[2]};

        vec4 sum = vec4(0.);
        vec4 xFragAtOutputCoords = getX(b, r, c, d);

        vec4 xAtOutputCoords = vec4(
          getChannel(xFragAtOutputCoords, vec2(c, d)),
          hasNextCol ?
            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,
          hasNextRow ?
            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,
          (hasNextRow && hasNextCol) ?
            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0
        );

        int firstChannel = d - ${i};
        vec2 cache = vec2(0.);
        if(firstChannel >= 0){
          vec4 firstChannelFrag = getX(b, r, c, firstChannel);
          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));
            if(hasNextRow){
              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));
            }
        }

        ivec2 depth = ivec2(d, d + 1);
        for (int j = - ${i}; j <= ${i}; j++) {
          ivec2 idx = depth + j;
          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${a}));

          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;
          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;

          if(depthInRange || depthPlusOneInRange){
            vec4 z = vec4(0.);
            vec4 xFragAtCurrentDepth;
            z.xz = cache.xy;
            if(depthPlusOneInRange && hasNextCol){
              xFragAtCurrentDepth = idx.y != d ?
                getX(b, r, c, idx.y) : xFragAtOutputCoords;
              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));
              if(hasNextRow){
                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));
              }
            }
            cache.xy = z.yw;
            sum += z * z;
          }
        }
        vec4 result = xAtOutputCoords * ${u};
        setOutput(result);
      }
    `}};var fnt=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{depthRadius:s,bias:i,alpha:a,beta:u}=n,l=M().getBool("WEBGL_PACK_NORMALIZATION")?new $C(o.shape,s,i,a,u):new AC(o.shape,s,i,a,u);return e.runWebGLProgram(l,[o],o.dtype)},n3={kernelName:$l,backendName:"webgl",kernelFunc:fnt};var DC=class{constructor(t,e,n,o,s){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=t,this.depth=t[3],this.depthRadius=e,this.bias=n,this.alpha=o,this.beta=s,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];

        float result = 0.0;
        for (int d = 0; d < ${this.depth}; ++d) {
          int depthBegin = int(max(0.0, float(d - ${e})));
          int depthEnd = int(min(float(${this.depth}),
              float(d + ${e} + 1)));

          const int MIN_DEPTH_BEGIN = 0;
          const int MAX_DEPTH_END = ${this.depth};

          float norm = 0.0;
          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
            if (k < depthBegin){
              continue;
            }
            else if (k >= depthBegin && k < depthEnd) {
              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
            }
            else {
              break;
            }
          }

          norm = float(${o}) * norm + float(${n});

          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
            if (k < depthBegin){
              continue;
            }
            else if (k >= depthBegin && k < depthEnd){
              float dyi = -2.0 * float(${o})
                * float(${s})
                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
                / norm;
              if (k == d) {
                dyi += pow(norm, -1.0 * ${s});
              }
              if (k == coords[3]) {
                dyi *= getDy(b, r, c, d);
                result += dyi;
              }
            }
            else {
              break;
            }
          }
      }
      setOutput(result);
      }
    `}};var dnt=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o,y:s,dy:i}=t,{depthRadius:a,bias:u,alpha:l,beta:c}=n,p=new DC(o.shape,a,u,l,c);return e.runWebGLProgram(p,[o,s,i],o.dtype)},o3={kernelName:Np,backendName:"webgl",kernelFunc:dnt};function s3(r,t,e,n){let o=y.sizeFromShape(t),i=y.sizeFromShape(r.shape)/o,a=st({inputs:{x:r},attrs:{shape:[i,o]},backend:n}),u=Gn(a,r.dtype,"max",n),l=st({inputs:{x:u},attrs:{shape:e},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(u),l}function xT(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{reductionIndices:s,keepDims:i}=n,a=o.shape.length,u=y.parseAxisParam(s,o.shape),l=u,c=S.getAxesPermutation(l,a),p=c!=null,m=e.shouldExecuteOnCPU([o]),f=o;if(p){if(m){let w=e.texData.get(f.dataId).values,C=new Array(a);for(let A=0;A<C.length;A++)C[A]=o.shape[c[A]];let N=Vc(w,o.shape,o.dtype,c,C);f=e.makeTensorInfo(C,o.dtype);let _=e.texData.get(f.dataId);_.values=N}else f=_u(o,c,e);l=S.getInnerMostAxes(l.length,a)}S.assertAxesAreInnerMostDims("max",l,a);let[d,h]=S.computeOutAndReduceShapes(f.shape,l),g=d;i&&(g=S.expandShapeToKeepDim(d,u));let x;if(m){let w=e.texData.get(f.dataId).values,C=yL(w,y.sizeFromShape(h),g,o.dtype);x=e.makeTensorInfo(g,o.dtype);let N=e.texData.get(x.dataId);N.values=C}else x=s3(f,h,g,e);return p&&e.disposeIntermediateTensorInfo(f),x}var i3={kernelName:as,backendName:"webgl",kernelFunc:xT};var hnt=bd+`
  return max(a, b);
`,gnt=`
  vec4 result = vec4(max(a, b));
  bvec4 isNaNA = isnan(a);
  bvec4 isNaNB = isnan(b);
  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
  `+ji+`
  return result;
`,xnt=le({opSnippet:hnt,packedOpSnippet:gnt,cpuKernelImpl:bL}),a3={kernelName:ls,backendName:"webgl",kernelFunc:xnt};function ynt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t;Zs(o,"maxPool");let{filterSize:s,strides:i,pad:a,dimRoundingMode:u}=n,l=1;y.assert(S.eitherStridesOrDilationsAreOne(i,l),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${l}'`);let c=S.computePool2DInfo(o.shape,s,i,l,a,u);if(c.filterWidth===1&&c.filterHeight===1&&y.arraysEqual(c.inShape,c.outShape))return tr({inputs:{x:o},backend:e});let p=new Qs(c,"max",!1);return e.runWebGLProgram(p,[o],o.dtype)}var l3={kernelName:us,backendName:"webgl",kernelFunc:ynt};function bnt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{filterSize:s,strides:i,pad:a,dataFormat:u,dimRoundingMode:l}=n,c=[1,1,1],p=S.computePool3DInfo(o.shape,s,i,c,a,l,u),m=new Au(p,"max",!1);return e.runWebGLProgram(m,[o],o.dtype)}var u3={kernelName:Dl,backendName:"webgl",kernelFunc:bnt};var RC=class{constructor(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;let e=t.strideHeight,n=t.strideWidth,o=t.dilationHeight,s=t.effectiveFilterHeight,i=t.effectiveFilterWidth,a=s-1-t.padInfo.top,u=i-1-t.padInfo.left,l=s*i-1;this.userCode=`
      const ivec2 pads = ivec2(${a}, ${u});

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];

        ivec2 dyRCCorner = coords.yz - pads;
        int dyRCorner = dyRCCorner.x;
        int dyCCorner = dyRCCorner.y;

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${s};
          wR += ${o}) {
          float dyR = float(dyRCorner + wR) / ${e}.0;

          if (dyR < 0.0 || dyR >= ${t.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          for (int wC = 0; wC < ${i}; wC++) {
            float dyC = float(dyCCorner + wC) / ${n}.0;

            if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            float dyValue = getDy(b, idyR, idyC, d);
            int maxPosValue = ${l} - int(getMaxPos(b, idyR, idyC, d));

            // Get the current value, check it against the value from the
            // position matrix.
            int curPosValue = wR * ${i} + wC;
            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);

            dotProd += dyValue * mask;
          }
        }
        setOutput(dotProd);
      }
    `}},FC=class{constructor(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;let e=t.strideDepth,n=t.strideHeight,o=t.strideWidth,s=t.dilationDepth,i=t.dilationHeight,a=t.dilationWidth,u=t.effectiveFilterDepth,l=t.effectiveFilterHeight,c=t.effectiveFilterWidth,p=u-1-t.padInfo.front,m=l-1-t.padInfo.top,f=c-1-t.padInfo.left,d=u*l*c-1;this.userCode=`
      const ivec3 pads = ivec3(${p}, ${m}, ${f});

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyDCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get
        // dx(xD, xR, xC, ch).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int wD = 0; wD < ${u};
           wD += ${s}) {
          float dyD = float(dyDCorner + wD) / ${e}.0;

          if (dyD < 0.0 || dyD >= ${t.outDepth}.0 || fract(dyD) > 0.0) {
            continue;
          }
          int idyD = int(dyD);

          for (int wR = 0; wR < ${l};
              wR += ${i}) {
            float dyR = float(dyRCorner + wR) / ${n}.0;

            if (dyR < 0.0 || dyR >= ${t.outHeight}.0 ||
                fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            for (int wC = 0; wC < ${c};
                wC += ${a}) {
              float dyC = float(dyCCorner + wC) / ${o}.0;

              if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              float dyValue = getDy(batch, idyD, idyR, idyC, ch);
              int maxPosValue = ${d} -
                  int(getMaxPos(batch, idyD, idyR, idyC, ch));

              // Get the current value, check it against the value from the
              // position matrix.
              int curPosValue =
                  wD * ${l} * ${c} +
                  wR * ${c} + wC;
              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);

              dotProd += dyValue * mask;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function wnt(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s,{filterSize:a,strides:u,pad:l,dimRoundingMode:c}=n,p=[1,1,1],m=S.computePool3DInfo(i.shape,a,u,p,l,c),f=new Au(m,"max",!0),d=e.runWebGLProgram(f,[i],i.dtype),h=new FC(m),g=e.runWebGLProgram(h,[o,d],i.dtype);return e.disposeIntermediateTensorInfo(d),g}var c3={kernelName:Tp,backendName:"webgl",kernelFunc:wnt};function Cnt(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s,output:i}=t,a=s;Zs([s,i],"maxPoolGrad");let{filterSize:u,strides:l,pad:c,dimRoundingMode:p}=n,m=S.computePool2DInfo(a.shape,u,l,1,c,p),f=!0,d=new Qs(m,"max",f),h=e.runWebGLProgram(d,[a],a.dtype),g=new RC(m),x=e.runWebGLProgram(g,[o,h],a.dtype);return e.disposeIntermediateTensorInfo(h),x}var p3={kernelName:kp,backendName:"webgl",kernelFunc:Cnt};function m3(r,t,e,n){let o=new Qs(e,"max",!1),s=n.runWebGLProgram(o,[r],"float32");o=new Qs(e,"max",!0,!0,t);let i=n.runWebGLProgram(o,[r],"float32");return[s,i]}var f3={kernelName:Ep,backendName:"webgl",kernelFunc:({inputs:r,attrs:t,backend:e})=>{let{x:n}=r,{filterSize:o,strides:s,pad:i,includeBatchInIndex:a}=t,u=e;y.assert(n.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${n.shape.length}.`);let l=[1,1];y.assert(S.eitherStridesOrDilationsAreOne(s,l),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${l}'`);let c=S.computePool2DInfo(n.shape,o,s,l,i),[p,m]=m3(n,a,c,u);return[p,m]}};function d3(r,t,e,n){let o=y.sizeFromShape(t),i=y.sizeFromShape(r.shape)/o,a=st({inputs:{x:r},attrs:{shape:[i,o]},backend:n}),u=Gn(a,"float32","mean",n),l=st({inputs:{x:u},attrs:{shape:e},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(u),l}var h3={kernelName:cs,backendName:"webgl",kernelFunc:({inputs:r,attrs:t,backend:e})=>{let{x:n}=r,{keepDims:o,axis:s}=t,i=e,a=n.shape.length,u=y.parseAxisParam(s,n.shape),l=u,c=S.getAxesPermutation(l,a),p=c!=null,m=i.shouldExecuteOnCPU([n]),f=[],d=n;if(p){if(m){let C=i.texData.get(d.dataId).values,N=new Array(a);for(let $=0;$<N.length;$++)N[$]=n.shape[c[$]];let _=Vc(C,n.shape,n.dtype,c,N);d=i.makeTensorInfo(N,n.dtype);let A=i.texData.get(d.dataId);A.values=_}else d=_u(n,c,i);f.push(d),l=S.getInnerMostAxes(l.length,a)}S.assertAxesAreInnerMostDims("sum",l,a);let[h,g]=S.computeOutAndReduceShapes(d.shape,l),x=h;o&&(x=S.expandShapeToKeepDim(h,u));let b=d3(d,g,x,i);for(let w of f)i.disposeIntermediateTensorInfo(w);return b}};function Int(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=y.parseAxisParam(s,o.shape),l=u,c=S.getAxesPermutation(l,a),p=o;c!=null&&(p=Fe({inputs:{x:o},backend:e,attrs:{perm:c}}),l=S.getInnerMostAxes(l.length,o.shape.length)),S.assertAxesAreInnerMostDims("min",l,a);let[m,f]=S.computeOutAndReduceShapes(p.shape,l),d=y.sizeFromShape(f),h=st({inputs:{x:p},backend:e,attrs:{shape:[-1,d]}}),g=Gn(h,h.dtype,"min",e),x;if(i){let b=S.expandShapeToKeepDim(m,u);x=st({inputs:{x:g},backend:e,attrs:{shape:b}})}else x=st({inputs:{x:g},backend:e,attrs:{shape:m}});return e.disposeIntermediateTensorInfo(h),e.disposeIntermediateTensorInfo(g),c!=null&&e.disposeIntermediateTensorInfo(p),x}var g3={kernelName:ps,backendName:"webgl",kernelFunc:Int};var vnt=bd+`
  return min(a, b);
`,Snt=`
  vec4 result = vec4(min(a, b));
  bvec4 isNaNA = isnan(a);
  bvec4 isNaNB = isnan(b);
  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
  `+ji+`
  return result;
`,Nnt=le({opSnippet:vnt,packedOpSnippet:Snt,cpuKernelImpl:wL}),x3={kernelName:ms,backendName:"webgl",kernelFunc:Nnt};var OC=class{constructor(t,e,n){this.variableNames=["x"],this.outputShape=e.map((c,p)=>c[0]+t[p]+c[1]);let o=t.length,s=zt(o),i=e.map(c=>c[0]).join(","),a=e.map((c,p)=>c[0]+t[p]).join(","),u=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,o),l=n==="reflect"?0:1;if(o===1){this.userCode=`
        int start = ${i};
        int end = ${a};

        void main() {
          int outC = getOutputCoords();
          if (outC < start) {
            outC = start * 2 - outC - ${l};
          } else if(outC >= end) {
            outC = (end - 1) * 2 - outC + ${l};
          }
          setOutput(getX(outC - start));
        }
      `;return}this.userCode=`
      ${s} start = ${s}(${i});
      ${s} end = ${s}(${a});

      void main() {
        ${s} outC = getOutputCoords();
        for (int i = 0; i < ${o}; i++) {
          if (outC[i] < start[i]) {
            outC[i] = start[i] * 2 - outC[i] - ${l};
          } else if(outC[i] >= end[i]) {
            outC[i] = (end[i] - 1) * 2 - outC[i] + ${l};
          }
        }
        ${s} coords = outC - start;
        setOutput(getX(${u}));
      }
    `}};var PC=class{constructor(t,e,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.map((d,h)=>d[0]+t[h]+d[1]);let o=t.length,s=zt(o),i=e.map(d=>d[0]).join(","),a=e.map((d,h)=>d[0]+t[h]).join(","),u=Qe("rc",o),l=Qe("source",o),c=`${u[o-1]} < ${this.outputShape[o-1]}`,p=o===1?"source":`vec2(${l.slice(-2).join()})`,m=n==="reflect"?0:1,f="";if(o===1){let d=`
        ${s} source = rc;
        if (source < start) {
          source = start * 2 - source - ${m};
        } else if (source >= end) {
          source = (end - 1) * 2 - source + ${m};
        }
        source -= start;
      `;f=`
        ${s} rc = outputLoc;
        ${d}
        result[0] = getChannel(getX(${l.join()}), ${p});
        ${u[o-1]} += 1;
        if(${c}) {
          ${d}
          result[1] = getChannel(getX(${l.join()}), ${p});
        }
      `}else{let d=`
        ${s} source = rc;
        ${s} lt = ${s}(lessThan(source, start));
        ${s} gte = ${s}(greaterThanEqual(source, end));
        ${s} orig = 1 - (lt + gte);
        source = orig * source +
                lt * (start * 2 - source - ${m}) +
                gte * ((end - 1) * 2 - source + ${m});
        source -= start;
      `;f=`
        ${s} rc = outputLoc;
        ${d}
        result[0] = getChannel(getX(${l.join()}), ${p});
        ${u[o-1]} += 1;
        if(${c}) {
          ${d}
          result[1] = getChannel(getX(${l.join()}), ${p});
        }
        rc = outputLoc;
        ${u[o-2]} += 1;
        if(${u[o-2]} < ${this.outputShape[o-2]}) {
          ${d}
          result[2] = getChannel(getX(${l.join()}), ${p});
          ${u[o-1]} += 1;
          if(${c}) {
            ${d}
            result[3] = getChannel(getX(${l.join()}), ${p});
          }
        }
      `}this.userCode=`
      const ${s} start = ${s}(${i});
      const ${s} end = ${s}(${a});

      void main() {
        ${s} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${f}
        setOutput(result);
      }
    `}};var knt=({inputs:r,backend:t,attrs:e})=>{let{x:n}=r,{paddings:o,mode:s}=e,i=M().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new PC(n.shape,o,s):new OC(n.shape,o,s);return t.runWebGLProgram(i,[n],n.dtype)},y3={kernelName:fs,backendName:"webgl",kernelFunc:knt};var Tnt=`if (b == 0.0) return NAN;
  return mod(a, b);`,Ent=`
  vec4 result = mod(a, b);
  bvec4 isNaN = equal(b, vec4(0.0));
  `+ji+`
  return result;
`,_nt=le({opSnippet:Tnt,packedOpSnippet:Ent}),b3={kernelName:_a,backendName:"webgl",kernelFunc:_nt};var LC=class{constructor(t,e,n){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[t,n],this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];

        float r = random(seed);
        float cdf = 0.0;

        for (int i = 0; i < ${e-1}; i++) {
          cdf += getProbs(batch, i);

          if (r < cdf) {
            setOutput(float(i));
            return;
          }
        }

        // If no other event happened, last event happened.
        setOutput(float(${e-1}));
      }
    `}};var Ant=`
if (a == b) {
  return 1.0;
};
return a / b;`,$nt=`
  // vec4 one = vec4(equal(a, b));
  // return one + (vec4(1.0) - one) * a / b;
  vec4 result = a / b;
  if(a.x == b.x) {
    result.x = 1.;
  }
  if(a.y == b.y) {
    result.y = 1.;
  }
  if(a.z == b.z) {
    result.z = 1.;
  }
  if(a.w == b.w) {
    result.w = 1.;
  }

  return result;
`,yT=le({opSnippet:Ant,packedOpSnippet:$nt,checkOutOfBounds:!0}),w3={kernelName:Jo,backendName:"webgl",kernelFunc:yT};var C3="return a - b;",bT=le({opSnippet:C3,packedOpSnippet:C3,supportsComplex:!0,cpuKernelImpl:zL}),I3={kernelName:Rs,backendName:"webgl",kernelFunc:bT};function wT(r){let{inputs:t,backend:e,attrs:n}=r,{logits:o}=t,{dim:s}=n,i=y.parseAxisParam([s],o.shape),a=xT({inputs:{x:o},backend:e,attrs:{reductionIndices:i,keepDims:!1}}),u=S.expandShapeToKeepDim(a.shape,i),l=st({inputs:{x:a},backend:e,attrs:{shape:u}}),c=bT({inputs:{a:o,b:l},backend:e}),p=dT({inputs:{x:c},backend:e}),m=Wc({inputs:{x:p},backend:e,attrs:{axis:i,keepDims:!1}}),f=st({inputs:{x:m},backend:e,attrs:{shape:u}}),d=yT({inputs:{a:p,b:f},backend:e});return e.disposeIntermediateTensorInfo(a),e.disposeIntermediateTensorInfo(l),e.disposeIntermediateTensorInfo(c),e.disposeIntermediateTensorInfo(p),e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f),d}var v3={kernelName:$s,backendName:"webgl",kernelFunc:wT};function Dnt(r){let{inputs:t,backend:e,attrs:n}=r,{logits:o}=t,{numSamples:s,seed:i,normalized:a}=n,u=a?o:wT({inputs:{logits:o},backend:e,attrs:{dim:o.shape.length-1}}),l=u.shape[0],c=u.shape[1],p=new LC(l,c,s),m=[[i]],f=e.runWebGLProgram(p,[u],"int32",m);return a||e.disposeIntermediateTensorInfo(u),f}var S3={kernelName:_p,backendName:"webgl",kernelFunc:Dnt};var Rnt=pr+`
  return -x;
`,Fnt=`
  vec4 result = -x;
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`;function Ont(r){let{inputs:t,backend:e}=r,{x:n}=t;if(e.shouldExecuteOnCPU([n])){let s=e.texData.get(n.dataId),[i,a]=IL(s.values,n.shape,n.dtype);return e.makeTensorInfo(a,n.dtype,i)}let o;return M().getBool("WEBGL_PACK_UNARY_OPERATIONS")?o=new no(n.shape,Fnt):o=new tn(n.shape,Rnt),e.runWebGLProgram(o,[n],n.dtype)}var N3={kernelName:ui,backendName:"webgl",kernelFunc:Ont};var Pnt=Wr.nonMaxSuppressionV3Impl;function Lnt(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:e,attrs:n}=r,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:a,scoreThreshold:u}=n,l=e.readSync(o.dataId),c=e.readSync(s.dataId),{selectedIndices:p}=Pnt(l,c,i,a,u);return e.makeTensorInfo([p.length],"int32",new Int32Array(p))}var k3={kernelName:$a,backendName:"webgl",kernelFunc:Lnt};var Mnt=Wr.nonMaxSuppressionV4Impl;function znt(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:e,attrs:n}=r,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:a,scoreThreshold:u,padToMaxOutputSize:l}=n,c=e.readSync(o.dataId),p=e.readSync(s.dataId),{selectedIndices:m,validOutputs:f}=Mnt(c,p,i,a,u,l);return[e.makeTensorInfo([m.length],"int32",new Int32Array(m)),e.makeTensorInfo([],"int32",new Int32Array([f]))]}var T3={kernelName:Da,backendName:"webgl",kernelFunc:znt};var Bnt=Wr.nonMaxSuppressionV5Impl;function Vnt(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:e,attrs:n}=r,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:a,scoreThreshold:u,softNmsSigma:l}=n,c=e.readSync(o.dataId),p=e.readSync(s.dataId),m=i,f=a,d=u,h=l,{selectedIndices:g,selectedScores:x}=Bnt(c,p,m,f,d,h);return[e.makeTensorInfo([g.length],"int32",new Int32Array(g)),e.makeTensorInfo([x.length],"float32",new Float32Array(x))]}var E3={kernelName:Ra,backendName:"webgl",kernelFunc:Vnt};var MC=class{constructor(t,e,n,o){this.variableNames=["indices"],this.outputShape=[t,e],this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int index = round(getIndices(coords.x));
        setOutput(mix(float(${o}), float(${n}),
                      float(index == coords.y)));
      }
    `}};var Gnt=r=>{let{inputs:t,backend:e,attrs:n}=r,{indices:o}=t,{dtype:s,depth:i,onValue:a,offValue:u}=n,l=y.sizeFromShape(o.shape),c=new MC(l,i,a,u),p=st({inputs:{x:o},backend:e,attrs:{shape:[l]}}),m=e.runWebGLProgram(c,[p],s);e.disposeIntermediateTensorInfo(p);let f=[...o.shape,i],d=st({inputs:{x:m},backend:e,attrs:{shape:f}});return e.disposeIntermediateTensorInfo(m),d},_3={kernelName:hs,backendName:"webgl",kernelFunc:Gnt};function tg(r){let{inputs:t,backend:e}=r,{x:n}=t;if(n.dtype==="complex64"){let o=yl({inputs:{input:n},backend:e}),s=tg({inputs:{x:o},backend:e}),i=Hc({inputs:{input:n},backend:e}),a=tg({inputs:{x:i},backend:e}),u=Tn({inputs:{real:s,imag:a},backend:e});return e.disposeIntermediateTensorInfo(o),e.disposeIntermediateTensorInfo(s),e.disposeIntermediateTensorInfo(i),e.disposeIntermediateTensorInfo(a),u}else return bl({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:e})}var A3={kernelName:yi,backendName:"webgl",kernelFunc:tg};function $3(r){let{inputs:t,backend:e}=r,{x:n}=t;if(n.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(n.dtype==="complex64"){let o=yl({inputs:{input:n},backend:e}),s=$3({inputs:{x:o},backend:e}),i=Hc({inputs:{input:n},backend:e}),a=tg({inputs:{x:i},backend:e}),u=Tn({inputs:{real:s,imag:a},backend:e});return e.disposeIntermediateTensorInfo(o),e.disposeIntermediateTensorInfo(s),e.disposeIntermediateTensorInfo(i),e.disposeIntermediateTensorInfo(a),u}else return bl({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:e})}var D3={kernelName:ci,backendName:"webgl",kernelFunc:$3};function Wnt(r){let{inputs:t,backend:e,attrs:n}=r,{axis:o}=n;if(t.length===1)return IC({inputs:{input:t[0]},backend:e,attrs:{dim:o}});let s=t[0].shape,i=t[0].dtype;t.forEach(c=>{y.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),y.assert(i===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let a=[],u=t.map(c=>{let p=IC({inputs:{input:c},backend:e,attrs:{dim:o}});return a.push(p),p}),l=fT({inputs:u,backend:e,attrs:{axis:o}});return a.forEach(c=>e.disposeIntermediateTensorInfo(c)),l}var R3={kernelName:pi,backendName:"webgl",kernelFunc:Wnt};var zC=class{constructor(t,e,n){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=e.map((l,c)=>l[0]+t[c]+l[1]);let o=t.length,s=zt(o),i=e.map(l=>l[0]).join(","),a=e.map((l,c)=>l[0]+t[c]).join(","),u=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,o);if(o===1){this.userCode=`
        int start = ${i};
        int end = ${a};

        void main() {
          int outC = getOutputCoords();
          if (outC < start || outC >= end) {
            setOutput(value);
          } else {
            setOutput(getX(outC - start));
          }
        }
      `;return}this.userCode=`
      ${s} start = ${s}(${i});
      ${s} end = ${s}(${a});

      void main() {
        ${s} outC = getOutputCoords();
        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
          setOutput(value);
        } else {
          ${s} coords = outC - start;
          setOutput(getX(${u}));
        }
      }
    `}};var BC=class{constructor(t,e,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=e.map((h,g)=>h[0]+t[g]+h[1]);let o=t.length,s=zt(o),i=e.map(h=>h[0]).join(","),a=e.map((h,g)=>h[0]+t[g]).join(","),u=Qe("rc",o),l=Qe("source",o),c=`${u[o-1]} < ${this.outputShape[o-1]}`,p=o===1?"source":`vec2(${l.slice(-2).join()})`,m=[`${s} rc = outputLoc;`,`${u[o-1]} += 1;
       if(${c}) {
      `,o===1?"":`}
       rc = outputLoc;
       ${u[o-2]} += 1;
       if(${u[o-2]} < ${this.outputShape[o-2]}) {`,o===1?"":`  ${u[o-1]} += 1;
         if(${c}) {`],f=o===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",d="";for(let h=0,g=o===1?2:4;h<g;h++)d+=`
        ${m[h]}
        if (${f}) {
          result[${h}] = float(value);
        } else {
          ${s} source = rc - start;
          result[${h}] = getChannel(getX(${l.join()}), ${p});
        }
      `;d+=o===1?"} ":"}}",this.userCode=`
      const ${s} start = ${s}(${i});
      const ${s} end = ${s}(${a});

      void main() {
        ${s} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${d}
        setOutput(result);
      }
    `}};var CT=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{paddings:s,constantValue:i}=n;if(y.sizeFromShape(o.shape)===0){let l=s.map((c,p)=>c[0]+o.shape[p]+c[1]);return bl({backend:e,attrs:{shape:l,value:i,dtype:o.dtype}})}let a=M().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new BC(o.shape,s,i):new zC(o.shape,s,i),u=[[i]];return e.runWebGLProgram(a,[o],o.dtype,u)},F3={kernelName:gs,backendName:"webgl",kernelFunc:CT};var Unt=`
  if(a < 0.0 && floor(b) < b){
    return NAN;
  }
  if (b == 0.0) {
    return 1.0;
  }
  return (round(mod(b, 2.0)) != 1) ?
      pow(abs(a), b) : sign(a) * pow(abs(a), b);
`,Hnt=`
  // 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);
  vec4 result = multiplier * pow(abs(a), b);

  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS
  bvec4 isExpZero = equal(b, vec4(0.0));
  result.r = isExpZero.r ? 1.0 : result.r;
  result.g = isExpZero.g ? 1.0 : result.g;
  result.b = isExpZero.b ? 1.0 : result.b;
  result.a = isExpZero.a ? 1.0 : result.a;

  bvec4 isNaN1 = lessThan(a, vec4(0.0));
  bvec4 isNaN2 = lessThan(floor(b), b);
  bvec4 isNaN = bvec4(isNaN1.x && isNaN2.x, isNaN1.y && isNaN2.y, isNaN1.z && isNaN2.z, isNaN1.w && isNaN2.w);
  `+ji+`
  return result;
`,qnt=le({opSnippet:Unt,packedOpSnippet:Hnt}),O3={kernelName:xs,backendName:"webgl",kernelFunc:qnt};function Knt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=[],l=y.parseAxisParam(s,o.shape),c=l,p=S.getAxesPermutation(c,a),m=o;p!=null&&(m=Fe({inputs:{x:o},backend:e,attrs:{perm:p}}),c=S.getInnerMostAxes(c.length,a),u.push(m)),S.assertAxesAreInnerMostDims("prod",c,a);let f;if(e.shouldExecuteOnCPU([m])){let d=e.texData.get(m.dataId).values,{outVals:h,outShape:g,outDtype:x}=SL(m.shape,m.dtype,d,c);f=e.makeTensorInfo(g,x,h)}else{let[d,h]=S.computeOutAndReduceShapes(m.shape,c),g=y.sizeFromShape(h),x=st({inputs:{x:m},backend:e,attrs:{shape:[-1,g]}}),b=Gu(o.dtype),w=Gn(x,b,"prod",e);f=st({inputs:{x:w},backend:e,attrs:{shape:d}}),u.push(x),u.push(w)}if(i){u.push(f);let d=S.expandShapeToKeepDim(f.shape,l);f=st({inputs:{x:f},backend:e,attrs:{shape:d}})}return u.forEach(d=>e.disposeIntermediateTensorInfo(d)),f}var P3={kernelName:bs,backendName:"webgl",kernelFunc:Knt};function jnt(r){let{inputs:t,backend:e,attrs:n}=r,{paramsNestedSplits:o,paramsDenseValues:s,indices:i}=t,{outputRaggedRank:a}=n,u=o.map(x=>e.readSync(x.dataId)),l=o.map(x=>x.shape),c=e.readSync(s.dataId),p=e.readSync(i.dataId),[m,f,d]=NL(u,l,c,s.shape,s.dtype,p,i.shape,a),h=m.map(x=>e.makeTensorInfo([x.length],"int32",x)),g=e.makeTensorInfo(d,s.dtype,f);return h.concat([g])}var L3={kernelName:Ap,backendName:"webgl",kernelFunc:jnt};function Xnt(r){let{inputs:t,backend:e,attrs:n}=r,{shape:o,values:s,defaultValue:i,rowPartitionTensors:a}=t,{rowPartitionTypes:u}=n,l=e.readSync(o.dataId),c=e.readSync(s.dataId),p=e.readSync(i.dataId),m=a.map(g=>e.readSync(g.dataId)),f=a.map(g=>g.shape),[d,h]=kL(l,o.shape,c,s.shape,s.dtype,p,i.shape,m,f,u);return e.makeTensorInfo(d,s.dtype,h)}var M3={kernelName:$p,backendName:"webgl",kernelFunc:Xnt};var IT=r=>{let{backend:t,attrs:e}=r,{start:n,stop:o,step:s,dtype:i}=e,a=TL(n,o,s,i);return t.makeTensorInfo([a.length],i,a)},z3={kernelName:Rl,backendName:"webgl",kernelFunc:IT};var Ynt="return 1.0 / x;",Znt=Ct({opSnippet:Ynt}),B3={kernelName:Fa,backendName:"webgl",kernelFunc:Znt};var Jnt=pr+`
  return (x < 0.0) ? 0.0 : x;
`,Qnt=`
  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,tot=Ct({opSnippet:Jnt,packedOpSnippet:Qnt}),V3={kernelName:ws,backendName:"webgl",kernelFunc:tot};var eot=pr+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,rot=`
  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,not=Ct({opSnippet:eot,packedOpSnippet:rot}),G3={kernelName:vs,backendName:"webgl",kernelFunc:not};var VC=class{constructor(t,e,n,o,s){this.variableNames=["A"],this.outputShape=[];let[i,a,u,l]=t;this.outputShape=[i,e,n,l];let c=[o&&e>1?a-1:a,o&&n>1?u-1:u],p=[o&&e>1?e-1:e,o&&n>1?n-1:n],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]},
          ${c[1]/p[1]});
      const vec2 inputShapeRC = vec2(${a}.0, ${u}.0);

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        ivec2 yRC = coords.yz;

        // Fractional source index.
        vec2 sourceFracIndexRC = ${m};

        // Compute the four integer indices.
        ivec2 sourceFloorRC = ivec2(max(sourceFracIndexRC, vec2(0.0)));
        ivec2 sourceCeilRC = ivec2(
          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));

        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);
        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);
        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);
        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);

        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);

        float top = topLeft + (topRight - topLeft) * fracRC.y;
        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;
        float newValue = top + (bottom - top) * fracRC.x;

        setOutput(newValue);
      }
    `}};var GC=class{constructor(t,e,n,o,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[i,a,u,l]=t;this.outputShape=[i,e,n,l];let c=[o&&e>1?a-1:a,o&&n>1?u-1:u],p=[o&&e>1?e-1:e,o&&n>1?n-1:n],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]},
          ${c[1]/p[1]});
      const vec3 inputShapeRC = vec3(${a}.0, ${u}.0,
                                     ${u}.0);

      float getAValue(int b, int r, int c, int d) {
        return getChannel(getA(b, r, c, d), vec2(c, d));
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        // Calculate values for next column in yRC.z.
        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);

        // Fractional source index.
        vec3 sourceFracIndexRC = ${m};

        // Compute the four integer indices.
        ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0)));
        ivec3 sourceCeilRC = ivec3(
          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));

        // Should we calculate next column and row elements in 2x2 packed cell.
        bool hasNextCol = d < ${l-1};
        bool hasNextRow = coords.z < ${n-1};

        // In parallel, construct four corners for all four components in
        // packed 2x2 cell.
        vec4 topLeft = vec4(
          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),
          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);

        vec4 bottomLeft = vec4(
          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),
          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);

        vec4 topRight = vec4(
          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),
          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);

        vec4 bottomRight = vec4(
          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),
          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);

        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);

        vec4 top = mix(topLeft, topRight, fracRC.yyzz);
        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);
        vec4 newValue = mix(top, bottom, fracRC.x);

        setOutput(newValue);
      }
    `}};function oot(r){let{inputs:t,backend:e,attrs:n}=r,{images:o}=t,{alignCorners:s,halfPixelCenters:i,size:a}=n,[u,l]=a,c=M().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new GC(o.shape,u,l,s,i):new VC(o.shape,u,l,s,i);return e.runWebGLProgram(c,[o],"float32")}var W3={kernelName:Is,backendName:"webgl",kernelFunc:oot};var WC=class{constructor(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e;let[,o,s]=e,[,i,a]=t,u=[n&&i>1?o-1:o,n&&a>1?s-1:s],l=[n&&i>1?i-1:i,n&&a>1?a-1:a],c=u[0]/l[0],p=u[1]/l[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];
        int d = coords[3];
        int r = coords[1];
        int c = coords[2];

        float accumulator = 0.0;

        const float heightScale = float(${c});
        const float widthScale = float(${p});

        const float invHeightScale = float(${m});
        const float invWidthScale = float(${f});

        const int winHeight = int(${d});
        const int winWidth = int(${h});

        // Compute bounds for where in dy we will look
        float startRLerp = floor(float(r) * invHeightScale);
        int startDyR = int(startRLerp - float(winHeight / 2));

        float startCLerp = floor(float(c) * invWidthScale);
        int startDyC = int(startCLerp - float(winWidth / 2));

        // Loop over dy
        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
          int dyR = dyROffset + startDyR;

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ${i}) {
            continue;
          }

          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
            int dyC = dyCOffset + startDyC;

            // Guard against the window exceeding the bounds of dy
            if (dyC < 0 || dyC >= ${a}) {
              continue;
            }

            float dxR = float(dyR) * heightScale;
            int topDxRIndex = int(floor(dxR));
            int bottomDxRIndex = int(min(ceil(dxR), ${o-1}.0));
            float dxRLerp = dxR - float(topDxRIndex);
            float inverseDxRLerp = 1.0 - dxRLerp;

            float dxC = float(dyC) * widthScale;
            int leftDxCIndex = int(floor(dxC));
            int rightDxCIndex = int(min(ceil(dxC), ${s-1}.0));
            float dxCLerp = dxC - float(leftDxCIndex);
            float inverseDxCLerp = 1.0 - dxCLerp;

            if (r == topDxRIndex && c == leftDxCIndex) {
              // topLeft
              accumulator +=
                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;
            }

            if (r == topDxRIndex && c == rightDxCIndex) {
              // topRight
              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;
            }

            if (r == bottomDxRIndex && c == leftDxCIndex) {
              // bottomLeft
              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;
            }

            if (r == bottomDxRIndex && c == rightDxCIndex) {
              // bottomRight
              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;
            }
          }
        }
        // End loop over dy

        setOutput(accumulator);
      }
    `}};function sot(r){let{inputs:t,backend:e,attrs:n}=r,{images:o,dy:s}=t,{alignCorners:i}=n,a=new WC(s.shape,o.shape,i);return e.runWebGLProgram(a,[s],s.dtype)}var U3={kernelName:Fp,backendName:"webgl",kernelFunc:sot};var UC=class{constructor(t,e,n,o,s){this.variableNames=["A"],this.outputShape=[];let[i,a,u,l]=t;this.outputShape=[i,e,n,l];let c=[o&&e>1?a-1:a,o&&n>1?u-1:u],p=[o&&e>1?e-1:e,o&&n>1?n-1:n],m=o?"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]},
          ${c[1]/p[1]});
      const vec2 inputShapeRC = vec2(${a}.0, ${u}.0);

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        ivec2 yRC = coords.yz;

        // Fractional source index.
        vec2 sourceFracIndexRC = ${f};

        // Compute the coordinators of nearest neighbor point.
        ivec2 sourceNearestRC = ivec2(
          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${m})));
        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);

        setOutput(newValue);
      }
    `}};var HC=class{constructor(t,e,n,o,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[i,a,u,l]=t;this.outputShape=[i,e,n,l];let c=[o&&e>1?a-1:a,o&&n>1?u-1:u],p=[o&&e>1?e-1:e,o&&n>1?n-1:n],m=o?"0.5":"0.0",f;s?f="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":f="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec3 effectiveInputOverOutputRatioRC = vec3(
          ${c[0]/p[0]},
          ${c[1]/p[1]},
          ${c[1]/p[1]});
      const vec3 inputShapeRC = vec3(${a}.0, ${u}.0,
                                     ${u}.0);

      float getAValue(int b, int r, int c, int d) {
        return getChannel(getA(b, r, c, d), vec2(c, d));
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        // Calculate values for next column in yRC.z.
        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);

        // Fractional source index.
        vec3 sourceFracIndexRC = ${f};

        // Compute the coordinators of nearest neighbor point.
        ivec3 sourceNearestRC = ivec3(
          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${m})));

        // Should we calculate next column and row elements in 2x2 packed cell.
        bool hasNextCol = d < ${l-1};
        bool hasNextRow = coords.z < ${n-1};

        vec4 newValue = vec4(
          getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
          hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);

        setOutput(newValue);
      }
    `}};function iot(r){let{inputs:t,backend:e,attrs:n}=r,{images:o}=t,{alignCorners:s,halfPixelCenters:i,size:a}=n,[u,l]=a,c=M().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new HC(o.shape,u,l,s,i):new UC(o.shape,u,l,s,i);return e.runWebGLProgram(c,[o],o.dtype)}var H3={kernelName:Cs,backendName:"webgl",kernelFunc:iot};var qC=class{constructor(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e;let[,o,s]=e,[,i,a]=t,u=[n&&i>1?o-1:o,n&&a>1?s-1:s],l=[n&&i>1?i-1:i,n&&a>1?a-1:a],c=u[0]/l[0],p=u[1]/l[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];
        int d = coords[3];
        int r = coords[1];
        int c = coords[2];

        float accumulator = 0.0;

        const float heightScale = float(${c});
        const float widthScale = float(${p});

        const float invHeightScale = float(${m});
        const float invWidthScale = float(${f});

        const int winHeight = int(${d});
        const int winWidth = int(${h});

        // Compute bounds for where in dy we will look
        float startRLerp = floor(float(r) * invHeightScale);
        int startDyR = int(floor(startRLerp - float(winHeight / 2)));

        float startCLerp = floor(float(c) * invWidthScale);
        int startDyC = int(floor(startCLerp - float(winWidth / 2)));

        // Loop over dy
        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
          int dyR = dyROffset + startDyR;

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ${i}) {
            continue;
          }

          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
            int dyC = dyCOffset + startDyC;

            // Guard against the window exceeding the bounds of dy
            if (dyC < 0 || dyC >= ${a}) {
              continue;
            }

            float sourceFracRow =
              float(${u[0]}) *
                (float(dyR) / float(${l[0]}));

            float sourceFracCol =
                float(${u[1]}) *
                  (float(dyC) / float(${l[1]}));

            int sourceNearestRow = int(min(
                float(int(${o}) - 1),
                ${n} ? float(round(sourceFracRow)) :
                                  float(floor(sourceFracRow))));

            int sourceNearestCol = int(min(
                float(int(${s}) - 1),
                ${n} ? float(round(sourceFracCol)) :
                                  float(floor(sourceFracCol))));

            if (r == sourceNearestRow && c == sourceNearestCol) {
              accumulator += getDy(b, dyR, dyC, d);
            }
          }
        }
        // End loop over dy

        setOutput(accumulator);
      }
    `}};function aot(r){let{inputs:t,backend:e,attrs:n}=r,{images:o,dy:s}=t,{alignCorners:i}=n,a=new qC(s.shape,o.shape,i);return e.runWebGLProgram(a,[s],s.dtype)}var q3={kernelName:Rp,backendName:"webgl",kernelFunc:aot};var KC=class{constructor(t,e){this.variableNames=["x"];let n=t.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=t,n===1){this.userCode=`
        void main() {
          int coord = getOutputCoords();
          setOutput(getX(${t[0]} - coord - 1));
        }
      `;return}let o=a=>e.indexOf(a)!==-1&&t[a]!==1?`${t[a]} - coords[${a}] - 1`:`coords[${a}]`,s=t.map((a,u)=>o(u)).join(","),i=zt(n);this.userCode=`
      void main() {
        ${i} coords = getOutputCoords();
        setOutput(getX(${s}));
      }
    `}};var jC=class{constructor(t,e){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=t.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=t;let o=Qe("rc",n),s=`${o[n-1]} + 1 < ${this.outputShape[n-1]}`,i=`${o[n-2]} + 1 < ${this.outputShape[n-2]}`,a=zt(n);n===1?this.userCode=`
        void main(){
          int rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = getChannel(getX(${t[0]} - rc - 1),
            ${t[0]} - rc - 1);
          if(${s}){
              result.g = getChannel(getX(${t[0]} - (rc  + 1) - 1),
                ${t[0]} - (rc  + 1) - 1);
          }
          setOutput(result);
        }
      `:this.userCode=`
        void main() {
          ${a} rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = ${u(o.slice())};
          if(${s}){
            result.g = ${l(o.slice())};
          }
          if(${i}) {
            result.b = ${c(o.slice())};
            if(${s}) {
              result.a = ${p(o.slice())};
            }
          }
          setOutput(result);
        }
    `;function u(d){return m(d)}function l(d){return d[n-1]="("+d[n-1]+" + 1)",m(d)}function c(d){return d[n-2]="("+d[n-2]+" + 1)",m(d)}function p(d){return d[n-1]="("+d[n-1]+" + 1)",d[n-2]="("+d[n-2]+" + 1)",m(d)}function m(d){let h=t.map((b,w)=>f(w,d)),g=h.join(","),x=h.slice(-2).join(",");return`getChannel(getX(${g}), vec2(${x}))`}function f(d,h){return e.indexOf(d)!==-1&&t[d]!==1?`${t[d]} - ${h[d]} - 1`:`${h[d]}`}}};function lot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{dims:s}=n,i=o.shape.length,a=y.parseAxisParam(s,o.shape);if(i===0)return tr({inputs:{x:o},backend:e});let u=M().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new jC(o.shape,a):new KC(o.shape,a);return e.runWebGLProgram(u,[o],o.dtype)}var K3={kernelName:Ss,backendName:"webgl",kernelFunc:lot};var XC=class{constructor(t,e){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let n=t[1],o=t[2];this.outputShape=t;let s="";typeof e=="number"?s=`float outputValue = ${e.toFixed(2)};`:s=`
        vec3 fill = vec3(${e.join(",")});
        float outputValue = fill[coords[3]];`,this.userCode=`
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];
          int y = coords[1];
          float coordXFloat = (float(x) - params[0]) * params[3] -
            (float(y) - params[1]) * params[2];
          float coordYFloat = (float(x) - params[0]) * params[2] +
            (float(y) - params[1]) * params[3];
          int coordX = int(round(coordXFloat + params[0]));
          int coordY = int(round(coordYFloat + params[1]));
          ${s}
          if(coordX >= 0 && coordX < ${o} && coordY >= 0 && coordY < ${n}) {
            outputValue = getImage(coords[0], coordY, coordX, coords[3]);
          }
          setOutput(outputValue);
        }
    `}};var j3={kernelName:Ua,backendName:"webgl",kernelFunc:({inputs:r,attrs:t,backend:e})=>{let{image:n}=r,{radians:o,fillValue:s,center:i}=t,a=e,u=new XC(n.shape,s),[l,c]=S.getImageCenter(i,n.shape[1],n.shape[2]),p=[[l,c,Math.sin(o),Math.cos(o)]];return a.runWebGLProgram(u,[n],n.dtype,p)}};var uot=`
  // OpenGL ES does not support round function.
  // The algorithm is based on banker's rounding.
  float base = floor(x);
  if ((x - base) < 0.5) {
    return floor(x);
  } else if ((x - base) > 0.5) {
    return ceil(x);
  } else {
    if (mod(base, 2.0) == 0.0) {
      return base;
    } else {
      return base + 1.0;
    }
  }
`,cot=Ct({opSnippet:uot}),X3={kernelName:Ns,backendName:"webgl",kernelFunc:cot};var pot="return inversesqrt(x);",mot=Ct({opSnippet:pot,cpuKernelImpl:EL}),Y3={kernelName:ks,backendName:"webgl",kernelFunc:mot};var Td=class{constructor(t,e,n,o,s,i,a=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=i;let u=zt(s.length),l=zt(i.length),c="";n===1?c="i":n===2&&(c="i, j");let p=`getIndices(${c})`,m="";o===1?m="i":o===2&&(m="i, coords[1]");let f=`getUpdates(${m})`,d=e>1?"strides[j]":"strides";this.userCode=`
        ${u} strides = ${u}(${s});

        void main() {
          ${l} coords = getOutputCoords();
          float sum = 0.0;
          bool found = false;
          for (int i = 0; i < ${t}; i++) {
            int flattenedIndex = 0;
            for (int j = 0; j < ${e}; j++) {
              int index = round(${p});
              flattenedIndex += index * ${d};
            }
            if (flattenedIndex == coords[0]) {
              sum += ${f};
              found = true;
            }
          }
          setOutput(mix(getDefaultValue(), sum, float(found)));
        }
      `}};function fot(r){let{inputs:t,backend:e,attrs:n}=r,{indices:o,updates:s}=t,{shape:i}=n,{sliceRank:a,numUpdates:u,sliceSize:l,strides:c,outputSize:p}=S.calculateShapes(s,o,i),m=[p/l,l];if(p===0)return e.makeTensorInfo(i,o.dtype);let f=st({inputs:{x:o},backend:e,attrs:{shape:[u,a]}}),d=st({inputs:{x:s},backend:e,attrs:{shape:[u,l]}}),h=e.makeTensorInfo([],"float32",new Float32Array([0])),g=new Td(u,a,f.shape.length,d.shape.length,c,m),x=e.runWebGLProgram(g,[d,f,h],d.dtype),b=st({inputs:{x},backend:e,attrs:{shape:i}});return e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(d),e.disposeIntermediateTensorInfo(x),e.disposeIntermediateTensorInfo(h),b}var Z3={kernelName:Oa,backendName:"webgl",kernelFunc:fot};var YC=class{constructor(t,e,n,o){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[t,n];let s="while (left < right) {",i=`for (int i = 0; i < ${Math.ceil(Math.log2(e+1))}; ++i) { if (left >= right) break;`,a=M().getNumber("WEBGL_VERSION")===2?s:i,u=o==="left"?"<":"<=";this.userCode=`
       int findBound(int batch, float value) {
         int left = 0;
         int right = numInputs;
         int mid;
         ${a}
           mid = (left + right) / 2;
           if (getSortedSequence(batch, mid) ${u} value) {
             left = mid + 1;
           } else {
             right = mid;
           }
         }
         return right;
       }

       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int valueIndex = coords[1];

         float value = getValues(batch, valueIndex);

         setOutput(float(findBound(batch, value)));
       }
     `}};function dot(r){let{inputs:t,backend:e,attrs:n}=r,{sortedSequence:o,values:s}=t,{side:i}=n,a=new YC(o.shape[0],o.shape[1],s.shape[1],i),u=[[o.shape[1]]];return e.runWebGLProgram(a,[o,s],"int32",u)}var J3={kernelName:Op,backendName:"webgl",kernelFunc:dot};var ZC=class{constructor(t,e,n){this.variableNames=["c","a","b"],this.outputShape=e;let o,s;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)s="resRC",o="resRC";else{let a=["resRC.x","resRC.y","resRC.z","resRC.w"],u=[],l=[];for(let c=0;c<e.length;c++)l.push(`${a[c]}`),c<t&&u.push(`${a[c]}`);o=u.join(),s=l.join()}let i=zt(n);this.userCode=`
      void main() {
        ${i} resRC = getOutputCoords();
        float cVal = getC(${o});
        if (cVal >= 1.0) {
          setOutput(getA(${s}));
        } else {
          setOutput(getB(${s}));
        }
      }
    `}};function hot(r){let{inputs:t,backend:e}=r,{condition:n,t:o,e:s}=t,i=new ZC(n.shape.length,o.shape,o.shape.length);return e.runWebGLProgram(i,[n,o,s],or(o.dtype,s.dtype))}var Q3={kernelName:fi,backendName:"webgl",kernelFunc:hot};var got=`
  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
  // see: https://arxiv.org/abs/1706.02515
  float scaleAlpha = ${S.SELU_SCALEALPHA};
  float scale = ${S.SELU_SCALE};
  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,xot=Ct({opSnippet:got}),tB={kernelName:Pa,backendName:"webgl",kernelFunc:xot};var yot=Oo+`
  return 1.0 / (1.0 + exp(-1.0 * x));
`,bot=`
  vec4 result = 1.0 / (1.0 + exp(-1.0 * x));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,wot=Ct({opSnippet:yot,packedOpSnippet:bot,cpuKernelImpl:AL}),eB={kernelName:Es,backendName:"webgl",kernelFunc:wot};var Cot=`
  if (isnan(x)) { return 0.0; }
  return sign(x);
`,Iot=Ct({opSnippet:Cot}),rB={kernelName:Ma,backendName:"webgl",kernelFunc:Iot};var vot=Oo+`
  return sin(x);
`,Sot=Ct({opSnippet:vot}),nB={kernelName:Ts,backendName:"webgl",kernelFunc:Sot};var Not=`
  float e2x = exp(x);
  return (e2x - 1.0 / e2x) / 2.0;
`,kot=Ct({opSnippet:Not}),oB={kernelName:La,backendName:"webgl",kernelFunc:kot};var Tot=`
  float epsilon = 1.1920928955078125e-7;
  float threshold = log(epsilon) + 2.0;

  bool too_large = x > -threshold;
  bool too_small = x < threshold;

  float result;
  float exp_x = exp(x);

  if (too_large){
    result = x;
  }
  else if (too_small){
    result = exp_x;
  }
  else{
    result = log(exp_x + 1.0);
  }
  return result;
`,Eot=Ct({opSnippet:Tot}),sB={kernelName:za,backendName:"webgl",kernelFunc:Eot};var _ot=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockShape:s,paddings:i}=n;y.assert(o.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let a=s.reduce((x,b)=>x*b),u=[[0,0]];u.push(...i);for(let x=1+s.length;x<o.shape.length;++x)u.push([0,0]);let l=[],c=CT({inputs:{x:o},backend:e,attrs:{paddings:u,constantValue:0}}),p=S.getReshaped(c.shape,s,a,!1),m=S.getPermuted(p.length,s.length,!1),f=S.getReshapedPermuted(c.shape,s,a,!1),d=st({inputs:{x:c},backend:e,attrs:{shape:p}}),h=Fe({inputs:{x:d},backend:e,attrs:{perm:m}}),g=st({inputs:{x:h},backend:e,attrs:{shape:f}});return l.push(c),l.push(d),l.push(h),l.forEach(x=>e.disposeIntermediateTensorInfo(x)),g},iB={kernelName:hi,backendName:"webgl",kernelFunc:_ot};function Aot(r){let{inputs:t,backend:e}=r,{indices:n,values:o,denseShape:s,defaultValue:i}=t;if(s.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
         ${s.shape}`);if(n.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
         ${n.shape}`);if(o.shape.length!==1)throw new Error(`Values must be a vector, saw:
         ${o.shape}`);if(i.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
        ${i.shape}`);let a=e.readSync(n.dataId),u=e.readSync(o.dataId),l=e.readSync(s.dataId),c=e.readSync(i.dataId)[0],[p,m,f,d,h]=DL(a,n.shape,n.dtype,u,o.dtype,l,c);return[e.makeTensorInfo(m,n.dtype,p),e.makeTensorInfo([m[0]],o.dtype,f),e.makeTensorInfo([d.length],"bool",new Uint8Array(d.map(g=>Number(g)))),e.makeTensorInfo([h.length],n.dtype,new Int32Array(h))]}var aB={kernelName:Fl,backendName:"webgl",kernelFunc:Aot};function $ot(r){let{inputs:t,backend:e}=r,{inputIndices:n,inputShape:o,newShape:s}=t;if(n.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${n.shape}`);if(o.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${o.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let i=Array.from(e.readSync(o.dataId)),a=e.readSync(n.dataId),u=Array.from(e.readSync(s.dataId)),[l,c,p]=RL(a,n.shape,n.dtype,i,u);return[e.makeTensorInfo(c,n.dtype,l),e.makeTensorInfo([p.length],s.dtype,new Int32Array(p))]}var lB={kernelName:Ba,backendName:"webgl",kernelFunc:$ot};function Dot(r){let{inputs:t,backend:e}=r,{data:n,indices:o,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(o.shape.length!==1)throw new Error(`Indices should be a vector but received shape
              ${o.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
              ${s.shape}`);let i=e.readSync(n.dataId),a=e.readSync(o.dataId),u=e.readSync(s.dataId),[l,c]=Fw(i,n.shape,n.dtype,a,u,!0);return e.makeTensorInfo(c,n.dtype,l)}var uB={kernelName:Ol,backendName:"webgl",kernelFunc:Dot};function Rot(r){let{inputs:t,backend:e}=r,{data:n,indices:o,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(o.shape.length!==1)throw new Error(`Indices should be a vector but received shape
             ${o.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
             ${s.shape}`);let i=e.readSync(n.dataId),a=e.readSync(o.dataId),u=e.readSync(s.dataId),[l,c]=Fw(i,n.shape,n.dtype,a,u);return e.makeTensorInfo(c,n.dtype,l)}var cB={kernelName:Pl,backendName:"webgl",kernelFunc:Rot};function Fot(r){let{inputs:t,backend:e,attrs:n}=r,{sparseIndices:o,sparseValues:s,defaultValue:i}=t,{outputShape:a}=n,{sliceRank:u,numUpdates:l,sliceSize:c,strides:p,outputSize:m}=S.calculateShapes(s,o,a),f=!1;if(s.dtype==="string"){let x=e.bufferSync(o),b=e.bufferSync(s),w=y.decodeString(e.readSync(i.dataId)[0]),C=_L(x,b,a,m,c,l,u,p,w,f);return e.makeTensorInfo(a,C.dtype,C.values)}let d=new Td(l,u,o.shape.length,s.shape.length,p,[m,1],f),h=e.runWebGLProgram(d,[s,o,i],s.dtype),g=st({inputs:{x:h},backend:e,attrs:{shape:a}});return e.disposeIntermediateTensorInfo(h),g}var pB={kernelName:Pp,backendName:"webgl",kernelFunc:Fot};function Oot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{numOrSizeSplits:s,axis:i}=n,a=y.parseAxisParam(i,o.shape)[0],u=S.prepareSplitSize(o,s,a),l=o.shape.length,c=new Array(l).fill(0),p=o.shape.slice();return u.map(m=>{let f=[...p];f[a]=m;let d=ti({inputs:{x:o},backend:e,attrs:{begin:c,size:f}});return c[a]+=m,d})}var mB={kernelName:gi,backendName:"webgl",kernelFunc:Oot};var fB="return sqrt(x);",Pot=Ct({opSnippet:fB,packedOpSnippet:fB,cpuKernelImpl:FL}),dB={kernelName:_s,backendName:"webgl",kernelFunc:Pot};var Lot="return x * x;",Mot=Ct({opSnippet:Lot}),hB={kernelName:Ll,backendName:"webgl",kernelFunc:Mot};var gB="return (a - b) * (a - b);",zot=le({opSnippet:gB,packedOpSnippet:gB}),xB={kernelName:Ds,backendName:"webgl",kernelFunc:zot};function Bot({inputs:r,attrs:t,backend:e}){let{x:n}=r,o=pr+`
    return x > 0.0 ? 1.0 : float(${t.alpha});
  `,s=new tn(n.shape,o);return e.runWebGLProgram(s,[n],n.dtype)}var yB={kernelName:uo,backendName:"webgl",kernelFunc:Bot};var JC=class{constructor(t,e,n){this.variableNames=["x"],this.outputShape=n;let o=n.length,s=zt(n.length),i=zt(n.length),a="";if(o===1)a="coords * strides + begin";else{let u=0;a=n.map((l,c)=>(u++,n.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${u-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
      ${s} begin = ${s}(${t});
      ${s} strides = ${s}(${e});

      void main() {
        ${i} coords = getOutputCoords();
        setOutput(getX(${a}));
      }
    `}};function Vot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{begin:s,end:i,strides:a,beginMask:u,endMask:l,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:m}=n,{finalShapeSparse:f,finalShape:d,isIdentity:h,sliceDim0:g,isSimpleSlice:x,begin:b,end:w,strides:C}=Pe.sliceInfo(o.shape,s,i,a,u,l,c,p,m),N;if(h)N=st({inputs:{x:o},backend:e,attrs:{shape:d}});else if(g||x){y.assert(o.shape.length>=1,()=>`Input must have rank at least 1, got: ${o.shape.length}`);let A=Pe.computeOutShape(b,w,C),$=ti({inputs:{x:o},backend:e,attrs:{begin:b,size:A}});N=st({inputs:{x:$},backend:e,attrs:{shape:d}}),e.disposeIntermediateTensorInfo($)}else if(e.shouldExecuteOnCPU([o])){let $=e.readSync(o.dataId),F=wt(o.shape,o.dtype,$),P=OL(f,F,C,b);N=e.makeTensorInfo(d,o.dtype,P.values)}else{let $=new JC(b,C,f);N=e.runWebGLProgram($,[o],o.dtype)}let _=st({inputs:{x:N},backend:e,attrs:{shape:d}});return e.disposeIntermediateTensorInfo(N),_}var bB={kernelName:Va,backendName:"webgl",kernelFunc:Vot};function Got(r){let{inputs:t,backend:e,attrs:n}=r,{separator:o,nGramWidths:s,leftPad:i,rightPad:a,padWidth:u,preserveShortSequences:l}=n,{data:c,dataSplits:p}=t,m=e.readSync(c.dataId),f=e.readSync(p.dataId),[d,h]=PL(m,f,o,s,i,a,u,l);return[e.makeTensorInfo([d.length],"string",d),e.makeTensorInfo(p.shape,"int32",h)]}var wB={kernelName:Ml,backendName:"webgl",kernelFunc:Got};function Wot(r){let{inputs:t,backend:e,attrs:n}=r,{skipEmpty:o}=n,{input:s,delimiter:i}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(s.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${s.shape}`);if(i.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${i.shape}`);let a=e.readSync(s.dataId),u=e.readSync(i.dataId)[0],[l,c,p]=LL(a,u,o),m=c.length;return[e.makeTensorInfo([m,2],"int32",l),e.makeTensorInfo([m],"string",c),e.makeTensorInfo([2],"int32",new Int32Array(p))]}var CB={kernelName:zl,backendName:"webgl",kernelFunc:Wot};function Uot(r){let{inputs:t,backend:e,attrs:n}=r,{numBuckets:o}=n,{input:s}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(o<=0)throw new Error("Number of buckets must be at least 1");let i=e.readSync(s.dataId),a=ML(i,o);return e.makeTensorInfo(s.shape,"int32",a)}var IB={kernelName:Bl,backendName:"webgl",kernelFunc:Uot};var Hot="return tan(x);",qot=Ct({opSnippet:Hot}),vB={kernelName:Fs,backendName:"webgl",kernelFunc:qot};var Kot=`
  float e2x = exp(-2.0 * abs(x));
  return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,jot=Ct({opSnippet:Kot}),SB={kernelName:Os,backendName:"webgl",kernelFunc:jot};var QC=class{constructor(t,e){this.variableNames=["A"];let n=new Array(t.length);for(let i=0;i<n.length;i++)n[i]=t[i]*e[i];this.outputShape=n,this.rank=n.length;let o=zt(this.rank),s=Xot(t);this.userCode=`
      void main() {
        ${o} resRC = getOutputCoords();
        setOutput(getA(${s}));
      }
    `}};function Xot(r){let t=r.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${r[0]})`;let e=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],n=[];for(let o=0;o<r.length;o++)n.push(`imod(${e[o]}, ${r[o]})`);return n.join()}function vT(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{reps:s}=n;if(o.dtype==="string"||o.shape.length>5){let u=e.readSync(o.dataId),l=o.dtype==="string"?u.map(m=>y.decodeString(m)):u,c=wt(o.shape,o.dtype,l),p=BL(c,s);return e.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new QC(o.shape,s);return e.runWebGLProgram(i,[o],o.dtype)}var NB={kernelName:Zn,backendName:"webgl",kernelFunc:vT};var tI=class{constructor(t){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"negativeInf",type:"float"},{name:"dir",type:"int"},{name:"inc",type:"int"}],this.outputShape=t,this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int elemIdx = coords[1];

         // We compare elements pair-wise within a group of size 2 * inc.
         // The comparing rule for each group alternates between ascending
         // and descending. Within each group, we compare each pair at
         // positions i and i+inc. To decide whether an element at position i
         // is x0 or x1, we mod it by 2 * inc, if the result is smaller than
         // inc, it is in the first half of the group, we denote it as x0,
         // otherwise we denote it as x1.
         // For example, as shown in the Bitonic top K paper referenced above,
         // Figure5(a) shows that element[1] is in the
         // second half of the group when group size is 2, but it is in the
         // first half of the group when group size is 4.

         bool isFirstInPair = imod(elemIdx, 2 * inc) < inc;
         int i = isFirstInPair ? elemIdx : elemIdx - inc;

         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));
         int i1 = firstPass == 1 ? i + inc : int(getIndices(batch, i + inc));
         float x0 = i0 < n ? getX(batch, i0) : negativeInf;
         float x1 = i1 < n ? getX(batch, i1) : negativeInf;

         // Denotes which direction indices are in (ascending or descending).
         bool reverse = imod(elemIdx, 2 * dir) >= dir;
         bool isGreater = x0 > x1 || (x0 == x1 && i1 > i0);
         if (reverse == isGreater) { // Elements in opposite order of direction
           int iTemp = i0;
           i0 = i1;
           i1 = iTemp;
         }
         if (isFirstInPair) {
            setOutput(float(i0));
         } else {
            setOutput(float(i1));
         }
       }
     `}},eI=class{constructor(t){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"k",type:"int"}],this.outputShape=t,this.userCode=`
    void main() {
         // Takes max of indices (0, k), (1, k + 1), (2, k + 2) ...
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int elemIdx = coords[1];

         // The output size is half of the previous size.
         // If the previous sequence is | | | | _ _ _ _  | | | |  _ _ _ _ (k=4),
         // we only need to output the indices at positions |, the indices at
         // positions _ can be thrown away, see Figure5(b) After Phase 2
         // (Merge phase) in the Bitonic Top K paper referenced above.
         // For example, the paper shows we only need to output the orange bars.
         // The output sequence should look like this | | | | | | | |.
         // Because the sequence is halved, to map the output index back
         // to the previous sequence to find the corresponding value,
         // we need to double the index. When we double the index,
         // we basically interpolate a position, so 2i looks like
         // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k position
         // of each 2k positions by - elemIdx % k. E.g. for output at
         // index 4,5,6,7, we want to get the corresponding element at
         // original index 8,9,10,11, for output at index 8,9,10,11,
         // we want to get the corresponding element at original index
         // 16,17,18,19, so on and so forth.

         int i = elemIdx < k ? elemIdx : (elemIdx * 2 - imod(elemIdx, k));
         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));
         int i1 = firstPass == 1 ? i + k : int(getIndices(batch, i + k));

         float x0 = getX(batch, i0);
         float x1 = i1 < n ? getX(batch, i1) : x0;

         setOutput(x0 >= x1 ? float(i0) : float(i1));
       }
     `}};function Kc(r,t){t!==null&&r.disposeIntermediateTensorInfo(t)}function kB(r){let t=1;for(;t<r;)t*=2;return t}function Yot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{k:s,sorted:i}=n,a=M().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),u=M().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),l=o.shape,c=l[l.length-1];if(e.shouldExecuteOnCPU([o])||c<a||s>u){let P=e.readSync(o.dataId),[V,G]=VL(P,l,o.dtype,s,i);return[e.makeTensorInfo(V.shape,V.dtype,V.values),e.makeTensorInfo(G.shape,G.dtype,G.values)]}if(s===0)return l[l.length-1]=0,[e.makeTensorInfo(l,o.dtype,[]),e.makeTensorInfo(l,"int32",[])];if(c===1)return[o,bl({attrs:{shape:l,dtype:"int32",value:0},backend:e})];let p=e.texData.get(o.dataId),m=p!==null&&p.isPacked,f=m?e.unpackTensor(o):o,h=y.sizeFromShape(l)/c,g=st({inputs:{x:f},attrs:{shape:[h,c]},backend:e});m&&Kc(e,f);let x=kB(s),b=kB(c),w=null,C=()=>w===null?[g,g]:[g,w],N=(P,V,G)=>{let W=C(),q=new tI(G),j=[[c],[w===null?1:0],[Number.NEGATIVE_INFINITY],[P],[V]],Y=w;w=e.runWebGLProgram(q,W,"int32",j),Kc(e,Y)};for(let P=1;P<x;P*=2){let V=P*2;for(let G=P;G>=1;G/=2)N(V,G,[h,b])}for(let P=b;P>x;P/=2){let V=C(),G=new eI([h,P/2]),q=[[c],[w===null?1:0],[x]],H=w;w=e.runWebGLProgram(G,V,"int32",q),Kc(e,H);let j=x/2,Y=j*2;for(let Z=j;Z>=1;Z/=2)N(Y,Z,w.shape)}let _=w;w=ti({inputs:{x:w},backend:e,attrs:{begin:0,size:[h,s]}}),Kc(e,_);let A=gT({inputs:{x:g,indices:w},backend:e,attrs:{axis:1,batchDims:1}});Kc(e,g);let $=l.slice(0,-1);$.push(s),_=w,w=st({inputs:{x:w},attrs:{shape:$},backend:e}),Kc(e,_);let F=A;return A=st({inputs:{x:A},attrs:{shape:$},backend:e}),Kc(e,F),[A,w]}var TB={kernelName:Ga,backendName:"webgl",kernelFunc:Yot};var rI=class{constructor(t,e,n,o,s,i){this.variableNames=["Image","Transforms"],this.outputShape=i;let a=n==="nearest"?1:2,u;switch(o){case"constant":u=1;break;case"reflect":u=2;break;case"wrap":u=3;break;case"nearest":u=4;break;default:u=1;break}this.userCode=`
            float mapCoord(float outCoord, float len) {
              float inCoord = outCoord;
              if(${u} == 2) {
                if (inCoord < 0.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz2 = 2.0 * len;
                    if (inCoord < sz2) {
                      inCoord = sz2 * float(int(float(-inCoord / sz2))) +
                      inCoord;
                    }
                    inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;
                  }
                } else if (inCoord > len - 1.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz2 = 2.0 * len;
                    inCoord -= sz2 * float(int(float(inCoord / sz2)));
                    if (inCoord >= len) {
                      inCoord = sz2 - inCoord - 1.0;
                    }
                  }
                }
                return clamp(inCoord, 0.0, len - 1.0);
              } else if (${u} == 3) {
                if (inCoord < 0.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz = len - 1.0;
                    inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
                  }
                } else if (inCoord > len - 1.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz = len - 1.0;
                    inCoord -= len * float(int(float(inCoord / sz)));
                  }
                }
                return clamp(inCoord, 0.0, len - 1.0);
              } else if (${u} == 4) {
                return clamp(outCoord, 0.0, len - 1.0);
              } else {
                return outCoord;
              }
            }

            float readWithFillValue(int batch, int coordY, int coordX,
              int channel) {
              float outputValue;
              if (0 <= coordY && coordY < ${t} && 0 <= coordX && coordX < ${e}) {
                  outputValue = getImage(batch, coordY, coordX, channel);
              } else {
                outputValue = float(${s});
              }
              return outputValue;
            }

            void main() {
              ivec4 coords = getOutputCoords();
              float outputValue;
              int batch = coords[0];
              int x = coords[2];
              int y = coords[1];
              int channel = coords[3];
              float xf = float(x);
              float yf = float(y);
              float a1 = getTransforms(batch, 0);
              float a2 = getTransforms(batch, 1);
              float a3 = getTransforms(batch, 2);
              float b1 = getTransforms(batch, 3);
              float b2 = getTransforms(batch, 4);
              float b3 = getTransforms(batch, 5);
              float c1 = getTransforms(batch, 6);
              float c2 = getTransforms(batch, 7);
              float projection = c1 * xf + c2 * yf + 1.0;
              if (projection == 0.0) {
                outputValue = float(${s});
              } else {
                float inX = (a1 * xf + a2 * yf + a3) / projection;
                float inY = (b1 * xf + b2 * yf + b3) / projection;
                float mapX = mapCoord(inX, float(${e}));
                float mapY = mapCoord(inY, float(${t}));

                if (${a} == 1) {
                  int coordY = int(round(mapY));
                  int coordX = int(round(mapX));
                  outputValue = readWithFillValue(batch, coordY, coordX,
                    channel);
                } else {
                  float yFloor = floor(mapY);
                  float xFloor = floor(mapX);
                  float yCeil = yFloor + 1.0;
                  float xCeil = xFloor + 1.0;
                  float valueYFloor = (xCeil - mapX) *
                  readWithFillValue(batch, int(yFloor), int(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, int(yFloor), int(xCeil), channel);
                  float valueYCeil = (xCeil - mapX) *
                  readWithFillValue(batch, int(yCeil), int(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, int(yCeil), int(xCeil), channel);
                  outputValue = (yCeil - mapY) * valueYFloor +
                  (mapY - yFloor) * valueYCeil;
                }
              }
              setOutput(outputValue);
            }
        `}};function Zot(r){let{inputs:t,backend:e,attrs:n}=r,{image:o,transforms:s}=t,{interpolation:i,fillMode:a,fillValue:u,outputShape:l}=n,[c,p,m,f]=o.shape,[d,h]=l!=null?l:[p,m],g=[c,d,h,f],x=new rI(p,m,i,a,u,g);return e.runWebGLProgram(x,[o,s],"float32")}var EB={kernelName:Wa,backendName:"webgl",kernelFunc:Zot};function Jot(r){let{inputs:t,attrs:e,backend:n}=r,{axis:o}=e,{x:s}=t;Zs(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=n.readSync(s.dataId),{outputValues:a,outputShape:u,indices:l}=GL(i,o,s.shape,s.dtype);return[n.makeTensorInfo(u,s.dtype,a),n.makeTensorInfo([l.length],"int32",l)]}var _B={kernelName:Lp,backendName:"webgl",kernelFunc:Jot};function Qot(r){let{inputs:t,backend:e,attrs:n}=r,{value:o}=t,{axis:s}=n;s<0&&(s+=o.shape.length);let i=o,a=i.shape.length,u=o.shape[s],l=new Array(a-1),c=0;for(let h=0;h<a;h++)h!==s&&(l[c++]=i.shape[h]);let p=[],m=new Array(a).fill(0),f=i.shape.slice();f[s]=1;let d=new Array(u);for(let h=0;h<d.length;h++){m[s]=h;let g=ti({inputs:{x:i},backend:e,attrs:{begin:m,size:f}}),x=st({inputs:{x:g},backend:e,attrs:{shape:l}});d[h]=x,p.push(g)}return p.forEach(h=>e.disposeIntermediateTensorInfo(h)),d}var AB={kernelName:xi,backendName:"webgl",kernelFunc:Qot};var nI=class{constructor(t,e){this.variableNames=["x","segmentIds"];let n=t.windowSize,o=t.batchSize,s=t.inSize,i=t.numSegments,a=i*Math.ceil(s/n);this.outputShape=[o,a];let u="0.0",l="sumValue",c=Math.floor(n/4)*4,p=n%4,m=`
        sumValue += dot(values, segFilter);
    `,f="";s%n>0&&(f=`
        if (inIdx < 0 || inIdx >= ${s}) {
          return initializationValue;
        }
      `);let d="";s%n>0&&(d=`
        if (inIdx < 0 || inIdx >= ${s}) {
          return -1.0;
        }
      `),this.userCode=`
      const float initializationValue = ${u};

      float getValue(int batch, int inIdx) {
        ${f}
        return getX(batch, inIdx);
      }

      float getSegmentIdAtIndex(int inIdx) {
        ${d}
        return getSegmentIds(inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = int(floor(float(outIdx) / float(
          ${i})) * float(${n}));
        int currentSeg = int(mod(float(outIdx), float(${i})));

        float sumValue = 0.0;

        for (int i = 0; i < ${c}; i += 4) {
          int inIdx = inOffset + i;
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0
          );

          ${m}
        }

        int inIdx = inOffset + ${c};
        if (${p===1}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            initializationValue,
            initializationValue,
            initializationValue
          );

          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            0,
            0,
            0
          );

          ${m}
        } else if (${p===2}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            initializationValue,
            initializationValue
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
              0,
              0
          );

          ${m}
        } else if (${p===3}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            initializationValue
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
            0
          );

          ${m}
        }
        setOutput(${l});
      }
    `}};function tst(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,segmentIds:s}=t,{numSegments:i}=n,a=o.shape.length,u=[],l=0,c=S.getAxesPermutation([l],a),p=o;c!=null&&(p=Fe({inputs:{x:o},backend:e,attrs:{perm:c}}),u.push(p),l=S.getInnerMostAxes(1,a)[0]);let m=S.segment_util.computeOutShape(p.shape,l,i),f=y.sizeFromShape([p.shape[l]]),d=st({inputs:{x:p},backend:e,attrs:{shape:[-1,f]}});u.push(d);let h=Gu(o.dtype),g=(C,N,_,A,$)=>{let F=C.shape[0],P=C.shape[1],V=S.segment_util.segOpComputeOptimalWindowSize(P,$),G={windowSize:V,inSize:P,batchSize:F,numSegments:$},W=new nI(G,N),q=e.compileAndRun(W,[C,_],A);if(u.push(q),q.shape[1]===$)return q;let H=IT({backend:e,attrs:{start:0,stop:$,step:1,dtype:"float32"}}),j=vT({inputs:{x:H},backend:e,attrs:{reps:[P/V]}});return u.push(H),u.push(j),g(q,N,j,A,$)},x=g(d,"unsortedSegmentSum",s,h,i),b=st({inputs:{x},backend:e,attrs:{shape:m}}),w=b;if(c!=null){u.push(b);let C=S.getUndoAxesPermutation(c);w=Fe({inputs:{x:w},backend:e,attrs:{perm:C}})}return u.forEach(C=>e.disposeIntermediateTensorInfo(C)),w}var $B={kernelName:Vl,backendName:"webgl",kernelFunc:tst};var est=[xM,bM,wM,CM,vM,SM,NM,kM,_M,AM,$M,DM,RM,FM,OM,PM,LM,MM,zM,BM,VM,WM,UM,HM,XM,ZM,JM,aM,tz,rz,nz,oz,sz,iz,az,lz,uz,cz,pz,dz,hz,gz,xz,yz,bz,wz,Cz,Iz,vz,Sz,Nz,kz,Tz,Ez,_z,$z,Dz,Rz,Fz,Pz,Lz,Mz,zz,Bz,Vz,Gz,Wz,Uz,iM,Hz,ez,qz,Kz,jz,lM,Xz,Yz,Zz,Jz,Qz,t3,e3,r3,n3,o3,i3,a3,l3,u3,c3,p3,f3,h3,g3,x3,y3,b3,S3,pM,N3,k3,T3,E3,qM,_3,D3,R3,F3,O3,uM,P3,L3,M3,z3,KM,w3,B3,V3,G3,fM,W3,U3,H3,q3,K3,j3,X3,Y3,Z3,J3,Q3,tB,eB,rB,nB,oB,GM,v3,sB,iB,aB,lB,uB,cB,pB,mB,dB,hB,xB,yB,bB,wB,CB,IB,I3,hM,vB,SB,NB,TB,EB,gM,_B,AB,$B,A3];for(let r of est)Pu(r);var Ht;(function(r){r[r.float32=0]="float32",r[r.int32=1]="int32",r[r.bool=2]="bool",r[r.string=3]="string",r[r.complex64=4]="complex64"})(Ht||(Ht={}));var $u;(function(r){r[r.linear=0]="linear",r[r.relu=1]="relu",r[r.relu6=2]="relu6",r[r.prelu=3]="prelu",r[r.leakyrelu=4]="leakyrelu",r[r.sigmoid=5]="sigmoid",r[r.elu=6]="elu"})($u||($u={}));var DB;function rst(r){DB=r.wasm.cwrap(bi,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function nst(r){let{inputs:t,backend:e,attrs:n}=r,{a:o,b:s,bias:i,preluActivationWeights:a}=t;if(o.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:u,transposeB:l,activation:c,leakyreluAlpha:p}=n,m=e.dataIdMap.get(o.dataId).id,f=e.dataIdMap.get(s.dataId).id,d=0;if(i!=null){let $=e.dataIdMap.get(i.dataId);if($.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${$.shape.length}.`);d=$.id}let h=a==null?0:e.dataIdMap.get(a.dataId).id,g=$u[c];if(g==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let x=u?o.shape[2]:o.shape[1],b=l?s.shape[1]:s.shape[2],w=zr.assertAndGetBroadcastShape(o.shape.slice(0,-2),s.shape.slice(0,-2)),C=e.makeOutput([...w,x,b],o.dtype),N=e.dataIdMap.get(C.dataId).id,_=new Uint8Array(new Int32Array(o.shape).buffer),A=new Uint8Array(new Int32Array(s.shape).buffer);return DB(m,_,o.shape.length,f,A,s.shape.length,u,l,g,d,h,p||0,N),C}var RB={kernelName:bi,backendName:"wasm",setupFunc:rst,kernelFunc:nst};function se(r,t){let e;function n(s){e=s.wasm.cwrap(r,null,["number","number","number"])}function o(s){let{backend:i,inputs:{x:a}}=s,u=i.dataIdMap.get(a.dataId).id,l=i.makeOutput(a.shape,t||a.dtype),c=i.dataIdMap.get(l.dataId).id;return y.sizeFromShape(l.shape)===0||e(u,Ht[a.dtype],c),l}return{kernelName:r,backendName:"wasm",setupFunc:n,kernelFunc:o}}var FB=se(oi);function ue(r,t,e){let n;function o(i){n=i.wasm.cwrap(r,null,["number","array","number","number","array","number","number","number"])}function s(i){let{backend:a,inputs:u}=i,{a:l,b:c}=u,p=a.dataIdMap.get(l.dataId).id,m=a.dataIdMap.get(c.dataId).id,f=e!=null?e:l.dtype,d=S.assertAndGetBroadcastShape(l.shape,c.shape),h=a.makeOutput(d,f);if(y.sizeFromShape(d)===0)return h;let g=new Uint8Array(new Int32Array(l.shape).buffer),x=new Uint8Array(new Int32Array(c.shape).buffer),b=a.dataIdMap.get(h.dataId).id;return(()=>n(p,g,l.shape.length,m,x,c.shape.length,Ht[l.dtype],b))(),h}return{kernelName:r,backendName:"wasm",setupFunc:o,kernelFunc:s}}var ost=!0,OB=ue(Yn,ost);var PB;function sst(r){PB=r.wasm.cwrap(Vo,null,["array","number","number","number"])}function ist(r){let{inputs:t,backend:e}=r,n=e.makeOutput(t[0].shape,t[0].dtype);if(y.sizeFromShape(n.shape)===0)return n;let o=t.map(a=>e.dataIdMap.get(a.dataId).id),s=new Uint8Array(new Int32Array(o).buffer),i=e.dataIdMap.get(n.dataId).id;return PB(s,o.length,Ht[n.dtype],i),n}var LB={kernelName:Vo,backendName:"wasm",setupFunc:sst,kernelFunc:ist};function jc(r){let{inputs:{x:t},backend:e}=r,n=e.makeOutput(t.shape,t.dtype),o=e.typedArrayFromHeap(t);return e.typedArrayFromHeap(n).set(o),n}var MB={kernelName:lo,backendName:"wasm",kernelFunc:jc};var zB;function ast(r){zB=r.wasm.cwrap(Jn,null,["number","array","number","number","number","array","number"])}function so(r){let{inputs:t,backend:e,attrs:n}=r,[o,s]=ust(t.x.shape,n.perm),i=!0;for(let d=0;d<s.length;d++)s[d]!==d&&(i=!1);let a=lst(t.x.shape,n.perm),u={dataId:t.x.dataId,shape:o,dtype:t.x.dtype};if(i){let d=jc({inputs:t,backend:e});return d.shape=a,d}let l=e.makeOutput(a,u.dtype),c=e.dataIdMap.get(u.dataId).id,p=e.dataIdMap.get(l.dataId).id,m=new Uint8Array(new Int32Array(s).buffer),f=new Uint8Array(new Int32Array(u.shape).buffer);return zB(c,f,u.shape.length,Ht[u.dtype],p,m,s.length),l}function lst(r,t){let e=new Array(r.length);for(let n=0;n<e.length;n++)e[n]=r[t[n]];return e}function ust(r,t){let e=[],n=[];for(let o=0;o<r.length;++o)r[o]!==1&&e.push(r[o]),r[t[o]]!==1&&n.push(t[o]);for(let o=0;o<n.length;++o){let s=-1;for(let i=0;i<n.length;++i)n[i]>=o&&(s===-1||n[s]>n[i])&&(s=i);n[s]=o}return[e,n]}var BB={kernelName:Jn,backendName:"wasm",kernelFunc:so,setupFunc:ast};function yn(r,t,e){let n=r.shape,o=r.shape.length,s=y.parseAxisParam(t,n),i=s,a=S.getAxesPermutation(i,o),u=null,l=!1;if(a!=null){let c=new Array(o);for(let f=0;f<c.length;f++)c[f]=n[a[f]];i=S.getInnerMostAxes(i.length,o),u=so({inputs:{x:r},attrs:{perm:a},backend:e});let p=e.dataIdMap.get(r.dataId).id;e.dataIdMap.get(u.dataId).id!==p&&(l=!0)}return{transposed:u,originalAxes:s,axes:i,inputWasTransposed:l}}var VB;function cst(r){VB=r.wasm.cwrap(oa,null,["number, number, number"])}function pst(r){let{backend:t,inputs:e,attrs:n}=r,{axis:o,keepDims:s}=n,{x:i}=e,u=t.dataIdMap.get(i.dataId).id,l=i,{transposed:c,axes:p,originalAxes:m,inputWasTransposed:f}=yn(i,o,t);if(f){let w=t.dataIdMap.get(c.dataId).id;l=c,u=w}let 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Tst(r){let{inputs:t,attrs:e,backend:n}=r,{x:o,filter:s}=t,i=n.dataIdMap.get(o.dataId).id,a=n.dataIdMap.get(s.dataId).id,{strides:u,dilations:l,pad:c,dimRoundingMode:p,dataFormat:m}=e,f=S.convertConv2DDataFormat(m),d=S.computeConv2DInfo(o.shape,s.shape,u,l,c,p,!1,f),h=d.filterHeight,g=d.filterWidth,x=d.padInfo.top,b=d.padInfo.right,w=d.padInfo.bottom,C=d.padInfo.left,N=d.dilationHeight,_=d.dilationWidth,A=d.strideHeight,$=d.strideWidth,F=d.inChannels,P=d.outChannels,V=d.padInfo.type==="SAME"?1:0;if(d.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${d.dataFormat}'. 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_st(r){let{backend:t,inputs:e,attrs:n}=r,{dy:o,filter:s}=e,{strides:i,pad:a,dataFormat:u,dimRoundingMode:l,inputShape:c}=n,p=1,m=S.convertConv2DDataFormat(u),f=S.computeConv2DInfo(c,s.shape,i,p,a,l,!1,m),{batchSize:d,filterHeight:h,filterWidth:g,inChannels:x,inHeight:b,inWidth:w,outChannels:C,outHeight:N,outWidth:_,strideHeight:A,strideWidth:$}=f,F=h-1-f.padInfo.top,P=g-1-f.padInfo.left,V=f.dataFormat==="channelsLast",G=y.computeStrides(f.inShape),W=y.computeStrides(o.shape),[q,H,j]=y.computeStrides(s.shape),Y=G[0],Z=V?G[1]:G[2],et=V?G[2]:1,rt=V?1:G[1],ot=W[0],at=V?W[1]:W[2],nt=V?W[2]:1,it=V?1:W[1],dt=t.makeOutput(f.inShape,"float32"),ht=t.dataIdMap.get(dt.dataId).id,bt=t.dataIdMap.get(o.dataId).id,Tt=t.dataIdMap.get(s.dataId).id;return aV(bt,Tt,d,h,g,b,w,x,N,_,C,A,$,F,P,q,H,j,Y,Z,et,rt,ot,at,nt,it,ht),dt}var lV={kernelName:Ko,backendName:"wasm",setupFunc:Est,kernelFunc:_st};var uV=se(jo);var cV=se(Xo);var NT;(function(r){r[r.bilinear=0]="bilinear",r[r.nearest=1]="nearest"})(NT||(NT={}));var pV;function Ast(r){pV=r.wasm.cwrap(ma,null,["number","number","number","number","array","number","number","number","number","number"])}function $st(r){let{backend:t,inputs:e,attrs:n}=r,{method:o,extrapolationValue:s,cropSize:i}=n,{image:a,boxes:u,boxInd:l}=e,c=u.shape[0],[p,m]=i,f=[c,p,m,a.shape[3]],d=t.dataIdMap.get(a.dataId),h;a.dtype!=="float32"&&(h=ei({backend:t,inputs:{x:a},attrs:{dtype:"float32"}}),d=t.dataIdMap.get(h.dataId));let g=d.id,x=t.dataIdMap.get(u.dataId).id,b=t.dataIdMap.get(l.dataId).id,w=t.makeOutput(f,"float32"),C=t.dataIdMap.get(w.dataId).id,N=new Uint8Array(new Int32Array(a.shape).buffer);return pV(g,x,b,c,N,p,m,NT[o],s,C),h!=null&&t.disposeData(h.dataId),w}var mV={kernelName:ma,backendName:"wasm",setupFunc:Ast,kernelFunc:$st};var fV;function Dst(r){fV=r.wasm.cwrap(pa,null,["number","number","number","number","number","number"])}function 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GPGPUContext,ya as GatherNd,li as GatherV2,$h as GraphModel,ba as Greater,os as GreaterEqual,Dy as History,Ip as IFFT,lo as Identity,vp as Imag,ye as InputSpec,wa as IsFinite,Ca as IsInf,Ia as IsNan,Mo as KernelBackend,$l as LRN,Np as LRNGrad,gh as LayerVariable,Mn as LayersModel,ss as LeakyRelu,va as Less,Sa as LessEqual,Sp as LinSpace,is as Log,Na as Log1p,l1 as LogSoftmax,ka as LogicalAnd,Ta as LogicalNot,Ea as LogicalOr,a1 as LogicalXor,rlt as LowerBound,Eu as MathBackendWebGL,as as Max,us as MaxPool,Dl as MaxPool3D,Tp as MaxPool3DGrad,kp as MaxPoolGrad,Ep as MaxPoolWithArgmax,ls as Maximum,cs as Mean,ps as Min,ms as Minimum,fs as MirrorPad,_a as Mod,fu as MomentumOptimizer,_p as Multinomial,ds as Multiply,ui as Neg,$a as NonMaxSuppressionV3,Da as NonMaxSuppressionV4,Ra as NonMaxSuppressionV5,Aa as NotEqual,IS as OP_SCOPE_SUFFIX,hs as OneHot,ci as OnesLike,Gr as Optimizer,Vs as OptimizerConstructors,pi as Pack,gs as PadV2,nlt as Pool,xs as Pow,ys as Prelu,bs as Prod,du as 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depthwiseConv2d,_Z as deregisterOp,Hl as device_util,zE as diag,Nx as dilation2d,ept as disableDeprecationWarnings,St as dispose,rpt as disposeVariables,pt as div,kx as divNoNan,Tx as dot,n0 as dropout,BE as einsum,Ri as elu,tpt as enableDebugMode,Qct as enableProdMode,o0 as enclosingPowerOfTwo,ho as engine,M as env,Ar as equal,Ex as erf,_x as euclideanNorm,er as exp,gr as expandDims,Ax as expm1,Yu as eye,su as fft,go as fill,lpt as findBackend,upt as findBackendFactory,Fi as floor,Xp as floorDiv,sM as forceHalfFloat,au as fused,Oi as gather,Qj as gatherND,Qg as gather_util,ipt as getBackend,oS as getGradient,jd as getKernel,Fg as getKernelsForBackend,zat as getThreadsCount,eT as gpgpu_util,aK as grad,lK as grads,He as greater,Fn as greaterEqual,Za as ifft,Kl as imag,lu as image,r6 as inTopKAsync,W$ as initializers,$0 as input,Er as io,gm as irfft,$x as isFinite,Dx as isInf,Rx as isNaN,De as keep,Wr as kernel_impls,CD as layers,Zl as leakyRelu,nm as less,On as lessEqual,i0 as linalg,WE as linspace,I7 as loadGraphModel,v7 as loadGraphModelSync,O8 as loadLayersModel,Fx as localResponseNormalization,Ir as log,Jl as log1p,Lx as logSigmoid,om as logSoftmax,sm as logSumExp,Dr as logicalAnd,Ql as logicalNot,im as logicalOr,Mx as logicalXor,rX as losses,UE as lowerBound,Lt as matMul,fE as math,Br as max,tu as maxPool,Bx as maxPool3d,HE as maxPoolWithArgmax,In as maximum,Se as mean,nh as memory,qE as meshgrid,ID as metrics,Xu as min,Pi as minimum,Vx as mirrorPad,Gx as mod,R8 as model,vD as models,Zu as moments,qj as movingAverage,R as mul,KE as multiRNNCell,jE as multinomial,Ut as neg,ph as nextFrame,Ya as norm,zs as notEqual,ki as oneHot,lr as ones,xr as onesLike,k as op,XE as outerProduct,un as pad,YE as pad1d,ZE as pad2d,JE as pad3d,QE as pad4d,Wx as pool,an as pow,ru as prelu,Kg as print,Ux as prod,npt as profile,t_ as raggedGather,e_ as raggedTensorToTensor,r_ as rand,b_ as randomGamma,tc as randomNormal,w_ as randomStandardNormal,Li as randomUniform,nu as range,spt as ready,Xa as real,Xx as reciprocal,jp as registerBackend,P8 as registerCallbackConstructor,c1 as registerGradient,Pu as registerKernel,EZ as registerOp,SD as regularizers,Rr as relu,am as relu6,apt as removeBackend,D as reshape,ur as reverse,C_ as reverse1d,I_ as reverse2d,v_ as reverse3d,S_ as reverse4d,iu as rfft,lm as round,um as rsqrt,mt as scalar,jj as scatterND,oh as scatter_util,ah as searchSorted,cm as selu,pm as separableConv2d,F8 as sequential,Q as serialization,G4 as setBackend,cpt as setPlatform,Mat as setThreadsCount,Pat as setWasmPath,Lat as setWasmPaths,hk as setWebGLContext,N_ as setdiff1dAsync,Xr as sigmoid,Yx as sign,eX as signal,mm as sin,fm as sinh,Dt as slice,dm as slice1d,uh as slice2d,hm as slice3d,ec as slice4d,Pe as slice_util,ou as softmax,Ms as softplus,eu as spaceToBatchND,nX as sparse,Zj as sparseToDense,tX as spectral,cr as split,ve as sqrt,Mt as square,xm as squaredDifference,Pn as squeeze,rr as stack,yo as step,Zx as stridedSlice,oX as string,ct as sub,ft as sum,Gu as sumOutType,Jx as tan,_i as tanh,wr as tensor,Le as tensor1d,Bs as tensor2d,Zg as tensor3d,k_ as tensor4d,T_ as tensor5d,E_ as tensor6d,fo as tensor_util,AE as test_util,B as tidy,$r as tile,opt as time,Qx as topk,ic as train,Ot as transpose,ym as truncatedNormal,ty as unique,clt as unregisterGradient,ult as unregisterKernel,bm as unsortedSegmentSum,vr as unstack,or as upcastType,__ as upperBound,y as util,uK as valueAndGrad,cK as valueAndGrads,ey as variable,Ox as variableGrads,Yat as version,nR as version_converter,$E as version_core,Wm as version_layers,Bat as version_wasm,oM as version_webgl,oTe as webgl,cd as webgl_util,_e as where,ny as whereAsync,Ne as zeros,It as zerosLike};