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21aea707e6
lapd-face-search/assets/index-CjUl3rHt.js
Kyle McDonald 21aea707e6 Updates
2025-06-20 16:03:27 -07:00

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Buffer shape=${this.shape}`;throw new Error(a)}t++}let r=e[e.length-1];for(let n=0;n<e.length-1;++n)r+=this.strides[n]*e[n];return this.values[r]}locToIndex(e){if(this.rank===0)return 0;if(this.rank===1)return e[0];let t=e[e.length-1];for(let r=0;r<e.length-1;++r)t+=this.strides[r]*e[r];return t}indexToLoc(e){if(this.rank===0)return[];if(this.rank===1)return[e];let t=new Array(this.shape.length);for(let r=0;r<t.length-1;++r)t[r]=Math.floor(e/this.strides[r]),e-=t[r]*this.strides[r];return t[t.length-1]=e,t}get rank(){return this.shape.length}toTensor(){return Dn().makeTensor(this.values,this.shape,this.dtype)}},Dn=null,fl=null;function SD(e){Dn=e}function ND(e){fl=e}var ze=class{constructor(e,t,r,n){this.kept=!1,this.isDisposedInternal=!1,this.shape=e.slice(),this.dtype=t||"float32",this.size=nt(e),this.strides=ql(e),this.dataId=r,this.id=n,this.rankType=this.rank<5?this.rank.toString():"higher"}get rank(){return this.shape.length}async buffer(){let e=await this.data();return fl.buffer(this.shape,this.dtype,e)}bufferSync(){return fl.buffer(this.shape,this.dtype,this.dataSync())}async array(){let e=await this.data();return wl(this.shape,e,this.dtype==="complex64")}arraySync(){return wl(this.shape,this.dataSync(),this.dtype==="complex64")}async data(){this.throwIfDisposed();let e=Dn().read(this.dataId);if(this.dtype==="string"){let t=await e;try{return t.map(r=>bc(r))}catch{throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}}return e}dataToGPU(e){return this.throwIfDisposed(),Dn().readToGPU(this.dataId,e)}dataSync(){this.throwIfDisposed();let e=Dn().readSync(this.dataId);if(this.dtype==="string")try{return e.map(t=>bc(t))}catch{throw new Error("Failed to decode the string bytes into utf-8. 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Reusing existing backend factory.`),!1):(this.registryFactory[t]={factory:r,priority:n},!0)}async setBackend(t){if(this.registryFactory[t]==null)throw new Error(`Backend name '${t}' not found in registry`);if(this.backendName=t,this.registry[t]==null){this.backendInstance=null;let{success:r,asyncInit:n}=this.initializeBackend(t);if(!(n?await r:r))return!1}return this.backendInstance=this.registry[t],this.setupRegisteredKernels(),this.profiler=new yD(this.backendInstance),!0}setupRegisteredKernels(){yc(this.backendName).forEach(t=>{t.setupFunc!=null&&t.setupFunc(this.backendInstance)})}disposeRegisteredKernels(t){yc(t).forEach(r=>{r.disposeFunc!=null&&r.disposeFunc(this.registry[t])})}initializeBackend(t){let r=this.registryFactory[t];if(r==null)throw new Error(`Cannot initialize backend ${t}, no registration found.`);try{let n=r.factory();if(n&&!(n instanceof pd)&&typeof n.then=="function"){let a=++this.pendingBackendInitId,s=n.then(i=>a<this.pendingBackendInitId?!1:(this.registry[t]=i,this.pendingBackendInit=null,!0)).catch(i=>(a<this.pendingBackendInitId||(this.pendingBackendInit=null,es(`Initialization of backend ${t} failed`),es(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 es(`Initialization of backend ${t} failed`),es(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(t){if(!(t in this.registryFactory))throw new Error(`${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,r)=>this.registryFactory[r].priority-this.registryFactory[t].priority)}initializeBackendsAndReturnBest(){let t=this.getSortedBackends();for(let r=0;r<t.length;r++){let n=t[r],{success:a,asyncInit:s}=this.initializeBackend(n);if(s||a)return{name:n,asyncInit:s}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(t,r){let n=this.state.tensorInfo.get(r),a=n.backend,s=this.readSync(r),i=a.refCount(r);a.disposeData(r,!0),n.backend=t,t.move(r,s,n.shape,n.dtype,i),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(t,r){let n=null;if(r==null){if(typeof t!="function")throw new Error("Please provide a function to tidy()");r=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 r!="function")throw new 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a=this.backend.numDataIds(),s=0;n.forEach(l=>{s+=l.dtype==="complex64"?3:1});let i=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],o=a-r-s-i;if(o>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${o} data ids) after running '${t}'`)}runKernelFunc(t){let r,n=[],a=this.isTapeOn(),s=this.state.numBytes,i=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let o;this.backendName==null&&this.backend;let l,p=Dm(t)?t.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(Dm(t)){let{kernelName:f,inputs:m,attrs:g}=t;this.backendName==null&&this.backend;let y=Kp(f,this.backendName);A(y!=null,()=>`Cannot find registered kernel '${f}' for backend '${this.backendName}'`),o=()=>{let b=this.backend.numDataIds();l=y.kernelFunc({inputs:m,attrs:g,backend:this.backend});let x=Array.isArray(l)?l:[l];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(f,b,x);let v=x.map(w=>w.rank!=null?w:this.makeTensorFromTensorInfo(w));if(a){let w=this.getTensorsForGradient(f,m,v);n=this.saveTensorsForBackwardMode(w)}return v}}else{let{forwardFunc:f}=t,m=g=>{a&&(n=g.map(y=>this.keep(this.clone(y))))};o=()=>{let g=this.backend.numDataIds();l=this.tidy(()=>f(this.backend,m));let y=Array.isArray(l)?l:[l];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(p,g,y),y}}let{inputs:u,attrs:d}=t,h=Dm(t)?null:t.backwardsFunc,c;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?r=o():(c=this.profiler.profileKernel(p,u,()=>o()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(c),r=c.outputs)}),a&&this.addTapeNode(p,u,r,h,n,d),this.state.profiling&&this.state.activeProfile.kernels.push({name:p,bytesAdded:this.state.numBytes-s,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-i,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(f=>u[f]!=null?u[f].shape:null),outputShapes:r.map(f=>f.shape),kernelTimeMs:c.timeMs,extraInfo:c.extraInfo}),Array.isArray(l)?r:r[0]}saveTensorsForBackwardMode(t){return t.map(r=>this.keep(this.clone(r)))}getTensorsForGradient(t,r,n){let a=rg(t);if(a!=null){let s=a.inputsToSave||[],i=a.outputsToSave||[],o;a.saveAllInputs?(A(Array.isArray(r),()=>"saveAllInputs is true, expected inputs to be an array."),o=Object.keys(r).map(p=>r[p])):o=s.map(p=>r[p]);let 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this.state.registeredVariables[s.name]=s,this.incRef(s,this.backend),s}trackTensor(t,r){this.state.numTensors++,t.dtype==="string"&&this.state.numStringTensors++;let n=0;t.dtype!=="complex64"&&t.dtype!=="string"&&(n=t.size*fc(t.dtype)),this.state.numBytes+=n,this.state.tensorInfo.has(t.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(t.dataId,{backend:r||this.backend,dtype:t.dtype,shape:t.shape,bytes:n})),t instanceof di||this.track(t)}incRef(t,r){this.trackTensor(t,r),this.backend.incRef(t.dataId)}removeDataId(t,r){this.state.tensorInfo.has(t)&&this.state.tensorInfo.get(t).backend===r&&(this.state.tensorInfo.delete(t),this.state.numDataBuffers--)}disposeTensor(t){if(!this.state.tensorInfo.has(t.dataId))return;let r=this.state.tensorInfo.get(t.dataId);if(this.state.numTensors--,t.dtype==="string"&&(this.state.numStringTensors--,this.state.numBytes-=r.bytes),t.dtype!=="complex64"&&t.dtype!=="string"){let n=t.size*fc(t.dtype);this.state.numBytes-=n}r.backend.disposeData(t.dataId)&&this.removeDataId(t.dataId,r.backend)}disposeVariables(){for(let t in this.state.registeredVariables){let r=this.state.registeredVariables[t];this.disposeVariable(r)}}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 r=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(a=>a.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-r,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let a of this.state.activeProfile.kernels)a.kernelTimeMs=await a.kernelTimeMs,a.extraInfo=await a.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(t,r,n,a,s,i){let o={id:this.state.nextTapeNodeId++,kernelName:t,inputs:r,outputs:n,saved:s},l=rg(t);l!=null&&(a=l.gradFunc),a!=null&&(o.gradient=p=>(p=p.map((u,d)=>{if(u==null){let h=n[d],c=Zc(h.size,h.dtype);return this.makeTensor(c,h.shape,h.dtype)}return u}),a(p.length>1?p:p[0],s,i))),this.state.activeTape.push(o)}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 r={track:[],name:"unnamed scope",id:this.state.nextScopeId++};t&&(r.name=t),this.state.scopeStack.push(r),this.state.activeScope=r}endScope(t){let r=Ay(t),n=new Set(r.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 a=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],r.forEach(s=>{!s.kept&&s.scopeId===a.id&&this.track(s)})}gradients(t,r,n,a=!1){if(A(r.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));A(s instanceof ze,()=>"The result y returned by f() must be a tensor.");let i=vD(this.state.activeTape,r,s);if(!a&&i.length===0&&r.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. 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t=!1;this.accumulatedGrads=e.map(r=>({originalName:r.name,variable:r.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}},Hb=class extends Pa{static get className(){return"Adam"}constructor(e,t,r,n=null){super(),this.learningRate=e,this.beta1=t,this.beta2=r,this.epsilon=n,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],W(()=>{this.accBeta1=we(t).variable(),this.accBeta2=we(r).variable()}),n==null&&(this.epsilon=O.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(r=>r.name):Object.keys(e);W(()=>{let r=de(1,this.accBeta1),n=de(1,this.accBeta2);t.forEach((a,s)=>{let 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Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}},qf=class extends Pa{static get className(){return"SGD"}constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,r)=>{let n=Array.isArray(e)?e[r].tensor:e[t];if(n==null)return;let a=O.registeredVariables[t];W(()=>{let s=J(z(this.c,n),a);a.assign(s)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Pt(we(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer does 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t=[],r,n=e.slice(0,this.inputs.length),a=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),s=[];for(let l=0;l<this.inputs.length;++l)s.push({key:this.inputs[l],value:n[l]});let i=new vl(s),o=$p(this.outputs,i);for(let l=0;l<this.lossFunctions.length;++l){let p=this.lossFunctions[l],u=kt(p(a[l],o[l]));l===0?r=u:r=J(r,u),t.push(r)}for(let l=0;l<this.metricsTensors.length;++l){let p=this.metricsTensors[l][0],u=this.metricsTensors[l][1],d=kt(p(a[u],o[u]));t.push(d)}return t})}async fit(e,t,r={}){if(this.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");this.isTraining=!0;let n,a,s,i,o,l,p,u,d;try{let h=r.batchSize==null?32:r.batchSize;Wm(h);let c=await this.standardizeUserData(e,t,r.sampleWeight,r.classWeight,!1,h);n=c[0],a=c[1],d=c[2];let f=!1,m;if(r.validationData!=null&&r.validationData.length>0){if(f=!0,r.validationData.length===2)o=r.validationData[0],l=r.validationData[1];else throw r.validationData.length===3?new 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a=or.getSaveHandlers(e);if(a.length===0)throw new V(`Cannot find any save handlers for URL '${e}'`);if(a.length>1)throw new V(`Found more than one (${a.length}) save handlers for URL '${e}'`);e=a[0]}if(e.save==null)throw new V("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let r=await or.encodeWeights(this.getNamedWeights(t)),n={modelTopology:this.toJSON(null,!1),format:jG,generatedBy:`TensorFlow.js tfjs-layers v${wx}`,convertedBy:null};if(t!=null&&t.includeOptimizer&&this.optimizer!=null){n.trainingConfig=this.getTrainingConfig();let a="optimizer",{data:s,specs:i}=await or.encodeWeights(await this.optimizer.getWeights(),a);r.specs.push(...i),r.data=or.concatenateArrayBuffers([r.data,s])}return 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if(this.dilationRate.length!==2)throw new V(`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 V(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(t){if(ea("kernelSize"in t,"required key 'kernelSize' not in config"),typeof t.kernelSize!="number"&&!tx(t.kernelSize,"number",1,3))throw new V(`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:vs(this.activation),useBias:this.useBias,biasInitializer:St(this.biasInitializer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),biasConstraint:Ut(this.biasConstraint)},r=super.getConfig();return Object.assign(t,r),t}},om=class o2 extends s2{constructor(t,r){super(t,r),this.kernel=null,o2.verifyArgs(r),this.filters=r.filters,Zt(this.filters,"filters"),this.kernelInitializer=xt(r.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Vt(r.kernelConstraint),this.kernelRegularizer=vt(r.kernelRegularizer)}build(t){t=Xe(t);let r=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[r]==null)throw new V(`The channel dimension of the input should be defined. Found ${t[r]}`);let n=t[r],a=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",a,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:{[r]:n}}],this.built=!0}call(t,r){return W(()=>{t=Te(t);let n,a=this.bias==null?null:this.bias.read(),s=uN(this.activation.getClassName());if(s!=null&&this.rank===2)n=q0(t,this.kernel.read(),a,this.strides,this.padding,this.dataFormat,this.dilationRate,s);else{if(this.rank===1)n=rH(t,this.kernel.read(),a,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=q0(t,this.kernel.read(),a,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=nH(t,this.kernel.read(),a,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Be("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(t){t=Xe(t);let r=[],n=this.dataFormat==="channelsLast"?t.slice(1,t.length-1):t.slice(2);for(let s=0;s<n.length;++s){let i=Ln(n[s],this.kernelSize[s],this.padding,this.strides[s],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[s]);r.push(i)}let a=[t[0]];return this.dataFormat==="channelsLast"?(a=a.concat(r),a.push(this.filters)):(a.push(this.filters),a=a.concat(r)),a}getConfig(){let t={filters:this.filters,kernelInitializer:St(this.kernelInitializer),kernelRegularizer:dt(this.kernelRegularizer),kernelConstraint:Ut(this.kernelConstraint)},r=super.getConfig();return Object.assign(t,r),t}static verifyArgs(t){if(!("filters"in t)||typeof t.filters!="number"||t.filters<1)throw new V(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(t.filters)}`)}},lm=class l2 extends om{constructor(t){super(2,t),l2.verifyArgs(t)}getConfig(){let t=super.getConfig();return delete t.rank,t}static verifyArgs(t){if(typeof t.kernelSize!="number"&&!tx(t.kernelSize,"number",1,2))throw new V(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(t.kernelSize)}.`)}};lm.className="Conv2D";ne.registerClass(lm);var um=class u2 extends om{constructor(t){super(3,t),u2.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 V(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(t.kernelSize)}.`)}};um.className="Conv3D";ne.registerClass(um);var Ax=class extends lm{constructor(e){if(super(e),this.inputSpec=[new Rt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new V(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=Xe(e),e.length!==4)throw new V("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V("The channel dimension of the inputs should be defined. Found `None`.");let r=e[t],n=this.kernelSize.concat([this.filters,r]);this.kernel=this.addWeight("kernel",n,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Rt({ndim:4,axes:{[t]:r}})],this.built=!0}call(e,t){return W(()=>{let r=Te(e);if(r.shape.length!==4)throw new V(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${r.shape.length}`);let n=r.shape,a=n[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=n[s],l=n[i],p=this.kernelSize[0],u=this.kernelSize[1],d=this.strides[0],h=this.strides[1],c=ta(o,d,p,this.padding),f=ta(l,h,u,this.padding),m=[a,c,f,this.filters];this.dataFormat!=="channelsLast"&&(r=Oe(r,[0,2,3,1]));let g=bf(r,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(g=Oe(g,[0,3,1,2])),this.bias!=null&&(g=qn(g,this.bias.read(),this.dataFormat)),this.activation!=null&&(g=this.activation.apply(g)),g})}computeOutputShape(e){e=Xe(e);let t=e.slice(),r,n,a;this.dataFormat==="channelsFirst"?(r=1,n=2,a=3):(r=3,n=1,a=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[r]=this.filters,t[n]=ta(t[n],o,s,this.padding),t[a]=ta(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};Ax.className="Conv2DTranspose";ne.registerClass(Ax);var Fx=class extends um{constructor(e){if(super(e),this.inputSpec=[new Rt({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new V(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=Xe(e),e.length!==5)throw new V("Input should have rank 5; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V("The channel dimension of the inputs should be defined. Found `None`.");let r=e[t],n=this.kernelSize.concat([this.filters,r]);this.kernel=this.addWeight("kernel",n,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Rt({ndim:5,axes:{[t]:r}})],this.built=!0}call(e,t){return W(()=>{let r=Te(e);if(r.shape.length!==5)throw new V(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${r.shape.length}`);let n=r.shape,a=n[0],s,i,o;this.dataFormat==="channelsFirst"?(o=2,s=3,i=4):(o=1,s=2,i=3);let l=n[o],p=n[s],u=n[i],d=this.kernelSize[0],h=this.kernelSize[1],c=this.kernelSize[2],f=this.strides[0],m=this.strides[1],g=this.strides[2],y=ta(l,f,d,this.padding),b=ta(p,m,h,this.padding),x=ta(u,g,c,this.padding),v=[a,y,b,x,this.filters];this.dataFormat!=="channelsLast"&&(r=Oe(r,[0,2,3,4,1]));let w=sb(r,this.kernel.read(),v,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(w=Oe(w,[0,4,1,2,3])),this.bias!==null&&(w=qn(w,this.bias.read(),this.dataFormat)),this.activation!==null&&(w=this.activation.apply(w)),w})}computeOutputShape(e){e=Xe(e);let t=e.slice(),r,n,a,s;this.dataFormat==="channelsFirst"?(r=1,n=2,a=3,s=4):(r=4,n=1,a=2,s=3);let i=this.kernelSize[0],o=this.kernelSize[1],l=this.kernelSize[2],p=this.strides[0],u=this.strides[1],d=this.strides[2];return t[r]=this.filters,t[n]=ta(t[n],p,i,this.padding),t[a]=ta(t[a],u,o,this.padding),t[s]=ta(t[s],d,l,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};Fx.className="Conv3DTranspose";ne.registerClass(Fx);var p2=class extends om{constructor(e,t){if(super(e,t),this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new V("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new V("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(t.padding!=null&&t.padding!=="same"&&t.padding!=="valid")throw new V(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=xt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=vt(t.depthwiseRegularizer),this.depthwiseConstraint=Vt(t.depthwiseConstraint),this.pointwiseInitializer=xt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=vt(t.pointwiseRegularizer),this.pointwiseConstraint=Vt(t.pointwiseConstraint)}build(e){if(e=Xe(e),e.length<this.rank+2)throw new V(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(e)}`);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null||e[t]<0)throw new V(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let r=e[t],n=this.kernelSize.concat([r,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(r*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",n,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Rt({ndim:this.rank+2,axes:{[t]:r}})],this.built=!0}call(e,t){return W(()=>{e=Te(e);let r;if(this.rank===1)throw new Be("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=Oe(e,[0,2,3,1])),r=tp(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(r=qn(r,this.bias.read(),this.dataFormat)),this.activation!=null&&(r=this.activation.apply(r)),this.dataFormat==="channelsFirst"&&(r=Oe(r,[0,3,1,2])),r})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=St(this.depthwiseInitializer),e.pointwiseInitializer=St(this.pointwiseInitializer),e.depthwiseRegularizer=dt(this.depthwiseRegularizer),e.pointwiseRegularizer=dt(this.pointwiseRegularizer),e.depthwiseConstraint=Ut(this.depthwiseConstraint),e.pointwiseConstraint=Ut(this.pointwiseConstraint),e}};p2.className="SeparableConv";var Rx=class extends p2{constructor(e){super(2,e)}};Rx.className="SeparableConv2D";ne.registerClass(Rx);var Dx=class d2 extends om{constructor(t){super(1,t),d2.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"&&!tx(t.kernelSize,"number",1,1))throw new V(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(t.kernelSize)}.`)}};Dx.className="Conv1D";ne.registerClass(Dx);var Mx=class extends We{constructor(e){super(e),typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return this.dataFormat==="channelsFirst"?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}call(e,t){return W(()=>{if(e=Te(e),this.dataFormat==="channelsLast"){let r=Dh(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Dh(r,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let r=Dh(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Dh(r,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Mx.className="Cropping2D";ne.registerClass(Mx);var Ox=class extends We{constructor(e){super(e),this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,dV(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],r=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,r]}else{let t=e[1]==null?null:this.size[0]*e[1],r=e[2]==null?null:this.size[1]*e[2];return[e[0],t,r,e[3]]}}call(e,t){return W(()=>{let r=Te(e),n=r.shape;if(this.dataFormat==="channelsFirst"){r=Oe(r,[0,2,3,1]);let a=this.size[0]*n[2],s=this.size[1]*n[3],i=this.interpolation==="nearest"?sn.resizeNearestNeighbor(r,[a,s]):sn.resizeBilinear(r,[a,s]);return Oe(i,[0,3,1,2])}else{let a=this.size[0]*n[1],s=this.size[1]*n[2];return this.interpolation==="nearest"?sn.resizeNearestNeighbor(r,[a,s]):sn.resizeBilinear(r,[a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat,interpolation:this.interpolation},t=super.getConfig();return Object.assign(e,t),e}};Ox.className="UpSampling2D";ne.registerClass(Ox);function aH(e,t,r=[1,1],n="valid",a,s){return W(()=>{a==null&&(a=Wn()),Ct(a);let i=$x(e,a);if(e.rank!==4)throw new V(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new V(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=Zo(i,t,r,n==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=Oe(i,[0,3,1,2])),i})}var Lx=class extends s2{constructor(e){super(2,e),this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=xt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Vt(e.depthwiseConstraint),this.depthwiseRegularizer=vt(e.depthwiseRegularizer)}build(e){if(e=Xe(e),e.length<4)throw new V(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new V(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let r=e[t],n=[this.kernelSize[0],this.kernelSize[1],r,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",n,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[r*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return W(()=>{e=Te(e);let r=aH(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(r=qn(r,this.bias.read(),this.dataFormat)),this.activation!=null&&(r=this.activation.apply(r)),r})}computeOutputShape(e){e=Xe(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],r=this.dataFormat==="channelsFirst"?e[3]:e[2],n=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Ln(t,this.kernelSize[0],this.padding,this.strides[0]),s=Ln(r,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],n,a,s]:[e[0],a,s,n]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=St(this.depthwiseInitializer),e.depthwiseRegularizer=dt(this.depthwiseRegularizer),e.depthwiseConstraint=Ut(this.depthwiseRegularizer),e}};Lx.className="DepthwiseConv2D";ne.registerClass(Lx);function h2(e,t,r,n){if(Array.isArray(e)){if(t!=null||r!=null)throw new V("When inputs is an array, neither initialState or constants should be provided");n!=null&&(r=e.slice(e.length-n,e.length),e=e.slice(0,e.length-n)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),r=a(r),{inputs:e,initialState:t,constants:r}}function c2(e,t,r,n=!1,a,s,i=!1,o=!1){return W(()=>{let l=t.shape.length;if(l<3)throw new V(`Input should be at least 3D, but is ${l}D.`);let p=[1,0].concat(Bn(2,l));t=Oe(t,p),s!=null,i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=se(se(a,"bool"),"float32"),a.rank===l-1&&(a=Xt(a,-1)),a=Oe(a,p)),n&&(t=mn(t,0),a!=null&&(a=mn(a,0)));let u=[],d,h=r,c=t.shape[0],f=Tt(t),m;a!=null&&(m=Tt(a));for(let y=0;y<c;++y){let b=f[y],x=W(()=>e(b,h));if(a==null)d=x[0],h=x[1];else{let v=W(()=>{let w=m[y],N=de(Zr(w),w),T=J(z(x[0],w),z(h[0],N)),E=h.map(($,R)=>J(z(x[1][R],w),z($,N)));return{output:T,newStates:E}});d=v.output,h=v.newStates}o&&u.push(d)}let g;return o&&(g=Mt(u,1)),[d,g,h]})}var Ba=class f2 extends We{constructor(t){super(t);let r;if(t.cell==null)throw new V("cell property is missing for the constructor of RNN.");if(Array.isArray(t.cell)?r=new hm({cells:t.cell}):r=t.cell,r.stateSize==null)throw new V("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=r,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 Rt({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 Bn(0,t).map(r=>null)}else return this.states_}setStates(t){this.states_=t}computeOutputShape(t){Ng(t)&&(t=t[0]),t=t;let r=this.cell.stateSize;Array.isArray(r)||(r=[r]);let n=r[0],a;if(this.returnSequences?a=[t[0],t[1],n]:a=[t[0],n],this.returnState){let s=[];for(let i of r)s.push([t[0],i]);return[a].concat(s)}else return a}computeMask(t,r){return W(()=>{Array.isArray(r)&&(r=r[0]);let n=this.returnSequences?r:null;if(this.returnState){let a=this.states.map(s=>null);return[n].concat(a)}else return n})}get states(){if(this.states_==null){let t=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,r=[];for(let n=0;n<t;++n)r.push(null);return r}else return this.states_}set states(t){this.states_=t}build(t){if(this.numConstants!=null)throw new Be("Constants support is not implemented in RNN yet.");Ng(t)&&(t=t[0]),t=t;let r=this.stateful?t[0]:null,n=t.slice(2);this.inputSpec[0]=new Rt({shape:[r,null,...n]});let a=[t[0]].concat(t.slice(2));this.cell.build(a);let s;if(Array.isArray(this.cell.stateSize)?s=this.cell.stateSize:s=[this.cell.stateSize],this.stateSpec!=null){if(!k.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),s))throw new V(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=s.map(i=>new Rt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(t,r=!1){W(()=>{if(!this.stateful)throw new Ya("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new V("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(a=>It([n,a])):this.states_=[It([n,this.cell.stateSize])];else if(t==null)Ce(this.states_),this.keptStates!=null&&(Ce(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(a=>It([n,a])):this.states_[0]=It([n,this.cell.stateSize]);else{if(Array.isArray(t)||(t=[t]),t.length!==this.states_.length)throw new V(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${t.length} state value(s). Input received: ${t}`);r===!0?this.keptStates.push(this.states_.slice()):Ce(this.states_);for(let a=0;a<this.states_.length;++a){let s=t[a],i=Array.isArray(this.cell.stateSize)?this.cell.stateSize[a]:this.cell.stateSize,o=[n,i];if(!k.arraysEqual(s.shape,o))throw new V(`State ${a} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${s.shape}`);this.states_[a]=s}}this.states_=this.states_.map(a=>Pt(a.clone()))})}apply(t,r){let n=r==null?null:r.initialState,a=r==null?null:r.constants;r==null&&(r={});let s=h2(t,n,a,this.numConstants);t=s.inputs,n=s.initialState,a=s.constants;let i=[],o=[];if(n!=null){r.initialState=n,i=i.concat(n),this.stateSpec=[];for(let l of n)this.stateSpec.push(new Rt({shape:l.shape}));o=o.concat(this.stateSpec)}if(a!=null&&(r.constants=a,i=i.concat(a),this.numConstants=a.length),i[0]instanceof Un){let l=[t].concat(i),p=this.inputSpec.concat(o),u=this.inputSpec;this.inputSpec=p;let d=super.apply(l,r);return this.inputSpec=u,d}else return super.apply(t,r)}call(t,r){return W(()=>{let n=r==null?null:r.mask,a=r==null?null:r.training,s=r==null?null:r.initialState;t=Te(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 V(`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 o={training:a},l=c2((c,f)=>{let m=this.cell.call([c].concat(f),o);return[m[0],m.slice(1)]},t,s,this.goBackwards,n,null,this.unroll,this.returnSequences),p=l[0],u=l[1],d=l[2];this.stateful&&this.resetStates(d,a);let h=this.returnSequences?u:p;return this.returnState?[h].concat(d):h})}getInitialState(t){return W(()=>{let r=It(t.shape);return r=ge(r,[1,2]),r=eh(r),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?Ig(r,[1,n]):r):this.cell.stateSize>1?[Ig(r,[1,this.cell.stateSize])]:[r]})}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(),r={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(r.numConstants=this.numConstants);let n=this.cell.getConfig();return this.getClassName()===f2.className&&(r.cell={className:this.cell.getClassName(),config:n}),Object.assign(Object.assign(Object.assign({},n),t),r)}static fromConfig(t,r,n={}){let a=r.cell,s=On(a,n);return new t(Object.assign(r,{cell:s}))}};Ba.className="RNN";ne.registerClass(Ba);var sh=class extends We{},pm=class extends sh{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Zt(this.units,"units"),this.activation=ws(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=xt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=xt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=xt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=vt(e.kernelRegularizer),this.recurrentRegularizer=vt(e.recurrentRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.kernelConstraint=Vt(e.kernelConstraint),this.recurrentConstraint=Vt(e.recurrentConstraint),this.biasConstraint=Vt(e.biasConstraint),this.dropout=Ll([1,xs([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Ll([1,xs([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=Xe(e),this.kernel=this.addWeight("kernel",[e[e.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return W(()=>{if(e=e,e.length!==2)throw new V(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let r=e[1];e=e[0];let n=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ks({ones:()=>Zr(e),rate:this.dropout,training:n,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ks({ones:()=>Zr(r),rate:this.recurrentDropout,training:n,dropoutFunc:this.dropoutFunc}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=oa(z(e,s),this.kernel.read()):a=oa(e,this.kernel.read()),this.bias!=null&&(a=qn(a,this.bias.read())),i!=null&&(r=z(r,i));let o=J(a,oa(r,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:vs(this.activation),useBias:this.useBias,kernelInitializer:St(this.kernelInitializer),recurrentInitializer:St(this.recurrentInitializer),biasInitializer:St(this.biasInitializer),kernelRegularizer:dt(this.kernelRegularizer),recurrentRegularizer:dt(this.recurrentRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:Ut(this.kernelConstraint),recurrentConstraint:Ut(this.recurrentConstraint),biasConstraint:Ut(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign(Object.assign({},e),t)}};pm.className="SimpleRNNCell";ne.registerClass(pm);var zx=class extends Ba{constructor(e){e.cell=new pm(e),super(e)}call(e,t){return W(()=>{this.cell.dropoutMask!=null&&(Ce(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ce(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let r=t==null?null:t.mask,n=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:r,training:n,initialState:a})})}static fromConfig(e,t){return new e(t)}};zx.className="SimpleRNN";ne.registerClass(zx);var dm=class extends sh{constructor(e){if(super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new V("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Zt(this.units,"units"),this.activation=ws(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ws(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=xt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=xt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=xt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=vt(e.kernelRegularizer),this.recurrentRegularizer=vt(e.recurrentRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.kernelConstraint=Vt(e.kernelConstraint),this.recurrentConstraint=Vt(e.recurrentConstraint),this.biasConstraint=Vt(e.biasConstraint),this.dropout=Ll([1,xs([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Ll([1,xs([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=Xe(e);let t=e[e.length-1];this.kernel=this.addWeight("kernel",[t,this.units*3],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*3],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units*3],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return W(()=>{if(e=e,e.length!==2)throw new V(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let r=t.training==null?!1:t.training,n=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ks({ones:()=>Zr(e),rate:this.dropout,training:r,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ks({ones:()=>Zr(n),rate:this.recurrentDropout,training:r,count:3,dropoutFunc:this.dropoutFunc}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=z(e,a[0]));let p=oa(e,this.kernel.read());this.useBias&&(p=qn(p,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(n=z(n,s[0]));let u=this.recurrentKernel.read(),[d,h]=Ar(u,[2*this.units,this.units],u.rank-1),c=oa(n,d),[f,m,g]=Ar(p,3,p.rank-1),[y,b]=Ar(c,2,c.rank-1);i=this.recurrentActivation.apply(J(f,y)),o=this.recurrentActivation.apply(J(m,b));let x=oa(z(o,n),h);l=this.activation.apply(J(g,x));let v=J(z(i,n),z(J(1,gt(i)),l));return[v,v]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:vs(this.activation),recurrentActivation:vs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:St(this.kernelInitializer),recurrentInitializer:St(this.recurrentInitializer),biasInitializer:St(this.biasInitializer),kernelRegularizer:dt(this.kernelRegularizer),recurrentRegularizer:dt(this.recurrentRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:Ut(this.kernelConstraint),recurrentConstraint:Ut(this.recurrentConstraint),biasConstraint:Ut(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign(Object.assign({},e),t)}};dm.className="GRUCell";ne.registerClass(dm);var Px=class extends Ba{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new dm(e),super(e)}call(e,t){return W(()=>{this.cell.dropoutMask!=null&&(Ce(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ce(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let r=t==null?null:t.mask,n=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:r,training:n,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Px.className="GRU";ne.registerClass(Px);var ih=class extends sh{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Zt(this.units,"units"),this.activation=ws(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ws(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=xt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=xt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=xt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=vt(e.kernelRegularizer),this.recurrentRegularizer=vt(e.recurrentRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.kernelConstraint=Vt(e.kernelConstraint),this.recurrentConstraint=Vt(e.recurrentConstraint),this.biasConstraint=Vt(e.biasConstraint),this.dropout=Ll([1,xs([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Ll([1,xs([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=Xe(e);let r=e[e.length-1];this.kernel=this.addWeight("kernel",[r,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let n;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;n=new(t=class extends Tn{apply(i,o){let l=a.apply([s]),p=new Zf().apply([s]),u=a.apply([s*2]);return A0(A0(l,p),u)}},t.className="CustomInit",t)}else n=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,n,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return W(()=>{let r=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new V(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ks({ones:()=>Zr(e),rate:this.dropout,training:r,count:4,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ks({ones:()=>Zr(n),rate:this.recurrentDropout,training:r,count:4,dropoutFunc:this.dropoutFunc}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,p,u;0<this.dropout&&this.dropout<1&&(e=z(e,s[0]));let d=oa(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(n=z(n,i[0])),d=J(d,oa(n,this.recurrentKernel.read())),this.useBias&&(d=qn(d,this.bias.read()));let[h,c,f,m]=Ar(d,4,d.rank-1);o=this.recurrentActivation.apply(h),l=this.recurrentActivation.apply(c),p=J(z(l,a),z(o,this.activation.apply(f))),u=this.recurrentActivation.apply(m);let g=z(u,this.activation.apply(p));return[g,g,p]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:vs(this.activation),recurrentActivation:vs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:St(this.kernelInitializer),recurrentInitializer:St(this.recurrentInitializer),biasInitializer:St(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:dt(this.kernelRegularizer),recurrentRegularizer:dt(this.recurrentRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:Ut(this.kernelConstraint),recurrentConstraint:Ut(this.recurrentConstraint),biasConstraint:Ut(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign(Object.assign({},e),t)}};ih.className="LSTMCell";ne.registerClass(ih);var Bx=class extends Ba{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new ih(e),super(e)}call(e,t){return W(()=>{this.cell.dropoutMask!=null&&(Ce(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ce(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let r=t==null?null:t.mask,n=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:r,training:n,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Bx.className="LSTM";ne.registerClass(Bx);var hm=class extends sh{constructor(e){super(e),this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return W(()=>{e=e;let r=e.slice(1),n=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?n.push(r.splice(0,i.stateSize.length)):n.push(r.splice(0,1));n.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];r=n[i],i===0?s=[e[0]].concat(r):s=[s[0]].concat(r),s=o.call(s,t),a.push(s.slice(1))}r=[];for(let i of a.slice().reverse())r.push(...i);return[s[0]].concat(r)})}build(e){Ng(e)&&(e=e[0]),e=e;let t;this.cells.forEach((r,n)=>{si(`RNNCell_${n}`,()=>{r.build(e),Array.isArray(r.stateSize)?t=r.stateSize[0]:t=r.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=n=>({className:n.getClassName(),config:n.getConfig()}),r={cells:this.cells.map(t)};return Object.assign(Object.assign({},e),r)}static fromConfig(e,t,r={}){let n=[];for(let a of t.cells)n.push(On(a,r));return new e({cells:n})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let r of this.cells)t.push(...r.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return _g(e)}setWeights(e){let t=[];for(let r of this.cells){let n=r.weights.length,a=e.splice(n);for(let s=0;s<r.weights.length;++s)t.push([r.weights[s],a[s]])}px(t)}};hm.className="StackedRNNCells";ne.registerClass(hm);function ks(e){let{ones:t,rate:r,training:n=!1,count:a=1,dropoutFunc:s}=e,i=()=>s!=null?s(t(),r):gN(t(),r),o=()=>rh(i,t,n);return!a||a<=1?Pt(o().clone()):Array(a).fill(void 0).map(o).map(l=>Pt(l.clone()))}var sH=function(e,t){var r={};for(var n in e)Object.prototype.hasOwnProperty.call(e,n)&&t.indexOf(n)<0&&(r[n]=e[n]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,n=Object.getOwnPropertySymbols(e);a<n.length;a++)t.indexOf(n[a])<0&&Object.prototype.propertyIsEnumerable.call(e,n[a])&&(r[n[a]]=e[n[a]]);return r},m2=class extends Ba{constructor(e){if(e.unroll)throw new Be("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Be("It is not possible at the moment to stack convolutional cells.");super(e),this.inputSpec=[new Rt({ndim:5})]}call(e,t){return W(()=>{if(this.cell.dropoutMask!=null&&(Ce(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ce(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new V("ConvRNN2D cell does not support constants");let r=t==null?null:t.mask,n=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:r,training:n,initialState:a})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return W(()=>{let{stateSize:t}=this.cell,r=e.shape,n=this.computeSingleOutputShape(r),a=[n[0],...n.slice(2)],s=It(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){W(()=>{if(!this.stateful)throw new Ya("Cannot call resetStates() on an RNN Layer that is not stateful.");let r=this.inputSpec[0].shape,n=this.computeSingleOutputShape(r),a=[n[0],...n.slice(2)];if(r[0]==null)throw new V("If an RNN is stateful, it needs to know its batch size. 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Input received: ${e}`);t?this.keptStates.push(this.states_.slice()):Ce(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!k.arraysEqual(i.shape,o))throw new V(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>Pt(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:r,kernelSize:n,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],p=e[o?4:3],u=Ln(l,n[0],a,s[0],i[0]),d=Ln(p,n[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[r,u,d]:[u,d,r]]}};m2.className="ConvRNN2D";var cm=class extends ih{constructor(e){let{filters:t,kernelSize:r,strides:n,padding:a,dataFormat:s,dilationRate:i}=e;super(Object.assign(Object.assign({},e),{units:t})),this.filters=t,Zt(this.filters,"filters"),this.kernelSize=Sl(r,2,"kernelSize"),this.kernelSize.forEach(o=>Zt(o,"kernelSize")),this.strides=Sl(n||1,2,"strides"),this.strides.forEach(o=>Zt(o,"strides")),this.padding=a||"valid",gn(this.padding),this.dataFormat=s||"channelsLast",Ct(this.dataFormat),this.dilationRate=Sl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Zt(o,"dilationRate"))}build(e){var t;e=Xe(e);let r=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[r]==null)throw new V(`The channel dimension of the input should be defined. Found ${e[r]}`);let n=e[r],a=4,s=this.kernelSize.concat([n,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,p=this.filters;o=new(t=class extends Tn{apply(u,d){let h=l.apply([p]),c=$r([p]),f=l.apply([p*2]);return rx([h,c,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return W(()=>{if(e.length!==3)throw new V(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=t.training||!1,n=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ks({ones:()=>Zr(n),rate:this.dropout,training:r,count:i,dropoutFunc:this.dropoutFunc}));let o=this.dropoutMask,l=(Z,ee,X)=>!ee||!ee[X]?Z:z(ee[X],Z),p=l(n,o,0),u=l(n,o,1),d=l(n,o,2),h=l(n,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ks({ones:()=>Zr(a),rate:this.recurrentDropout,training:r,count:i,dropoutFunc:this.dropoutFunc}));let c=this.recurrentDropoutMask,f=l(a,c,0),m=l(a,c,1),g=l(a,c,2),y=l(a,c,3),b=3,[x,v,w,N]=Ar(this.kernel.read(),i,b),[T,E,$,R]=this.useBias?Ar(this.bias.read(),i):[null,null,null,null];p=this.inputConv(p,x,T,this.padding),u=this.inputConv(u,v,E,this.padding),d=this.inputConv(d,w,$,this.padding),h=this.inputConv(h,N,R,this.padding);let[F,S,D,P]=Ar(this.recurrentKernel.read(),i,b);f=this.recurrentConv(f,F),m=this.recurrentConv(m,S),g=this.recurrentConv(g,D),y=this.recurrentConv(y,P);let U=this.recurrentActivation.apply(J(p,f)),H=this.recurrentActivation.apply(J(u,m)),q=J(z(H,s),z(U,this.activation.apply(J(d,g)))),G=z(this.recurrentActivation.apply(J(h,y)),this.activation.apply(q));return[G,G,q]})}getConfig(){let e=super.getConfig(),{units:t}=e,r=sH(e,["units"]),n={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign(Object.assign({},r),n)}inputConv(e,t,r,n){let a=br(e,t,this.strides,n||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return r?qn(a,r,this.dataFormat):a}recurrentConv(e,t){return br(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};cm.className="ConvLSTM2DCell";ne.registerClass(cm);var Wx=class extends m2{constructor(e){let t=new cm(e);super(Object.assign(Object.assign({},e),{cell:t}))}static fromConfig(e,t){return new e(t)}};Wx.className="ConvLSTM2D";ne.registerClass(Wx);var fm=class extends We{constructor(e){super(e),this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,r=[];for(let n=0;n<this.noiseShape.length;++n)r.push(this.noiseShape[n]==null?t[n]:this.noiseShape[n]);return r}call(e,t){return W(()=>{this.invokeCallHook(e,t);let r=Te(e);if(0<this.rate&&this.rate<1){let n=t.training==null?!1:t.training,a=this.getNoiseShape(r);return rh(()=>gN(r,this.rate,a,this.seed),()=>r,n)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};fm.className="Dropout";ne.registerClass(fm);var Ux=class extends fm{constructor(e){super(e),this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};Ux.className="SpatialDropout1D";ne.registerClass(Ux);var Vx=class extends We{constructor(e){if(super(e),this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.batchInputShape==null&&e.inputShape==null&&e.inputDim!=null){let t=null;e.batchSize!=null&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,Zt(this.units,"units"),this.activation=ws(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=xt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=xt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Vt(e.kernelConstraint),this.biasConstraint=Vt(e.biasConstraint),this.kernelRegularizer=vt(e.kernelRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.activityRegularizer=vt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=Xe(e);let t=e[e.length-1];this.kernel==null&&(this.kernel=this.addWeight("kernel",[t,this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint))),this.inputSpec=[{minNDim:2,axes:{[-1]:t}}],this.built=!0}computeOutputShape(e){e=Xe(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return W(()=>{this.invokeCallHook(e,t);let r=Te(e),n=uN(this.activation.getClassName()),a;return n!=null?a=oa(r,this.kernel.read(),n,this.bias?this.bias.read():null):(a=oa(r,this.kernel.read()),this.bias!=null&&(a=qn(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:vs(this.activation),useBias:this.useBias,kernelInitializer:St(this.kernelInitializer),biasInitializer:St(this.biasInitializer),kernelRegularizer:dt(this.kernelRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:Ut(this.kernelConstraint),biasConstraint:Ut(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Vx.className="Dense";ne.registerClass(Vx);var Gx=class extends We{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=Xe(e);for(let t of e.slice(1))if(t==null)throw new V(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). 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W(()=>(e=Te(e),mV(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};jx.className="RepeatVector";ne.registerClass(jx);var qx=class extends We{constructor(e){super(e),this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let r="Total size of new array must be unchanged.",n=t.slice(),a=1,s=null;for(let o=0;o<n.length;++o){let l=n[o];if(this.isUnknown(l))if(s===null)s=o;else throw new V("Can only specifiy one unknown dimension.");else a*=l}let i=ls(e);if(s!==null){if(a===0||i%a!==0)throw new V(r);n[s]=i/a}else if(i!==a)throw new V(r);return n}computeOutputShape(e){let t=!1;for(let r=0;r<e.length;++r)if(this.isUnknown(e[r])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))}call(e,t){return W(()=>{this.invokeCallHook(e,t);let r=Te(e),n=r.shape,a=n.slice(0,1).concat(this.fixUnknownDimension(n.slice(1),this.targetShape));return B(r,a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};qx.className="Reshape";ne.registerClass(qx);var Kx=class extends We{constructor(e){if(super(e),e.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(e.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${e.dims} instead.`);let t=Bn(1,e.dims.length+1);if(!k.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new Rt({ndim:this.dims.length+1})]}computeOutputShape(e){e=Xe(e);let t=e.slice();return this.dims.forEach((r,n)=>{t[n+1]=e[r]}),t}call(e,t){return 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o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=ge(z(e,t),s[0]):o=ge(z(Oe(e,[1,0]),t),s[1]);else{let l=s[0]!==e.shape.length-1,p=s[1]===t.shape.length-1;o=Me(e,t,l,p)}if(i>0){let l;n>a?l=n+a-3:l=n-1;let p=[];for(let u=l;u<l+i;++u)p.push(u);o=Ms(o,p)}return o.shape.length===1&&(o=Xt(o,1)),o})}var nv=class extends tl{constructor(e){super(e),this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){k.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],r=e[1];if(t.length>3||r.length>3)throw new Be("Dot layer does not support tensors of 4D or higher rank yet.");let n=this.interpretAxes(t,r);if(t[n[0]]!==r[n[1]])throw new V(`Dimension incompatibility: ${t[n[0]]} !== ${r[n[1]]}`)}mergeFunction(e){if(e.length!==2)throw new V(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} 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e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:St(this.betaInitializer),gammaInitializer:St(this.gammaInitializer),betaRegularizer:dt(this.betaRegularizer),gammaRegularizer:dt(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};lv.className="LayerNormalization";ne.registerClass(lv);function pH(e,t,r){return W(()=>{if(e.rank!==4)throw new V(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new V("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(r==null&&(r=Wn()),r!=="channelsLast"&&r!=="channelsFirst")throw new V(`Unknown data format: ${r}. 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We{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new V(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Zt(this.poolSize,"poolSize"),Zt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),gn(this.padding),this.inputSpec=[new Rt({ndim:5})]}computeOutputShape(e){e=Xe(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],r=this.dataFormat==="channelsFirst"?e[3]:e[2],n=this.dataFormat==="channelsFirst"?e[4]:e[3];return 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n={};if(n.className=e.layer.getClassName(),n.config=t,this.backwardLayer=On(n),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?hH:e.mergeMode,dH(this.mergeMode),e.weights)throw new Be("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,r=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,r)),this.backwardLayer.setWeights(e.slice(r))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let r,n,a;return this.returnState&&(a=t.slice(1)),r=t[0],r=r,this.mergeMode==="concat"?(r[r.length-1]*=2,n=[r]):this.mergeMode==null?n=[r,r.slice()]:n=[r],this.returnState?this.mergeMode==null?n.concat(a).concat(a.slice()):[r].concat(a).concat(a.slice()):Er(n)}apply(e,t){let r=t==null?null:t.initialState,n=t==null?null:t.constants;t==null&&(t={});let a=h2(e,r,n,this.numConstants);if(e=a.inputs,r=a.initialState,n=a.constants,Array.isArray(e)&&(r=e.slice(1),e=e[0]),(r==null||r.length===0)&&n==null)return super.apply(e,t);let s=[],i=[];if(r!=null){let l=r.length;if(l%2>0)throw new V("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=r,s.push(...r);let p=r.map(u=>new 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n=I("size",e,t,r),a=I("dtype",e,t,r),s=I("elementShape",e,t,r),i=I("dynamicSize",e,t,r),o=I("clearAfterRead",e,t,r),l=I("identicalElementShapes",e,t,r),p=I("name",e,t,r),u=new _j(p,a,n,s,l,i,o);return r.addTensorArray(u),[u.idTensor,we(1)]}case"TensorArrayWriteV3":{let n=I("tensorArrayId",e,t,r),a=I("index",e,t,r),s=I("tensor",e,t,r),i=r.getTensorArray(n.id);return i.write(a,s),[i.idTensor]}case"TensorArrayReadV3":{let n=I("tensorArrayId",e,t,r),a=I("index",e,t,r);return[r.getTensorArray(n.id).read(a)]}case"TensorArrayGatherV3":{let n=I("tensorArrayId",e,t,r),a=I("indices",e,t,r),s=I("dtype",e,t,r);return[r.getTensorArray(n.id).gather(a,s)]}case"TensorArrayScatterV3":{let n=I("tensorArrayId",e,t,r),a=I("indices",e,t,r),s=I("tensor",e,t,r),i=r.getTensorArray(n.id);return i.scatter(a,s),[i.idTensor]}case"TensorArrayConcatV3":{let n=I("tensorArrayId",e,t,r),a=r.getTensorArray(n.id),s=I("dtype",e,t,r);return[a.concat(s)]}case"TensorArraySplitV3":{let 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n=I("elementShape",e,t,r),a=I("elementDType",e,t,r),s;e.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=I(s,e,t,r),o=e.op==="TensorListReserve"?-1:i,l=Cj(n,a,i,o);return r.addTensorList(l),[l.idTensor]}case"TensorListGather":{let n=I("tensorListId",e,t,r),a=I("indices",e,t,r),s=I("elementShape",e,t,r),i=I("elementDType",e,t,r);return[r.getTensorList(n.id).gather(a,i,s)]}case"TensorListStack":{let n=I("tensorListId",e,t,r),a=I("elementShape",e,t,r),s=I("elementDType",e,t,r),i=I("numElements",e,t,r);return[r.getTensorList(n.id).stack(a,s,i)]}case"TensorListFromTensor":{let n=I("tensor",e,t,r),a=I("elementShape",e,t,r),s=I("elementDType",e,t,r),i=Tj(n,a,s);return r.addTensorList(i),[i.idTensor]}case"TensorListConcat":case"TensorListConcatV2":{let n=I("tensorListId",e,t,r),a=r.getTensorList(n.id),s=I("dtype",e,t,r),i=I("elementShape",e,t,r);return[a.concat(s,i)]}case"TensorListPushBack":{let n=I("tensorListId",e,t,r),a=I("tensor",e,t,r),s=r.getTensorList(n.id);return 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a=I("outputShape",e,t,r),s=I("strides",e,t,r),i=Jh(e,t,r);return[n.conv2dTranspose(I("x",e,t,r),I("filter",e,t,r),a,[s[1],s[2]],i)]}case"DepthwiseConv2dNative":case"DepthwiseConv2d":{let a=I("strides",e,t,r),s=Jh(e,t,r),i=I("dilations",e,t,r),o=I("dataFormat",e,t,r).toUpperCase();return[n.depthwiseConv2d(I("input",e,t,r),I("filter",e,t,r),[a[1],a[2]],s,o,[i[1],i[2]])]}case"Conv3D":{let a=I("strides",e,t,r),s=I("pad",e,t,r),i=I("dataFormat",e,t,r).toUpperCase(),o=I("dilations",e,t,r);return[n.conv3d(I("x",e,t,r),I("filter",e,t,r),[a[1],a[2],a[3]],s,i,[o[1],o[2],o[3]])]}case"AvgPool":{let a=I("strides",e,t,r),s=I("pad",e,t,r),i=I("kernelSize",e,t,r);return[n.avgPool(I("x",e,t,r),[i[1],i[2]],[a[1],a[2]],s)]}case"MaxPool":{let a=I("strides",e,t,r),s=I("pad",e,t,r),i=I("kernelSize",e,t,r);return[n.maxPool(I("x",e,t,r),[i[1],i[2]],[a[1],a[2]],s)]}case"MaxPoolWithArgmax":{let a=I("strides",e,t,r),s=I("pad",e,t,r),i=I("kernelSize",e,t,r),o=I("includeBatchInIndex",e,t,r),{result:l,indexes:p}=n.maxPoolWithArgmax(I("x",e,t,r),[i[1],i[2]],[a[1],a[2]],s,o);return[l,p]}case"AvgPool3D":{let a=I("strides",e,t,r),s=I("pad",e,t,r),i=I("kernelSize",e,t,r);return[n.avgPool3d(I("x",e,t,r),[i[1],i[2],i[3]],[a[1],a[2],a[3]],s)]}case"MaxPool3D":{let a=I("strides",e,t,r),s=I("pad",e,t,r),i=I("kernelSize",e,t,r);return[n.maxPool3d(I("x",e,t,r),[i[1],i[2],i[3]],[a[1],a[2],a[3]],s)]}case"Dilation2D":{let a=I("strides",e,t,r),s=I("pad",e,t,r),i=I("dilations",e,t,r),o=a[1],l=a[2],p=i[1],u=i[2];return[n.dilation2d(I("x",e,t,r),I("filter",e,t,r),[o,l],s,[p,u],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Rj=(e,t,r,n=er)=>{switch(e.op){case"Fill":{let a=I("shape",e,t,r),s=I("dtype",e,t,r),i=I("value",e,t,r);return[n.fill(a,i,s)]}case"LinSpace":{let a=I("start",e,t,r),s=I("stop",e,t,r),i=I("num",e,t,r);return[n.linspace(a,s,i)]}case"Multinomial":{let a=I("logits",e,t,r),s=I("numSamples",e,t,r),i=I("seed",e,t,r);return[n.multinomial(a,s,i)]}case"OneHot":{let a=I("indices",e,t,r),s=I("depth",e,t,r),i=I("onValue",e,t,r),o=I("offValue",e,t,r),l=I("dtype",e,t,r);return[n.oneHot(a,s,i,o,l)]}case"Ones":return[n.ones(I("shape",e,t,r),I("dtype",e,t,r))];case"OnesLike":return[n.onesLike(I("x",e,t,r))];case"RandomStandardNormal":return[n.randomStandardNormal(I("shape",e,t,r),I("dtype",e,t,r),I("seed",e,t,r))];case"RandomUniform":return[n.randomUniform(I("shape",e,t,r),I("minval",e,t,r),I("maxval",e,t,r),I("dtype",e,t,r))];case"RandomUniformInt":return[n.randomUniformInt(I("shape",e,t,r),I("minval",e,t,r),I("maxval",e,t,r),I("seed",e,t,r))];case"Range":{let a=I("start",e,t,r),s=I("stop",e,t,r),i=I("step",e,t,r);return[n.range(a,s,i,I("dtype",e,t,r))]}case"TruncatedNormal":{let 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a=I("x",e,t,r),s=I("axis",e,t,r),i=n.unique(a,s);return[i.values,i.indices]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Oj=(e,t,r,n=er)=>{switch(e.op){case"Const":return t[e.name];case"PlaceholderWithDefault":let a=I("default",e,t,r);return[ar(e.name,t,r)||a];case"Placeholder":return[ar(e.name,t,r)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":{let u=I("x",e,t,r);return[Sa(u)]}case"IdentityN":return I("x",e,t,r).map(u=>Sa(u));case"Snapshot":let s=I("x",e,t,r);return[Sa(s)];case"Shape":return[n.tensor1d(I("x",e,t,r).shape,"int32")];case"ShapeN":return I("x",e,t,r).map(u=>n.tensor1d(u.shape));case"Size":return[n.scalar(I("x",e,t,r).size,"int32")];case"Rank":return[n.scalar(I("x",e,t,r).rank,"int32")];case"NoOp":return[n.scalar(1)];case"Print":let i=I("x",e,t,r),o=I("data",e,t,r),l=I("message",e,t,r),p=I("summarize",e,t,r);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down 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n=[];for(let a=0;a<r.length;a++){let s=r[a],i=this.findWithDefault(s,t);n.push(i)}return Mt(n)})}findWithDefault(e,t){let r=this.tensorMap.get(e);return r??t}checkKeyAndValueTensor(e,t){if(e.dtype!==this.keyDType)throw new Error(`Expect key dtype ${this.keyDType}, but got ${e.dtype}`);if(t.dtype!==this.valueDType)throw new Error(`Expect value dtype ${this.valueDType}, but got ${t.dtype}`)}},zj=async(e,t,r,n)=>{switch(e.op){case"HashTable":case"HashTableV2":{let a=n.getHashTableHandleByName(e.name);if(a!=null)return[a];{let s=I("keyDType",e,t,r),i=I("valueDType",e,t,r),o=new Lj(s,i);return n.addHashTable(e.name,o),[o.handle]}}case"InitializeTable":case"InitializeTableV2":case"LookupTableImport":case"LookupTableImportV2":{let a=I("tableHandle",e,t,r,n),s=I("keys",e,t,r),i=I("values",e,t,r);return[await n.getHashTableById(a.id).import(s,i)]}case"LookupTableFind":case"LookupTableFindV2":{let a=I("tableHandle",e,t,r,n),s=I("keys",e,t,r),i=I("defaultValue",e,t,r);return[await n.getHashTableById(a.id).find(s,i)]}case"LookupTableSize":case"LookupTableSizeV2":{let a=I("tableHandle",e,t,r,n);return[n.getHashTableById(a.id).tensorSize()]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Pj=(e,t,r,n=er)=>{switch(e.op){case"ResizeBilinear":{let a=I("images",e,t,r),s=I("size",e,t,r),i=I("alignCorners",e,t,r),o=I("halfPixelCenters",e,t,r);return[n.image.resizeBilinear(a,[s[0],s[1]],i,o)]}case"ResizeNearestNeighbor":{let a=I("images",e,t,r),s=I("size",e,t,r),i=I("alignCorners",e,t,r),o=I("halfPixelCenters",e,t,r);return[n.image.resizeNearestNeighbor(a,[s[0],s[1]],i,o)]}case"CropAndResize":{let a=I("image",e,t,r),s=I("boxes",e,t,r),i=I("boxInd",e,t,r),o=I("cropSize",e,t,r),l=I("method",e,t,r),p=I("extrapolationValue",e,t,r);return[n.image.cropAndResize(a,s,i,o,l,p)]}case"ImageProjectiveTransformV3":{let a=I("images",e,t,r),s=I("transforms",e,t,r),i=I("outputShape",e,t,r),o=I("fillValue",e,t,r),l=I("interpolation",e,t,r),p=I("fillMode",e,t,r);return[n.image.transform(a,s,l.toLowerCase(),p.toLowerCase(),o,i)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Bj=(e,t,r,n=er)=>{switch(e.op){case"Equal":return[n.equal(I("a",e,t,r),I("b",e,t,r))];case"NotEqual":return[n.notEqual(I("a",e,t,r),I("b",e,t,r))];case"Greater":return[n.greater(I("a",e,t,r),I("b",e,t,r))];case"GreaterEqual":return[n.greaterEqual(I("a",e,t,r),I("b",e,t,r))];case"Less":return[n.less(I("a",e,t,r),I("b",e,t,r))];case"LessEqual":return[n.lessEqual(I("a",e,t,r),I("b",e,t,r))];case"LogicalAnd":return[n.logicalAnd(I("a",e,t,r),I("b",e,t,r))];case"LogicalNot":return[n.logicalNot(I("a",e,t,r))];case"LogicalOr":return[n.logicalOr(I("a",e,t,r),I("b",e,t,r))];case"Select":case"SelectV2":return[n.where(I("condition",e,t,r),I("a",e,t,r),I("b",e,t,r))];case"BitwiseAnd":return[n.bitwiseAnd(I("a",e,t,r),I("b",e,t,r))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Wj=(e,t,r,n=er)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[n.matMul(I("a",e,t,r),I("b",e,t,r),I("transposeA",e,t,r),I("transposeB",e,t,r))];case"Einsum":return[n.einsum(I("equation",e,t,r),...I("tensors",e,t,r))];case"Transpose":return[n.transpose(I("x",e,t,r),I("perm",e,t,r))];case"_FusedMatMul":let[a,s]=I("fusedOps",e,t,r),i=a==="biasadd",o=s==="prelu",l=I("numArgs",e,t,r),p=I("leakyreluAlpha",e,t,r);if(i){if(o&&l!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!o&&l!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[u,d]=I("args",e,t,r);return[n.fused.matMul({a:I("a",e,t,r),b:I("b",e,t,r),transposeA:I("transposeA",e,t,r),transposeB:I("transposeB",e,t,r),bias:u,activation:s,preluActivationWeights:d,leakyreluAlpha:p})];case"MatrixBandPart":return[n.linalg.bandPart(I("a",e,t,r),I("numLower",e,t,r),I("numUpper",e,t,r))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Uj=(e,t,r,n=er)=>{switch(e.op){case"EuclideanNorm":return[n.euclideanNorm(I("x",e,t,r),I("axis",e,t,r),I("keepDims",e,t,r))];case"FusedBatchNorm":case"FusedBatchNormV2":return[n.batchNorm(I("x",e,t,r),I("mean",e,t,r),I("variance",e,t,r),I("offset",e,t,r),I("scale",e,t,r),I("epsilon",e,t,r))];case"FusedBatchNormV3":return[n.batchNorm(I("x",e,t,r),I("mean",e,t,r),I("variance",e,t,r),I("offset",e,t,r),I("scale",e,t,r),I("epsilon",e,t,r))];case"LRN":return[n.localResponseNormalization(I("x",e,t,r),I("radius",e,t,r),I("bias",e,t,r),I("alpha",e,t,r),I("beta",e,t,r))];case"Softmax":return[n.softmax(I("x",e,t,r))];case"LogSoftmax":return[n.logSoftmax(I("x",e,t,r))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Vj=(e,t,r,n=er)=>{switch(e.op){case"RaggedGather":{let{outputNestedSplits:a,outputDenseValues:s}=n.raggedGather(I("paramsNestedSplits",e,t,r),I("paramsDenseValues",e,t,r),I("indices",e,t,r),I("outputRaggedRank",e,t,r));return a.concat(s)}case"RaggedRange":{let{rtNestedSplits:a,rtDenseValues:s}=n.raggedRange(I("starts",e,t,r),I("limits",e,t,r),I("splits",e,t,r));return[a,s]}case"RaggedTensorToTensor":return[n.raggedTensorToTensor(I("shape",e,t,r),I("values",e,t,r),I("defaultValue",e,t,r),I("rowPartitionTensors",e,t,r),I("rowPartitionTypes",e,t,r))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Gj=(e,t,r,n=er)=>{switch(e.op){case"Max":{let o=I("axis",e,t,r),l=I("keepDims",e,t,r);return[n.max(I("x",e,t,r),o,l)]}case"Mean":{let o=I("axis",e,t,r),l=I("keepDims",e,t,r);return[n.mean(I("x",e,t,r),o,l)]}case"Min":{let o=I("axis",e,t,r),l=I("keepDims",e,t,r);return[n.min(I("x",e,t,r),o,l)]}case"Sum":{let 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implemented`)}},qj=(e,t,r,n=er)=>{switch(e.op){case"FFT":return[n.fft(I("x",e,t,r))];case"IFFT":return[n.ifft(I("x",e,t,r))];case"RFFT":return[n.rfft(I("x",e,t,r))];case"IRFFT":return[n.irfft(I("x",e,t,r))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Kj=(e,t,r,n=er)=>{switch(e.op){case"StaticRegexReplace":return[n.string.staticRegexReplace(I("input",e,t,r),I("pattern",e,t,r),I("rewrite",e,t,r),I("replaceGlobal",e,t,r))];case"StringNGrams":{let{nGrams:a,nGramsSplits:s}=n.string.stringNGrams(I("data",e,t,r),I("dataSplits",e,t,r),I("separator",e,t,r),I("nGramWidths",e,t,r),I("leftPad",e,t,r),I("rightPad",e,t,r),I("padWidth",e,t,r),I("preserveShortSequences",e,t,r));return[a,s]}case"StringSplit":{let{indices:a,values:s,shape:i}=n.string.stringSplit(I("input",e,t,r),I("delimiter",e,t,r),I("skipEmpty",e,t,r));return[a,s,i]}case"StringToHashBucketFast":return[n.string.stringToHashBucketFast(I("input",e,t,r),I("numBuckets",e,t,r))];default:throw TypeError(`Node type 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Zj(e,t){let{usedNodes:r,inputs:n}=t,a=Object.keys(n).map(g=>Vr(g)[0]).map(g=>e.nodes[g]),s=e.initNodes||[],i=g=>r.has(typeof g=="string"?g:g.name);function o(g){return[...new Map(g.map(y=>[y.name,y])).values()]}let l=o([...a,...e.weights,...s]).filter(i),p=o([...l,...Object.values(e.nodes)]).filter(i),u=new Map(p.map(g=>[g.name,g])),d={};for(let g of p){d[g.name]=d[g.name]||0;for(let y of g.children)i(y)||(d[y.name]=Number.POSITIVE_INFINITY),d[y.name]=(d[y.name]||0)+1}let h=Object.entries(d).filter(([,g])=>g===0).map(([g])=>g),c=[...h];for(;h.length>0;){let g=h.pop(),y=u.get(g);for(let b of y.children.filter(i))--d[b.name]===0&&(c.push(b.name),h.push(b.name))}let f=c.map(g=>u.get(g)),m=Jj(f,l);return Yj(m,l),m}function Jj(e,t){let r=new Map(e.map(s=>[s.name,s])),n=t.map(s=>s.name),a=new Set(n);for(;n.length>0;){let s=n.pop(),i=r.get(s);for(let o of i.children)!r.has(o.name)||a.has(o.name)||(a.add(o.name),n.push(o.name))}return e.filter(s=>a.has(s.name))}var Lh=class extends Error{constructor(e){super(`NodesExecutionOrderError: ${e}`)}};function Yj(e,t){let r=new Map(e.map((o,l)=>[o.name,l])),n=new Set(t.map(o=>o.name)),a=o=>n.has(typeof o=="string"?o:o.name),s=new Set(e.map(o=>o.name)),i=o=>s.has(typeof o=="string"?o:o.name);for(let o of e){for(let l of o.children.filter(i)){if(!r.has(l.name))throw new Lh(`Child ${l.name} of node ${o.name} is unreachable.`);if(r.get(o.name)>r.get(l.name))throw new Lh(`Node ${o.name} is scheduled to run after its child ${l.name}.`)}if(!a(o))for(let l of o.inputs){if(!r.has(l.name))throw new Lh(`Input ${l.name} of node ${o.name} is unreachable.`);if(r.get(l.name)>r.get(o.name))throw new Lh(`Node ${o.name} is scheduled to run before its input ${l.name}.`)}}}function Qj(e){let t=new Map(e.map((o,l)=>[o.name,l])),r=Number.MAX_SAFE_INTEGER,n=e.map((o,l)=>Qs(o)?r:l),a=o=>{let l=n[t.get(o.name)];return l??-1},s=e.map((o,l)=>o.children.map(a).reduce((p,u)=>Math.max(p,u),n[l])),i=new Map;for(let o=0;o<e.length;++o){let l=s[o];if(l===r)continue;let p=e[o],u=e[l];i.has(u.name)||i.set(u.name,[]),i.get(u.name).push(p)}return i}var eq=new Set(["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"]),tq=new Set(["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"]),rq=new Set(["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"]);function Qs(e){return eq.has(e.op)}function nq(e){return tq.has(e.op)}function aq(e){return rq.has(e.op)}var i1=class r_{get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(t){let r=Object.keys(t).map(n=>t[n].map(a=>a.id));this._weightIds=[].concat(...r),this._weightMap=t}set resourceManager(t){this._resourceManager=t}get 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Map,this._weightMap={},this.SEPARATOR=",",this._functions={},this._functionExecutorMap={},this.keepIntermediateTensors=!1,this._outputs=t.outputs,this._inputs=t.inputs,this._initNodes=t.initNodes,this._signature=t.signature,this._functions=t.functions,t.functions!=null&&Object.keys(t.functions).forEach(n=>{this._functionExecutorMap[n]=new r_(t.functions[n],this)})}getCompilationKey(t,r){let n=t.map(s=>s.name).sort(),a=r.map(s=>s.name).sort();return n.join(this.SEPARATOR)+"--"+a.join(this.SEPARATOR)}compile(t,r){let n=s1(t,r,this.weightMap,this._initNodes),{missingInputs:a,dynamicNode:s,syncInputs:i}=n;if(s!=null)throw new Error(`This execution contains the node '${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(a.length>0){let p=r.map(d=>d.name),u=Object.keys(t);throw new Error(`Cannot compute the outputs [${p}] from the provided inputs [${u}]. Missing the following inputs: [${a}]`)}let o=Zj(this.graph,n),l=Qj(o);return{orderedNodes:o,nodeLiveUntilMap:l}}cloneAndKeepTensor(t){if(t==null)return null;let r=t.clone();return Pt(r),r}cloneTensorList(t){return t?t.map(r=>this.cloneAndKeepTensor(r)):null}cloneTensorMap(t){return Object.fromEntries(Object.entries(t).map(([r,n])=>[r,this.cloneTensorList(n)]))}execute(t,r){this.disposeIntermediateTensors(),t=this.mapInputs(t);let n=Object.keys(t).sort();this.checkInputs(t),this.checkInputShapeAndType(t),r=this.mapOutputs(r),this.checkOutputs(r);let a=n.map(h=>this.graph.nodes[Vr(h)[0]]),s=r.map(h=>Vr(h)[0]),i=new Set(s),o=s.map(h=>this.graph.nodes[h]);o.length===0&&(o=this._outputs);let l=this.getCompilationKey(a,o),p=this.compiledMap.get(l);p==null&&(p=this.compile(t,o),this.compiledMap.set(l,p));try{this.keepIntermediateTensors=j().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(h){this.keepIntermediateTensors=!1,console.warn(h.message)}let u={},d={};return W(()=>{let h=new a1(this.weightMap,u,d,this.functionExecutorMap,this.parseNodeNameCache),c=Object.assign({},this.weightMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap)),Object.keys(t).forEach(y=>{let[b,x]=Vr(y,h),v=[];v[x]=t[y],c[b]=v,this.keepIntermediateTensors&&(this.clonedTensorsMap[b]=this.cloneTensorList(v))});let f=this.getFrozenTensorIds(c),{orderedNodes:m,nodeLiveUntilMap:g}=p;for(let y of m){if(c[y.name])continue;let b=n1(y,c,h,this._resourceManager);if(k.isPromise(b))throw new Error(`The execution of the op '${y.op}' returned a promise. Please use model.executeAsync() instead.`);c[y.name]=b,this.keepIntermediateTensors&&(this.clonedTensorsMap[y.name]=this.cloneTensorList(b)),this.checkTensorForDisposalWithNodeLiveUntilInfo(y,c,h,f,i,g.get(y.name))}return this.parent==null&&h.dispose(f),r.map(y=>ar(y,c,h))})}getFrozenTensorIds(t){let r=[].concat.apply([],Object.keys(t).map(n=>t[n]).map(n=>n.map(a=>a.id)));return new Set(r)}checkTensorForDisposal(t,r,n,a,s,i,o){if(!(Qs(r)||i.has(t))){for(let l of n[t])l!=null&&(o[l.id]=(o[l.id]||0)+r.children.length);for(let l of r.inputs){if(Qs(l))continue;let p=Y0(l.name,n,a);if(p!=null)for(let u of p){if(!u||u.kept||s.has(u.id))continue;let d=o[u.id];d===1?(u.dispose(),delete o[u.id]):d!=null&&o[u.id]--}}}}checkTensorForDisposalWithNodeLiveUntilInfo(t,r,n,a,s,i){function o(l){return Qs(l)||s.has(l.name)}if(!(Qs(t)||i==null))for(let l of i){if(o(l))continue;let p=Y0(l.name,r,n);for(let u of p)!u||u.kept||a.has(u.id)||u.dispose()}}async executeAsync(t,r){return this._executeAsync(t,r)}disposeIntermediateTensors(){this.clonedTensorsMap&&(Object.values(this.clonedTensorsMap).forEach(t=>{for(let r of t)r&&!r.isDisposed&&r.dispose()}),this.clonedTensorsMap=null)}getIntermediateTensors(){return this.clonedTensorsMap}async _executeAsync(t,r,n=!1,a={},s={}){this.disposeIntermediateTensors(),n||(t=this.mapInputs(t),this.checkInputs(t),this.checkInputShapeAndType(t),r=this.mapOutputs(r),this.checkOutputs(r));try{this.keepIntermediateTensors=j().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(h){this.keepIntermediateTensors=!1,console.warn(h.message)}let i=new a1(this.weightMap,a,s,this.functionExecutorMap,this.parseNodeNameCache);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap));let o=await this.executeWithControlFlow(t,i,r,n),l=r.map(h=>ar(h,o,i)),p=l.map(h=>h.id),u=Object.keys(t).map(h=>t[h].id),d=new Set([...p,...u,...this.weightIds]);return Object.values(o).forEach(h=>{h.forEach(c=>{c&&!c.isDisposed&&!d.has(c.id)&&c.dispose()})}),this.parent==null&&i.dispose(d),l}async executeFunctionAsync(t,r,n){let a=t.reduce((s,i,o)=>(s[this.inputs[o].name]=i,s),{});return this._executeAsync(a,this.outputNodes,!0,r,n)}async executeWithControlFlow(t,r,n,a){let s=Object.keys(t),i=s.map(v=>this.graph.nodes[Vr(v)[0]]),o=n.map(v=>Vr(v)[0]),l=new Set(o),p=o.map(v=>this.graph.nodes[v]);p.length===0&&(p=this._outputs);let{usedNodes:u,missingInputs:d,dynamicNode:h,syncInputs:c}=s1(t,p,this.weightMap,this._initNodes),f=[...i,...this.graph.weights,...this._initNodes||[]].map(v=>({node:v,contexts:r.currentContext})),m=Object.assign({},this.weightMap);Object.keys(t).forEach(v=>{let[w,N]=Vr(v),T=[];T[N]=t[v],m[w]=T});let g={},y=this.getFrozenTensorIds(m),b={};for(;f.length>0;){let v=this.processStack(i,f,r,m,b,y,l,g,u);await Promise.all(v)}h==null&&!a&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let x=p.filter(v=>!Qs(v)&&!ar(v.name,m,r)).map(v=>v.name);if(x.length>0){let v="";throw h!=null&&(v=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${c}]`),new Error(`Cannot compute the outputs [${x}] from the provided inputs [${s}]. Consider providing the following inputs: [${d}]. ${v}`)}return m}processStack(t,r,n,a,s,i,o,l,p){let u=[];for(;r.length>0;){let d=r.pop();n.currentContext=d.contexts;let h="";if(d.node.op==="Enter"&&I("isConstant",d.node,a,n)&&([h]=Ia(d.node.name,n)),a[d.node.name]==null){let c=n1(d.node,a,n,this._resourceManager);h||([h]=Ia(d.node.name,n));let f=n.currentContext;k.isPromise(c)?u.push(c.then(m=>(a[h]=m,this.keepIntermediateTensors&&(this.clonedTensorsMap[h]=this.cloneTensorList(m)),n.currentContext=f,this.checkTensorForDisposal(h,d.node,a,n,i,o,l),this.processChildNodes(d.node,r,n,a,s,p),m))):(a[h]=c,this.keepIntermediateTensors&&(this.clonedTensorsMap[h]=this.cloneTensorList(c)),this.checkTensorForDisposal(h,d.node,a,n,i,o,l),this.processChildNodes(d.node,r,n,a,s,p))}else this.processChildNodes(d.node,r,n,a,s,p)}return u}processChildNodes(t,r,n,a,s,i){t.children.forEach(o=>{let[l]=Ia(o.name,n);s[l]||!i.has(o.name)||(o.op==="Merge"?o.inputNames.some(p=>!!ar(p,a,n))&&(s[l]=!0,r.push({contexts:n.currentContext,node:o})):o.inputNames.every(p=>!!ar(p,a,n))&&(s[l]=!0,r.push({contexts:n.currentContext,node:o})))})}dispose(){Object.keys(this.weightMap).forEach(t=>this.weightMap[t].forEach(r=>r.dispose()))}checkInputShapeAndType(t){Object.keys(t).forEach(r=>{let n=t[r],[a]=Vr(r),s=this.graph.nodes[a];if(s.attrParams.shape&&s.attrParams.shape.value){let i=s.attrParams.shape.value,o=i.length===n.shape.length&&n.shape.every((l,p)=>i[p]===-1||i[p]===l);k.assert(o,()=>`The shape of dict['${s.name}'] provided in model.execute(dict) must be [${i}], but was [${n.shape}]`)}s.attrParams.dtype&&s.attrParams.dtype.value&&k.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 ${n.dtype}`)})}mapInputs(t){var r,n;let a={};for(let s in t){let i=(n=(r=this._signature)===null||r===void 0?void 0:r.inputs)===null||n===void 0?void 0:n[s];i!=null?a[i.name]=t[s]:a[s]=t[s]}return a}checkInputs(t){let r=Object.keys(t).filter(n=>{let[a]=Vr(n);return this.graph.nodes[a]==null});if(r.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${r}] that are not part of graph`)}mapOutputs(t){return t.map(r=>{var n,a;let s=(a=(n=this._signature)===null||n===void 0?void 0:n.outputs)===null||a===void 0?void 0:a[r];return s!=null?s.name:r},{})}checkOutputs(t){t.forEach(r=>{let[n]=Vr(r);if(!this.graph.nodes[n])throw new Error(`The output '${r}' is not found in the graph`)})}},sq=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},iq="?tfjs-format=file",oq="model.json",Fv=class{get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}constructor(e,t={},r=or){this.modelUrl=e,this.loadOptions=t,this.version="n/a",this.io=r,t==null&&(this.loadOptions={}),this.resourceManager=new sq}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=this.io.browserHTTPRequest(e,this.loadOptions);else{let t=this.io.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(this.io.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=this.handler.load();return k.isPromise(e)?e.then(t=>t.getWeightStream==null?this.loadSync(t):this.loadStreaming(t)):this.loadSync(e)}loadSync(e){let t=this.io.decodeWeights(e.weightData,e.weightSpecs);return this.loadWithWeightMap(e,t)}async loadStreaming(e){if(e.getWeightStream==null)throw new Error("Model artifacts missing streamWeights function");let t=await sI(e.getWeightStream(),e.weightSpecs);return this.loadWithWeightMap(e,t)}loadWithWeightMap(e,t){this.artifacts=e;let r=this.artifacts.modelTopology,n=this.artifacts.signature;if(this.artifacts.userDefinedMetadata!=null){let a=this.artifacts.userDefinedMetadata;a.signature!=null&&(n=a.signature),a.structuredOutputKeys!=null&&(this.structuredOutputKeys=a.structuredOutputKeys)}if(this.signature=n,this.version=`${r.versions.producer}.${r.versions.minConsumer}`,this.executor=new i1(Q0.Instance.transformGraph(r,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(t),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let a=Q0.Instance.transformGraph(e.modelInitializer);this.initializer=new i1(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializerSignature=e.initializerSignature}return!0}async save(e,t){if(typeof e=="string"){let r=this.io.getSaveHandlers(e);if(r.length===0)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(r.length>1)throw new Error(`Found more than one (${r.length}) save handlers for URL '${e}'`);e=r[0]}if(e.save==null)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return e.save(this.artifacts)}addStructuredOutputNames(e){if(this.structuredOutputKeys){let t=e instanceof ze?[e]:e,r={};return t.forEach((n,a)=>r[this.structuredOutputKeys[a]]=n),r}return e}predict(e,t){let r=this.execute(e,this.outputNodes);return this.addStructuredOutputNames(r)}async predictAsync(e,t){let r=await this.executeAsync(e,this.outputNodes);return this.addStructuredOutputNames(r)}normalizeInputs(e){var t;if(!(e instanceof ze)&&!Array.isArray(e)){let a=(t=this.signature)===null||t===void 0?void 0:t.inputs;if(a!=null)for(let s in a){let i=a[s];i.resourceId!=null&&(e[s]=this.resourceIdToCapturedInput[i.resourceId])}return e}e=Array.isArray(e)?e:[e];let r=Object.keys(this.resourceIdToCapturedInput).length;if(e.length+r!==this.inputNodes.length)throw new Error(`Input tensor count mismatch, the graph model has ${this.inputNodes.length-r} non-resource placeholders, while there are ${e.length} input tensors provided.`);let n=0;return this.inputNodes.reduce((a,s)=>{var i,o,l;let p=(l=(o=(i=this.signature)===null||i===void 0?void 0:i.inputs)===null||o===void 0?void 0:o[s])===null||l===void 0?void 0:l.resourceId;return p!=null?a[s]=this.resourceIdToCapturedInput[p]:a[s]=e[n++],a},{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}executeInitializerGraph(){return this.initializer==null?[]:this.initializerSignature==null?this.initializer.execute({},[]):this.initializer.execute({},Object.keys(this.initializerSignature.outputs))}async executeInitializerGraphAsync(){return this.initializer==null?[]:this.initializerSignature==null?this.initializer.executeAsync({},[]):this.initializer.executeAsync({},Object.keys(this.initializerSignature.outputs))}setResourceIdToCapturedInput(e){if(this.resourceIdToCapturedInput={},this.initializerSignature){let t=this.initializerSignature.outputs,r=Object.keys(t);for(let n=0;n<r.length;n++){let a=r[n],s=t[a];this.resourceIdToCapturedInput[s.resourceId]=e[n]}}}execute(e,t){this.resourceIdToCapturedInput==null&&this.setResourceIdToCapturedInput(this.executeInitializerGraph()),e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let r=this.executor.execute(e,t);return r.length>1?r:r[0]}async executeAsync(e,t){this.resourceIdToCapturedInput==null&&this.setResourceIdToCapturedInput(await this.executeInitializerGraphAsync()),e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let r=await this.executor.executeAsync(e,t);return r.length>1?r:r[0]}getIntermediateTensors(){return this.executor.getIntermediateTensors()}disposeIntermediateTensors(){this.executor.disposeIntermediateTensors()}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,r)=>(t[r]=[e[r]],t),{})}dispose(){this.executor.dispose(),this.initializer&&(this.initializer.dispose(),this.resourceIdToCapturedInput&&Ce(this.resourceIdToCapturedInput)),this.resourceManager.dispose()}};async function lq(e,t={},r=or){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&typeof e=="string"&&(e=pq(e));let n=new Fv(e,t,r);return await n.load(),n}function uq(e){if(e==null)throw new Error("modelUrl in loadGraphModelSync() cannot be null. Please provide model artifacts or an IOHandler that loads the model");let t;if(e instanceof Array){let[n,a]=e;if(!n)throw new Error("modelJSON must be the first element of the array");if(!a||!(a instanceof ArrayBuffer))throw new Error("An ArrayBuffer of weights must be the second element of the array");if(!("modelTopology"in n))throw new Error("Model JSON is missing 'modelTopology'");if(!("weightsManifest"in n))throw new Error("Model JSON is missing 'weightsManifest'");let s=or.getWeightSpecs(n.weightsManifest),i=or.getModelArtifactsForJSONSync(n,s,a);t=or.fromMemorySync(i)}else if("load"in e)t=e;else if("modelTopology"in e&&"weightSpecs"in e&&"weightData"in e)t=or.fromMemorySync(e);else throw new Error("Unknown model format");let r=new Fv(t);return r.load(),r}function pq(e){return e.endsWith("/")||(e=e+"/"),`${e}${oq}${iq}`}var 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n=e[0];if(r.has(n))throw new Error("Circular references are not supported.");let a=t(e);if(a.recurse&&a.value!==null)throw new Error("A deep zip function may not return both a value and recurse=true.");if(a.recurse)if(Pl(n)){let s=Array.isArray(n)?[]:{};r.add(n);for(let i in n){let o=e.map(p=>p[i]),l=a_(o,t,r);s[i]=l}return r.delete(n),s}else throw new Error(`Can't recurse into non-iterable type: ${n}`);else return a.value}function s_(e){return e===null?null:Pl(e[0])?{value:null,recurse:!0}:{value:e,recurse:!1}}async function i_(e,t){let r=new Map;Ac(e,t,r);for(let n of Array.from(r.keys())){let a=r.get(n);if(k.isPromise(a)){let s=await a;r.set(n,s)}}return Ac(e,t,r)}function Pl(e){let t=!1;if(j().get("IS_BROWSER"))t=e instanceof TextDecoder;else{let{StringDecoder:r}=Nk();t=e instanceof r}return e!=null&&!ArrayBuffer.isView(e)&&(Array.isArray(e)||typeof e=="object"&&!(e instanceof ze)&&!(e instanceof Promise)&&!t)}function gq(e){return e==null||yq(e)||Array.isArray(e)||typeof 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o_{constructor(){super(u_.INITIAL_CAPACITY)}isFull(){return!1}push(t){super.isFull()&&this.expand(),super.push(t)}unshift(t){super.isFull()&&this.expand(),super.unshift(t)}expand(){let t=this.capacity*2,r=new Array(t),n=this.length();for(let a=0;a<n;a++)r[a]=this.get(this.wrap(this.begin+a));this.data=r,this.capacity=t,this.doubledCapacity=2*this.capacity,this.begin=0,this.end=n}};l_.INITIAL_CAPACITY=32;function p_(e){return new kq(e)}function Rv(e){return new Iq(e)}function vq(e,t){return new d_(e,t)}function wq(e,t=as.FAIL){return new Fq(e,t)}var Qt=class{async toArray(){let e=[],t=await this.next();for(;!t.done;)e.push(t.value),t=await this.next();return e}async toArrayForTest(){let e=this.prefetch(100),t=[],r=await e.next();for(;!r.done;)t.push(r.value),r=await e.next();return t}async resolveFully(){let e=await this.next();for(;!e.done;)e=await this.next()}async resolveWhile(e){let t=await this.next(),r=e(t.value);for(;!t.done&&r;)t=await this.next(),r=e(t.value)}handleErrors(e){return new $q(this,e)}filter(e){return new Cq(this,e)}map(e){return new Eq(this,e)}mapAsync(e){return new o1(this,e)}serialMapAsync(e){return new o1(this,e).serial()}flatmap(e){return new Aq(this,e)}async forEachAsync(e){return this.map(e).resolveFully()}async serialForEach(e){return this.serialMapAsync(e).resolveWhile(t=>t===!0)}rowMajorBatch(e,t=!0){return new Tq(this,e,t)}columnMajorBatch(e,t=!0,r=s_){return this.rowMajorBatch(e,t).map(n=>mq(n,r))}concatenate(e,t){return new d_(p_([this,e]),t)}take(e){return e<0||e==null?this:new _q(this,e)}skip(e){return e<0||e==null?this:new Nq(this,e)}prefetch(e){return new h_(this,e)}shuffle(e,t){return new Rq(this,e,t)}serial(){return new Sq(this)}},kq=class extends Qt{constructor(e){super(),this.items=e,this.trav=0}summary(){return`Array of ${this.items.length} items`}async next(){if(this.trav>=this.items.length)return{value:null,done:!0};let e=this.items[this.trav];return this.trav++,{value:bq(e),done:!1}}},Iq=class extends Qt{constructor(e){super(),this.nextFn=e}summary(){return"Function call"}async next(){try{return this.nextFn()}catch(e){throw e.message=`Error thrown while iterating through a dataset: ${e.message}`,e}}},Sq=class extends Qt{constructor(e){super(),this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},Nq=class extends Qt{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++<this.maxCount;){let e=await this.upstream.next();if(e.done)return e;Ce(e.value)}return this.upstream.next()}},_q=class extends Qt{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},Tq=class extends Qt{constructor(e,t,r=!0){super(),this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=r,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},Cq=class extends Qt{constructor(e,t){super(),this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;Ce(e.value)}}},Eq=class extends Qt{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Mn.getTensorsInContainer(e.value),r=this.transform(e.value),n=Mn.getTensorsInContainer(r);for(let a of t)Mn.isTensorInList(a,n)||a.dispose();return{value:r,done:!1}}},$q=class extends Qt{constructor(e,t){super(),this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},o1=class extends Qt{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Mn.getTensorsInContainer(e.value),r=await this.transform(e.value),n=Mn.getTensorsInContainer(r);for(let a of t)Mn.isTensorInList(a,n)||a.dispose();return{value:r,done:!1}}},Dv=class extends Qt{constructor(){super(),this.outputQueue=new l_,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},Aq=class extends Dv{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=Mn.getTensorsInContainer(e.value),r=this.transform(e.value),n=Mn.getTensorsInContainer(r);this.outputQueue.pushAll(r);for(let a of t)Mn.isTensorInList(a,n)||a.dispose();return!0}},d_=class extends Qt{constructor(e,t){super(),this.baseErrorHandler=t,this.lastRead=null,this.iterator=null,this.moreIterators=e}summary(){return"TODO: fill in upstream of chained summaries -> Chained"}async next(){return this.lastRead=this.readFromChain(this.lastRead),this.lastRead}async readFromChain(e){if(await e,this.iterator==null){let r=await this.moreIterators.next();if(r.done)return{value:null,done:!0};this.iterator=r.value,this.baseErrorHandler!=null&&(this.iterator=this.iterator.handleErrors(this.baseErrorHandler))}let t=await this.iterator.next();return t.done?(this.iterator=null,this.readFromChain(e)):t}},as;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(as||(as={}));var Fq=class extends Qt{constructor(e,t=as.FAIL){super(),this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,r=0;function n(s){return s instanceof Qt?{value:s.next().then(i=>(t++,i.done&&r++,i.value)),recurse:!1}:{value:null,recurse:!0}}let a=await i_(this.iterators,n);if(t===r)return{value:null,done:!0};if(r>0)switch(this.mismatchMode){case as.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case as.SHORTEST:return{value:null,done:!0};case as.LONGEST:}return this.count++,{value:a,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},h_=class extends Qt{constructor(e,t){super(),this.upstream=e,this.bufferSize=t,this.buffer=new o_(t)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){let e=this.upstream.next();this.buffer.push(e)}}next(){return this.refill(),this.buffer.shift()}},Rq=class extends h_{constructor(e,t,r){super(e,t),this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=cq.alea(r||k.now().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}randomInt(e){return Math.floor(this.random()*e)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){let e=this.chooseIndex(),t=await this.buffer.shuffleExcise(e);if(t.done)this.upstreamExhausted=!0;else return this.refill(),t}return{value:null,done:!0}}},ip=class{constructor(){this.size=null}batch(e,t=!0){let r=this;k.assert(e>0,()=>`batchSize needs to be positive, but it is
${e}`);let n;return this.size===1/0||this.size==null?n=this.size:t?n=Math.ceil(this.size/e):n=Math.floor(this.size/e),Ur(async()=>(await r.iterator()).columnMajorBatch(e,t,Oq),n)}concatenate(e){let t=this,r;return this.size===1/0||e.size===1/0?r=1/0:this.size!=null&&e.size!=null?r=this.size+e.size:r=null,Ur(async()=>(await t.iterator()).concatenate(await e.iterator()),r)}filter(e){let t=this,r;return this.size===1/0?r=1/0:r=null,Ur(async()=>(await t.iterator()).filter(n=>W(()=>e(n))),r)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return Ur(async()=>(await t.iterator()).map(r=>W(()=>e(r))),this.size)}mapAsync(e){let t=this;return Ur(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return Ur(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,r;return this.size!=null&&e>0?r=this.size*e:e===0?r=0:this.size!=null&&(e===void 0||e<0)?r=1/0:r=null,Ur(async()=>{let n=Rv(async()=>({value:await t.iterator(),done:!1}));return vq(n.take(e))},r)}skip(e){let t=this,r;return this.size!=null&&e>=0&&this.size>=e?r=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?r=0:r=null,Ur(async()=>(await t.iterator()).skip(e),r)}shuffle(e,t,r=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified. If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let n=this,a=hq.alea(t||k.now().toString());return Ur(async()=>{let s=a.int32();return r&&(s+=a.int32()),(await n.iterator()).shuffle(e,s.toString())},this.size)}take(e){let t=this,r;return this.size!=null&&this.size>e?r=e:this.size!=null&&this.size<=e?r=this.size:r=null,Ur(async()=>(await t.iterator()).take(e),r)}async toArray(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};ip.MAX_BUFFER_SIZE=1e4;function Ur(e,t=null){return new class extends ip{constructor(){super(...arguments),this.size=t}async iterator(){return e()}}}function Dq(e){return Ur(async()=>p_(e),e.length)}function Mq(e){if(!Pl(e))throw new Error("The argument to zip() must be an object or array.");let t;if(Array.isArray(e))for(let r=0;r<e.length;r++)t=t==null?e[r].size:Math.min(t,e[r].size);else if(e instanceof Object)for(let r in e)t=t==null?e[r].size:Math.min(t,e[r].size);return Ur(async()=>{let r=await i_(e,n=>{if(n instanceof ip)return{value:n.iterator(),recurse:!1};if(Pl(n))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return wq(r,as.SHORTEST)},t)}function Oq(e){if(e===null)return null;let t=e[0];return gq(t)?{value:Lq(e),recurse:!1}:{value:null,recurse:!0}}function Lq(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof ze?Mt(e):yr(e)}var c_=class extends ip{constructor(e){super(),this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
`).map(e=>(e.endsWith("\r")&&(e=e.slice(0,-1)),e))}},zh='"',Np=Symbol("out"),l1=Symbol("field"),Ph=Symbol("quote"),Hm=Symbol("quoteafterquote"),u1=Symbol("quoteinquote"),f_=class extends ip{async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&k.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((n,a)=>(n[a]=n[a]+1||1,n),{}),r=Object.keys(t).filter(n=>t[n]>1);if(k.assert(r.length===0,()=>"Duplicate column names found: "+r.toString()),this.columnConfigs){for(let n of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(n)===-1)throw new Error('The key "'+n+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let e=await(await this.base.iterator()).next();if(e.done)throw new Error("No data was found for CSV parsing.");let t=e.value;return this.parseRow(t,!1)}else return null}constructor(e,t){super(),this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new c_(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(k.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),r={},n={};for(let a=0;a<this.fullColumnNames.length;a++){let s=this.fullColumnNames[a],i=this.columnConfigs?this.columnConfigs[s]:null;if(!(this.configuredColumnsOnly&&!i)){let o=t[a],l=null;if(o==="")if(i&&i.default!==void 0)l=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${s} is empty in this line: ${e}`);l=void 0}else{let p=Number(o);if(isNaN(p))i&&i.dtype==="bool"?l=this.getBoolean(o):l=o;else if(!i||!i.dtype)l=p;else switch(i.dtype){case"float32":l=p;break;case"int32":l=Math.floor(p);break;case"bool":l=this.getBoolean(o);break;default:l=p}}i&&i.isLabel?n[s]=l:r[s]=l}}return Object.keys(n).length===0?r:{xs:r,ys:n}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let r=[],n=0,a=e.length,s=Np;for(let i=0;i<a;i++)switch(s){case Np:switch(e.charAt(i)){case zh:n=i+1,s=Ph;break;case this.delimiter:if(n=i+1,this.delimiter===" "&&this.delimWhitespace)break;r.push(""),s=Np;break;default:s=l1,n=i;break}break;case l1:switch(e.charAt(i)){case this.delimiter:r.push(e.substring(n,i)),s=Np,n=i+1;break}break;case Ph:switch(e.charAt(i)){case zh:s=Hm;break}break;case Hm:switch(e.charAt(i)){case this.delimiter:r.push(e.substring(n,i-1)),s=Np,n=i+1;break;case zh:s=Ph;break;default:s=u1;break}break;case u1:switch(e.charAt(i)){case zh:s=Ph;break}break}if(s===Hm?r.push(e.substring(n,a-1)):r.push(e.substring(n)),t&&r.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${r}`);return r}},zq=class m_ extends Qt{constructor(t){super(),this.microphoneConfig=t,this.isClosed=!1,this.fftSize=t.fftSize||1024;let r=Math.log2(this.fftSize);if(this.fftSize<0||r<4||r>14||!Number.isInteger(r))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(!j().get("IS_BROWSER"))throw new Error("microphone API is only supported in browser environment.");let r=new m_(t);return await r.start(),r}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 r=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,r.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,r,n=await this.getAudioData();if(this.includeSpectrogram){let a=this.flattenQueue(n.freqDataQueue);t=this.getTensorFromAudioDataArray(a,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let a=this.flattenQueue(n.timeDataQueue);r=this.getTensorFromAudioDataArray(a,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:t,waveform:r},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let t=[],r=[],n=0;return new Promise(a=>{let s=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&a({freqDataQueue:t,timeDataQueue:r}),t.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),r.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(s),a({freqDataQueue:t,timeDataQueue:r}))},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 r=t[0].length,n=new Float32Array(t.length*r);return t.forEach((a,s)=>n.set(a,s*r)),n}getTensorFromAudioDataArray(t,r){let n=new Float32Array(k.sizeFromShape(r));return n.set(t,n.length-t.length),yr(n,r)}},Pq=class g_ extends Qt{constructor(t,r){if(super(),this.webcamVideoElement=t,this.webcamConfig=r,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=Qe([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,a=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,s=(1-n)/2,i=(1-a)/2,o=s+n,l=a+i;this.cropBox=ia([i,s,l,o],[1,4])}else this.cropBox=ia([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(t,r={}){if(!j().get("IS_BROWSER"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!t){if(t=document.createElement("video"),!r.resizeWidth||!r.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");t.width=r.resizeWidth,t.height=r.resizeHeight}let n=new g_(t,r);return await n.start(),n}async start(){this.webcamConfig.facingMode&&k.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=Yd.fromPixels(this.webcamVideoElement)}catch(r){throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(r)}`)}if(this.resize)try{return{value:this.cropAndResizeFrame(t),done:!1}}catch(r){throw new Error(`Error thrown cropping the video: ${r.message}`)}finally{t.dispose()}else return{value:t,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(t){return W(()=>{let r=Xt(se(t,"float32"),0),n;n=sn.cropAndResize(r,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let a=n.shape;return B(n,a.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(t=>t.stop());try{this.webcamVideoElement.srcObject=null}catch(t){console.log(t),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},y_=class{},b_=class extends Qt{split(e){return new Bq(this,e)}},Bq=class extends b_{constructor(e,t){super(),this.upstream=e,this.impl=new Wq(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Wq=class extends Dv{constructor(e,t){super(),this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let r of t.slice(0,-1))this.outputQueue.push(r);return this.carryover=t[t.length-1],!0}},Uq=class extends Qt{decodeUTF8(){return new Vq(this)}},Vq=class extends b_{constructor(e){super(),this.upstream=e,this.impl=new Gq(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Gq=class extends Dv{constructor(e){if(super(),this.upstream=e,j().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=Nk();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let r;return j().get("IS_BROWSER")?r=this.decoder.decode(t,{stream:!0}):r=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(r),!0}},x_=class extends Uq{constructor(e,t={}){super(),this.file=e,this.options=t,k.assert(e instanceof Uint8Array||(j().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((e,t)=>{let r=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,r)));else{let n=new FileReader;n.onload=s=>{let i=n.result;if(i instanceof 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E_=ya(e=>Math.ceil(e)),p5=Os(Wi,E_),d5={kernelName:Wi,backendName:"cpu",kernelFunc:p5};function Pv(e,t,r,n){let a=k.getArrayFromDType(r,k.sizeFromShape(t));if(n&&r!=="string"){let s=0;e.forEach(i=>{let o=k.sizeFromShape(i.shape);a.set(i.vals,s),s+=o})}else{let s=0;e.forEach(i=>{let o=r==="string"?_.fromUint8ToStringArray(i.vals):i.vals,l=0;for(let p=0;p<i.shape[0];++p){let u=p*t[1]+s;for(let d=0;d<i.shape[1];++d)a[u+d]=o[l++]}s+=i.shape[1]})}return a}var $_=Et((e,t)=>e===t?1:0),A_=Gt(pu,$_,null,"bool"),h5={kernelName:pu,backendName:"cpu",kernelFunc:A_},F_=ya(e=>Math.exp(e)),R_=Os(Qi,F_,"float32"),c5={kernelName:Qi,backendName:"cpu",kernelFunc:R_},D_=ya(e=>Math.expm1(e)),f5=Os(eo,D_),m5={kernelName:eo,backendName:"cpu",kernelFunc:f5},M_=ya(e=>Math.floor(e)),g5=Os(to,M_),y5={kernelName:to,backendName:"cpu",kernelFunc:g5},O_=Et((e,t)=>Math.floor(e/t)),b5=Gt(ro,O_,null,"int32"),x5={kernelName:ro,backendName:"cpu",kernelFunc:b5};function L_(e,t,r,n,a,s,i,o,l){let p=Le([n,s],r);for(let 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G_=ya(e=>Math.log(e)),C5=Os(po,G_),E5={kernelName:po,backendName:"cpu",kernelFunc:C5};function H_(e,t,r,n){let a=k.getTypedArrayFromDType(n,k.sizeFromShape(r));for(let s=0;s<a.length;++s){let i=s*t,o=e[i];for(let l=0;l<t;++l){let p=e[i+l];(Number.isNaN(p)||p>o)&&(o=p)}a[s]=o}return a}var j_=Et((e,t)=>Math.max(e,t)),$5=Gt(mo,j_),A5={kernelName:mo,backendName:"cpu",kernelFunc:$5},q_=Et((e,t)=>Math.min(e,t)),F5=Gt(xo,q_),R5={kernelName:xo,backendName:"cpu",kernelFunc:F5},Bv=Et((e,t)=>e*t),D5=Lv((e,t,r,n)=>({real:e*r-t*n,imag:e*n+t*r})),ym=Gt(ko,Bv,D5),M5={kernelName:ko,backendName:"cpu",kernelFunc:ym};function K_(e,t,r){let n=k.createScalarValue(-1,r);return Bv([],t,n,e,r)}function O5(e){let{inputs:t,backend:r}=e,{x:n}=t;ye(n,"neg");let a=r.data.get(n.dataId).values,[s,i]=K_(a,n.shape,n.dtype);return r.makeTensorInfo(i,n.dtype,s)}var L5={kernelName:Nu,backendName:"cpu",kernelFunc:O5},X_=Et((e,t)=>e!==t?1:0),z5=Gt(_u,X_,null,"bool"),P5={kernelName:_u,backendName:"cpu",kernelFunc:z5};function Wv(e,t,r,n,a){let s=t.length,i=k.sizeFromShape(t),o=k.computeStrides(t),l=k.computeStrides(a),p=k.getTypedArrayFromDType(r,k.sizeFromShape(a));for(let u=0;u<i;++u){let d=k.indexToLoc(u,s,o),h=new Array(d.length);for(let f=0;f<h.length;f++)h[f]=d[n[f]];let c=k.locToIndex(h,s,l);p[c]=e[u]}return p}function Mr(e){let{inputs:t,attrs:r,backend:n}=e,{x:a}=t,{perm:s}=r;ye(a,"transpose");let i=a.shape.length,o=new Array(i);for(let u=0;u<o.length;u++)o[u]=a.shape[s[u]];let l=n.data.get(a.dataId).values,p=Wv(l,a.shape,a.dtype,s,o);return{dataId:n.write(p,o,a.dtype),shape:o,dtype:a.dtype}}var B5={kernelName:Ta,backendName:"cpu",kernelFunc:Mr};function Z_(e,t,r,n){let[a,s]=_.computeOutAndReduceShapes(e,n),i=cn(t,"int32"),o=k.makeZerosTypedArray(k.sizeFromShape(a),i),l=k.sizeFromShape(s);for(let p=0;p<o.length;++p){let u=p*l,d=1;for(let h=0;h<l;++h)d*=r[u+h];o[p]=d}return{outVals:o,outShape:a,outDtype:i}}function W5(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n;ye(a,"prod");let o=a.shape.length,l=k.parseAxisParam(s,a.shape),p=_.getAxesPermutation(l,o),u=l,d=a,h=[];p!=null&&(d=Mr({inputs:{x:a},backend:r,attrs:{perm:p}}),h.push(d),u=_.getInnerMostAxes(u.length,o));let c=r.data.get(d.dataId).values,{outVals:f,outShape:m,outDtype:g}=Z_(d.shape,d.dtype,c,u),y=m;return i&&(y=_.expandShapeToKeepDim(m,l)),h.forEach(b=>r.disposeIntermediateTensorInfo(b)),r.makeTensorInfo(y,g,f)}var U5={kernelName:To,backendName:"cpu",kernelFunc:W5};function V5(e,t,r){e.forEach((n,a)=>{if(n<0||n>=r){let s=k.indexToLoc(a,t.length,k.computeStrides(t)).join(",");throw new Error(`indices[${s}] = ${n} is not in [0, ${r})`)}})}function G5(e,t){for(let r=0;r<e.length;++r){let n=e[r],a=r===e.length-1?t:e[r+1].length;if(n.length===0)throw new Error("Ragged splits may not be empty");if(n[0]<0)throw new Error("Ragged splits must be 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i=p1(t,2)[1],o=p1(s,2)[1],l=0;for(let p of r)for(let u=p[0];u<p[1];++u){for(let d=0;d<n;++d)a[l*o+d]=e[u*i+d];++l}}function K5(e,t,r,n,a){let s=t.slice();s[0]=a;let i=k.getArrayFromDType(r,k.sizeFromShape(s)),o=e.length,l=o===0?0:o/t[0];return q5(e,t,n,l,i,s),[i,s]}function J_(e,t,r,n,a,s,i,o){if(e.length===0)throw new Error("paramsNestedSplits must be non empty");if(t[0].length===0)throw new Error("Split tensors must not be scalars");let l=t[0][0]-1;if(V5(s,i,l),n.length===0)throw new Error("params.rank must be nonzero");let p=n[0],{outSplits:u,valueSlices:d,numValues:h}=H5(s,i,e,p),c=j5(u),f=K5(r,n,a,d,h);return[c,f[0],f[1]]}var d1=2147483647;function Y_(e,t,r,n,a,s,i){if(t.length>1)throw new Error("starts must be a scalar or vector");if(a.length>1)throw new Error("limits must be a scalar or vector");if(i.length>1)throw new Error("deltas must be a scalar or vector");let o=t.length===0,l=a.length===0,p=i.length===0,u=[];o||u.push(t[0]),l||u.push(a[0]),p||u.push(i[0]);for(let g=1;g<u.length;++g)if(u[g]!==u[g-1])throw new Error("starts, limits, and deltas must have the same shape");let d=u.length===0?1:u[0],h=k.getArrayFromDType("int32",d+1);h[0]=0;for(let g=0;g<d;++g){let y=o?e[0]:e[g],b=l?n[0]:n[g],x=p?s[0]:s[g];if(x===0)throw new Error("Requires delta != 0");let v;if(x>0&&b<y||x<0&&b>y)v=0;else if(v=Math.ceil(Math.abs((b-y)/x)),v>d1)throw new Error(`Requires ((limit - start) / delta) <= ${d1}`);h[g+1]=h[g]+v}let c=h[d],f=k.getArrayFromDType(r,c),m=0;for(let g=0;g<d;++g){let y=h[g+1]-h[g],b=o?e[0]:e[g],x=p?s[0]:s[g];for(let v=0;v<y;++v)f[m++]=b,b+=x}return[h,f]}var xn=_.RowPartitionType,X5=class Gg{constructor(t,r,n,a,s,i,o,l,p,u){this.shape=t,this.shapeShape=r,this.values=n,this.valuesShape=a,this.valuesDType=s,this.defaultValue=i,this.defaultValueShape=o,this.rowPartitionValues=l,this.rowPartitionValuesShapes=p,this.rowPartitionTypes=_.getRowPartitionTypesHelper(u),this.raggedRank=_.getRaggedRank(this.rowPartitionTypes)}getRowPartitionTypeByDimension(t){return this.rowPartitionTypes[0]===xn.FIRST_DIM_SIZE?this.rowPartitionTypes[t+1]:this.rowPartitionTypes[t]}getRowPartitionTensor(t){return this.rowPartitionTypes[0]===xn.FIRST_DIM_SIZE?this.rowPartitionValues[t+1]:this.rowPartitionValues[t]}getMaxWidth(t){let r=this.getRowPartitionTensor(t-1);switch(this.getRowPartitionTypeByDimension(t-1)){case xn.VALUE_ROWIDS:return Gg.getMaxWidthValueRowID(r);case xn.ROW_SPLITS:return Gg.getMaxWidthRowSplit(r);default:throw new Error(`Cannot handle partition type ${xn[this.getRowPartitionTypeByDimension(t-1)]}`)}}static getMaxWidthRowSplit(t){let r=t.length;if(r===0||r===1)return 0;let n=0;for(let a=0;a<r-1;++a){let s=t[a+1]-t[a];s>n&&(n=s)}return n}static getMaxWidthValueRowID(t){let r=t.length;if(r===0)return 0;let n=0,a=t[0],s=0;for(let i=1;i<r;++i){let o=t[i];o!==a&&(a=o,s=Math.max(i-n,s),n=i)}return Math.max(r-n,s)}tensorShapeFromTensor(t,r,n=!0){if(r.length===0){if(t[0]===-1)return[];throw new Error("The only valid scalar shape tensor is the fully unknown shape specified as -1.")}return c1(t,n)}calculateOutputSize(t){let r=this.valuesShape,n=this.defaultValueShape;_.validateDefaultValueShape(n,r);let a=this.tensorShapeFromTensor(this.shape,this.shapeShape),s=_.combineRaggedTensorToTensorShapes(this.raggedRank,a,r);s[0]<0&&(s[0]=t);for(let i=1;i<=this.raggedRank;++i)s[i]<0&&(s[i]=this.getMaxWidth(i));return s}calculateFirstParentOutputIndex(t,r,n){let a=Math.min(t,n),s=[],i=0;for(let o=0;o<a;++o,i+=r)s.push(i);for(let o=a;o<t;++o)s.push(-1);return k.assert(s.length===t,()=>"Final length of result must be equal to firstDimension."),s}calculateOutputIndexRowSplit(t,r,n,a){let s=t.length,i=[];for(let o=0;o<s-1;++o){let l=t[o+1]-t[o],p=Math.min(a,l),u=r[o];u===-1&&(p=0);for(let d=0;d<p;++d)i.push(u),u+=n;for(let d=0;d<l-p;++d)i.push(-1)}if(s>0&&i.length!==t[s-1])throw new Error("Invalid row split size.");return i}calculateOutputIndexValueRowID(t,r,n,a){let s=t.length,i=[];if(s===0)return[];let o=0,l=t[0];if(l>=r.length)throw new Error(`Got currentValueRowId=${l}, which is not less than ${r.length}`);let p=r[l];i.push(p);for(let u=1;u<s;++u){let d=t[u];if(d===l)p>=0&&(++o,o<a?p+=n:p=-1);else{if(o=0,l=d,d>=r.length)throw new Error(`Got nextValueRowId=${d} which is not less than ${r.length}`);p=r[d]}i.push(p)}if(i.length!==t.length)throw new Error("Invalid row ids.");return i}calculateOutputIndex(t,r,n,a){let s=this.getRowPartitionTensor(t),i=this.getRowPartitionTypeByDimension(t);switch(i){case xn.VALUE_ROWIDS:return this.calculateOutputIndexValueRowID(s,r,n,a);case xn.ROW_SPLITS:if(s.length-1>r.length)throw new Error(`Row partition size is greater than output size: ${s.length-1} > ${r.length}`);return this.calculateOutputIndexRowSplit(s,r,n,a);default:throw new Error(`Unsupported partition type: ${xn[i]}`)}}getFirstDimensionSize(){let t=this.rowPartitionValues[0];if(this.rowPartitionTypes.length===0)throw new Error("No row_partition_types given.");let r=this.rowPartitionTypes[0];switch(r){case xn.FIRST_DIM_SIZE:return t[0];case xn.VALUE_ROWIDS:throw new Error("Cannot handle VALUE_ROWIDS in first dimension.");case xn.ROW_SPLITS:return this.rowPartitionValuesShapes[0][0]-1;default:throw new Error(`Cannot handle type ${xn[r]}`)}}compute(){if(this.rowPartitionValues[0].length<=0)throw new Error("Invalid first partition input. Tensor requires at least one element.");let t=this.getFirstDimensionSize(),r=this.calculateOutputSize(t),n=new Array(this.raggedRank+1);n[n.length-1]=1;for(let i=n.length-2;i>=0;--i)n[i]=n[i+1]*r[i+1];let a=c1(r,!1),s=k.getArrayFromDType(this.valuesDType,k.sizeFromShape(a));if(n[0]*r[0]>0){let i=this.calculateFirstParentOutputIndex(t,n[0],r[0]);for(let o=1;o<=this.raggedRank;++o)i=this.calculateOutputIndex(o-1,i,n[o],r[o]);this.setOutput(this.raggedRank,i,s,a)}return[a,s]}setOutput(t,r,n,a){if(n.length===0)return;let s=this.values,i=n,o=a.slice();o=o.slice(t+1);let l=k.sizeFromShape(o),p=r.length,u=this.defaultValue;if(u.length!==l&&u.length!==1){let f=this.defaultValueShape;W(()=>{let m=B(u,f);u=ai(m,o).dataSync()})}let d=0,h=0,c=0;for(let f=0;f<=p;++f){let m=f<p?r[f]:-1;if(m===c){++c;continue}if(h<c){let g=s.subarray(d*l),y=i.subarray(h*l),b=(c-h)*l;h1(y,g,b)}if(f>=p){let 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o=k.parseAxisParam(s,a.shape),l=o,p=_.getAxesPermutation(l,a.shape.length),u=a;p!=null&&(u=Mr({inputs:{x:a},backend:r,attrs:{perm:p}}),l=_.getInnerMostAxes(l.length,a.shape.length)),_.assertAxesAreInnerMostDims("any",l,u.shape.length);let[d,h]=_.computeOutAndReduceShapes(u.shape,l),c=k.sizeFromShape(h),f=k.makeZerosTypedArray(k.sizeFromShape(d),u.dtype),m=r.data.get(u.dataId).values;for(let y=0;y<f.length;++y){let b=y*c,x=m[b];for(let v=0;v<c;++v){let w=m[b+v];x=x||w}f[y]=x}p!=null&&r.disposeIntermediateTensorInfo(u);let g=r.makeTensorInfo(d,u.dtype,f);if(i){let y=_.expandShapeToKeepDim(d,o),b=yt({inputs:{x:g},backend:r,attrs:{shape:y}});return r.disposeIntermediateTensorInfo(g),b}return g}var FK={kernelName:Zl,backendName:"cpu",kernelFunc:AK};function RK(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s}=n;ye(a,"argMax");let i=k.parseAxisParam(s,a.shape),o=_.getAxesPermutation(i,a.shape.length),l=a,p=[];o!=null&&(l=Mr({inputs:{x:a},backend:r,attrs:{perm:o}}),p.push(l),i=_.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],_.assertAxesAreInnerMostDims("argMax",i,l.shape.length);let[u,d]=_.computeOutAndReduceShapes(l.shape,i),h=k.sizeFromShape(u),c=k.makeZerosTypedArray(h,"int32"),f=k.sizeFromShape(d),m=r.data.get(l.dataId).values;for(let g=0;g<c.length;++g){let y=g*f,b=m[y],x=0;for(let v=0;v<f;++v){let w=m[y+v];w>b&&(b=w,x=v)}c[g]=x}return p.forEach(g=>r.disposeIntermediateTensorInfo(g)),r.makeTensorInfo(u,"int32",c)}var DK={kernelName:Jl,backendName:"cpu",kernelFunc:RK};function MK(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s}=n;ye(a,"argMin");let i=k.parseAxisParam(s,a.shape),o=_.getAxesPermutation(i,a.shape.length),l=a,p=[];o!=null&&(l=Mr({inputs:{x:a},backend:r,attrs:{perm:o}}),p.push(l),i=_.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],_.assertAxesAreInnerMostDims("argMin",i,l.shape.length);let[u,d]=_.computeOutAndReduceShapes(l.shape,i),h=k.sizeFromShape(u),c=k.makeZerosTypedArray(h,"int32"),f=k.sizeFromShape(d),m=r.data.get(l.dataId).values;for(let g=0;g<c.length;++g){let y=g*f,b=m[y],x=0;for(let v=0;v<f;++v){let w=m[y+v];w<b&&(b=w,x=v)}c[g]=x}return p.forEach(g=>r.disposeIntermediateTensorInfo(g)),r.makeTensorInfo(u,"int32",c)}var 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e8={kernelName:cd,backendName:"cpu",kernelFunc:QK};function t8(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,input:s}=t,i=s;ye([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:p}=n,u=_.computePool2DInfo(i.shape,o,l,1,p),d=u.strideHeight,h=u.strideWidth,c=u.filterHeight,f=u.filterWidth,m=u.dilationHeight,g=u.dilationWidth,y=u.effectiveFilterHeight,b=u.effectiveFilterWidth,x=b-1-u.padInfo.left,v=y-1-u.padInfo.top,w=Le(i.shape,"float32"),N=1/(c*f),T=r.data.get(a.dataId).values,E=Le(a.shape,"float32",T);for(let $=0;$<u.batchSize;++$)for(let R=0;R<u.inChannels;++R)for(let F=0;F<u.inHeight;++F)for(let S=0;S<u.inWidth;++S){let D=F-v,P=S-x,U=0;for(let H=0;H<y;H+=m){let q=(D+H)/d;if(!(q<0||q>=u.outHeight||Math.floor(q)!==q))for(let G=0;G<b;G+=g){let Z=(P+G)/h;if(Z<0||Z>=u.outWidth||Math.floor(Z)!==Z)continue;let ee=E.get($,q,Z,R);U+=ee}}w.set(U*N,$,F,S,R)}return r.makeTensorInfo(w.shape,w.dtype,w.values)}var r8={kernelName:hd,backendName:"cpu",kernelFunc:t8};function 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r.makeTensorInfo(a.shape,a.dtype,m)}var a8={kernelName:no,backendName:"cpu",kernelFunc:n8};function s8(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockShape:s,crops:i}=n;ye([a],"batchToSpaceND");let o=s.reduce((y,b)=>y*b),l=_.getReshaped(a.shape,s,o),p=_.getPermuted(l.length,s.length),u=_.getReshapedPermuted(a.shape,s,o),d=_.getSliceBeginCoords(i,s.length),h=_.getSliceSize(u,i,s.length),c=yt({inputs:{x:a},backend:r,attrs:{shape:l}}),f=Mr({inputs:{x:c},backend:r,attrs:{perm:p}}),m=yt({inputs:{x:f},backend:r,attrs:{shape:u}}),g=ki({inputs:{x:m},backend:r,attrs:{begin:d,size:h}});return r.disposeIntermediateTensorInfo(c),r.disposeIntermediateTensorInfo(f),r.disposeIntermediateTensorInfo(m),g}var i8={kernelName:eu,backendName:"cpu",kernelFunc:s8};function o8(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,weights:s}=t,{size:i}=n,o=r.data.get(a.dataId).values,l=r.data.get(s.dataId).values,p=zv(o,l,s.dtype,s.shape,i);return r.makeTensorInfo([i],s.dtype,p)}var l8={kernelName:tu,backendName:"cpu",kernelFunc:o8};function u8(e){let{inputs:t,backend:r}=e,{s0:n,s1:a}=t,s=r.data.get(n.dataId).values,i=r.data.get(a.dataId).values,o=_.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return r.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var p8={kernelName:fd,backendName:"cpu",kernelFunc:u8},d8=at(Cs,(e,t)=>{let r=t;return e>r.clipValueMax?r.clipValueMax:e<r.clipValueMin?r.clipValueMin:e}),h8={kernelName:Cs,backendName:"cpu",kernelFunc:d8},c8=e=>{let{x:t}=e.inputs,r=e.backend,n=new Float32Array(k.sizeFromShape(t.shape)),a=r.data.get(t.dataId),s=a.complexTensorInfos.real,i=a.complexTensorInfos.imag,o=r.data.get(s.dataId).values,l=r.data.get(i.dataId).values;for(let p=0;p<o.length;p++){let u=o[p],d=l[p];n[p]=Math.hypot(u,d)}return r.makeOutput(n,t.shape,"float32")},f8={kernelName:md,backendName:"cpu",kernelFunc:c8};function 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r.makeTensorInfo(b.shape,b.dtype,b.values)}var x8={kernelName:Qc,backendName:"cpu",kernelFunc:b8};function v8(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:p,dimRoundingMode:u}=n;ye([a,s],"conv2dBackpropInput");let d=k.computeStrides(s.shape),h=k.computeStrides(a.shape),c=_.convertConv2DDataFormat(p),f=_.computeConv2DInfo(i,s.shape,o,1,l,u,!1,c),m=new Dt(f.inShape,"float32"),g=m.values,y=r.data.get(a.dataId).values,b=r.data.get(s.dataId).values,[x,v,w]=d,{batchSize:N,filterHeight:T,filterWidth:E,inChannels:$,inHeight:R,inWidth:F,outChannels:S,outHeight:D,outWidth:P,strideHeight:U,strideWidth:H}=f;c=f.dataFormat;let q=T-1-f.padInfo.top,G=E-1-f.padInfo.left,Z=c==="channelsLast",ee=m.strides[0],X=Z?m.strides[1]:m.strides[2],re=Z?m.strides[2]:1,te=Z?1:m.strides[1],ae=h[0],ie=Z?h[1]:h[2],ve=Z?h[2]:1,be=Z?1:h[1];for(let he=0;he<N;++he)for(let Ie=0;Ie<$;++Ie)for(let _e=0;_e<R;++_e){let Fe=_e-q,Pe=Math.max(0,Math.ceil(Fe/U)),st=Math.min(D,(T+Fe)/U);for(let Ge=0;Ge<F;++Ge){let qe=Ge-G,$e=Math.max(0,Math.ceil(qe/H)),Je=Math.min(P,(E+qe)/H),ht=0;for(let _t=Pe;_t<st;++_t){let Nr=_t*U-Fe;for(let tr=$e;tr<Je;++tr){let _r=tr*H-qe,yn=ae*he+ie*_t+ve*tr,zr=x*(T-1-Nr)+v*(E-1-_r)+w*Ie;for(let Tr=0;Tr<S;++Tr){let rr=y[yn+be*Tr],Qr=b[zr+Tr];ht+=rr*Qr}}}let Lr=ee*he+X*_e+re*Ge+te*Ie;g[Lr]=ht}}return r.makeTensorInfo(m.shape,m.dtype,m.values)}var w8={kernelName:Vi,backendName:"cpu",kernelFunc:v8};function k8(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=n;ye([a,s],"conv3d");let p=_.computeConv3DInfo(a.shape,s.shape,i,l,o),{filterDepth:u,filterHeight:d,filterWidth:h,dilationDepth:c,dilationHeight:f,dilationWidth:m,padInfo:g}=p,y=g.front,b=g.left,x=g.top,v=new Dt(p.outShape,a.dtype),w=r.data.get(a.dataId).values,N=r.data.get(s.dataId).values,T=v.values,E=k.computeStrides(a.shape),$=k.computeStrides(s.shape);for(let R=0;R<p.batchSize;++R){let F=R*E[0],S=R*v.strides[0];for(let D=0;D<p.outDepth;++D){let P=S+D*v.strides[1],U=D*p.strideDepth-y;for(let H=0;H<u;++H){let q=U+H*c;if(q<0||q>=p.inDepth)continue;let G=H*$[0],Z=F+q*E[1];for(let ee=0;ee<p.outHeight;++ee){let X=P+ee*v.strides[2],re=ee*p.strideHeight-x;for(let te=0;te<d;++te){let ae=re+te*f;if(ae<0||ae>=p.inHeight)continue;let ie=G+te*$[1],ve=Z+ae*E[2];for(let be=0;be<p.outWidth;++be){let he=X+be*p.outChannels,Ie=be*p.strideWidth-b;for(let _e=0;_e<h;++_e){let Fe=Ie+_e*m;if(Fe<0||Fe>=p.inWidth)continue;let Pe=ie+_e*$[2],st=ve+Fe*p.inChannels,Ge=Pe;for(let qe=0;qe<p.inChannels;++qe){let $e=w[st+qe];for(let Je=0;Je<p.outChannels;++Je)T[he+Je]+=$e*N[Ge+Je];Ge+=p.outChannels}}}}}}}}return r.makeTensorInfo(v.shape,v.dtype,v.values)}var I8={kernelName:Gi,backendName:"cpu",kernelFunc:k8};function S8(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=n;ye([a,s],"conv3dBackpropFilterV2");let p=k.computeStrides(a.shape),u=k.computeStrides(s.shape),d=_.computeConv3DInfo(a.shape,l,i,1,o),h=d.strideDepth,c=d.strideHeight,f=d.strideWidth,m=d.filterDepth,g=d.filterHeight,y=d.filterWidth,b=new Dt(d.filterShape,"float32"),x=b.values,[v,w,N,T]=b.strides,E=r.data.get(s.dataId).values,[$,R,F,S]=u,D=r.data.get(a.dataId).values,[P,U,H,q]=p,G=d.padInfo.front,Z=d.padInfo.left,ee=d.padInfo.top;for(let X=0;X<m;++X){let re=Math.max(0,Math.ceil((G-X)/h)),te=Math.min(d.outDepth,(d.inDepth+G-X)/h),ae=X*v;for(let ie=0;ie<g;++ie){let ve=Math.max(0,Math.ceil((ee-ie)/c)),be=Math.min(d.outHeight,(d.inHeight+ee-ie)/c),he=ie*w+ae;for(let Ie=0;Ie<y;++Ie){let _e=Math.max(0,Math.ceil((Z-Ie)/f)),Fe=Math.min(d.outWidth,(d.inWidth+Z-Ie)/f),Pe=Ie*N+he;for(let st=0;st<d.inChannels;++st){let Ge=st*T+Pe;for(let qe=0;qe<d.outChannels;++qe){let $e=0;for(let Je=0;Je<d.batchSize;++Je){let ht=Je*P,Lr=Je*$;for(let _t=re;_t<te;++_t){let Nr=(X+_t*h-G)*U+ht,tr=_t*R+Lr;for(let _r=ve;_r<be;++_r){let yn=(ie+_r*c-ee)*H+Nr,zr=_r*F+tr;for(let Tr=_e;Tr<Fe;++Tr){let rr=(Ie+Tr*f-Z)*q+yn,Qr=Tr*S+zr;$e+=D[rr+st]*E[Qr+qe]}}}}x[Ge+qe]=$e}}}}}return r.makeTensorInfo(b.shape,b.dtype,b.values)}var N8={kernelName:au,backendName:"cpu",kernelFunc:S8};function _8(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=n;ye([a],"conv3dBackpropInputV2");let p=k.computeStrides(a.shape),u=k.computeStrides(s.shape),d=_.computeConv3DInfo(l,s.shape,o,1,i),h=new Dt(d.inShape,"float32"),c=h.values,[f,m,g,y]=h.strides,b=r.data.get(a.dataId).values,[x,v,w,N]=p,T=r.data.get(s.dataId).values,[E,$,R,F]=u,{batchSize:S,filterDepth:D,filterHeight:P,filterWidth:U,inChannels:H,inDepth:q,inHeight:G,inWidth:Z,outChannels:ee,outDepth:X,outHeight:re,outWidth:te,strideDepth:ae,strideHeight:ie,strideWidth:ve}=d,be=D-1-d.padInfo.front,he=P-1-d.padInfo.top,Ie=U-1-d.padInfo.left;for(let _e=0;_e<S;++_e)for(let Fe=0;Fe<H;++Fe)for(let Pe=0;Pe<q;++Pe){let 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Ie=v[be];be=ve+te*w[2]+Z*w[1]+D*w[0];let _e=v[be];be=ve+ae*w[2]+Z*w[1]+D*w[0];let Fe=v[be],Pe=he+(Ie-he)*ie,st=_e+(Fe-_e)*ie;be=ve+X*N[2]+H*N[1]+T*N[0],y.values[be]=Pe+(st-Pe)*ee}}}else for(let G=0;G<g;++G){let Z=g>1?R*(h-1)+G*U:.5*(R+S)*(h-1);if(Z<0||Z>h-1){for(let re=0;re<c;re++){let te=re+G*N[2]+H*N[1]+T*N[0];y.values[te]=p}continue}let ee=Math.round(Z),X=Math.round(q);for(let re=0;re<c;re++){let te=re+ee*w[2]+X*w[1]+D*w[0],ae=re+G*N[2]+H*N[1]+T*N[0];y.values[ae]=v[te]}}}}return r.makeTensorInfo(y.shape,y.dtype,y.values)}var R8={kernelName:ou,backendName:"cpu",kernelFunc:F8};function D8(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n;ye(a,"cumprod");let l=_.getAxesPermutation([s],a.shape.length),p=a;l!=null&&(p=Mr({inputs:{x:a},backend:r,attrs:{perm:l}}));let u=_.getInnerMostAxes(1,a.shape.length)[0];if(u!==p.shape.length-1)throw new Error(`backend.cumprod in CPU expects an inner-most axis=${p.shape.length-1} but got axis=${u}`);let d=cn(p.dtype,"int32"),h=k.makeOnesTypedArray(k.sizeFromShape(p.shape),d),c=r.data.get(p.dataId).values,f=p.shape[p.shape.length-1],m=o?(y,b)=>y+f-b-1:(y,b)=>y+b;for(let y=0;y<c.length;y+=f)for(let b=0;b<f;b++){let x=m(y,b);if(b===0)h[x]=i?1:c[x];else{let v=m(y,b-1);h[x]=i?c[v]*h[v]:c[x]*h[v]}}let g=r.makeTensorInfo(p.shape,d,h);if(l!=null){let y=_.getUndoAxesPermutation(l),b=Mr({inputs:{x:g},backend:r,attrs:{perm:y}});return r.disposeIntermediateTensorInfo(g),r.disposeIntermediateTensorInfo(p),b}return g}var M8={kernelName:iu,backendName:"cpu",kernelFunc:D8};function O8(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n;ye(a,"cumsum");let l=_.getAxesPermutation([s],a.shape.length),p=a;l!=null&&(p=Mr({inputs:{x:a},backend:r,attrs:{perm:l}}));let u=_.getInnerMostAxes(1,a.shape.length)[0];if(u!==p.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${p.shape.length-1} but got axis=${u}`);let d=cn(p.dtype,"int32"),h=k.makeZerosTypedArray(k.sizeFromShape(p.shape),d),c=r.data.get(p.dataId).values,f=p.shape[p.shape.length-1],m=o?(y,b)=>y+f-b-1:(y,b)=>y+b;for(let y=0;y<c.length;y+=f)for(let b=0;b<f;b++){let x=m(y,b);if(b===0)h[x]=i?0:c[x];else{let v=m(y,b-1);h[x]=i?c[v]+h[v]:c[x]+h[v]}}let g=r.makeTensorInfo(p.shape,d,h);if(l!=null){let y=_.getUndoAxesPermutation(l),b=Mr({inputs:{x:g},backend:r,attrs:{perm:y}});return r.disposeIntermediateTensorInfo(g),r.disposeIntermediateTensorInfo(p),b}return g}var L8={kernelName:qi,backendName:"cpu",kernelFunc:O8};function z8(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=n;if(a.shape.length===1){let l=r.data.get(a.dataId).values,p=r.data.get(s.dataId).values,u=zv(l,p,s.dtype,s.shape,i);return r.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=r.bufferSync(a),p=r.bufferSync(s),u=T_(l,p,i,o);return r.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var P8={kernelName:gd,backendName:"cpu",kernelFunc:z8};function B8(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockSize:s,dataFormat:i}=n;k.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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V8(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:p,filterShape:u}=n;ye([a,s],"depthwiseConv2dNativeBackpropFilter");let d=_.computeConv2DInfo(a.shape,u,i,o,l,p,!0),{strideHeight:h,strideWidth:c,filterHeight:f,filterWidth:m}=d,g=new Dt(d.filterShape,"float32"),y=d.padInfo.left,b=d.padInfo.top,x=d.outChannels/d.inChannels,v=r.data.get(a.dataId).values,w=new Dt(a.shape,a.dtype,v),N=r.data.get(s.dataId).values,T=new Dt(s.shape,s.dtype,N);for(let E=0;E<f;++E){let $=Math.max(0,Math.ceil((b-E)/h)),R=Math.min(d.outHeight,(d.inHeight+b-E)/h);for(let F=0;F<m;++F){let S=Math.max(0,Math.ceil((y-F)/c)),D=Math.min(d.outWidth,(d.inWidth+y-F)/c);for(let P=0;P<d.outChannels;++P){let U=Math.trunc(P/x),H=P%x,q=0;for(let G=0;G<d.batchSize;++G)for(let Z=$;Z<R;++Z){let ee=E+Z*h-b;for(let X=S;X<D;++X){let re=F+X*c-y;q+=w.get(G,ee,re,U)*T.get(G,Z,X,P)}}g.set(q,E,F,U,H)}}}return r.makeTensorInfo(g.shape,g.dtype,g.values)}var G8={kernelName:ef,backendName:"cpu",kernelFunc:V8};function H8(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:p,inputShape:u}=n;ye([a,s],"depthwiseConv2DNativeBackpropInput");let d=k.computeStrides(a.shape),h=k.computeStrides(s.shape),c=_.computeConv2DInfo(u,s.shape,i,o,l,p,!0),f=new Dt(c.inShape,"float32"),m=f.values,[g,y,b]=f.strides,x=r.data.get(a.dataId).values,[v,w,N]=d,T=r.data.get(s.dataId).values,[E,$,R]=h,{batchSize:F,filterHeight:S,filterWidth:D,inChannels:P,inHeight:U,inWidth:H,outChannels:q,outHeight:G,outWidth:Z,strideHeight:ee,strideWidth:X}=c,re=S-1-c.padInfo.top,te=D-1-c.padInfo.left,ae=q/P;for(let ie=0;ie<F;++ie)for(let ve=0;ve<P;++ve)for(let be=0;be<U;++be){let he=be-re,Ie=Math.max(0,Math.ceil(he/ee)),_e=Math.min(G,(S+he)/ee);for(let Fe=0;Fe<H;++Fe){let Pe=Fe-te,st=Math.max(0,Math.ceil(Pe/X)),Ge=Math.min(Z,(D+Pe)/X),qe=0;for(let $e=Ie;$e<_e;++$e){let Je=$e*ee-he;for(let ht=st;ht<Ge;++ht){let 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K8={kernelName:yd,backendName:"cpu",kernelFunc:q8},X8={kernelName:Xi,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:r})=>{let{x:n,filter:a}=e,{strides:s,pad:i,dilations:o}=r,l=t,p=l.data.get(n.dataId).values,u=n.shape.length,d=l.data.get(a.dataId).values,h=a.shape.length,{batchSize:c,inHeight:f,inWidth:m,inChannels:g,outHeight:y,outWidth:b,padInfo:x,strideHeight:v,strideWidth:w,filterHeight:N,filterWidth:T,dilationHeight:E,dilationWidth:$,outShape:R}=_.computeDilation2DInfo(n.shape,a.shape,s,i,"NHWC",o),F=k.sizeFromShape(R),S=R.length,D=k.getArrayFromDType(n.dtype,F);for(let P=0;P<c;++P)for(let U=0;U<y;++U){let H=U*v-x.top;for(let q=0;q<b;++q){let G=q*w-x.left;for(let Z=0;Z<g;++Z){let ee=Number.MIN_SAFE_INTEGER;for(let re=0;re<N;++re){let te=H+re*E;if(te>=0&&te<f)for(let ae=0;ae<T;++ae){let ie=G+ae*$;if(ie>=0&&ie<m){let ve=k.locToIndex([P,te,ie,Z],u,k.computeStrides(n.shape)),be=k.locToIndex([re,ae,Z],h,k.computeStrides(a.shape)),he=p[ve]+d[be];he>ee&&(ee=he)}}}let X=k.locToIndex([P,U,q,Z],S,k.computeStrides(R));D[X]=ee}}}return{dataId:l.write(k.toTypedArray(D,n.dtype),R,n.dtype),shape:R,dtype:n.dtype}}},Z8={kernelName:Cl,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:r})=>{let{x:n,filter:a,dy:s}=e,{strides:i,pad:o,dilations:l}=r,p=t,u=k.toNestedArray(n.shape,p.data.get(n.dataId).values),d=k.toNestedArray(a.shape,p.data.get(a.dataId).values),{batchSize:h,inHeight:c,inWidth:f,inChannels:m,outHeight:g,outWidth:y,padInfo:b,strideHeight:x,strideWidth:v,filterHeight:w,filterWidth:N,dilationHeight:T,dilationWidth:E,outShape:$}=_.computeDilation2DInfo(n.shape,a.shape,i,o,"NHWC",l);k.assert(s.rank===$.length,()=>`Error in ${Cl}, dy must have the same rank as output ${$.length}, but got ${s.rank}`);let R=k.toNestedArray($,p.data.get(s.dataId).values),F=k.makeZerosNestedTypedArray(a.shape,a.dtype);for(let S=0;S<h;++S)for(let D=0;D<g;++D){let P=D*x-b.top;for(let U=0;U<y;++U){let H=U*v-b.left;for(let q=0;q<m;++q){let 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o;a.dtype==="bool"?o=Is({inputs:{x:a},backend:r,attrs:{dtype:"int32"}}):o=ca({inputs:{x:a},backend:r});let l=o.shape.length,p=k.parseAxisParam(s,o.shape),u=_.getAxesPermutation(p,l),d=p,h=o;u!=null&&(h=Mr({inputs:{x:o},backend:r,attrs:{perm:u}}),d=_.getInnerMostAxes(d.length,l)),_.assertAxesAreInnerMostDims("sum",d,h.shape.length);let[c,f]=_.computeOutAndReduceShapes(h.shape,d),m=_.upcastType(h.dtype,"int32"),g=Fc(r,c,m),y=k.sizeFromShape(f),b=r.data.get(g.dataId).values,x=r.data.get(h.dataId).values;for(let v=0;v<b.length;++v){let w=v*y,N=0;for(let T=0;T<y;++T)N+=x[w+T];b[v]=N}if(i){let v=_.expandShapeToKeepDim(g.shape,p),w=g;g=yt({inputs:{x:g},backend:r,attrs:{shape:v}}),r.disposeIntermediateTensorInfo(w)}return r.disposeIntermediateTensorInfo(o),u!=null&&r.disposeIntermediateTensorInfo(h),g}var eX={kernelName:Vo,backendName:"cpu",kernelFunc:oh};function 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Wa(e,()=>e.createTexture(),"Unable to create WebGLTexture.")}function zT(e,t){let r=j().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(e<=0||t<=0){let n=`[${e}x${t}]`;throw new Error("Requested texture size "+n+" is invalid.")}if(e>r||t>r){let n=`[${e}x${t}]`,a=`[${r}x${r}]`;throw new Error("Requested texture size "+n+" greater than WebGL maximum on this browser / GPU "+a+".")}}function PT(e){return Wa(e,()=>e.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function qg(e,t,r,n,a,s,i){let o=e.getAttribLocation(t,r);return o===-1?!1:(pe(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),pe(e,()=>e.vertexAttribPointer(o,a,e.FLOAT,!1,s,i)),pe(e,()=>e.enableVertexAttribArray(o)),!0)}function BT(e,t,r){HT(e,r),pe(e,()=>e.activeTexture(e.TEXTURE0+r)),pe(e,()=>e.bindTexture(e.TEXTURE_2D,t))}function PJ(e,t){HT(e,t),pe(e,()=>e.activeTexture(e.TEXTURE0+t)),pe(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function WT(e,t,r){return Wa(e,()=>e.getUniformLocation(t,r),'uniform "'+r+'" not present in 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r=j().getNumber("WEBGL_MAX_TEXTURE_SIZE"),n=j().getNumber("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE");n===1/0&&j().getBool("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE")&&(n=r/2),t&&(r=r*2,n=n*2,e=e.map((o,l)=>l>=e.length-2?k.nearestLargerEven(e[l]):e[l]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=k.squeezeShape(e).newShape);let a=k.sizeFromShape(e),s=null;e.length<=1&&a<=r?s=[1,a]:e.length===2&&e[0]<=r&&e[1]<=r?s=e:e.length===3&&e[0]*e[1]<=r&&e[2]<=r?s=[e[0]*e[1],e[2]]:e.length===3&&e[0]<=r&&e[1]*e[2]<=r?s=[e[0],e[1]*e[2]]:e.length===4&&e[0]*e[1]*e[2]<=r&&e[3]<=r?s=[e[0]*e[1]*e[2],e[3]]:e.length===4&&e[0]<=r&&e[1]*e[2]*e[3]<=r&&(s=[e[0],e[1]*e[2]*e[3]]);let i=s!=null&&Math.max(...s)>n&&Math.min(...s)<=(t?2:1)&&Math.min(...s)>0;if(s==null||i)if(t){let o=Ii(e),l=2,p=2;e.length&&([l,p]=Si(e)),a=o*(l/2)*(p/2),s=k.sizeToSquarishShape(a).map(u=>u*2)}else s=k.sizeToSquarishShape(a);return s}function Uh(e){return e%2===0}function sd(e,t){if(e=e.slice(-2),t=t.slice(-2),k.arraysEqual(e,t)||!e.length||!t.length||e[0]===0||e[1]===0||t[0]===0||t[1]===0)return!0;if(e.length!==t.length){let r=e[e.length-1],n=t[t.length-1];if(r===n||Uh(r)&&Uh(n)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&Uh(e[0])&&Uh(t[0])}var ec,tc;function qT(e){if(ec==null){let t=Vn(e);ec=t.getParameter(t.MAX_TEXTURE_SIZE)}return ec}function WJ(){ec=null}function UJ(){tc=null}function KT(e){if(tc==null){let t=Vn(e);tc=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,tc)}function XT(e){if(e===0)return 0;let t,r=Vn(e);return ln(r,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:ln(r,"EXT_disjoint_timer_query")?t=1:t=0,t}function ln(e,t){return e.getExtension(t)!=null}function Xg(e){try{if(Vn(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function ZT(e){if(e===0)return!1;let t=Vn(e);if(e===1){if(!ln(t,"OES_texture_float"))return!1}else if(!ln(t,"EXT_color_buffer_float"))return!1;return 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a=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,a),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let s=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(a),s}function YT(e){return e!==2?!1:Vn(e).fenceSync!=null}function lp(e,t){Array.isArray(e)||(e=[e]),e.forEach(r=>{r!=null&&k.assert(r.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var xe=j();xe.registerFlag("HAS_WEBGL",()=>xe.getNumber("WEBGL_VERSION")>0);xe.registerFlag("WEBGL_VERSION",()=>Xg(2)?2:Xg(1)?1:0);xe.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);xe.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>xe.get("WEBGL_VERSION")===2);xe.registerFlag("WEBGL_CPU_FORWARD",()=>!0);xe.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);xe.registerFlag("WEBGL_PACK",()=>xe.getBool("HAS_WEBGL"));xe.registerFlag("WEBGL_PACK_NORMALIZATION",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_CLIP",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_REDUCE",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_LAZILY_UNPACK",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_CONV_IM2COL",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_CONV2DTRANSPOSE",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>qT(xe.getNumber("WEBGL_VERSION")));xe.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>KT(xe.getNumber("WEBGL_VERSION")));xe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let 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${e}.`)});xe.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>Od.isMobile()?1:-1,e=>{if(typeof e!="number")throw new Error(`WEBGL_FLUSH_THRESHOLD must be a number but got ${e}.`);if(e<0&&e!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});xe.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);xe.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);xe.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);xe.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);xe.registerFlag("WEBGL_EXP_CONV",()=>!1);xe.registerFlag("SOFTWARE_WEBGL_ENABLED",()=>xe.getBool("IS_TEST"));xe.registerFlag("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE",()=>1/0);xe.registerFlag("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE",()=>!1);xe.registerFlag("WEBGL2_ISNAN_CUSTOM",()=>!1);xe.registerFlag("ENGINE_COMPILE_ONLY",()=>!1);function Sr(){let e,t,r,n,a,s,i,o,l,p;return j().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",r="out",n="in",a="texture",s="outputColor",i="out vec4 outputColor;",o=j().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)
`:"",l="",p=`
#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)));
}
`):(e="",t="attribute",r="varying",n="varying",a="texture2D",s="gl_FragColor",i="",o=`
#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));
}
`,l=`
uniform float INFINITY;
bool isinf(float val) {
return abs(val) == INFINITY;
}
bvec4 isinf(vec4 val) {
return equal(abs(val), vec4(INFINITY));
}
`,p=`
int round(float value) {
return int(floor(value + 0.5));
}
ivec4 round(vec4 value) {
return ivec4(floor(value + vec4(0.5)));
}
`),{version:e,attribute:t,varyingVs:r,varyingFs:n,texture2D:a,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:p}}function rl(e,t,r="index"){let n=k.computeStrides(t);return n.map((a,s)=>{let i=`int ${e[s]} = ${r} / ${a}`,o=s===n.length-1?`int ${e[s+1]} = ${r} - ${e[s]} * ${a}`:`index -= ${e[s]} * ${a}`;return`${i}; ${o};`}).join("")}function bm(e,t,r="index"){let n=k.computeStrides(t);return n.map((a,s)=>{let i=`int ${e[s]} = ${r} / outShapeStrides[${s}]`,o=s===n.length-1?`int ${e[s+1]} = ${r} - ${e[s]} * outShapeStrides[${s}]`:`index -= ${e[s]} * outShapeStrides[${s}]`;return`${i}; ${o};`}).join("")}function GJ(e,t){let r=e.length,n=e.map(s=>`${t}[${s}]`),a=new Array(r-1);a[r-2]=n[r-1];for(let s=r-3;s>=0;--s)a[s]=`(${a[s+1]} * ${n[s+1]})`;return a}function HJ(e,t,r="index"){let n=e.map((s,i)=>i),a=GJ(n,t);return a.map((s,i)=>{let o=`int ${e[i]} = ${r} / ${a[i]}`,l=i===a.length-1?`int ${e[i+1]} = ${r} - ${e[i]} * ${a[i]}`:`index -= ${e[i]} * ${a[i]}`;return`${o}; ${l};`}).join("")}function ew(e){let t=k.computeStrides(e).map(r=>r.toString());return`
int getFlatIndex(ivec3 coords) {
return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
}
`}function tw(){return`
int getFlatIndex(ivec3 coords) {
return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
}
`}var QT=`
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;
}
`,{getBroadcastDims:eC}=_;function jJ(e,t,r){let n=[];if(e.forEach(h=>{let c=k.sizeFromShape(h.shapeInfo.logicalShape);if(h.shapeInfo.isUniform?n.push(`uniform float ${h.name}${c>1?`[${c}]`:""};`):(n.push(`uniform sampler2D ${h.name};`),n.push(`uniform int offset${h.name};`)),r.enableShapeUniforms){let{uniformShape:f}=rw(r.packedInputs,h.shapeInfo.logicalShape,h.shapeInfo.texShape);switch(f.length){case 1:n.push(`uniform int ${h.name}Shape;`);break;case 2:n.push(`uniform ivec2 ${h.name}Shape;`);break;case 3:n.push(`uniform ivec3 ${h.name}Shape;`);break;case 4:n.push(`uniform ivec4 ${h.name}Shape;`);break}n.push(`uniform ivec2 ${h.name}TexShape;`)}}),r.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}n.push("uniform ivec2 outTexShape;")}r.customUniforms&&r.customUniforms.forEach(h=>{n.push(`uniform ${h.type} ${h.name}${h.arrayIndex?`[${h.arrayIndex}]`:""};`)});let a=n.join(`
`),s=e.map(h=>qJ(h,t,r.packedInputs,r.enableShapeUniforms)).join(`
`),i=t.texShape,o=Sr(),l=ZJ(o),p,u,d=QJ(o);return t.isPacked?(p=KJ(t.logicalShape,i,r.enableShapeUniforms),u=YJ(o)):(p=XJ(t.logicalShape,i,r.enableShapeUniforms),u=JJ(o)),r.packedInputs&&(d+=n9),[d,l,u,a,p,s,r.userCode].join(`
`)}function up(e,t=!1){let r=e.shapeInfo.logicalShape;switch(r.length){case 0:return m9(e,t);case 1:return y9(e,t);case 2:return x9(e,t);case 3:return w9(e,t);case 4:return I9(e,t);case 5:return S9(e);case 6:return N9(e);default:throw new Error(`${r.length}-D input sampling is not yet supported`)}}function tC(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return f9(e);case 1:return g9(e,t);case 2:return b9(e,t);case 3:return v9(e,t);default:return k9(e,t)}}function qJ(e,t,r=!1,n){let a="";r?a+=tC(e,n):a+=up(e,n);let s=e.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(r?a+=_9(e,t):a+=T9(e,t)),a}function KJ(e,t,r){switch(e.length){case 0:return rC();case 1:return a9(e,t,r);case 2:return h9(e,t,r);case 3:return i9(e,t,r);default:return l9(e,t,r)}}function XJ(e,t,r){switch(e.length){case 0:return rC();case 1:return s9(e,t,r);case 2:return c9(e,t,r);case 3:return o9(e,t,r);case 4:return u9(e,t,r);case 5:return p9(e,t);case 6:return d9(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function ZJ(e){return`
float sampleTexture(sampler2D textureSampler, vec2 uv) {
return ${e.texture2D}(textureSampler, uv).r;
}
`}function JJ(e){return`
void setOutput(float val) {
${e.output} = vec4(val, 0, 0, 0);
}
`}function YJ(e){return`
void setOutput(vec4 val) {
${e.output} = val;
}
`}function QJ(e){return`${e.version}
precision highp float;
precision highp int;
precision highp sampler2D;
${e.varyingFs} vec2 resultUV;
${e.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;
${e.defineSpecialNaN}
${e.defineSpecialInf}
${e.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);
}
${e9}
${t9}
${r9}
`}var e9=`
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);
}
`,t9=`
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);
}
`,r9=`
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);
}
`,n9=`
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 rC(){return`
int getOutputCoords() {
return 0;
}
`}function a9(e,t,r){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?r?`
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?r?`
int getOutputCoords() {
return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
}
`:`
int getOutputCoords() {
return 2 * int(resultUV.y * ${n[0]}.0);
}
`:r?`
int getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
}
`}function s9(e,t,r){return t[0]===1?r?`
int getOutputCoords() {
return int(resultUV.x * float(outTexShape[1]));
}
`:`
int getOutputCoords() {
return int(resultUV.x * ${t[1]}.0);
}
`:t[1]===1?r?`
int getOutputCoords() {
return int(resultUV.y * float(outTexShape[0]));
}
`:`
int getOutputCoords() {
return int(resultUV.y * ${t[0]}.0);
}
`:r?`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
return resTexRC.x * outTexShape[1] + resTexRC.y;
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
return resTexRC.x * ${t[1]} + resTexRC.y;
}
`}function i9(e,t,r){if(r)return`
ivec3 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec3(b, r, c);
}
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],a=Math.ceil(e[2]/2),s=a*Math.ceil(e[1]/2);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
int b = index / ${s};
index -= b * ${s};
int r = 2 * (index / ${a});
int c = imod(index, ${a}) * 2;
return ivec3(b, r, c);
}
`}function o9(e,t,r){if(r)return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
${bm(["r","c","d"],e)}
return ivec3(r, c, d);
}
`;let n=rl(["r","c","d"],e);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec3(r, c, d);
}
`}function l9(e,t,r){if(r)return`
ivec4 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
int texelsInBatchN = texelsInBatch * outShape[1];
int b2 = index / texelsInBatchN;
index -= b2 * texelsInBatchN;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec4(b2, b, r, c);
}
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],a=Math.ceil(e[e.length-1]/2),s=a*Math.ceil(e[e.length-2]/2),i=s,o="",l="b, r, c";for(let p=2;p<e.length-1;p++)i*=e[e.length-p-1],o=`
int b${p} = index / ${i};
index -= b${p} * ${i};
`+o,l=`b${p}, `+l;return`
ivec${e.length} getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
${o}
int b = index / ${s};
index -= b * ${s};
int r = 2 * (index / ${a});
int c = imod(index, ${a}) * 2;
return ivec${e.length}(${l});
}
`}function u9(e,t,r){if(r)return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
${bm(["r","c","d","d2"],e)}
return ivec4(r, c, d, d2);
}
`;let n=rl(["r","c","d","d2"],e);return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec4(r, c, d, d2);
}
`}function p9(e,t){let r=rl(["r","c","d","d2","d3"],e);return`
ivec5 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${r}
ivec5 outShape = ivec5(r, c, d, d2, d3);
return outShape;
}
`}function d9(e,t){let r=rl(["r","c","d","d2","d3","d4"],e);return`
ivec6 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${r}
ivec6 result = ivec6(r, c, d, d2, d3, d4);
return result;
}
`}function h9(e,t,r){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(k.arraysEqual(e,t))return r?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
}
`;let a=Math.ceil(e[1]/2);return r?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec2(r, c);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
int r = 2 * (index / ${a});
int c = imod(index, ${a}) * 2;
return ivec2(r, c);
}
`}function c9(e,t,r){return k.arraysEqual(e,t)?r?`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
}
`:e[1]===1?r?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
return ivec2(index, 0);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
return ivec2(index, 0);
}
`:e[0]===1?r?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
return ivec2(0, index);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
return ivec2(0, index);
}
`:r?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
int r = index / outShape[1];
int c = index - r * outShape[1];
return ivec2(r, c);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
int r = index / ${e[1]};
int c = index - r * ${e[1]};
return ivec2(r, c);
}
`}function nl(e){return`offset${e}`}function f9(e){let t=e.name,r="get"+t.charAt(0).toUpperCase()+t.slice(1),n=Sr();return`
vec4 ${r}() {
return ${n.texture2D}(${t}, halfCR);
}
`}function m9(e,t){let r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${r};}`;let[a,s]=e.shapeInfo.texShape;if(a===1&&s===1)return`
float ${n}() {
return sampleTexture(${r}, halfCR);
}
`;let i=nl(r);if(t)return`
float ${n}() {
vec2 uv = uvFromFlat(${r}TexShape[0], ${r}TexShape[1], ${i});
return sampleTexture(${r}, uv);
}
`;let[o,l]=e.shapeInfo.texShape;return`
float ${n}() {
vec2 uv = uvFromFlat(${o}, ${l}, ${i});
return sampleTexture(${r}, uv);
}
`}function g9(e,t){let r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1),a=e.shapeInfo.texShape,s=Sr();if(t)return`
vec4 ${n}(int index) {
ivec2 packedTexShape = ivec2(ceil(float(${r}TexShape[0]) / 2.0), ceil(float(${r}TexShape[1]) / 2.0));
vec2 uv = packedUVfrom1D(
packedTexShape[0], packedTexShape[1], index);
return ${s.texture2D}(${r}, uv);
}
`;let i=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];return`
vec4 ${n}(int index) {
vec2 uv = packedUVfrom1D(
${i[0]}, ${i[1]}, index);
return ${s.texture2D}(${r}, uv);
}
`}function y9(e,t){let r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1);if(e.shapeInfo.isUniform)return`
float ${n}(int index) {
${pp(e)}
}
`;let a=e.shapeInfo.texShape,s=a[0],i=a[1];if(i===1&&s===1)return`
float ${n}(int index) {
return sampleTexture(${r}, halfCR);
}
`;let o=nl(r);return i===1?t?`
float ${n}(int index) {
vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / float(${r}TexShape[0]));
return sampleTexture(${r}, uv);
}
`:`
float ${n}(int index) {
vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / ${s}.0);
return sampleTexture(${r}, uv);
}
`:s===1?t?`
float ${n}(int index) {
vec2 uv = vec2((float(index + ${o}) + 0.5) / float(${r}TexShape[1]), 0.5);
return sampleTexture(${r}, uv);
}
`:`
float ${n}(int index) {
vec2 uv = vec2((float(index + ${o}) + 0.5) / ${i}.0, 0.5);
return sampleTexture(${r}, uv);
}
`:t?`
float ${n}(int index) {
vec2 uv = uvFromFlat(${r}TexShape[0], ${r}TexShape[1], index + ${o});
return sampleTexture(${r}, uv);
}
`:`
float ${n}(int index) {
vec2 uv = uvFromFlat(${s}, ${i}, index + ${o});
return sampleTexture(${r}, uv);
}
`}function b9(e,t){let r=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape,i=s[0],o=s[1],l=Sr();if(s!=null&&k.arraysEqual(r,s))return t?`
vec4 ${a}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
return ${l.texture2D}(${n}, uv);
}
`:`
vec4 ${a}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${o}.0, ${i}.0);
return ${l.texture2D}(${n}, uv);
}
`;if(t)return`
vec4 ${a}(int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${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 ${l.texture2D}(${n}, uv);
}
`;let p=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],u=Math.ceil(r[1]/2);return`
vec4 ${a}(int row, int col) {
vec2 uv = packedUVfrom2D(${u}, ${p[0]}, ${p[1]}, row, col);
return ${l.texture2D}(${n}, uv);
}
`}function x9(e,t){let r=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape;if(s!=null&&k.arraysEqual(r,s)){if(t)return`
float ${a}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`;let h=s[0],c=s[1];return`
float ${a}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${c}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`}let{newShape:i,keptDims:o}=k.squeezeShape(r),l=i;if(l.length<r.length){let h=dp(e,l),c=["row","col"];return`
${up(h,t)}
float ${a}(int row, int col) {
return ${a}(${hp(c,o)});
}
`}if(e.shapeInfo.isUniform)return`
float ${a}(int row, int col) {
int index = round(dot(vec2(row, col), vec2(${r[1]}, 1)));
${pp(e)}
}
`;let p=s[0],u=s[1],d=nl(n);return u===1?t?`
float ${a}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${n}Shape[1], 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / float(${n}TexShape[0]));
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${r[1]}, 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / ${p}.0);
return sampleTexture(${n}, uv);
}
`:p===1?t?`
float ${a}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${n}Shape[1], 1, 1));
vec2 uv = vec2((index + 0.5) / float(${n}TexShape[1]), 0.5);
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${r[1]}, 1, 1));
vec2 uv = vec2((index + 0.5) / ${u}.0, 0.5);
return sampleTexture(${n}, uv);
}
`:t?`
float ${a}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${n}Shape[1] + col + ${d};
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${r[1]} + col + ${d};
vec2 uv = uvFromFlat(${p}, ${u}, index);
return sampleTexture(${n}, uv);
}
`}function v9(e,t){let r=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];if(r[0]===1){let h=r.slice(1),c=[1,2],f=dp(e,h),m=["b","row","col"];return`
${tC(f,t)}
vec4 ${a}(int b, int row, int col) {
return ${a}(${hp(m,c)});
}
`}let o=Sr();if(t)return`
vec4 ${a}(int b, int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${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 ${o.texture2D}(${n}, uv);
}
`;let l=i[0],p=i[1],u=Math.ceil(r[2]/2),d=u*Math.ceil(r[1]/2);return`
vec4 ${a}(int b, int row, int col) {
vec2 uv = packedUVfrom3D(
${l}, ${p}, ${d}, ${u}, b, row, col);
return ${o.texture2D}(${n}, uv);
}
`}function w9(e,t){let r=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r[1]*r[2],i=r[2],{newShape:o,keptDims:l}=k.squeezeShape(r),p=o;if(p.length<r.length){let m=dp(e,p),g=["row","col","depth"];return`
${up(m,t)}
float ${a}(int row, int col, int depth) {
return ${a}(${hp(g,l)});
}
`}if(e.shapeInfo.isUniform)return`
float ${a}(int row, int col, int depth) {
int index = round(dot(vec3(row, col, depth),
vec3(${s}, ${i}, 1)));
${pp(e)}
}
`;let u=e.shapeInfo.texShape,d=u[0],h=u[1],c=e.shapeInfo.flatOffset;if(h===s&&c==null)return t?`
float ${a}(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 ${a}(int row, int col, int depth) {
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(${i}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${h}.0, ${d}.0);
return sampleTexture(${n}, uv);
}
`;if(h===i&&c==null)return t?`
float ${a}(int row, int col, int depth) {
float texR = dot(vec2(row, col), vec2(${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 ${a}(int row, int col, int depth) {
float texR = dot(vec2(row, col), vec2(${r[1]}, 1));
float texC = float(depth);
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${h}.0, ${d}.0);
return sampleTexture(${n}, uv);
}
`;let f=nl(n);return t?`
float ${a}(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 + ${f};
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${s} + col * ${i} + depth + ${f};
vec2 uv = uvFromFlat(${d}, ${h}, index);
return sampleTexture(${n}, uv);
}
`}function k9(e,t){let r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1),a=Sr();if(t)return`
vec4 ${n}(int b2, int b, int row, int col) {
int valuesPerRow = int(ceil(float(${r}Shape[3]) / 2.0));
int texelsInBatch = valuesPerRow * int(ceil(float(${r}Shape[2]) / 2.0));
int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);
texelsInBatch *= ${r}Shape[1];
index = b2 * texelsInBatch + index;
ivec2 packedTexShape = ivec2(ceil(float(${r}TexShape[0]) / 2.0), ceil(float(${r}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 ${a.texture2D}(${r}, uv);
}
`;let s=e.shapeInfo.logicalShape,i=s.length,o=e.shapeInfo.texShape,l=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],p=l[0],u=l[1],d=Math.ceil(s[i-1]/2),h=d*Math.ceil(s[i-2]/2),c="int b, int row, int col",f=`b * ${h} + (row / 2) * ${d} + (col / 2)`;for(let m=2;m<i-1;m++)c=`int b${m}, `+c,h*=s[i-m-1],f=`b${m} * ${h} + `+f;return`
vec4 ${n}(${c}) {
int index = ${f};
int texR = index / ${u};
int texC = index - texR * ${u};
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${u}, ${p});
return ${a.texture2D}(${r}, uv);
}
`}function I9(e,t){let r=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r[3],i=r[2]*s,o=r[1]*i,{newShape:l,keptDims:p}=k.squeezeShape(r);if(l.length<r.length){let b=dp(e,l),x=["row","col","depth","depth2"];return`
${up(b,t)}
float ${a}(int row, int col, int depth, int depth2) {
return ${a}(${hp(x,p)});
}
`}if(e.shapeInfo.isUniform)return`
float ${a}(int row, int col, int depth, int depth2) {
int index = round(dot(vec4(row, col, depth, depth2),
vec4(${o}, ${i}, ${s}, 1)));
${pp(e)}
}
`;let u=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,h=d[0],c=d[1],f=`int stride2 = ${n}Shape[3];`,m=`int stride1 = ${n}Shape[2] * stride2;`,g=`int stride0 = ${n}Shape[1] * stride1;`;if(c===o&&u==null)return t?`
float ${a}(int row, int col, int depth, int depth2) {
${f}
${m}
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(stride1, stride2, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int row, int col, int depth, int depth2) {
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(${i}, ${s}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${c}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`;if(c===s&&u==null)return t?`
float ${a}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${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 ${a}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${r[1]*r[2]}, ${r[2]}, 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${c}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`;let y=nl(n);return t?`
float ${a}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
${f}
${m}
${g}
int index = row * stride0 + col * stride1 +
depth * stride2 + depth2;
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index + ${y});
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${o} + col * ${i} +
depth * ${s} + depth2;
vec2 uv = uvFromFlat(${h}, ${c}, index + ${y});
return sampleTexture(${n}, uv);
}
`}function S9(e){let t=e.shapeInfo.logicalShape,r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:p}=k.squeezeShape(t);if(l.length<t.length){let m=dp(e,l),g=["row","col","depth","depth2","depth3"];return`
${up(m)}
float ${n}(int row, int col, int depth, int depth2, int depth3) {
return ${n}(${hp(g,p)});
}
`}if(e.shapeInfo.isUniform)return`
float ${n}(int row, int col, int depth, int depth2, int depth3) {
float index = dot(
vec4(row, col, depth, depth2),
vec4(${o}, ${i}, ${s}, ${a})) +
depth3;
${pp(e)}
}
`;let u=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,h=d[0],c=d[1];if(c===o&&u==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}, ${a}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${c}.0, ${h}.0);
return sampleTexture(${r}, uv);
}
`;if(c===a&&u==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]}, ${t[3]}, 1));
int texC = depth3;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${c}.0, ${h}.0);
return sampleTexture(${r}, uv);
}
`;let f=nl(r);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 * ${o} + col * ${i} + depth * ${s} +
depth2 * ${a} + depth3 + ${f};
vec2 uv = uvFromFlat(${h}, ${c}, index);
return sampleTexture(${r}, uv);
}
`}function N9(e){let t=e.shapeInfo.logicalShape,r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1),{newShape:a,keptDims:s}=k.squeezeShape(t);if(a.length<t.length){let g=dp(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
${up(g)}
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
return ${n}(${hp(y,s)});
}
`}let i=t[5],o=t[4]*i,l=t[3]*o,p=t[2]*l,u=t[1]*p;if(e.shapeInfo.isUniform)return`
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int index = round(dot(
vec4(row, col, depth, depth2),
vec4(${u}, ${p}, ${l}, ${o})) +
dot(
vec2(depth3, depth4),
vec2(${i}, 1)));
${pp(e)}
}
`;let d=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,c=h[0],f=h[1];if(f===u&&d==null)return`
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${p}, ${l}, ${o}, ${i})) +
float(depth4);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${f}.0, ${c}.0);
return sampleTexture(${r}, uv);
}
`;if(f===i&&d==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]},
${t[4]})) + float(depth3);
int texC = depth4;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${f}.0, ${c}.0);
return sampleTexture(${r}, uv);
}
`;let m=nl(r);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 * ${u} + col * ${p} + depth * ${l} +
depth2 * ${o} + depth3 * ${i} + depth4 + ${m};
vec2 uv = uvFromFlat(${c}, ${f}, index);
return sampleTexture(${r}, uv);
}
`}function pp(e){let t=e.name,r=k.sizeFromShape(e.shapeInfo.logicalShape);return r<2?`return ${t};`:`
for (int i = 0; i < ${r}; i++) {
if (i == index) {
return ${t}[i];
}
}
`}function _9(e,t){let r=e.name,n=r.charAt(0).toUpperCase()+r.slice(1),a="get"+n+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=eC(e.shapeInfo.logicalShape,t.logicalShape),l=pt(i),p=i-s,u,d=["x","y","z","w","u","v"];s===0?u="":i<2&&o.length>=1?u="coords = 0;":u=o.map(g=>`coords.${d[g+p]} = 0;`).join(`
`);let h="";i<2&&s>0?h="coords":h=e.shapeInfo.logicalShape.map((g,y)=>`coords.${d[y+p]}`).join(", ");let c="return outputValue;",f=k.sizeFromShape(e.shapeInfo.logicalShape)===1,m=k.sizeFromShape(t.logicalShape)===1;if(s===1&&!f&&!m)c=`
return vec4(outputValue.xy, outputValue.xy);
`;else if(f&&!m)i===1?c=`
return vec4(outputValue.x, outputValue.x, 0., 0.);
`:c=`
return vec4(outputValue.x);
`;else if(o.length){let g=s-2,y=s-1;o.indexOf(g)>-1&&o.indexOf(y)>-1?c="return vec4(outputValue.x);":o.indexOf(g)>-1?c="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":o.indexOf(y)>-1&&(c="return vec4(outputValue.xx, outputValue.zz);")}return`
vec4 ${a}() {
${l} coords = getOutputCoords();
${u}
vec4 outputValue = get${n}(${h});
${c}
}
`}function T9(e,t){let r=e.name,n=r.charAt(0).toUpperCase()+r.slice(1),a="get"+n+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&k.arraysEqual(i,s))return`
float ${a}() {
return sampleTexture(${r}, resultUV);
}
`;let p=pt(l),u=eC(e.shapeInfo.logicalShape,t.logicalShape),d=l-o,h,c=["x","y","z","w","u","v"];o===0?h="":l<2&&u.length>=1?h="coords = 0;":h=u.map(m=>`coords.${c[m+d]} = 0;`).join(`
`);let f="";return l<2&&o>0?f="coords":f=e.shapeInfo.logicalShape.map((m,g)=>`coords.${c[g+d]}`).join(", "),`
float ${a}() {
${p} coords = getOutputCoords();
${h}
return get${n}(${f});
}
`}function pt(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function rw(e,t,r){let{newShape:n,keptDims:a}=k.squeezeShape(t),s=t.length,i=e&&s===3&&t[0]===1,o=i?t.slice(1):n,l=!e&&s>1&&!k.arraysEqual(t,r)&&n.length<s||i;return{useSqueezeShape:l,uniformShape:l?o:t,keptDims:a}}function dp(e,t){let r=JSON.parse(JSON.stringify(e));return r.shapeInfo.logicalShape=t,r}function hp(e,t){return t.map(r=>e[r]).join(", ")}function C9(e,t,r,n){let a=r.map((u,d)=>{let h={logicalShape:u.shape,texShape:u.isUniform?null:u.texData.texShape,isUniform:u.isUniform,isPacked:u.isUniform?!1:u.texData.isPacked,flatOffset:null};return u.texData!=null&&u.texData.slice!=null&&u.texData.slice.flatOffset>0&&(h.flatOffset=u.texData.slice.flatOffset),{name:t.variableNames[d],shapeInfo:h}}),s=a.map(u=>u.shapeInfo),i={logicalShape:n.shape,texShape:n.texData.texShape,isUniform:!1,isPacked:n.texData.isPacked,flatOffset:null},o=jJ(a,i,t),l=FT(e.gl,o),p=e.createProgram(l);return j().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:l,source:o,webGLProgram:p,inShapeInfos:s,outShapeInfo:i,variablesLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:(e.buildVao(p),Object.assign({program:t,fragmentShader:l,source:o,webGLProgram:p,inShapeInfos:s,outShapeInfo:i},nC(e,t,p)))}function nC(e,t,r){let n=[],a=[],s,i,o,l=null,p=null;p=e.getUniformLocation(r,"NAN",!1),j().getNumber("WEBGL_VERSION")===1&&(l=e.getUniformLocation(r,"INFINITY",!1));let u=!1;for(let d of t.variableNames){let h={name:d,uniform:e.getUniformLocation(r,d,u),offset:e.getUniformLocation(r,`offset${d}`,u)};t.enableShapeUniforms&&(h.shape=e.getUniformLocation(r,`${d}Shape`,u),h.texShape=e.getUniformLocation(r,`${d}TexShape`,u)),n.push(h)}if(t.enableShapeUniforms&&(s=e.getUniformLocation(r,"outShape",u),o=e.getUniformLocation(r,"outShapeStrides",u),i=e.getUniformLocation(r,"outTexShape",u)),t.customUniforms)for(let d of t.customUniforms)a.push(e.getUniformLocation(r,d.name,u));return{variablesLocations:n,customUniformLocations:a,infLoc:l,nanLoc:p,outShapeLocation:s,outShapeStridesLocation:o,outTexShapeLocation:i}}function g1(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((r,n)=>{let a=r.logicalShape,s=t[n],i=s.shape;if(!k.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(r.isUniform&&s.isUniform)return;let o=r.texShape,l=s.isUniform?null:s.texData.texShape;if(!k.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function E9(e,t,r,n,a){t.program.enableShapeUniforms||(g1(t.inShapeInfos,r),g1([t.outShapeInfo],[n]));let s=n.texData.texture,i=n.texData.texShape;n.texData.isPacked?e.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):e.setOutputMatrixTexture(s.texture,i[0],i[1]),e.setProgram(t.webGLProgram),e.bindVertexArray(t.webGLProgram.vao),j().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN);for(let l=0;l<r.length;++l){let p=r[l],{uniform:u,offset:d,shape:h,texShape:c}=t.variablesLocations[l];if(h){let{uniformShape:f}=rw(t.program.packedInputs,p.shape,p.texData.texShape);switch(f.length){case 1:e.gl.uniform1iv(h,new Int32Array(f));break;case 2:e.gl.uniform2iv(h,new Int32Array(f));break;case 3:e.gl.uniform3iv(h,new Int32Array(f));break;case 4:e.gl.uniform4iv(h,new Int32Array(f));break}}if(c&&e.gl.uniform2i(c,p.texData.texShape[0],p.texData.texShape[1]),u!=null){if(p.isUniform){if(k.sizeFromShape(p.shape)<2)e.gl.uniform1f(u,p.uniformValues[0]);else{let f=p.uniformValues;f instanceof Float32Array||(f=new Float32Array(f)),e.gl.uniform1fv(u,f)}continue}p.texData.slice!=null&&d!=null&&e.gl.uniform1i(d,p.texData.slice.flatOffset),e.setInputMatrixTexture(p.texData.texture.texture,u,l)}}let o=t.outShapeLocation;if(o)switch(n.shape.length){case 1:e.gl.uniform1iv(o,new Int32Array(n.shape));break;case 2:e.gl.uniform2iv(o,new Int32Array(n.shape));break;case 3:e.gl.uniform3iv(o,new Int32Array(n.shape));break;case 4:e.gl.uniform4iv(o,new Int32Array(n.shape));break}if(t.outShapeStridesLocation){let l=k.computeStrides(n.shape);switch(n.shape.length){case 2:e.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(l));break;case 3:e.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(l));break;case 4:e.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(l));break}}if(t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,n.texData.texShape[0],n.texData.texShape[1]),t.program.customUniforms&&a)for(let l=0;l<t.program.customUniforms.length;++l){let p=t.program.customUniforms[l],u=t.customUniformLocations[l],d=a[l];if(p.type==="float")e.gl.uniform1fv(u,d);else if(p.type==="vec2")e.gl.uniform2fv(u,d);else if(p.type==="vec3")e.gl.uniform3fv(u,d);else if(p.type==="vec4")e.gl.uniform4fv(u,d);else if(p.type==="int")e.gl.uniform1iv(u,d);else if(p.type==="ivec2")e.gl.uniform2iv(u,d);else if(p.type==="ivec3")e.gl.uniform3iv(u,d);else if(p.type==="ivec4")e.gl.uniform4iv(u,d);else throw Error(`uniform type ${p.type} is not supported yet.`)}e.executeProgram()}function $9(e,t,r){let n="";t.concat(r).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!i.isUniform){let l=i.texData.texShape,{useSqueezeShape:p,uniformShape:u,keptDims:d}=rw(e.packedInputs,i.shape,l),h="",c="",f="";if(u.length===1&&e.packedInputs){let w=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];h=`${w[0]>1}_${w[1]>1}`}else if(u.length===2&&!e.packedInputs)c=`${u[0]>1}_${u[1]>1}`;else if(u.length>2&&!e.packedInputs){let w=k.computeStrides(u);f=`${w[0]===l[1]}_${w[w.length-1]===l[1]}`}let m=i.shape.length,g=u.length===2&&k.arraysEqual(i.shape,l),y=k.sizeFromShape(i.shape)===1,b=_.getBroadcastDims(i.shape,r.shape),x=!e.packedInputs&&m===r.shape.length&&k.arraysEqual(l,r.texData.texShape),v=e.packedInputs||u.length>2?"":`${l[0]>1}_${l[1]>1}`;n+=`${m}_${x}_${p?d:""}_${u.length}_${y}_${b}_${g}_${h}_${c}_${f}_${v}_${o}`}else{let l=i.isUniform?"uniform":i.texData.texShape;n+=`${i.shape}_${l}_${o}`}});let a=e.userCode,s=e.constructor.name;return s+="_"+n+"_"+a+`${j().getNumber("WEBGL_VERSION")}`,s}function hr(e){return j().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var A9=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=ad.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=Sr();this.outputShape=e,this.enableShapeUniforms=hr(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?bm(["r","c","d"],e):rl(["r","c","d"],e)}
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);
}
${t.output} = result;
}
`}},F9=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=ad.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=Sr();this.outputShape=e,this.enableShapeUniforms=hr(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?bm(["r","c","d"],e):rl(["r","c","d"],e)}
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));
}
${t.output} = result;
}
`}},R9=class{constructor(e){this.variableNames=["A"],this.outTexUsage=on.DOWNLOAD;let t=Sr();this.outputShape=e,this.userCode=`
${QT}
void main() {
float x = getAAtOutCoords();
${t.output} = encode_float(x);
}
`}},D9=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=on.DOWNLOAD;let t=Sr();this.outputShape=e,this.userCode=`
${QT}
void main() {
ivec3 coords = getOutputCoords();
float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
${t.output} = encode_float(x);
}
`}},M9={R:0,G:1,B:2,A:3},y1=class{constructor(e,t=!1,r="RGBA"){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=Sr();this.outputShape=e,this.enableShapeUniforms=hr(this.outputShape.length);let a="result";t&&(a="floor(result * 255. + 0.5)");let s="";for(let i=0;i<r.length;i++){let o=r[i];s+=`
if(offset == ${i}) {
result = values[${M9[o]}];
}`}this.userCode=`
${this.enableShapeUniforms?tw():ew(e)}
void main() {
ivec3 coords = getOutputCoords();
int flatIndex = getFlatIndex(coords);
float result = 0.;
int offset = imod(flatIndex, ${r.length});
flatIndex = idiv(flatIndex, ${r.length}, 1.);
int r = flatIndex / texShape[1];
if (r < texShape[0]) {
int c = imod(flatIndex, texShape[1]);
vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
vec4 values = ${n.texture2D}(A, uv);
${s}
}
${n.output} = vec4(${a}, 0., 0., 0.);
}
`}},O9=class{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let r=Sr();this.outputShape=e,this.enableShapeUniforms=hr(this.outputShape.length);let n="",a="result";t&&(a="floor(result * 255. + 0.5)");for(let s=0;s<=1;s++)for(let i=0;i<=1;i++){let o=s*2+i;n+=`
localCoords = coords;
if(localCoords[2] + ${i} < ${this.enableShapeUniforms?"outShape[2]":`${e[2]}`}) {
localCoords[2] += ${i};
if (localCoords[1] + ${s} < ${this.enableShapeUniforms?"outShape[1]":`${e[1]}`}) {
localCoords[1] += ${s};
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 = ${r.texture2D}(A, uv);
if (offset == 0) {
result[${o}] = values[0];
} else if (offset == 1) {
result[${o}] = values[1];
} else if (offset == 2) {
result[${o}] = values[2];
} else {
result[${o}] = values[3];
}
}
}
`}this.userCode=`
${this.enableShapeUniforms?tw():ew(e)}
void main() {
ivec3 coords = getOutputCoords();
vec4 result = vec4(0.);
int flatIndex, r, c, offset;
ivec3 localCoords;
vec2 uv;
vec4 values;
${n}
${r.output} = ${a};
}
`}},aC={};Ee(aC,{bindVertexProgramAttributeStreams:()=>cC,createBufferFromOutputTexture:()=>gC,createFloat16MatrixTexture:()=>uC,createFloat16PackedMatrixTexture:()=>hC,createFloat32MatrixTexture:()=>lC,createIndexBuffer:()=>oC,createPackedMatrixTexture:()=>dC,createUnsignedBytesMatrixTexture:()=>pC,createVertexBuffer:()=>iC,createVertexShader:()=>sC,downloadByteEncodedFloatMatrixFromOutputTexture:()=>bC,downloadFloat32MatrixFromBuffer:()=>yC,downloadMatrixFromPackedOutputTexture:()=>vC,downloadPackedMatrixFromBuffer:()=>xC,getInternalFormatForFloat16MatrixTexture:()=>aw,getInternalFormatForFloat16PackedMatrixTexture:()=>ow,getInternalFormatForFloat32MatrixTexture:()=>nw,getInternalFormatForPackedMatrixTexture:()=>iw,getInternalFormatForUnsignedBytesMatrixTexture:()=>sw,uploadDenseMatrixToTexture:()=>fC,uploadPixelDataToTexture:()=>mC});function sC(e){let t=Sr(),r=`${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 AT(e,r)}function iC(e){let t=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return MT(e,t)}function oC(e){let t=new Uint16Array([0,1,2,2,1,3]);return OT(e,t)}function uh(e,t,r,n,a,s){zT(t,r);let i=LT(e),o=e.TEXTURE_2D;return pe(e,()=>e.bindTexture(o,i)),pe(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),pe(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),pe(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),pe(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),j().getNumber("WEBGL_VERSION")===1?pe(e,()=>e.texImage2D(o,0,n,t,r,0,a,s,null)):pe(e,()=>e.texStorage2D(o,1,n,t,r)),pe(e,()=>e.bindTexture(e.TEXTURE_2D,null)),{texture:i,texShape:[r,t]}}function nw(e){return e.internalFormatFloat}function lC(e,t,r,n){let[a,s]=lh(t,r);return uh(e,a,s,nw(n),n.textureFormatFloat,e.FLOAT)}function aw(e){return e.internalFormatHalfFloat}function uC(e,t,r,n){let[a,s]=lh(t,r);return uh(e,a,s,aw(n),n.textureFormatFloat,n.textureTypeHalfFloat)}function sw(e){return e.downloadTextureFormat}function pC(e,t,r,n){let[a,s]=lh(t,r);return uh(e,a,s,sw(n),e.RGBA,e.UNSIGNED_BYTE)}function iw(e){return e.internalFormatPackedFloat}function dC(e,t,r,n){let[a,s]=op(t,r);return uh(e,a,s,iw(n),e.RGBA,e.FLOAT)}function ow(e){return e.internalFormatPackedHalfFloat}function hC(e,t,r,n){let[a,s]=op(t,r);return uh(e,a,s,ow(n),e.RGBA,n.textureTypeHalfFloat)}function cC(e,t,r){return pe(e,()=>e.bindBuffer(e.ARRAY_BUFFER,r)),qg(e,t,"clipSpacePos",r,3,20,0)&&qg(e,t,"uv",r,2,20,12)}function fC(e,t,r,n,a,s){pe(e,()=>e.bindTexture(e.TEXTURE_2D,t));let i,o,l;a instanceof Uint8Array?(i=new Uint8Array(r*n*4),o=e.UNSIGNED_BYTE,l=e.RGBA):(i=new Float32Array(r*n*4),o=e.FLOAT,l=s.internalFormatPackedFloat),i.set(a),j().getNumber("WEBGL_VERSION")===2?pe(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,r,n,e.RGBA,o,i)):pe(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,r,n,0,e.RGBA,o,i)),pe(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function mC(e,t,r){pe(e,()=>e.bindTexture(e.TEXTURE_2D,t)),r.data instanceof Uint8Array?j().getNumber("WEBGL_VERSION")===2?pe(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,r.width,r.height,e.RGBA,e.UNSIGNED_BYTE,r.data)):pe(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,r.width,r.height,0,e.RGBA,e.UNSIGNED_BYTE,r.data)):j().getNumber("WEBGL_VERSION")===2?pe(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,r)):pe(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,r)),pe(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function gC(e,t,r,n){let a=e.createBuffer();pe(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,a));let s=4*4*t*r;return pe(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),pe(e,()=>e.readPixels(0,0,r,t,e.RGBA,e.FLOAT,0)),pe(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),a}function yC(e,t,r){let n=e,a=new Float32Array(r);return n.bindBuffer(n.PIXEL_PACK_BUFFER,t),n.getBufferSubData(n.PIXEL_PACK_BUFFER,0,a),n.bindBuffer(n.PIXEL_PACK_BUFFER,null),a}function bC(e,t,r,n){let[a,s]=lh(t,r),i=4,o=new Uint8Array(FJ(t*r,i));return pe(e,()=>e.readPixels(0,0,a,s,n.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function xC(e,t,r,n,a,s,i,o){let l=e,p=new Float32Array(RJ(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,p),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),p}function vC(e,t,r){let n=new Float32Array(t*r*4);return pe(e,()=>e.readPixels(0,0,r,t,e.RGBA,e.FLOAT,n)),n}var rc=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.itemsToPoll=[];let t=j().getNumber("WEBGL_VERSION");if(e!=null?(this.gl=e,CT(t,e)):this.gl=Vn(t),e=this.gl,j().getNumber("WEBGL_VERSION")===2){let a=e;this.createVertexArray=()=>pe(a,()=>a.createVertexArray()),this.bindVertexArray=s=>pe(a,()=>a.bindVertexArray(s)),this.deleteVertexArray=s=>pe(a,()=>a.deleteVertexArray(s)),this.getVertexArray=()=>pe(a,()=>a.getParameter(a.VERTEX_ARRAY_BINDING))}else if(e!=null){let a=e.getExtension("OES_vertex_array_object");if(a==null)throw new Error("All WebGL1 implementations are expected to offer OES_vertex_array_object.");this.createVertexArray=()=>pe(e,()=>a.createVertexArrayOES()),this.bindVertexArray=s=>pe(e,()=>a.bindVertexArrayOES(s)),this.deleteVertexArray=s=>pe(e,()=>a.deleteVertexArrayOES(s)),this.getVertexArray=()=>pe(e,()=>e.getParameter(a.VERTEX_ARRAY_BINDING_OES))}let r="WEBGL_color_buffer_float",n="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),j().getNumber("WEBGL_VERSION")===1){let a="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=Rp(this.gl,a),ln(this.gl,s))this.textureHalfFloatExtension=Rp(this.gl,s);else if(j().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(r),ln(this.gl,n))this.colorBufferHalfFloatExtension=Rp(this.gl,n);else if(j().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(r="EXT_color_buffer_float",ln(this.gl,r))this.colorBufferFloatExtension=this.gl.getExtension(r);else if(ln(this.gl,n))this.colorBufferHalfFloatExtension=this.gl.getExtension(n);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=iC(this.gl),this.indexBuffer=oC(this.gl),this.framebuffer=PT(this.gl),this.textureConfig=Yv(this.gl,this.textureHalfFloatExtension)}get debug(){return j().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),this.outputTexture!=null&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture. This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let e=this.gl;pe(e,()=>e.finish()),pe(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),pe(e,()=>e.deleteFramebuffer(this.framebuffer)),pe(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),pe(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),pe(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),lC(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),uC(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),pC(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),mC(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,r,n){this.throwIfDisposed(),fC(this.gl,e,t,r,n,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),hC(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),dC(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(Kg(this.gl,this.framebuffer),this.outputTexture=null),pe(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,r){return this.downloadMatrixDriver(e,()=>bC(this.gl,t,r,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,r,n,a,s){return xC(this.gl,e,t,r,n,a,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return yC(this.gl,e,t)}createBufferFromTexture(e,t,r){this.bindTextureToFrameBuffer(e);let n=gC(this.gl,t,r,this.textureConfig);return this.unbindTextureToFrameBuffer(),n}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,r;if(j().getBool("WEBGL_FENCE_API_ENABLED")){let n=e,a=n.fenceSync(n.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),r=()=>{let s=n.clientWaitSync(a,0,0);return s===n.ALREADY_SIGNALED||s===n.CONDITION_SATISFIED},t=a}else j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),r=()=>this.isQueryAvailable(t,j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):r=()=>!0;return{query:t,isFencePassed:r}}downloadMatrixFromPackedTexture(e,t,r){return this.downloadMatrixDriver(e,()=>vC(this.gl,t,r))}createProgram(e){this.throwIfDisposed();let t=this.gl;this.vertexShader==null&&(this.vertexShader=sC(t));let r=RT(t);pe(t,()=>t.attachShader(r,this.vertexShader)),pe(t,()=>t.attachShader(r,e)),DT(t,r);let n=Object.assign(r,{vao:this.createVertexArray()});return this.debug&&Yh(t,n),n}buildVao(e){this.setProgram(e),this.bindVertexArray(e.vao);let t=this.gl;pe(t,()=>t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,this.indexBuffer)),cC(t,e,this.vertexBuffer)}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&(pe(this.gl,()=>this.gl.deleteProgram(e)),this.deleteVertexArray(e.vao))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&Yh(this.gl,this.program),pe(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,r=!0){return this.throwIfDisposed(),r?WT(this.gl,e,t):UT(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),pe(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,r){this.throwIfDisposed(),this.throwIfNoProgram(),VT(this.gl,e,t,r)}setOutputMatrixTexture(e,t,r){this.setOutputMatrixTextureDriver(e,r,t)}setOutputPackedMatrixTexture(e,t,r){this.throwIfDisposed();let[n,a]=op(t,r);this.setOutputMatrixTextureDriver(e,n,a)}setOutputMatrixWriteRegion(e,t,r,n){this.setOutputMatrixWriteRegionDriver(r,e,n,t)}setOutputPackedMatrixWriteRegion(e,t,r,n){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&Yh(this.gl,this.program),Dp(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;if(this.debug){let t=this.getVertexArray();console.assert(t===this.program.vao,"VAO changed between setProgram and executeProgram!"),this.debugValidate()}pe(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),pe(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=Rp(this.gl,j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}getQueryTimerExtensionWebGL2(){return this.getQueryTimerExtension()}getQueryTimerExtensionWebGL1(){return this.getQueryTimerExtension()}beginQuery(){if(j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let r=this.gl,n=this.getQueryTimerExtensionWebGL2(),a=r.createQuery();return r.beginQuery(n.TIME_ELAPSED_EXT,a),a}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,r=this.getQueryTimerExtensionWebGL2();t.endQuery(r.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await k.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let r=this.gl;return r.getQueryParameter(e,r.QUERY_RESULT)/1e6}else{let r=this.getQueryTimerExtensionWebGL1();return r.getQueryObjectEXT(e,r.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let r=this.gl,n=this.getQueryTimerExtensionWebGL2(),a=r.getQueryParameter(e,r.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),a&&!this.disjoint}else{let r=this.getQueryTimerExtensionWebGL1(),n=r.getQueryObjectEXT(e,r.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),n&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=L9(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:r}=this.itemsToPoll[t];r()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){if(this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),this.itemsToPoll.length>1)return;let r;"setTimeoutCustom"in j().platform&&(r=j().platform.setTimeoutCustom.bind(j().platform)),k.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0),()=>0,null,r)}bindTextureToFrameBuffer(e){this.throwIfDisposed(),Qh(this.gl,e,this.framebuffer),this.debug&&Dp(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(Qh(this.gl,this.outputTexture,this.framebuffer),this.debug&&Dp(this.gl)):Kg(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let r=t();return this.unbindTextureToFrameBuffer(),r}setOutputMatrixTextureDriver(e,t,r){this.throwIfDisposed();let n=this.gl;Qh(n,e,this.framebuffer),this.debug&&Dp(n),this.outputTexture=e,pe(n,()=>n.viewport(0,0,t,r)),pe(n,()=>n.scissor(0,0,t,r))}setOutputMatrixWriteRegionDriver(e,t,r,n){this.throwIfDisposed(),pe(this.gl,()=>this.gl.scissor(e,t,r,n))}throwIfDisposed(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(this.program==null)throw new Error("No GPU program is currently set.")}};function L9(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:z9,bincountImpl:wC,bincountReduceImpl:P9,bitwiseAndImpl:B9,castImpl:W9,ceilImpl:U9,concatImpl:V9,equalImpl:G9,expImpl:H9,expm1Impl:j9,floorImpl:q9,gatherNdImpl:K9,gatherV2Impl:X9,greaterImpl:Z9,greaterEqualImpl:J9,lessImpl:Y9,lessEqualImpl:Q9,linSpaceImpl:eY,logImpl:tY,maxImpl:rY,maximumImpl:nY,minimumImpl:aY,multiplyImpl:sY,negImpl:iY,notEqualImpl:oY,prodImpl:lY,raggedGatherImpl:uY,raggedRangeImpl:pY,raggedTensorToTensorImpl:dY,rangeImpl:hY,rsqrtImpl:cY,scatterImpl:fY,sigmoidImpl:mY,simpleAbsImpl:kC,sliceImpl:gY,sparseFillEmptyRowsImpl:yY,sparseReshapeImpl:bY,sparseSegmentReductionImpl:IC,sqrtImpl:xY,staticRegexReplaceImpl:vY,stridedSliceImpl:wY,stringNGramsImpl:kY,stringSplitImpl:IY,stringToHashBucketFastImpl:SY,subImpl:NY,tileImpl:_Y,topKImpl:TY,transposeImpl:lw,uniqueImpl:CY}=Ov;function SC(e,t){return["x","y","z","w","u","v"].slice(0,t).map(r=>`${e}.${r}`)}function gr(e,t){return t===1?[e]:SC(e,t)}function EY(e,t){if(e===1)return"rc";let r="";for(let n=0;n<e;n++)r+=t[n],n<e-1&&(r+=",");return r}var $Y=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=hr(this.outputShape.length),this.rank===0)this.userCode=`
void main() {
setOutput(vec4(getA(), 0., 0., 0.));
}
`;else{let t=gr("rc",this.rank),r=pt(this.rank),n=this.getOutOfBoundsCondition(t),a=this.getSetup(t),s=this.getOutput(t);this.userCode=`
void main() {
${r} rc = getOutputCoords();
if(${n}) {
setOutput(vec4(0));
} else {
${a}
setOutput(vec4(${s}));
}
}
`}}getSourceCoordsArr(e){let t=[];for(let r=0;r<=1;r++)for(let n=0;n<=1;n++){let a=`${r===0?"r":"rp1"}, ${n===0?"c":"cp1"}`;for(let s=2;s<this.rank;s++)a=`${e[e.length-1-s]},`+a;t.push(a)}return t}getOutOfBoundsCondition(e){if(this.rank===1)return`rc > ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let t="";for(let r=this.rank-2;r<this.rank;r++)t+=`${e[r]} >= ${this.enableShapeUniforms?`outShape[${r}]`:this.outputShape[r]}`,r<this.rank-1&&(t+="||");return t}getSetup(e){if(this.rank===1)return"";let t=e.slice(-2),r=this.enableShapeUniforms?`outShape[${this.rank} - 1]`:this.outputShape[this.rank-1],n=this.enableShapeUniforms?`outShape[${this.rank} - 2]`:this.outputShape[this.rank-2];return`
int r = ${t[0]};
int c = ${t[1]};
int rp1 = r + 1;
int cp1 = c + 1;
bool cEdge = cp1 >= ${r};
bool rEdge = rp1 >= ${n};
`}getOutput(e){let t=this.getSourceCoordsArr(e);return this.rank===1?`getA(rc), (rc + 1 >= ${this.enableShapeUniforms?"outShape":this.outputShape[0]} ? 0. : getA(rc + 1)), 0, 0`:`getA(${t[0]}),
cEdge ? 0. : getA(${t[1]}),
rEdge ? 0. : getA(${t[2]}),
rEdge || cEdge ? 0. : getA(${t[3]})`}},NC=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=hr(this.outputShape.length);let r="";for(let n=0;n<4;n++){let a="thisRC = rc;";n%2===1&&(a+="thisRC.z += 1;"),n>1&&(a+="thisRC.y += 1;"),r+=`
${a}
${n>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
int flatIndex = getFlatIndex(thisRC);
ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));
result[${n}] =
getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
${n>0?"}":""}
`}this.userCode=`
${AY(t,this.enableShapeUniforms)}
${this.enableShapeUniforms?tw():ew(e)}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = vec4(0.);
ivec3 thisRC;
int rows = ${this.enableShapeUniforms?"outShape[1]":e[1]};
int cols = ${this.enableShapeUniforms?"outShape[2]":e[2]};
${r}
setOutput(result);
}
`}};function AY(e,t){return`
ivec3 inputCoordsFromReshapedOutCoords(int index) {
${t?HJ(["r","c","d"],"inputShape"):rl(["r","c","d"],e)}
return ivec3(r, c, d);
}
`}var FY=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.usedTextures={},this.logEnabled=!1}acquireTexture(e,t,r){let n=x1(t,r),a=v1(e,n,r);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=b1(e,n,this.gpgpu.gl,this.gpgpu.textureConfig,r);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].pop();return this.usedTextures[a].push(o),o}let i;return n===sr.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):n===sr.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):n===sr.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):n===sr.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):n===sr.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,r,n){if(this.freeTextures==null)return;let a=x1(r,n),s=v1(t,a,n);s in this.freeTextures||(this.freeTextures[s]=[]);let i=b1(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,n),o=j().getNumber("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],p=l&&l.indexOf(e);if(p==null||p<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l[p]=l[l.length-1],l.pop(),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function RY(e,t){let r=e;if(t===r.R32F)return 4;if(t===r.R16F)return 2;if(t===r.RGBA32F||t===e.RGBA)return 16;if(t===r.RGBA16F)return 8;if(t===r.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function b1(e,t,r,n,a){let s=DY(t,n),i;if(a){let[l,p]=op(e[0],e[1]);i=l*p}else{let[l,p]=lh(e[0],e[1]);i=l*p}let o=RY(r,s);return i*o}function DY(e,t){switch(e){case sr.PACKED_2X2_FLOAT32:return iw(t);case sr.PACKED_2X2_FLOAT16:return ow(t);case sr.UNPACKED_FLOAT32:return nw(t);case sr.UNPACKED_FLOAT16:return aw(t);case sr.PACKED_4X1_UNSIGNED_BYTE:return sw(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function MY(e){return j().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?sr.PACKED_2X2_FLOAT32:sr.UNPACKED_FLOAT32:e?sr.PACKED_2X2_FLOAT16:sr.UNPACKED_FLOAT16}function x1(e,t){if(e===on.UPLOAD)return sr.PACKED_2X2_FLOAT32;if(e===on.RENDER||e==null)return MY(t);if(e===on.DOWNLOAD||e===on.PIXELS)return sr.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function v1(e,t,r){return`${e[0]}_${e[1]}_${t}_${r}`}var aa=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=hr(this.outputShape.length),this.userCode=`
float unaryOperation(float x) {
${t}
}
void main() {
float x = getAAtOutCoords();
float y = unaryOperation(x);
setOutput(y);
}
`}},Cn="if (isnan(x)) return x;",OY="return x;",w1="return abs(x);",LY="return (x >= 0.0) ? x : (exp(x) - 1.0);",zY=Cn+`
return (x < 0.0) ? 0.0 : x;
`,PY=Cn+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,Qa="return x;",BY="return 1.0 / (1.0 + exp(-1.0 * x));",WY="return x;",UY=`
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;
`,VY=`
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;
`,GY=`
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;
`,HY="return 1.0 / (1.0 + exp(-1.0 * x));",ss=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=hr(this.outputShape.length),this.userCode=`
vec4 unaryOperation(vec4 x) {
${t}
}
void main() {
vec4 x = getAAtOutCoords();
vec4 y = unaryOperation(x);
setOutput(y);
}
`}},jY=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=hr(this.outputShape.length);let t=e.length,r=gr("rc",t),n=pt(t),a=EY(t,r),s=r.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
void main() {
${n} rc = getOutputCoords();
vec4 packedInput = getA(${a});
setOutput(getChannel(packedInput, ${i}));
}
`}},qY=ga.whereImpl,KY=1e-7,XY=1e-4,jm={};function ZY(e){return e in jm||(jm[e]={}),jm[e]}var JY=j().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),YY=600;function QY(){return j().global.screen==null?1024:j().global.screen.height*j().global.screen.width*window.devicePixelRatio*YY/1024/1024}var uw=class _C extends pd{nextDataId(){return _C.nextDataId++}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,!j().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let r;if(t!=null){if(t instanceof rc)r=t;else{let n=Vn(j().getNumber("WEBGL_VERSION"),t);r=new rc(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Vn(j().getNumber("WEBGL_VERSION"));r=new rc(n),this.binaryCache=ZY(j().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=r,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new FY(this.gpgpu),this.numMBBeforeWarning=QY(),this.texData=new Xc(this,wn())}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}writeTexture(t,r,n,a,s,i){let o=this.makeTensorInfo(r,n),l=this.texData.get(o.dataId);l.isPacked=!1,l.texture={texture:t,texShape:[a,s]},l.texShape=[a,s];let p=Mp(r),u=new y1(p,!1,i),d=this.runWebGLProgram(u,[o],n,[[a,s]]);return d.shape=r,l.texture=null,this.disposeIntermediateTensorInfo(o),d.dataId}write(t,r,n){if((j().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||j().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 a={id:this.nextDataId()};return this.texData.set(a,{shape:r,dtype:n,values:t,usage:on.UPLOAD,refCount:1}),a}refCount(t){return this.texData.has(t)?this.texData.get(t).refCount:0}incRef(t){let r=this.texData.get(t);r.refCount++}decRef(t){if(this.texData.has(t)){let r=this.texData.get(t);r.refCount--}}move(t,r,n,a,s){if(j().getBool("DEBUG")&&this.checkNumericalProblems(r),a==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(t,{shape:n,dtype:a,values:r,usage:on.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(t){this.disposeData(t.dataId)}readSync(t){let r=this.texData.get(t),{values:n,dtype:a,complexTensorInfos:s,slice:i,shape:o,isPacked:l}=r;if(i!=null){let h;l?h=new ss(o,Qa):h=new aa(o,Qa);let c=this.runWebGLProgram(h,[{dataId:t,shape:o,dtype:a}],a),f=this.readSync(c.dataId);return this.disposeIntermediateTensorInfo(c),f}if(n!=null)return this.convertAndCacheOnCPU(t);if(a==="string")return n;let p=this.activeTimers!=null,u;p&&(u=k.now());let d;if(a==="complex64"){let h=this.readSync(s.real.dataId),c=this.readSync(s.imag.dataId);d=_.mergeRealAndImagArrays(h,c)}else d=this.getValuesFromTexture(t);return p&&(this.downloadWaitMs+=k.now()-u),this.convertAndCacheOnCPU(t,d)}async read(t){if(this.pendingRead.has(t)){let f=this.pendingRead.get(t);return new Promise(m=>f.push(m))}let r=this.texData.get(t),{values:n,shape:a,slice:s,dtype:i,complexTensorInfos:o,isPacked:l}=r;if(s!=null){let f;l?f=new ss(a,Qa):f=new aa(a,Qa);let m=this.runWebGLProgram(f,[{dataId:t,shape:a,dtype:i}],i),g=this.read(m.dataId);return this.disposeIntermediateTensorInfo(m),g}if(n!=null)return this.convertAndCacheOnCPU(t);if(j().getBool("DEBUG")&&!j().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&j().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let p=null,u;if(i!=="complex64"&&j().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(t);let f=this.texData.get(u.dataId);p=this.gpgpu.createBufferFromTexture(f.texture.texture,...Wh(a))}this.pendingRead.set(t,[]),i!=="complex64"&&await this.gpgpu.createAndWaitForFence();let d;if(i==="complex64"){let f=await Promise.all([this.read(o.real.dataId),this.read(o.imag.dataId)]),m=f[0],g=f[1];d=_.mergeRealAndImagArrays(m,g)}else if(p==null)d=this.getValuesFromTexture(t);else{let f=k.sizeFromShape(a);d=this.gpgpu.downloadFloat32MatrixFromBuffer(p,f)}if(u!=null&&this.disposeIntermediateTensorInfo(u),p!=null){let f=this.gpgpu.gl;pe(f,()=>f.deleteBuffer(p))}let h=this.convertAndCacheOnCPU(t,d),c=this.pendingRead.get(t);return this.pendingRead.delete(t),c.forEach(f=>f(h)),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t)&&wn().removeDataId(t,this),this.pendingDeletes--),h}readToGPU(t,r={}){let n=this.texData.get(t),{values:a,shape:s,slice:i,dtype:o,isPacked:l,texture:p}=n;if(o==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(i!=null){let c;l?c=new ss(s,Qa):c=new aa(s,Qa);let f=this.runWebGLProgram(c,[{dataId:t,shape:s,dtype:o}],o),m=this.readToGPU(f,r);return this.disposeIntermediateTensorInfo(f),m}if(p==null)throw a!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let u=this.decode(t,r.customTexShape),d=wn().makeTensorFromTensorInfo(u),h=this.texData.get(u.dataId);return Object.assign({tensorRef:d},h.texture)}bufferSync(t){let r=this.readSync(t.dataId);if(t.dtype==="string")try{let n=r.map(a=>k.decodeString(a));return Le(t.shape,t.dtype,n)}catch{throw new Error("Failed to decode encoded string bytes into utf-8")}return Le(t.shape,t.dtype,r)}checkNumericalProblems(t){if(t!=null)for(let r=0;r<t.length;r++){let n=t[r];if(!ET(n))throw j().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(t){let{shape:r,dtype:n,isPacked:a}=this.texData.get(t),s=k.sizeFromShape(r);if(j().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(t),c=this.texData.get(h.dataId),f=this.gpgpu.downloadMatrixFromPackedTexture(c.texture.texture,...Wh(r)).subarray(0,s);return this.disposeIntermediateTensorInfo(h),f}let i=j().getBool("WEBGL_PACK")&&a===!0,o=i?Mp(r):r,l=i?new D9(o):new R9(o),p=this.runWebGLProgram(l,[{shape:o,dtype:n,dataId:t}],"float32"),u=this.texData.get(p.dataId),d=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture.texture,u.texShape[0],u.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(p),d}timerAvailable(){return j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(t){let r=this.activeTimers,n=[],a=!1;this.programTimersStack==null?(this.programTimersStack=n,a=!0):this.activeTimers.push(n),this.activeTimers=n,t();let s=k.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),i=k.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=r,a&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let l=await Promise.all(s);o.kernelMs=k.sum(l),o.getExtraProfileInfo=()=>l.map((p,u)=>({name:i[u],ms:p})).map(p=>`${p.name}: ${p.ms}`).join(", ")}else o.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,o})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:k.now(),endMs:null}}endTimer(t){return j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),t):(t.endMs=k.now(),t)}async getQueryTime(t){if(j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(t);let r=t;return r.endMs-r.startMs}disposeData(t,r=!1){if(this.pendingDisposal.has(t))return!1;if(!this.texData.has(t))return!0;if(r?this.texData.get(t).refCount=0:this.texData.get(t).refCount--,!r&&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,r),this.disposeData(n.imag.dataId,r)),this.texData.delete(t),!0}releaseGPUData(t){let{texture:r,dtype:n,texShape:a,usage:s,isPacked:i,slice:o}=this.texData.get(t),l=o&&o.origDataId||t,p=this.dataRefCount.get(l);p>1?this.dataRefCount.set(l,p-1):(this.dataRefCount.delete(l),r!=null&&(this.numBytesInGPU-=this.computeBytes(a,n),this.textureManager.releaseTexture(r,a,s,i)));let u=this.texData.get(t);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(t){return this.uploadToGPU(t),this.texData.get(t).texture.texture}getDataInfo(t){return this.texData.get(t)}shouldExecuteOnCPU(t,r=JY){return j().getBool("WEBGL_CPU_FORWARD")&&t.every(n=>this.texData.get(n.dataId).texture==null&&k.sizeFromShape(n.shape)<r)}getGPGPUContext(){return this.gpgpu}where(t){_.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let r=t.dataSync();return qY(t.shape,r)}packedUnaryOp(t,r,n){let a=new ss(t.shape,r),s=this.compileAndRun(a,[t],n);return wn().makeTensorFromTensorInfo(s)}abs(t){if(this.shouldExecuteOnCPU([t])&&t.dtype!=="complex64"){let a=kC(this.texData.get(t.dataId).values);return this.makeOutput(t.shape,t.dtype,a)}if(j().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,w1,t.dtype);let r=new aa(t.shape,w1),n=this.compileAndRun(r,[t]);return wn().makeTensorFromTensorInfo(n)}makeTensorInfo(t,r,n){let a;if(r==="string"&&n!=null&&n.length>0&&k.isString(n[0])){let s=n.map(i=>k.encodeString(i));a=this.write(s,t,r)}else a=this.write(n,t,r);return this.texData.get(a).usage=null,{dataId:a,shape:t,dtype:r}}makeOutput(t,r,n){return wn().makeTensorFromTensorInfo(this.makeTensorInfo(t,r,n),this)}unpackTensor(t){let r=new jY(t.shape);return this.runWebGLProgram(r,[t],t.dtype)}packTensor(t){let r=new $Y(t.shape);return this.runWebGLProgram(r,[t],t.dtype,null,!0)}packedReshape(t,r){let n=[Ii(t.shape),...Si(t.shape)],a={dtype:t.dtype,shape:n,dataId:t.dataId},s=[Ii(r),...Si(r)],i=new NC(s,n),o=!0,l=[n],p=this.runWebGLProgram(i,[a],t.dtype,l,o);return{dataId:p.dataId,shape:r,dtype:p.dtype}}decode(t,r){let n=this.texData.get(t),{isPacked:a,shape:s,dtype:i}=n;if(r!=null){let h=k.sizeFromShape(s),c=r[0]*r[1]*4;k.assert(h<=c,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let o=Mp(s),l;a?l=new F9(o):l=new A9(o);let p=!0,u=[r??Wh(o)],d=this.runWebGLProgram(l,[{shape:o,dtype:i,dataId:t}],i,u,p,r);return{dtype:i,shape:s,dataId:d.dataId}}runWebGLProgram(t,r,n,a,s=!1,i){let o=this.makeTensorInfo(t.outputShape,n),l=this.texData.get(o.dataId);if(t.packedOutput&&(l.isPacked=!0),t.outPackingScheme===ad.DENSE){let y=i??Wh(t.outputShape);l.texShape=y.map(b=>b*2)}if(t.outTexUsage!=null&&(l.usage=t.outTexUsage),k.sizeFromShape(o.shape)===0)return l.values=k.getTypedArrayFromDType(o.dtype,0),o;let p=[],u=r.map(y=>{if(y.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(y.dataId);if(b.texture==null){if(!t.packedInputs&&k.sizeFromShape(y.shape)<=j().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:y.shape,texData:null,isUniform:!0,uniformValues:b.values};t.packedInputs&&(b.isPacked=!0,b.shape=y.shape)}if(this.uploadToGPU(y.dataId),!!b.isPacked!=!!t.packedInputs)y=b.isPacked?this.unpackTensor(y):this.packTensor(y),p.push(y),b=this.texData.get(y.dataId);else if(b.isPacked&&!sd(b.shape,y.shape)){let x=y,v=y.shape;y.shape=b.shape,y=this.packedReshape(y,v),p.push(y),b=this.texData.get(y.dataId),x.shape=v}return{shape:y.shape,texData:b,isUniform:!1}});this.uploadToGPU(o.dataId);let d={shape:o.shape,texData:l,isUniform:!1},h=$9(t,u,d),c=this.getAndSaveBinary(h,()=>C9(this.gpgpu,t,u,d)),f=this.activeTimers!=null,m;f&&(m=this.startTimer()),j().get("ENGINE_COMPILE_ONLY")||E9(this.gpgpu,c,u,d,a),p.forEach(y=>this.disposeIntermediateTensorInfo(y)),f&&(m=this.endTimer(m),this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime(m)}));let g=j().getNumber("WEBGL_FLUSH_THRESHOLD");if(g>0){let y=k.now();y-this.lastGlFlushTime>g&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=y)}if(!j().getBool("WEBGL_LAZILY_UNPACK")&&l.isPacked&&s===!1){let y=this.unpackTensor(o);return this.disposeIntermediateTensorInfo(o),y}return o}compileAndRun(t,r,n,a,s=!1){return n=n||r[0].dtype,this.runWebGLProgram(t,r,n,a,s)}getAndSaveBinary(t,r){return t in this.binaryCache||(this.binaryCache[t]=r()),this.binaryCache[t]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(j().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(t=>{this.gpgpu.deleteProgram(this.binaryCache[t].webGLProgram),delete this.binaryCache[t]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement<"u"&&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=W(()=>{if(!j().get("WEBGL_RENDER_FLOAT32_ENABLED")){let t=j().getBool("DEBUG");j().set("DEBUG",!1);let r=this.abs(we(1e-8)).dataSync()[0];if(j().set("DEBUG",t),r>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?KY:XY}uploadToGPU(t){let r=this.texData.get(t),{shape:n,dtype:a,values:s,texture:i,usage:o,isPacked:l}=r;if(i!=null)return;let p=this.activeTimers!=null,u;p&&(u=k.now());let d=r.texShape;if(d==null&&(d=jT(n,l),r.texShape=d),s!=null){let h=Mp(n),c,f=d[1],m=d[0],g=s instanceof Uint8Array||s instanceof Uint8ClampedArray;(l||!g)&&([f,m]=op(d[0],d[1])),l?c=new O9(h,g):c=new y1(h,g);let y=g?[m,f]:d,b=this.makeTensorInfo(y,a),x=this.texData.get(b.dataId);g?x.usage=on.PIXELS:x.usage=on.UPLOAD,x.texShape=y,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(b.dataId),f,m,s);let v=[[m,f]],w=this.runWebGLProgram(c,[b],a,v,!0),N=this.texData.get(w.dataId);r.texShape=N.texShape,r.isPacked=N.isPacked,r.usage=N.usage,j().get("ENGINE_COMPILE_ONLY")?this.disposeData(w.dataId):(r.texture=N.texture,r.values=null,this.texData.delete(w.dataId)),this.disposeIntermediateTensorInfo(b),p&&(this.uploadWaitMs+=k.now()-u)}else{let h=this.acquireTexture(d,o,a,l);r.texture=h}}convertAndCacheOnCPU(t,r){let n=this.texData.get(t),{dtype:a}=n;return r!=null&&(n.values=eQ(r,a)),n.values}acquireTexture(t,r,n,a){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,r,a)}computeBytes(t,r){return t[0]*t[1]*k.bytesPerElement(r)}checkCompileCompletion(){for(let[,t]of Object.entries(this.binaryCache))this.checkCompletion_(t)}async checkCompileCompletionAsync(){let t=[];if(this.gpgpu.parallelCompilationExtension){for(let[,r]of Object.entries(this.binaryCache))t.push(this.checkCompletionAsync_(r));return Promise.all(t)}else{for(let[,r]of Object.entries(this.binaryCache)){let n=new Promise(a=>{try{this.checkCompletion_(r),a(!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 Yb(),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?(Qv(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.values(this.binaryCache)){this.gpgpu.buildVao(t.webGLProgram);let{variablesLocations:r,customUniformLocations:n,infLoc:a,nanLoc:s,outShapeLocation:i,outShapeStridesLocation:o,outTexShapeLocation:l}=nC(this.gpgpu,t.program,t.webGLProgram);t.variablesLocations=r,t.customUniformLocations=n,t.infLoc=a,t.nanLoc=s,t.outShapeLocation=i,t.outShapeStridesLocation=o,t.outTexShapeLocation=l}}createTensorFromGPUData(t,r,n){t.channels=t.channels||"RGBA";let{texture:a,height:s,width:i,channels:o}=t,l=wn().backend;if(!l.gpgpu.gl.isTexture(a))throw new Error("The texture is invalid. Also, please make sure the texture and the TFJS WebGL backend are using the same canvas. If you want to use your own custom canvas, you have to create and use the custom TFJS WebGL backend created from the canvas through 'new tf.MathBackendWebGL(customCanvas)'.");let p=l.writeTexture(a,r,n,s,i,o);return wn().makeTensorFromDataId(p,r,n,l)}};uw.nextDataId=0;function eQ(e,t){if(t==="float32"||t==="complex64")return e;if(t==="int32"||t==="bool"){let r=t==="int32"?new Int32Array(e.length):new Uint8Array(e.length);for(let n=0;n<r.length;++n)r[n]=Math.round(e[n]);return r}else throw new Error(`Unknown dtype ${t}`)}var tQ="4.22.0";function TC(){j().set("WEBGL_FORCE_F16_TEXTURES",!0)}Od.isBrowser()&&ff("webgl",()=>new uw,2);var rQ={forceHalfFloat:TC},pw=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,Ni=class{constructor(e,t,r){this.variableNames=["A","B"],this.outputShape=_.assertAndGetBroadcastShape(t,r),this.enableShapeUniforms=hr(this.outputShape.length),this.userCode=`
float binaryOperation(float a, float b) {
${e}
}
void main() {
float a = getAAtOutCoords();
float b = getBAtOutCoords();
setOutput(binaryOperation(a, b));
}
`}},al=`
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;
`,cp=class{constructor(e,t,r,n=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=_.assertAndGetBroadcastShape(t,r);let a=this.outputShape.length;this.enableShapeUniforms=hr(a);let s="";if(n)if(a===0||k.sizeFromShape(this.outputShape)===1)s=`
result.y = 0.;
result.z = 0.;
result.w = 0.;
`;else if(s=`
${pt(a)} coords = getOutputCoords();
`,a===1)this.enableShapeUniforms?s+=`
result.y = (coords + 1) >= outShape ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`:s+=`
result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`;else{let i=gr("coords",a);this.enableShapeUniforms?s+=`
bool nextRowOutOfBounds =
(${i[a-2]} + 1) >= outShape[${a} - 2];
bool nextColOutOfBounds =
(${i[a-1]} + 1) >= outShape[${a} - 1];
result.y = nextColOutOfBounds ? 0. : result.y;
result.z = nextRowOutOfBounds ? 0. : result.z;
result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
`:s+=`
bool nextRowOutOfBounds =
(${i[a-2]} + 1) >= ${this.outputShape[a-2]};
bool nextColOutOfBounds =
(${i[a-1]} + 1) >= ${this.outputShape[a-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) {
${e}
}
void main() {
vec4 a = getAAtOutCoords();
vec4 b = getBAtOutCoords();
vec4 result = binaryOperation(a, b);
${s}
setOutput(result);
}
`}};function Jr(e){let{inputs:t,backend:r}=e,{x:n}=t;return r.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var nQ={kernelName:so,backendName:"webgl",kernelFunc:Jr};function Ls(e){let{inputs:t,backend:r}=e,{real:n,imag:a}=t,s=r.makeTensorInfo(n.shape,"complex64"),i=r.texData.get(s.dataId),o=Jr({inputs:{x:n},backend:r}),l=Jr({inputs:{x:a},backend:r});return i.complexTensorInfos={real:o,imag:l},s}var aQ={kernelName:Yc,backendName:"webgl",kernelFunc:Ls},CC="return (a < 0.) ? b * a : a;",EC=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function sQ(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{alpha:s}=n,i=r.makeTensorInfo([],"float32",k.createScalarValue(s,"float32")),o=j().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new cp(EC,a.shape,i.shape):new Ni(CC,a.shape,i.shape),l=r.runWebGLProgram(o,[a,i],"float32");return r.disposeIntermediateTensorInfo(i),l}var iQ={kernelName:uo,backendName:"webgl",kernelFunc:sQ},$C="return (a < 0.) ? b * a : a;",AC=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function oQ(e){let{inputs:t,backend:r}=e,{x:n,alpha:a}=t,s=j().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new cp(AC,n.shape,a.shape):new Ni($C,n.shape,a.shape);return r.runWebGLProgram(s,[n,a],"float32")}var lQ={kernelName:_o,backendName:"webgl",kernelFunc:oQ},fp="if (isnan(x)) return x;";function Ke({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:r,dtype:n}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=n||i.dtype;if(o.shouldExecuteOnCPU([i])&&r!=null){let d=o.texData.get(i.dataId),h=r(d.values,l);return o.makeTensorInfo(i.shape,l,h)}let p=j().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,u;return p?u=new ss(i.shape,t):u=new aa(i.shape,e),o.runWebGLProgram(u,[i],l)}}function lr({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:r=!1,supportsComplex:n=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:p}=i,u=o;if(n&&l.dtype==="complex64"){let f=u.texData.get(l.dataId),m=u.texData.get(p.dataId),[g,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(x=>{let[v,w]=x,N={dataId:v.dataId,dtype:v.dtype,shape:l.shape},T={dataId:w.dataId,dtype:w.dtype,shape:p.shape},E=new Ni(e,l.shape,p.shape);return u.runWebGLProgram(E,[N,T],cn(v.dtype,w.dtype))}),b=Ls({inputs:{real:g,imag:y},backend:u});return u.disposeIntermediateTensorInfo(g),u.disposeIntermediateTensorInfo(y),b}let d=s||cn(l.dtype,p.dtype);if((l.dtype==="string"||p.dtype==="string"||u.shouldExecuteOnCPU([l,p]))&&a!=null){let f=u.texData.get(l.dataId).values,m=u.texData.get(p.dataId).values,g=l.dtype==="string"?_.fromUint8ToStringArray(f):f,y=l.dtype==="string"?_.fromUint8ToStringArray(m):m,[b,x]=a(l.shape,p.shape,g,y,d),v=u.makeTensorInfo(x,d),w=u.texData.get(v.dataId);return w.values=b,v}let h=j().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,c;return h?c=new cp(t,l.shape,p.shape,r):c=new Ni(e,l.shape,p.shape),u.runWebGLProgram(c,[l,p],d)}}function id(e,t=!1){if(e==="linear")return t?WY:OY;if(e==="relu")return t?VY:zY;if(e==="elu")return t?UY:LY;if(e==="relu6")return t?GY:PY;if(e==="prelu")return t?AC:$C;if(e==="leakyrelu")return t?EC:CC;if(e==="sigmoid")return t?HY:BY;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var FC=class{constructor(e,t,r,n=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=r,this.enableShapeUniforms=hr(this.outputShape.length);let p=n?e[1]:e[2],u=Math.ceil(p/2),d=n?"i * 2, rc.y":"rc.y, i * 2",h=a?"rc.z, i * 2":"i * 2, rc.z",c=n?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",g="";i&&(o?m=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${i}
}`:l?m=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${i}
}`:m=`vec4 activation(vec4 x) {
${i}
}`,g="result = activation(result);");let y=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let b="rc.x",x="rc.x";e[0]<t[0]?b=`imod(rc.x, ${e[0]})`:t[0]<e[0]&&(x=`imod(rc.x, ${t[0]})`),this.userCode=`
${m}
// Don't use uniform for sharedDimensionPacked for performance.
const float sharedDimension = ${u}.0;
vec4 dot2x2ARowBCol(ivec3 rc) {
vec4 result = vec4(0);
int batchA = ${b};
int batchB = ${x};
for (int i = 0; i < ${u}; i++) {
vec4 a = getMatrixA(batchA, ${d});
vec4 b = getMatrixB(batchB, ${h});
// These swizzled products need to be separately added.
// See: https://github.com/tensorflow/tfjs/issues/1735
result += (${c[0]} * ${f[0]});
result += (${c[1]} * ${f[1]});
}
return result;
}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = dot2x2ARowBCol(rc);
${y}
${g}
setOutput(result);
}
`}},k1={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},I1=class{constructor(e,t,r){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=_.assertAndGetBroadcastShape(t,r),this.userCode=`
float binaryOpComplex(
float areal, float aimag, float breal, float bimag) {
${e}
}
void main() {
float areal = getARealAtOutCoords();
float aimag = getAImagAtOutCoords();
float breal = getBRealAtOutCoords();
float bimag = getBImagAtOutCoords();
setOutput(binaryOpComplex(areal, aimag, breal, bimag));
}
`}},S1="return a * b;";function dw(e){let{inputs:t,backend:r}=e,{a:n,b:a}=t,s=_.upcastType(n.dtype,a.dtype);if(n.dtype==="complex64"){let o=r.texData.get(n.dataId),l=r.texData.get(a.dataId),p=new I1(k1.REAL,n.shape,a.shape),u=new I1(k1.IMAG,n.shape,a.shape),d=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:n.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:n.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],h=r.runWebGLProgram(p,d,"float32"),c=r.runWebGLProgram(u,d,"float32"),f=Ls({inputs:{real:h,imag:c},backend:r});return r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(c),f}if(r.shouldExecuteOnCPU([n,a])){let o=r.texData.get(n.dataId),l=r.texData.get(a.dataId),[p,u]=sY(n.shape,a.shape,o.values,l.values,s),d=r.makeTensorInfo(u,s),h=r.texData.get(d.dataId);return h.values=p,d}let i;return j().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new cp(S1,n.shape,a.shape):i=new Ni(S1,n.shape,a.shape),r.runWebGLProgram(i,[n,a],s)}var uQ={kernelName:ko,backendName:"webgl",kernelFunc:dw};function pQ(e,t,r){let n=[Ii(e.shape),...Si(e.shape)],a={dtype:e.dtype,shape:n,dataId:e.dataId},s=[Ii(t),...Si(t)],i=new NC(s,n),o=!0,l=[n],p=r.runWebGLProgram(i,[a],e.dtype,l,o);return{dataId:p.dataId,shape:t,dtype:p.dtype}}function ue(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{shape:s}=n,i=r,o=k.sizeFromShape(a.shape),l=k.inferFromImplicitShape(s,o),p=k.sizeFromShape(l);k.assert(o===p,()=>`The new shape (${l}) has ${p} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let u=i.texData.get(a.dataId);return u.isPacked&&!sd(a.shape,l)&&!(u.texture!==null&&sd(u.shape,l))?pQ(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var dQ={kernelName:Fu,backendName:"webgl",kernelFunc:ue},N1=class{constructor(e,t){this.variableNames=["x"];let{windowSize:r,batchSize:n,inSize:a,outSize:s}=e;this.outputShape=[n,s];let i=Math.floor(r/4)*4,o=r%4,l="sumValue += dot(values, ones);";if(t!=null){let u=1/t;l=`sumValue += dot(values * ${k.isInt(u)?u.toPrecision(2):u}, ones);`}let p="";a%r>0&&(p=`
if (inIdx < 0 || inIdx >= ${a}) {
return 0.0;
}
`),this.userCode=`
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float getValue(int batch, int inIdx) {
${p}
return getX(batch, inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${r};
float sumValue = 0.0;
for (int i = 0; i < ${i}; 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 + ${i};
if (${o===1}) {
vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);
${l}
} else if (${o===2}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1), 0.0, 0.0);
${l}
} else if (${o===3}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2), 0.0);
${l}
}
setOutput(sumValue);
}
`}},hQ=class{constructor(e,t){this.variableNames=["x"];let{windowSize:r,batchSize:n,inSize:a,outSize:s}=e;this.outputShape=[n,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let p=Math.floor(r/4)*4,u=r%4,d=`
if (${t==="sum"}) {
sumValue += dot(values, ones);
} else if (${t==="prod"}) {
vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
prodValue *= tmp[0] * tmp[1];
} else {
minMaxValue = ${o}(values, minMaxValue);
if (${t==="min"} || ${t==="max"}) {
minMaxValue = ${o}(values, minMaxValue);
bvec4 isNaN = isnan(values);
if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {
minMaxValue = vec4(NAN);
}
}
}
`,h="vec4";t==="all"?(i="1.0",d=`
bool reducedAllValue = all(values);
float floatedReducedAllValue = float(reducedAllValue);
allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
`,h="bvec4"):t==="any"&&(i="0.0",d=`
bool reducedAnyValue = any(values);
float floatedReducedAnyValue = float(reducedAnyValue);
anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
`,h="bvec4");let c="";a%r>0&&(c=`
if (inIdx < 0 || inIdx >= ${a}) {
return initializationValue;
}
`),this.userCode=`
const float initializationValue = ${i};
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 * ${r};
vec4 minMaxValue = vec4(${i});
float prodValue = 1.0;
float sumValue = 0.0;
float allValue = 1.0;
float anyValue = 0.0;
for (int i = 0; i < ${p}; i += 4) {
int inIdx = inOffset + i;
${h} values = ${h}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
getValue(batch, inIdx + 3)
);
${d}
}
int inIdx = inOffset + ${p};
if (${u===1}) {
${h} values = ${h}(
getValue(batch, inIdx),
initializationValue,
initializationValue,
initializationValue
);
${d}
} else if (${u===2}) {
${h} values = ${h}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
initializationValue,
initializationValue
);
${d}
} else if (${u===3}) {
${h} values = ${h}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
initializationValue
);
${d}
}
setOutput(${l});
}
`}};function cQ(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let r=t.length?t[t.length-1].outSize:e[1],n=_.computeOptimalWindowSize(r);t.push({inSize:r,windowSize:n,outSize:Math.ceil(r/n)})}return t}function sl(e,t,r,n){let a=cQ(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:p}=a[i],u,d;r==="mean"?u=i===0?new N1({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:p},o):new N1({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:p}):u=new hQ({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:p},r),d=s,s=n.runWebGLProgram(u,[s],t),d.dataId!==e.dataId&&n.disposeIntermediateTensorInfo(d)}return s}var fQ=class{constructor(e,t){this.variableNames=["A"];let r=new Array(e.length);for(let s=0;s<r.length;s++)r[s]=e[t[s]];this.outputShape=r,this.rank=r.length;let n=pt(this.rank),a=mQ(t);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
setOutput(getA(${a}));
}
`}};function mQ(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let r=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],n=new Array(t);for(let a=0;a<e.length;a++)n[e[a]]=r[a];return n.join()}var gQ=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let r=new Array(e.length);for(let p=0;p<r.length;p++)r[p]=e[t[p]];if(this.outputShape=r,this.rank=r.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let n=pt(this.rank),a=SC("rc",this.rank),s=new Array(this.rank);for(let p=0;p<t.length;p++)s[t[p]]=a[p];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${r[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
void main() {
${n} rc = getOutputCoords();
vec4 result = vec4(0.);
result[0] = ${l};
if(${o}) {
result[1] = ${l};
}
--${a[this.rank-1]};
if(++${a[this.rank-2]} < ${r[this.rank-2]}) {
result[2] = ${l};
if(${o}) {
result[3] = ${l};
}
}
setOutput(result);
}
`}};function xm(e,t,r){let n=j().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new gQ(e.shape,t):new fQ(e.shape,t);return r.runWebGLProgram(n,[e],e.dtype)}function yQ(e,t,r,n){let a=t,s=e.shape.length,i=k.parseAxisParam(a,e.shape),o=i,l=_.getAxesPermutation(o,s),p=l!=null,u=e;p&&(u=xm(e,l,n),o=_.getInnerMostAxes(o.length,s)),_.assertAxesAreInnerMostDims("sum",o,s);let[d,h]=_.computeOutAndReduceShapes(u.shape,o),c=d;r&&(c=_.expandShapeToKeepDim(d,i));let f=k.sizeFromShape(h),m=k.sizeFromShape(e.shape)/f,g=ue({inputs:{x:u},attrs:{shape:[m,f]},backend:n}),y=cf(e.dtype),b=sl(g,y,"sum",n),x=ue({inputs:{x:b},attrs:{shape:c},backend:n});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(b),p&&n.disposeIntermediateTensorInfo(u),x}function vm(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n;return yQ(a,s,i,r)}var bQ={kernelName:Vo,backendName:"webgl",kernelFunc:vm};function xr(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{perm:s}=n,i=r,o=a.shape.length,l=new Array(o);for(let u=0;u<l.length;u++)l[u]=a.shape[s[u]];let p;if(i.shouldExecuteOnCPU([a])){let u=i.texData.get(a.dataId).values,d=lw(u,a.shape,a.dtype,s,l);p=i.makeTensorInfo(l,a.dtype);let h=i.texData.get(p.dataId);h.values=d}else p=xm(a,s,i);return p}var xQ={kernelName:Ta,backendName:"webgl",kernelFunc:xr},RC=1e3;function Lc({a:e,b:t,transposeA:r,transposeB:n,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let p=e.shape.length,u=t.shape.length,d=r?e.shape[p-2]:e.shape[p-1],h=n?t.shape[u-1]:t.shape[u-2],c=r?e.shape[p-1]:e.shape[p-2],f=n?t.shape[u-2]:t.shape[u-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=k.sizeFromShape(m),b=k.sizeFromShape(g),x=Zu.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([c,f]);k.assert(d===h,()=>`Error in matMul: inner shapes (${d}) and (${h}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${r} and transposeB=${n} must match.`);let v=r?[y,d,c]:[y,c,d],w=n?[b,f,h]:[b,h,f],N=ue({inputs:{x:e},backend:a,attrs:{shape:v}}),T=ue({inputs:{x:t},backend:a,attrs:{shape:w}}),E=[N,T],$=Math.max(y,b),R=r?N.shape[1]:N.shape[2],F=s!=null,S=i!=null,D=l==="leakyrelu",P=l!=null?id(l,!0):null,U=F||S||D||P!=null,H;if((c===1||f===1)&&R>RC&&U===!1){let G=N,Z=T;r&&(G=xr({inputs:{x:N},backend:a,attrs:{perm:[0,2,1]}}),E.push(G)),n&&(Z=xr({inputs:{x:T},backend:a,attrs:{perm:[0,2,1]}}),E.push(Z));let ee=f!==1,X=f===1,re=G;ee&&(re=ue({inputs:{x:G},backend:a,attrs:{shape:[$,R,1]}}),E.push(re));let te=f===1?2:1,ae=Z;X&&(ae=ue({inputs:{x:Z},backend:a,attrs:{shape:[$,1,R]}}),E.push(ae));let ie=dw({inputs:{a:re,b:ae},backend:a});H=vm({inputs:{x:ie},backend:a,attrs:{axis:te,keepDims:!0}}),E.push(ie)}else{let G=cn(e.dtype,t.dtype),Z=new FC(v,w,[$,c,f],r,n,F,P,S,D),ee=[N,T];if(s!=null&&ee.push(s),S&&ee.push(i),D){let X=a.makeTensorInfo([],"float32",k.createScalarValue(o,"float32"));ee.push(X),E.push(X)}H=a.runWebGLProgram(Z,ee,G)}let q=ue({inputs:{x:H},backend:a,attrs:{shape:x}});E.push(H);for(let G of E)a.disposeIntermediateTensorInfo(G);return q}function vQ(e){let{inputs:t,backend:r,attrs:n}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:p,activation:u,leakyreluAlpha:d}=n;return Lc({a,b:s,transposeA:l,transposeB:p,backend:r,bias:i,preluActivationWeights:o,leakyreluAlpha:d,activation:u})}var wQ={kernelName:li,backendName:"webgl",kernelFunc:vQ},_1="return abs(x);";function kQ(e){let{inputs:t,backend:r}=e,{x:n}=t;if(r.shouldExecuteOnCPU([n])&&n.dtype!=="complex64"){let s=r.texData.get(n.dataId),i=kC(s.values);return r.makeTensorInfo(n.shape,n.dtype,i)}let a;return j().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new ss(n.shape,_1):a=new aa(n.shape,_1),r.runWebGLProgram(a,[n],n.dtype)}var IQ={kernelName:Kl,backendName:"webgl",kernelFunc:kQ},SQ=Cn+`
if (abs(x) > 1.) {
return NAN;
}
return acos(x);
`,NQ=Ke({opSnippet:SQ}),_Q={kernelName:$i,backendName:"webgl",kernelFunc:NQ},TQ=Cn+`
if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,CQ=Ke({opSnippet:TQ}),EQ={kernelName:Ai,backendName:"webgl",kernelFunc:CQ},T1="return a + b;",$Q=lr({opSnippet:T1,packedOpSnippet:T1,supportsComplex:!0,cpuKernelImpl:z9}),AQ={kernelName:Ts,backendName:"webgl",kernelFunc:$Q},FQ=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let r=[];this.variableNames.forEach(a=>{r.push(`float v${a} = get${a}AtOutCoords();`)});let n=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
void main() {
${r.join(`
`)}
float result = ${n};
setOutput(result);
}
`}},RQ=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let r=[];this.variableNames.forEach(a=>{r.push(`vec4 v${a} = get${a}AtOutCoords();`)});let n=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
void main() {
${r.join(`
`)}
vec4 result = ${n};
setOutput(result);
}
`}};function nc(e){let{inputs:t,backend:r}=e,n=t;if(n.length===1)return Jr({inputs:{x:n[0]},backend:r});if(n.length>j().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(n.length/2),l=nc({inputs:n.slice(0,o),backend:r}),p=nc({inputs:n.slice(o),backend:r});return nc({inputs:[l,p],backend:r})}let a=n.map(o=>o.dtype).reduce((o,l)=>cn(o,l)),s=n.map(o=>o.shape),i=j().getBool("WEBGL_PACK")?new RQ(n[0].shape,s):new FQ(n[0].shape,s);return r.runWebGLProgram(i,n,a)}var DQ={kernelName:Fi,backendName:"webgl",kernelFunc:nc};function MQ(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n,o=a.shape.length,l=k.parseAxisParam(s,a.shape),p=l,u=_.getAxesPermutation(p,o),d=a;u!=null&&(d=xr({inputs:{x:a},backend:r,attrs:{perm:u}}),p=_.getInnerMostAxes(p.length,o)),_.assertAxesAreInnerMostDims("all",p,o);let[h,c]=_.computeOutAndReduceShapes(d.shape,p),f=k.sizeFromShape(c),m=ue({inputs:{x:d},backend:r,attrs:{shape:[-1,f]}}),g=sl(m,m.dtype,"all",r),y;if(i){let b=_.expandShapeToKeepDim(h,l);y=ue({inputs:{x:g},backend:r,attrs:{shape:b}})}else y=ue({inputs:{x:g},backend:r,attrs:{shape:h}});return r.disposeIntermediateTensorInfo(m),r.disposeIntermediateTensorInfo(g),u!=null&&r.disposeIntermediateTensorInfo(d),y}var OQ={kernelName:Xl,backendName:"webgl",kernelFunc:MQ};function LQ(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n,o=a.shape.length,l=k.parseAxisParam(s,a.shape),p=l,u=_.getAxesPermutation(p,o),d=a;u!=null&&(d=xr({inputs:{x:a},backend:r,attrs:{perm:u}}),p=_.getInnerMostAxes(p.length,o)),_.assertAxesAreInnerMostDims("any",p,o);let[h,c]=_.computeOutAndReduceShapes(d.shape,p),f=k.sizeFromShape(c),m=ue({inputs:{x:d},backend:r,attrs:{shape:[-1,f]}}),g=sl(m,m.dtype,"any",r),y;if(i){let b=_.expandShapeToKeepDim(h,l);y=ue({inputs:{x:g},backend:r,attrs:{shape:b}})}else y=ue({inputs:{x:g},backend:r,attrs:{shape:h}});return r.disposeIntermediateTensorInfo(m),r.disposeIntermediateTensorInfo(g),u!=null&&r.disposeIntermediateTensorInfo(d),y}var zQ={kernelName:Zl,backendName:"webgl",kernelFunc:LQ},PQ=class{constructor(e,t,r){this.variableNames=["A"];let{windowSize:n,batchSize:a,outSize:s}=e;r||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=r?"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 * ${n};
int bestIndex = inOffset;
float bestValue = getA(batch, bestIndex);
for (int i = 0; i < ${n}; i++) {
int inIdx = ${o};
float candidate = getA(batch, inIdx);
if (candidate ${i} bestValue) {
bestValue = candidate;
bestIndex = inIdx;
}
}
setOutput(float(bestIndex));
}
`}},BQ=class{constructor(e,t,r,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,k.assert(e.length>2,()=>`Packed arg${r.charAt(0).toUpperCase()+r.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),n||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=pt(o),p=gr("coords",o),u,d;if(s===1){d=o+1;let T=pt(d);u=`
${T} sourceLocR = ${T}(${p.join()}, 0);
++${p[o-1]};
${T} sourceLocG = ${T}(${p.join()}, 0);
++${p[o-2]};
${T} sourceLocA = ${T}(${p.join()}, 0);
--${p[o-1]};
${T} sourceLocB = ${T}(${p.join()}, 0);
--${p[o-2]};`}else d=o,u=`
${l} sourceLocR = coords;
++${p[o-1]};
${l} sourceLocG = coords;
++${p[o-2]};
${l} sourceLocA = coords;
--${p[o-1]};
${l} sourceLocB = coords;
--${p[o-2]};`;let h=["x","y","z","w","u","v"].slice(0,d),c="."+h[d-1],f=h.map(T=>"int "+T),m=gr("sourceLocR",d-1).concat("inIdx.r"),g=gr("sourceLocG",d-1).concat("inIdx.g"),y=gr("sourceLocB",d-1).concat("inIdx.b"),b=gr("sourceLocA",d-1).concat("inIdx.a"),x=r==="max"?"greaterThan":"lessThan",v=n?"":`
inIdx = round(vec4(getBestIndicesAChannel(${m.join()}),
getBestIndicesAChannel(${g.join()}),
getBestIndicesAChannel(${y.join()}),
getBestIndicesAChannel(${b.join()})));`,w=`vec4(
getAChannel(${m.join()}),
hasNextCol ? getAChannel(${g.join()}) : 0.,
hasNextRow ? getAChannel(${y.join()}) : 0.,
hasNextRow && hasNextCol ? getAChannel(${b.join()}) : 0.)`,N=n?"":`
float getBestIndicesAChannel(${f.join()}) {
return getChannel(getBestIndicesA(${h.join()}),
vec2(${h.slice(-2).join()}));
}`;this.userCode=`
float getAChannel(${f.join()}) {
return getChannel(getA(${h.join()}),
vec2(${h.slice(-2).join()}));
}
${N}
void main() {
${l} coords = getOutputCoords();
bool hasNextCol = ${p[o-1]} < ${i[o-1]-1};
bool hasNextRow = ${p[o-2]} < ${i[o-2]-1};
${u}
ivec4 srcIdx = ivec4(sourceLocR${c}, sourceLocG${c},
sourceLocB${c}, sourceLocA${c}) * ${t};
ivec4 inIdx = srcIdx;
vec4 bestIndex = vec4(inIdx);
vec4 bestValue = ${w};
for (int i = 0; i < ${t}; i++) {
inIdx = srcIdx;
${v}
vec4 candidate = ${w};
bvec4 nan = isnan(candidate);
bvec4 replace = bvec4(
vec4(${x}(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 DC(e,t,r,n=null){let a=t.shape[0],s=t.shape[1];n!=null&&(a=n.shape[0],s=n.shape[1]);let i=_.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new PQ(o,r,n==null),p=[t];n!=null&&p.push(n);let u=e.runWebGLProgram(l,p,"int32");if(u.shape[1]===1)return u;let d=DC(e,t,r,u);return e.disposeIntermediateTensorInfo(u),d}function MC(e,t,r,n=null){let a=n!=null?n.shape:t.shape,s=a[a.length-1],i=_.computeOptimalWindowSize(s),o=new BQ(a,i,r,n==null),l=n==null?[t]:[t,n],p=e.runWebGLProgram(o,l,"int32");if(p.shape.length===t.shape.length){let u=MC(e,t,r,p);return e.disposeIntermediateTensorInfo(p),u}return p}function OC(e,t,r,n){let a=[r];if(_.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),a,t.shape.length),!j().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],i=e.texData.get(t.dataId),o=i!==null&&i.isPacked,l=t;o&&(l=e.unpackTensor(t),s.push(l));let[p,u]=_.computeOutAndReduceShapes(l.shape,a),d=k.sizeFromShape(u),h=ue({inputs:{x:l},backend:e,attrs:{shape:[-1,d]}});s.push(h);let c=DC(e,h,n);s.push(c);let f=ue({inputs:{x:c},backend:e,attrs:{shape:p}});return s.forEach(m=>e.disposeIntermediateTensorInfo(m)),f}return MC(e,t,n)}function WQ(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s}=n,i=k.parseAxisParam(s,a.shape),o=_.getAxesPermutation(i,a.shape.length),l=a,p=[];o!=null&&(l=xr({inputs:{x:a},backend:r,attrs:{perm:o}}),p.push(l),i=_.getInnerMostAxes(i.length,l.shape.length)),_.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let u=OC(r,l,i[0],"max");return p.forEach(d=>r.disposeIntermediateTensorInfo(d)),u}var UQ={kernelName:Jl,backendName:"webgl",kernelFunc:WQ};function VQ(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s}=n,i=k.parseAxisParam(s,a.shape),o=_.getAxesPermutation(i,a.shape.length),l=a,p=[];o!=null&&(l=xr({inputs:{x:a},backend:r,attrs:{perm:o}}),p.push(l),i=_.getInnerMostAxes(i.length,l.shape.length)),_.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let u=OC(r,l,i[0],"min");return p.forEach(d=>r.disposeIntermediateTensorInfo(d)),u}var GQ={kernelName:Yl,backendName:"webgl",kernelFunc:VQ},HQ=Cn+`
if (abs(x) > 1.) {
return NAN;
}
return asin(x);
`,jQ=Ke({opSnippet:HQ}),qQ={kernelName:Ri,backendName:"webgl",kernelFunc:jQ},KQ=Cn+"return log(x + sqrt(x * x + 1.0));",XQ=Ke({opSnippet:KQ}),ZQ={kernelName:Di,backendName:"webgl",kernelFunc:XQ},JQ=Cn+`
return atan(x);
`,YQ=Ke({opSnippet:JQ}),QQ={kernelName:Mi,backendName:"webgl",kernelFunc:YQ},eee=pw+`
return atan(a, b);
`,tee=`
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);
`+al+`
return result;
`,ree=lr({opSnippet:eee,packedOpSnippet:tee}),nee={kernelName:Li,backendName:"webgl",kernelFunc:ree},aee=Cn+`
if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,see=Ke({opSnippet:aee}),iee={kernelName:Oi,backendName:"webgl",kernelFunc:see},od=class{constructor(e,t,r,n=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&r)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,p=e.dilationWidth,u=e.effectiveFilterHeight,d=e.effectiveFilterWidth,h=e.padInfo.top,c=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),r){let T=">=";this.userCode=`
const ivec2 strides = ivec2(${i}, ${o});
const ivec2 pads = ivec2(${h}, ${c});
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 < ${u};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${d};
wC += ${p}) {
int xC = xCCorner + wC;
if (xC < 0 || xC >= ${e.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 ${T} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${n?a?m:g:`wR * ${d} + wC`};
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let b="max",x=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(x="avgValue / max(count, 1.0)");let v=Math.floor(s/4)*4,w=s%4,N=`
if (${f}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${b}(values, minMaxValue);
}
`;this.userCode=`
const ivec2 strides = ivec2(${i}, ${o});
const ivec2 pads = ivec2(${h}, ${c});
const float initializationValue = ${y};
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 >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xR, xC, d);
}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
vec4 minMaxValue = vec4(${y});
float avgValue = 0.0;
count = 0.0;
for (int wR = 0; wR < ${u};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${v}; wC += 4) {
int xC = xCCorner + wC * ${p};
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${p}, d),
getValue(batch, xR, xC + 2 * ${p}, d),
getValue(batch, xR, xC + 3 * ${p}, d)
);
${N}
}
int xC = xCCorner + ${v};
if (${w===1}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
initializationValue,
initializationValue,
initializationValue
);
${N}
} else if (${w===2}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${p}, d),
initializationValue,
initializationValue
);
${N}
} else if (${w===3}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${p}, d),
getValue(batch, xR, xC + 2 * ${p}, d),
initializationValue
);
${N}
}
}
setOutput(${x});
}
`}},hw=class{constructor(e,t,r,n=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&r)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,p=e.dilationDepth,u=e.dilationHeight,d=e.dilationWidth,h=e.effectiveFilterDepth,c=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,g=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let b=t==="avg",x="0.0";if(b||(x="-1.0 / 1e-20"),r){let $=">=";this.userCode=`
const ivec3 strides =
ivec3(${i}, ${o}, ${l});
const ivec3 pads = ivec3(${m}, ${g}, ${y});
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 < ${h};
wD += ${p}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${c};
wR += ${u}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${f};
wC += ${d}) {
int xC = xCCorner + wC;
if (xC < 0 || xC >= ${e.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 ${$} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${n?a?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${c} * ${f} +
wR * ${f} + wC`};
}
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let v="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / max(count, 1.0)");let N=Math.floor(s/4)*4,T=s%4,E=`
if (${b}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${v}(values, minMaxValue);
}
`;this.userCode=`
const ivec3 strides =
ivec3(${i}, ${o}, ${l});
const ivec3 pads = ivec3(${m}, ${g}, ${y});
const float initializationValue = ${x};
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 >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xD, xR, xC, ch);
}
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xDCorner = xCorner.x;
int xRCorner = xCorner.y;
int xCCorner = xCorner.z;
// max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
// ? = to be determined
vec4 minMaxValue = vec4(${x});
float avgValue = 0.0;
count = 0.0;
for (int wD = 0; wD < ${h};
wD += ${p}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${c};
wR += ${u}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${N}; wC += 4) {
int xC = xCCorner + wC * ${d};
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${d}, ch),
getValue(batch, xD, xR, xC + 2 * ${d}, ch),
getValue(batch, xD, xR, xC + 3 * ${d}, ch)
);
${E}
}
int xC = xCCorner + ${N};
if (${T===1}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
initializationValue,
initializationValue,
initializationValue
);
${E}
} else if (${T===2}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${d}, ch),
initializationValue,
initializationValue
);
${E}
} else if (${T===3}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${d}, ch),
getValue(batch, xD, xR, xC + 2 * ${d}, ch),
initializationValue
);
${E}
}
}
}
setOutput(${w});
}
`}};function oee(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t;lp(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,p=1;k.assert(_.eitherStridesOrDilationsAreOne(i,p),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${p}'`);let u=_.computePool2DInfo(a.shape,s,i,p,o,l);if(u.filterWidth===1&&u.filterHeight===1&&k.arraysEqual(u.inShape,u.outShape))return Jr({inputs:{x:a},backend:r});let d=new od(u,"avg",!1);return r.runWebGLProgram(d,[a],"float32")}var lee={kernelName:zi,backendName:"webgl",kernelFunc:oee};function uee(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:p}=n,u=[1,1,1],d=_.computePool3DInfo(a.shape,s,i,u,o,l,p),h=new hw(d,"avg",!1);return r.runWebGLProgram(h,[a],"float32")}var pee={kernelName:Ql,backendName:"webgl",kernelFunc:uee},dee=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,p=o-1-e.padInfo.top,u=l-1-e.padInfo.left,d=1/(t*r);this.userCode=`
const ivec2 pads = ivec2(${p}, ${u});
const float avgMultiplier = float(${d});
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 < ${o};
wR += ${s}) {
float dyR = float(dyRCorner + wR) / ${n}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${l};
wC+= ${i}) {
float dyC = float(dyCCorner + wC) / ${a}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
dotProd += dyValue * avgMultiplier;
}
}
setOutput(dotProd);
}
`}},hee=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,r=e.filterHeight,n=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,p=e.dilationWidth,u=e.effectiveFilterDepth,d=e.effectiveFilterHeight,h=e.effectiveFilterWidth,c=u-1-e.padInfo.front,f=d-1-e.padInfo.top,m=h-1-e.padInfo.left,g=1/(t*r*n);this.userCode=`
const ivec3 pads = ivec3(${c}, ${f}, ${m});
const float avgMultiplier = float(${g});
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 < ${u};
wD += ${o}) {
float dyD = float(dyDCorner + wD) / ${a}.0;
if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
continue;
}
int idyD = int(dyD);
for (int wR = 0; wR < ${d};
wR += ${l}) {
float dyR = float(dyRCorner + wR) / ${s}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${h};
wC += ${p}) {
float dyC = float(dyCCorner + wC) / ${i}.0;
if (dyC < 0.0 || dyC >= ${e.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 cee(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:p,dimRoundingMode:u}=n,d=[1,1,1],h=_.computePool3DInfo(i.shape,o,l,d,p,u),c=new hee(h);return r.runWebGLProgram(c,[a],i.dtype)}var fee={kernelName:cd,backendName:"webgl",kernelFunc:cee};function mee(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,input:s}=t,i=s;lp([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:p}=n,u=_.computePool2DInfo(i.shape,o,l,1,p),d=new dee(u);return r.runWebGLProgram(d,[a],i.dtype)}var gee={kernelName:hd,backendName:"webgl",kernelFunc:mee};function yee(e){let{inputs:t,backend:r,attrs:n}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=n;return Lc({a,b:s,transposeA:i,transposeB:o,backend:r})}var bee={kernelName:Pi,backendName:"webgl",kernelFunc:yee},xee=class{constructor(e,t,r,n,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],_.assertAndGetBroadcastShape(e,t),_.assertAndGetBroadcastShape(e,r);let i="0.0";n!=null&&(_.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(_.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
float x = getXAtOutCoords();
float mean = getMeanAtOutCoords();
float variance = getVarianceAtOutCoords();
float offset = ${i};
float scale = ${o};
float inv = scale * inversesqrt(variance + float(${s}));
setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
}
`}},vee=class{constructor(e,t,r,n,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],_.assertAndGetBroadcastShape(e,t),_.assertAndGetBroadcastShape(e,r);let i="vec4(0.0)";n!=null&&(_.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(_.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
vec4 offset = ${i};
vec4 scale = ${o};
vec4 x = getXAtOutCoords();
vec4 mean = getMeanAtOutCoords();
vec4 variance = getVarianceAtOutCoords();
vec4 inv = scale * inversesqrt(variance + vec4(${s}));
setOutput((x - mean) * inv + offset);
}
`}},wee=({inputs:e,backend:t,attrs:r})=>{let{x:n,mean:a,variance:s,offset:i,scale:o}=e;k.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),k.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),k.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=r;l==null&&(l=.001);let p=[n,a,s],u=null;i!=null&&(u=i.shape,p.push(i));let d=null;o!=null&&(d=o.shape,p.push(o));let h=j().getBool("WEBGL_PACK_NORMALIZATION")?new vee(n.shape,a.shape,s.shape,u,d,l):new xee(n.shape,a.shape,s.shape,u,d,l);return t.runWebGLProgram(h,p,p[0].dtype)},kee={kernelName:no,backendName:"webgl",kernelFunc:wee},Iee=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=pt(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let r=See(this.rank),n,a=e.map((s,i)=>`sourceLoc.${Jg[i]} = start[${i}] + coords.${Jg[i]};`);n=`
${t} sourceLoc;
${t} coords = getOutputCoords();
${a.join(`
`)}
`,this.userCode=`
void main() {
${n}
setOutput(getSource(${r}));
}
`}},Jg=["x","y","z","w","u","v"];function See(e){if(e===1)return"sourceLoc";if(e<=6)return Jg.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var Nee=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=pt(this.rank),r=gr("coords",this.rank),n=gr("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${n.slice(-2).join()})`,s=`getChannel(getSource(${n.join()}), ${a})`,i=`
result.x = ${s};
if (++${r[this.rank-1]} < ${e[this.rank-1]}) {
++${n[this.rank-1]};
result.y = ${s};
--${n[this.rank-1]};
}
`,o=this.rank===1?"":`
--${r[this.rank-1]};
if (++${r[this.rank-2]} < ${e[this.rank-2]}) {
++${n[this.rank-2]};
result.z = ${s};
if (++${r[this.rank-1]} < ${e[this.rank-1]}) {
++${n[this.rank-1]};
result.w = ${s};
}
}
`,l=this.rank<=4?`sourceLoc = coords +
${t}(${e.map((p,u)=>`start[${u}]`).join()});`:e.map((p,u)=>`${n[u]} = ${r[u]} + start[${u}];`).join(`
`);this.userCode=`
void main() {
${t} coords = getOutputCoords();
${t} sourceLoc;
${l}
vec4 result = vec4(0.);
${i}
${o}
setOutput(result);
}
`}};function _ee(e,t,r,n){let a=n.texData.get(e.dataId),s=n.makeTensorInfo(r,e.dtype),i=n.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=r,i.dtype=e.dtype;let o=Wt.computeFlatOffset(t,k.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=n.dataRefCount.get(i.slice.origDataId)||1;return n.dataRefCount.set(i.slice.origDataId,l+1),s}function mp(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{begin:s,size:i}=n,[o,l]=Wt.parseSliceParams(a,s,i);if(Wt.assertParamsValid(a,o,l),k.sizeFromShape(l)===0)return r.makeTensorInfo(l,a.dtype,[]);if(r.shouldExecuteOnCPU([a])||a.dtype==="string"){let d=r.texData.get(a.dataId),h=gY(d.values,o,l,a.shape,a.dtype);return r.makeTensorInfo(l,a.dtype,h)}let{isPacked:p}=r.texData.get(a.dataId),u=Wt.isSliceContinous(a.shape,o,l);if(p||!u){let d=j().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Nee(l):new Iee(l),h=[o];return r.runWebGLProgram(d,[a],a.dtype,h)}return r.uploadToGPU(a.dataId),_ee(a,o,l,r)}var Tee={kernelName:Pu,backendName:"webgl",kernelFunc:mp},Cee=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockShape:s,crops:i}=n;k.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((b,x)=>b*x),l=_.getReshaped(a.shape,s,o),p=_.getPermuted(l.length,s.length),u=_.getReshapedPermuted(a.shape,s,o),d=_.getSliceBeginCoords(i,s.length),h=_.getSliceSize(u,i,s.length),c=[],f=ue({inputs:{x:a},backend:r,attrs:{shape:l}}),m=xr({inputs:{x:f},backend:r,attrs:{perm:p}}),g=ue({inputs:{x:m},backend:r,attrs:{shape:u}}),y=mp({inputs:{x:g},backend:r,attrs:{begin:d,size:h}});return c.push(f),c.push(m),c.push(g),c.forEach(b=>r.disposeIntermediateTensorInfo(b)),y},Eee={kernelName:eu,backendName:"webgl",kernelFunc:Cee};function $ee(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,weights:s}=t,{size:i}=n,o=r.readSync(a.dataId),l=r.readSync(s.dataId),p=wC(o,l,s.dtype,s.shape,i);return r.makeTensorInfo([i],s.dtype,p)}var Aee={kernelName:tu,backendName:"webgl",kernelFunc:$ee},Fee=`
int r = int(a.r) & int(b.r);
int g = int(a.g) & int(b.g);
int rb = int(a.b) & int(b.b);
int ra = int(a.a) & int(b.a);
return vec4(r, g, rb, ra);
`,Ree=`
return float(int(a.r) & int(b.r));
`;function Dee(e){let{inputs:t,backend:r}=e,{a:n,b:a}=t,s=j().getBool("WEBGL_PACK_BINARY_OPERATIONS"),i=j().getNumber("WEBGL_VERSION");if(r.shouldExecuteOnCPU([n,a])||i===1){let l=r.texData.get(n.dataId).values,p=r.texData.get(a.dataId).values,[u,d]=B9(n.shape,a.shape,l,p,n.dtype),h=r.makeTensorInfo(d,n.dtype),c=r.texData.get(h.dataId);return c.values=u,h}let o;return s?o=new cp(Fee,n.shape,a.shape,!1):o=new Ni(Ree,n.shape,a.shape),r.runWebGLProgram(o,[n,a],n.dtype)}var Mee={kernelName:ru,backendName:"webgl",kernelFunc:Dee};function Oee(e){let{inputs:t,backend:r}=e,{s0:n,s1:a}=t,s=r.readSync(n.dataId),i=r.readSync(a.dataId),o=_.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return r.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var Lee={kernelName:fd,backendName:"webgl",kernelFunc:Oee},zee="return float(a != b);",LC=lr({opSnippet:zee,cpuKernelImpl:oY,dtype:"bool"}),Pee={kernelName:_u,backendName:"webgl",kernelFunc:LC};function ph(e){let{inputs:t,backend:r}=e,{input:n}=t,a=r.texData.get(n.dataId);return Jr({inputs:{x:a.complexTensorInfos.real},backend:r})}var Bee={kernelName:df,backendName:"webgl",kernelFunc:ph},Wee="return float(int(x));";function Uee(e,t){let r=new aa(e.shape,Wee),n=t.runWebGLProgram(r,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function Yg(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{dtype:s}=n;if(s==="complex64"){if(a.dtype==="complex64")return Jr({inputs:{x:a},backend:r});let i=It(a.shape),o=Yg({inputs:{x:a},backend:r,attrs:{dtype:"float32"}}),l=Ls({inputs:{real:o,imag:i},backend:r});return i.dispose(),r.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=ph({inputs:{input:a},backend:r}),o=Yg({inputs:{x:i},backend:r,attrs:{dtype:s}});return r.disposeIntermediateTensorInfo(i),o}if(!k.hasEncodingLoss(a.dtype,s)){let i=Jr({inputs:{x:a},backend:r});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(r.shouldExecuteOnCPU([a])){let i=r.texData.get(a.dataId).values,[o,l,p]=W9(i,a.shape,a.dtype,s);return r.makeTensorInfo(o,l,p)}if(s==="int32")return Uee(a,r);if(s==="bool"){let i=r.makeTensorInfo([],"bool",k.getTypedArrayFromDType("bool",1)),o=LC({inputs:{a,b:i},backend:r});return r.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var Vee={kernelName:Bi,backendName:"webgl",kernelFunc:Yg},C1="return ceil(x);",Gee=Ke({opSnippet:C1,packedOpSnippet:C1,cpuKernelImpl:U9}),Hee={kernelName:Wi,backendName:"webgl",kernelFunc:Gee},jee=class{constructor(e){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=`
void main() {
float value = getAAtOutCoords();
if (isnan(value)) {
setOutput(value);
return;
}
setOutput(clamp(value, minVal, maxVal));
}
`}},qee=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=`
void main() {
vec4 value = getAAtOutCoords();
if (any(isnan(value))) {
setOutput(value);
return;
}
setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
}
`}};function Kee(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=n,o;j().getBool("WEBGL_PACK_CLIP")?o=new qee(a.shape):o=new jee(a.shape);let l=[[s],[i]];return r.runWebGLProgram(o,[a],a.dtype,l)}var Xee={kernelName:Cs,backendName:"webgl",kernelFunc:Kee},Zee=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,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 E1(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function Jee(e){let{inputs:t,backend:r}=e,{x:n}=t,a=r.texData.get(n.dataId),s=new Zee(n.shape),i=[E1(n,a.complexTensorInfos.real),E1(n,a.complexTensorInfos.imag)];return r.runWebGLProgram(s,i,i[0].dtype)}var Yee={kernelName:md,backendName:"webgl",kernelFunc:Jee},Qee=class{constructor(e){this.outputShape=[],this.outputShape=_.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let r=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];r.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let n=t.length,a=t[t.length-1];r.push(`else setOutput(getT${n}(yR, yC-${a}));`),this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int yR = coords.x;
int yC = coords.y;
${r.join(`
`)}
}
`}},ete=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=_.computeOutShape(e,t);let r=this.outputShape,n=r.length,a=pt(n),s=gr("coords",n),i=["x","y","z","w","u","v"].slice(0,n);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],p=i.slice(-2),u=i.join(),d=`if (${l} < ${o[0]}) {
return getChannel(
getT0(${u}), vec2(${p.join()}));
}`;for(let f=1;f<o.length;f++){let m=o[f-1];d+=`
if (${l} < ${o[f]} && ${l} >= ${o[f-1]}) {
return getChannel(
getT${f}(${Vh(i,l,m)}),
vec2(${Vh(p,l,m)}));
}`}let h=o.length,c=o[o.length-1];d+=`
return getChannel(
getT${h}(${Vh(i,l,c)}),
vec2(${Vh(p,l,c)}));`,this.userCode=`
float getValue(${i.map(f=>"int "+f)}) {
${d}
}
void main() {
${a} coords = getOutputCoords();
vec4 result = vec4(getValue(${s}), 0., 0., 0.);
${s[n-1]} = ${s[n-1]} + 1;
if (${s[n-1]} < ${r[n-1]}) {
result.g = getValue(${s});
}
${s[n-2]} = ${s[n-2]} + 1;
if (${s[n-2]} < ${r[n-2]}) {
result.a = getValue(${s});
}
${s[n-1]} = ${s[n-1]} - 1;
if (${s[n-2]} < ${r[n-2]} &&
${s[n-1]} < ${r[n-1]}) {
result.b = getValue(${s});
}
setOutput(result);
}
`}};function Vh(e,t,r){let n=e.indexOf(t);return e.map((a,s)=>s===n?`${a} - ${r}`:a).join()}function wm(e){let{inputs:t,backend:r}=e,{input:n}=t,a=r.texData.get(n.dataId);return Jr({inputs:{x:a.complexTensorInfos.imag},backend:r})}var tte={kernelName:of,backendName:"webgl",kernelFunc:wm};function Op(e,t,r){let n=e[0].dtype;if(n==="complex64"){let c=e.map(b=>ph({inputs:{input:b},backend:r})),f=e.map(b=>wm({inputs:{input:b},backend:r})),m=Op(c,t,r),g=Op(f,t,r),y=Ls({inputs:{real:m,imag:g},backend:r});return c.forEach(b=>r.disposeIntermediateTensorInfo(b)),f.forEach(b=>r.disposeIntermediateTensorInfo(b)),r.disposeIntermediateTensorInfo(m),r.disposeIntermediateTensorInfo(g),y}let a=r.shouldExecuteOnCPU(e);if(n==="string"&&(a=!0),a){let c=e.map(v=>{let w=[-1,k.sizeFromShape(v.shape.slice(t))];return ue({inputs:{x:v},backend:r,attrs:{shape:w}})}),f=c.map(v=>({vals:r.readSync(v.dataId),shape:v.shape})),m=_.computeOutShape(c.map(v=>v.shape),1),g=c[0].shape[0]===1,y=V9(f,m,n,g),b=_.computeOutShape(e.map(v=>v.shape),t),x=r.makeTensorInfo(b,n,y);return c.forEach(v=>r.disposeIntermediateTensorInfo(v)),x}let s=e.filter(c=>k.sizeFromShape(c.shape)>0),i=j().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&s[0].shape.length>1;if(s.length===1){let c=i?new aa(e[0].shape,Qa):new ss(e[0].shape,Qa);return r.runWebGLProgram(c,e,n)}let o=j().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(s.length>o){let c=[];for(let m=0;m<s.length;m+=o){let g=s.slice(m,m+o);c.push(Op(g,t,r))}let f=Op(c,t,r);for(let m of c)r.disposeIntermediateTensorInfo(m);return f}if(i){let c=new ete(s.map(f=>f.shape),t);return r.runWebGLProgram(c,s,n)}let{tensors2D:l,outShape:p}=rte(s,t,r),u=new Qee(l.map(c=>c.shape)),d=r.runWebGLProgram(u,l,n);l.forEach(c=>r.disposeIntermediateTensorInfo(c));let h=ue({inputs:{x:d},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(d),h}function rte(e,t,r){let n=_.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>ue({inputs:{x:a},attrs:{shape:[-1,k.sizeFromShape(a.shape.slice(t))]},backend:r})),outShape:n}}function zC(e){let{inputs:t,backend:r,attrs:n}=e,{axis:a}=n,s=k.parseAxisParam(a,t[0].shape)[0],i=t.map(p=>p.shape);_.assertParamsConsistent(i,s);let o=_.computeOutShape(t.map(p=>p.shape),s);if(k.sizeFromShape(o)===0)return r.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(p=>k.sizeFromShape(p.shape)>0);return l.length===1?Jr({inputs:{x:l[0]},backend:r}):Op(l,s,r)}var nte={kernelName:nu,backendName:"webgl",kernelFunc:zC},PC=class{constructor(e,t=!1,r=null,n=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,p=e.dilationHeight,u=e.dilationWidth,d=e.filterHeight,h=e.filterWidth,c=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",g=m?1:2,y=m?2:3,b=m?3:1,x="",v="";r&&(n?x=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${r}
}`:a?x=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${r}
}`:x=`
float activation(float x) {
${r}
}
`,v="result = activation(result);");let w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${x}
const ivec2 strides = ivec2(${o}, ${l});
const ivec2 pads = ivec2(${s}, ${i});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d2 = coords[${b}];
ivec2 xRCCorner =
ivec2(coords[${g}], coords[${y}]) * 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 < ${d}; wR++) {
int xR = xRCorner + wR * ${p};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${h}; wC++) {
int xC = xCCorner + wC * ${u};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${c}; d1 += 4) {
vec4 wValues = vec4(
getW(wR, wC, d1, d2),
getW(wR, wC, d1 + 1, d2),
getW(wR, wC, d1 + 2, d2),
getW(wR, wC, d1 + 3, d2)
);
if (${m}) {
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 (${f===1}) {
if (${m}) {
dotProd +=
getX(batch, xR, xC, ${c}) *
getW(wR, wC, ${c}, d2);
} else {
dotProd +=
getX(batch, ${c}, xR, xC) *
getW(wR, wC, ${c}, d2);
}
} else if (${f===2}) {
vec2 wValues = vec2(
getW(wR, wC, ${c}, d2),
getW(wR, wC, ${c} + 1, d2)
);
if (${m}) {
vec2 xValues = vec2(
getX(batch, xR, xC, ${c}),
getX(batch, xR, xC, ${c} + 1)
);
dotProd += dot(xValues, wValues);
} else {
vec2 xValues = vec2(
getX(batch, ${c}, xR, xC),
getX(batch, ${c} + 1, xR, xC)
);
dotProd += dot(xValues, wValues);
}
} else if (${f===3}) {
vec3 wValues = vec3(
getW(wR, wC, ${c}, d2),
getW(wR, wC, ${c} + 1, d2),
getW(wR, wC, ${c} + 2, d2)
);
if (${m}) {
vec3 xValues = vec3(
getX(batch, xR, xC, ${c}),
getX(batch, xR, xC, ${c} + 1),
getX(batch, xR, xC, ${c} + 2)
);
dotProd += dot(xValues, wValues);
} else {
vec3 xValues = vec3(
getX(batch, ${c}, xR, xC),
getX(batch, ${c} + 1, xR, xC),
getX(batch, ${c} + 2, xR, xC)
);
dotProd += dot(xValues, wValues);
}
}
}
}
float result = dotProd;
${w}
${v}
setOutput(result);
}
`}},ate=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,r=e.padInfo.top,n=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,p=e.dilationWidth,u=e.filterDepth,d=e.filterHeight,h=e.filterWidth,c=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
const ivec3 strides = ivec3(${a}, ${s}, ${i});
const ivec3 pads = ivec3(${t}, ${r}, ${n});
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 < ${u}; wF++) {
int xF = xFCorner + wF * ${o};
if (xF < 0 || xF >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${d}; wR++) {
int xR = xRCorner + wR * ${l};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${h}; wC++) {
int xC = xCCorner + wC * ${p};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${c}; d1 += 4) {
vec4 xValues = vec4(
getX(batch, xF, xR, xC, d1),
getX(batch, xF, xR, xC, d1 + 1),
getX(batch, xF, xR, xC, d1 + 2),
getX(batch, xF, xR, xC, d1 + 3)
);
vec4 wValues = vec4(
getW(wF, wR, wC, d1, d2),
getW(wF, wR, wC, d1 + 1, d2),
getW(wF, wR, wC, d1 + 2, d2),
getW(wF, wR, wC, d1 + 3, d2)
);
dotProd += dot(xValues, wValues);
}
if (${f===1}) {
dotProd +=
getX(batch, xF, xR, xC, ${c}) *
getW(wF, wR, wC, ${c}, d2);
} else if (${f===2}) {
vec2 xValues = vec2(
getX(batch, xF, xR, xC, ${c}),
getX(batch, xF, xR, xC, ${c} + 1)
);
vec2 wValues = vec2(
getW(wF, wR, wC, ${c}, d2),
getW(wF, wR, wC, ${c} + 1, d2)
);
dotProd += dot(xValues, wValues);
} else if (${f===3}) {
vec3 xValues = vec3(
getX(batch, xF, xR, xC, ${c}),
getX(batch, xF, xR, xC, ${c} + 1),
getX(batch, xF, xR, xC, ${c} + 2)
);
vec3 wValues = vec3(
getW(wF, wR, wC, ${c}, d2),
getW(wF, wR, wC, ${c} + 1, d2),
getW(wF, wR, wC, ${c} + 2, d2)
);
dotProd += dot(xValues, wValues);
}
}
}
}
setOutput(dotProd);
}
`}},BC=class{constructor(e,t=!1,r=null,n=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=hr(this.outputShape.length);let s=e.padInfo.left,i=e.strideWidth,o=e.dilationWidth,l=e.filterHeight,p=e.filterWidth,u=p,d=`
int xR; int xC; int xCOffset;
vec4 wTexel; vec4 previous; vec4 final;`;for(let m=0;m<p;m++)d+=`
vec4 xTexelC${m*2};
int xTexelC${m*2}Ready;
vec4 xTexelC${m*2+1};
int xTexelC${m*2+1}Ready;
vec4 xC${m};`;d+=`
for (int r = 0; r < ${l}; r++) {
for (int d1 = 0; d1 < ${e.inChannels}; d1 += 2) {
`;for(let m=0;m<p;m++)d+=`
xTexelC${m*2} = vec4(0.0);
xTexelC${m*2}Ready = 0;
xTexelC${m*2+1} = vec4(0.0);
xTexelC${m*2+1}Ready = 0;
xC${m} = vec4(0.0);`;d+=`
xR = xRCorner + r * dilations[0];
if (xR >=0 && xR < inDims[0]) {
`;for(let m=0;m<(u+1)/2;m++){let g=m*2;if(d+=`
xC = xCCorner + ${g*o};
`,i===1){if(g<p&&(s%2===1?(d+=`
xCOffset = xC + 1;
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
xTexelC${g} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g}.zw = vec2(0.0);
}
xTexelC${g}Ready = 1;
}
`,o===1&&g>0?d+=`
xC${g} = vec4(xTexelC${g-2}.zw, xTexelC${g}.xy);
`:d+=`
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${g} = vec4(previous.zw, xTexelC${g}.xy);
} else {
xC${g} = vec4(0.0, 0.0, xTexelC${g}.xy);
}
`):d+=`
if (xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) {
xTexelC${g} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${g}.zw = vec2(0.0);
}
xTexelC${g}Ready = 1;
}
xC${g} = xTexelC${g};
`,g+1<p)){let y=s%2===0?k.nearestLargerEven(o):o;o%2===0&&s%2===1||o%2!==0&&s%2!==1?(d+=`
xCOffset = xC + imod(pads[1], 2) + ${y};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.0);
}
xTexelC${g+1}Ready = 1;
}
`,o>1?d+=`
xCOffset -= 2;
if (xCOffset >= 0 && xCOffset < inDims[1]) {
previous = getX(batch, xR, xCOffset, d1);
xC${g+1} = vec4(previous.zw, xTexelC${g+1}.xy);
} else {
xC${g+1} = vec4(0.0, 0.0, xTexelC${g+1}.xy);
}
`:d+=`
xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.xy);
`):y===1?d+=`
xC${g+1} = xTexelC${g};
`:d+=`
xCOffset = xC + ${y};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.0);
}
xTexelC${g+1}Ready = 1;
}
xC${g+1} = xTexelC${g+1};
`}}else g<p&&(s%2===1?(d+=`
xCOffset = xC + 1 - strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
xTexelC${g} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g}.zw = vec2(0.0);
}
xTexelC${g}Ready = 1;
}
if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xC + 1, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xC + 2 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.0);
}
xTexelC${g+1}Ready = 1;
}
xC${g} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw);
`,g+1<p&&(d+=`
final = vec4(0.0);
xCOffset = xC + 1 + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1]) {
final = getX(batch, xR, xCOffset, d1);
}
xC${g+1} = vec4(xTexelC${g+1}.xy, final.xy);
`)):(d+=`
if(xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) {
xTexelC${g} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${g}.zw = vec2(0.0);
}
xTexelC${g}Ready = 1;
}
xCOffset = xC + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.);
}
xTexelC${g+1}Ready = 1;
}
xC${g} = vec4(
xTexelC${g}.xy, xTexelC${g+1}.xy);
`,g+1<p&&(d+=`
xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw);
`)));g<p&&(d+=`
wTexel = getW(r, ${g}, d1, d2);
dotProd += xC${g}.xxzz * vec4(wTexel.xy, wTexel.xy);
if(d1 + 1 < ${e.inChannels}) {
dotProd += xC${g}.yyww * vec4(wTexel.zw, wTexel.zw);
}
`,g+1<p&&(d+=`
wTexel = getW(r, ${g+1}, d1, d2);
dotProd += xC${g+1}.xxzz * vec4(wTexel.xy, wTexel.xy);
if(d1 + 1 < ${e.inChannels}) {
dotProd += xC${g+1}.yyww * vec4(wTexel.zw, wTexel.zw);
}
`))}d+=`
}
`,d+=`
}
`,d+=`
}
`;let h="",c="";r&&(n?h=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${r}
}`:a?h=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${r}
}`:h=`vec4 activation(vec4 x) {
${r}
}`,c="result = activation(result);");let f=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${h}
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);
${d}
vec4 result = dotProd - vec4(0.000000000000001);
${f}
${c}
setOutput(result);
}
`}},ste=class{constructor(e,t){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=e,this.enableShapeUniforms=hr(this.outputShape.length);let{dataFormat:r}=t,n=Sr(),a=r==="channelsLast",s=a?1:2,i=a?2:3,o=this.enableShapeUniforms?"if(blockIndex < outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${e[2]} && pos < ${e[1]}) {`,l="";for(let p=0;p<=1;p++)for(let u=0;u<=1;u++)l+=`
blockIndex = rc.z + ${u};
pos = rc.y + ${p};
${o}
offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];
d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);
if(d0 < inputShape[${s}] && 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[${i}] && d1 >= 0) {
ch = imod(pos, inChannels);
if (${a}) {
innerDims = vec2(d1, ch);
result[${p*2+u}] = getChannel(
getA(rc.x, d0, int(innerDims.x),
int(innerDims.y)), innerDims);
} else {
innerDims = vec2(d0, d1);
result[${p*2+u}] = 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}
${n.output} = result;
}
`}};function zc(e,t){let r=e.length;return r>=3?t?[...e.slice(0,-3),e[r-3]*e[r-2],e[r-1]]:[...e.slice(0,-3),e[r-3],e[r-2]*e[r-1]]:!t&&r===1&&e[0]>1?[e[0],1]:null}function WC({x:e,filter:t,convInfo:r,backend:n,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,p=n.texData.get(e.dataId),u=r.inChannels,d=l[0]*l[1]*l[2],h=r.outChannels,c=r.dataFormat==="channelsLast",f=!1,m=!1,g,y=[];if(s!=null){let b=zc(s.shape,c);b!=null&&(s=ue({inputs:{x:s},backend:n,attrs:{shape:b}}),y.push(s))}if(a!=null){let b=zc(a.shape,c);b!=null&&(a=ue({inputs:{x:a},backend:n,attrs:{shape:b}}),y.push(a))}if(!((d===1||h===1)&&u>RC)&&p.isPacked&&c&&p.texture!=null&&l[2]%2!==0&&k.arraysEqual(p.shape.slice(-3),l.slice(-3))){let b=l[0]*l[1]*(l[2]+1),x={dataId:e.dataId,shape:[1,b,r.inChannels],dtype:e.dtype},v=p.shape;p.shape=p.shape.slice(),p.shape[p.shape.length-2]++,k.assert(sd(p.shape,x.shape),()=>`packed reshape ${p.shape} to ${x.shape} isn't free`);let w=ue({inputs:{x:t},backend:n,attrs:{shape:[1,r.inChannels,r.outChannels]}});y.push(w);let N=Lc({a:x,b:w,backend:n,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),T=n.texData.get(N.dataId);k.assert(T.isPacked,()=>"batchMatMul result is expected to be packed"),p.shape=v,T.shape=r.outShape,g=Jr({inputs:{x:N},backend:n}),g.shape=r.outShape,y.push(N)}else{let b=r.outHeight*r.outWidth,x=ue({inputs:{x:e},backend:n,attrs:{shape:c?[r.batchSize,b,r.inChannels]:[r.batchSize,r.inChannels,b]}}),v=ue({inputs:{x:t},backend:n,attrs:{shape:[1,r.inChannels,r.outChannels]}}),w=Lc({a:c?x:v,b:c?v:x,transposeA:!c,transposeB:m,backend:n,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});g=ue({inputs:{x:w},backend:n,attrs:{shape:r.outShape}}),y.push(x),y.push(v),y.push(w)}for(let b of y)n.disposeIntermediateTensorInfo(b);return g}function UC({x:e,filter:t,convInfo:r,backend:n,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:p,inChannels:u,outWidth:d,outHeight:h,dataFormat:c}=r,f=c==="channelsLast",m=l*p*u,g=h*d,y=[r.batchSize,m,g],b=!0,x=!1,v=[];if(s!=null){let G=zc(s.shape,f);G!=null&&(s=ue({inputs:{x:s},backend:n,attrs:{shape:G}}),v.push(s))}if(a!=null){let G=zc(a.shape,f);G!=null&&(a=ue({inputs:{x:a},backend:n,attrs:{shape:G}}),v.push(a))}let w=ue({inputs:{x:t},backend:n,attrs:{shape:[1,m,k.sizeFromShape(t.shape)/m]}});v.push(w);let N=new ste(y,r),T=[e.shape,[r.padInfo.top,r.padInfo.left],[r.strideHeight,r.strideWidth],[r.dilationHeight,r.dilationWidth],[r.inChannels],[r.filterWidth*r.inChannels],[r.outWidth]],E=n.runWebGLProgram(N,[e],"float32",T),$=ue({inputs:{x:E},backend:n,attrs:{shape:y}});v.push(E),v.push($);let R=a!=null,F=s!=null,S=o==="leakyrelu",D=o?id(o,!0):null,P=new FC(f?$.shape:w.shape,f?w.shape:$.shape,f?[r.batchSize,g,r.outChannels]:[r.batchSize,r.outChannels,g],b,x,R,D,F,S),U=f?[$,w]:[w,$];if(a&&U.push(a),F&&U.push(s),S){let G=n.makeTensorInfo([],"float32",k.createScalarValue(i,"float32"));U.push(G),v.push(G)}let H=n.runWebGLProgram(P,U,"float32"),q=ue({inputs:{x:H},backend:n,attrs:{shape:r.outShape}});v.push(H);for(let G of v)n.disposeIntermediateTensorInfo(G);return q}function ite(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:p,dimRoundingMode:u}=n,d=_.convertConv2DDataFormat(l),h=_.computeConv2DInfo(a.shape,s.shape,i,p,o,u,!1,d),c;if(h.filterHeight===1&&h.filterWidth===1&&h.dilationHeight===1&&h.dilationWidth===1&&h.strideHeight===1&&h.strideWidth===1&&(h.padInfo.type==="SAME"||h.padInfo.type==="VALID"))c=WC({x:a,filter:s,convInfo:h,backend:r});else if(h.strideWidth<=2&&d==="channelsLast"&&j().getBool("WEBGL_EXP_CONV")){let m=new BC(h),g=[[h.padInfo.top,h.padInfo.left],[h.strideHeight,h.strideWidth],[h.dilationHeight,h.dilationWidth],[h.inHeight,h.inWidth]];c=r.runWebGLProgram(m,[a,s],"float32",g)}else if(j().getBool("WEBGL_CONV_IM2COL"))c=UC({x:a,filter:s,convInfo:h,backend:r});else{let m=new PC(h);c=r.runWebGLProgram(m,[a,s],"float32")}let f=ue({inputs:{x:c},backend:r,attrs:{shape:h.outShape}});return r.disposeIntermediateTensorInfo(c),f}var ote={kernelName:Ui,backendName:"webgl",kernelFunc:ite},lte=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,r=e.strideWidth,n=e.padInfo.top,a=e.padInfo.left,s=e.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 < ${e.batchSize}; b++) {
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${t} - ${n};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${r} - ${a};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
${s?`float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);`:`float dyValue = getDy(b, d2, yR, yC);
float xValue = getX(b, d1, xR, xC);
dotProd += (xValue * dyValue);`}
}
}
}
setOutput(dotProd);
}
`}},ute=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=r-1-e.padInfo.left,l=s?1:2,p=s?2:3,u=s?3:1;this.userCode=`
const ivec2 pads = ivec2(${i}, ${o});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[${u}];
ivec2 dyCorner = ivec2(coords[${l}], coords[${p}]) - 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 < ${t}; wR++) {
float dyR = float(dyRCorner + wR) / ${n}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${t} - 1 - wR;
for (int wC = 0; wC < ${r}; wC++) {
float dyC = float(dyCCorner + wC) / ${a}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${r} - 1 - wC;
for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
if (${s}) {
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);
}
`}},pte=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,r=e.strideHeight,n=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
void main() {
ivec5 coords = getOutputCoords();
int wF = coords.x;
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 < ${e.batchSize}; b++) {
for (int yF = 0; yF < ${e.outDepth}; yF++) {
int xF = wF + yF * ${t} - ${a};
if (xF < 0 || xF >= ${e.inDepth}) {
continue;
}
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${r} - ${s};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${n} - ${i};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yF, yR, yC, d2);
float xValue = getX(b, xF, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},dte=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,r=e.filterHeight,n=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=r-1-e.padInfo.top,p=n-1-e.padInfo.left;this.userCode=`
const ivec3 pads = ivec3(${o}, ${l}, ${p});
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 < ${t}; wF++) {
float dyF = float(dyFCorner + wF) / ${a}.0;
if (dyF < 0.0 || dyF >= ${e.outDepth}.0 || fract(dyF) > 0.0) {
continue;
}
int idyF = int(dyF);
int wFPerm = ${t} - 1 - wF;
for (int wR = 0; wR < ${r}; wR++) {
float dyR = float(dyRCorner + wR) / ${s}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${r} - 1 - wR;
for (int wC = 0; wC < ${n}; wC++) {
float dyC = float(dyCCorner + wC) / ${i}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${n} - 1 - wC;
for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
float xValue = getDy(batch, idyF, idyR, idyC, d2);
float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
}
}
}
}
setOutput(dotProd);
}
`}};function hte(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:p,filterShape:u}=n,d=_.convertConv2DDataFormat(l),h=_.computeConv2DInfo(a.shape,u,i,1,o,p,!1,d),c=new lte(h);return r.runWebGLProgram(c,[a,s],"float32")}var cte={kernelName:Qc,backendName:"webgl",kernelFunc:hte},fte=class{constructor(e){this.variableNames=["dy","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"strides",type:"vec2"}],this.outputShape=e.inShape,this.enableShapeUniforms=hr(this.outputShape.length);let t=e.filterHeight,r=e.filterWidth,n=t-1-e.padInfo.top,a=r-1-e.padInfo.left;this.userCode=`
const ivec2 pads = ivec2(${n}, ${a});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[3];
ivec2 dyCorner = ivec2(coords[1], coords[2]) - pads;
int dyRCorner = dyCorner.x;
int dyCCorner = dyCorner.y;
vec4 result = vec4(0.);
for (int wR = 0; wR < ${t}; wR++) {
float dyR = float(dyRCorner + wR) / strides[0];
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${t} - 1 - wR;
for (int wC = 0; wC < ${r}; wC++) {
int wCPerm = ${r} - 1 - wC;
float dyC = float(dyCCorner + wC) / strides[1];
bool idyCVal = (dyC >= 0.0) && (dyC < ${e.outWidth}.0)
&& (fract(dyC) == 0.0);
int idyC = int(dyC);
float dyC2 = float(dyCCorner + wC + 1) / strides[1];
bool idyCVal2 = (dyC2 >= 0.0) && (dyC2 < ${e.outWidth}.0)
&& (fract(dyC2) == 0.0);
int idyC2 = int(dyC2);
if (idyCVal && idyCVal2) {
for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
vec4 dySample = getDy(batch, idyR, idyC, d2);
vec4 dySample2 = (idyC / 2 == idyC2 / 2) ?
dySample : getDy(batch, idyR, idyC2, d2);
vec2 dyValue = mod(float(idyC), 2.) == 0. ?
dySample.xy : dySample.zw;
result.xy += vec2(dot(dyValue, wValue.xy),
dot(dyValue, wValue.zw));
dyValue = mod(float(idyC2), 2.) == 0. ?
dySample2.xy : dySample2.zw;
result.zw += vec2(dot(dyValue, wValue.xy),
dot(dyValue, wValue.zw));
}
} else if (idyCVal) {
for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
vec4 dySample = getDy(batch, idyR, idyC, d2);
vec2 dyValue = mod(float(idyC), 2.) == 0. ?
dySample.xy : dySample.zw;
result.xy += vec2(dot(dyValue, wValue.xy),
dot(dyValue, wValue.zw));
}
} else if (idyCVal2) {
for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
vec4 dySample = getDy(batch, idyR, idyC2, d2);
vec2 dyValue = mod(float(idyC2), 2.) == 0. ?
dySample.xy : dySample.zw;
result.zw += vec2(dot(dyValue, wValue.xy),
dot(dyValue, wValue.zw));
}
}
}
}
setOutput(result);
}
`}};function mte(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:p,dimRoundingMode:u}=n,d=_.convertConv2DDataFormat(p),h=_.computeConv2DInfo(i,s.shape,o,1,l,u,!1,d);if(j().getBool("WEBGL_PACK_CONV2DTRANSPOSE")&&d==="channelsLast"){let c=[[h.strideHeight,h.strideWidth]],f=new fte(h);return r.runWebGLProgram(f,[a,s],"float32",c)}else{let c=new ute(h);return r.runWebGLProgram(c,[a,s],"float32")}}var gte={kernelName:Vi,backendName:"webgl",kernelFunc:mte};function yte(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=n,p=_.computeConv3DInfo(a.shape,s.shape,i,l,o),u=new ate(p);return r.runWebGLProgram(u,[a,s],"float32")}var bte={kernelName:Gi,backendName:"webgl",kernelFunc:yte};function xte(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=n,p=_.computeConv3DInfo(a.shape,l,i,1,o),u=new pte(p);return r.runWebGLProgram(u,[a,s],"float32")}var vte={kernelName:au,backendName:"webgl",kernelFunc:xte};function wte(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=n,p=_.computeConv3DInfo(l,s.shape,o,1,i),u=new dte(p);return r.runWebGLProgram(u,[a,s],"float32")}var kte={kernelName:su,backendName:"webgl",kernelFunc:wte},Ite=fp+`
return cos(x);
`,Ste=`
vec4 result = cos(x);
bvec4 isNaN = isnan(x);
${al}
return result;
`,Nte=Ke({opSnippet:Ite,packedOpSnippet:Ste}),_te={kernelName:Hi,backendName:"webgl",kernelFunc:Nte},Tte=`
float e2x = exp(-x);
return (e2x + 1.0 / e2x) / 2.0;
`,Cte=Ke({opSnippet:Tte}),Ete={kernelName:ji,backendName:"webgl",kernelFunc:Cte},$te=class{constructor(e,t,r,n,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[p]=t,[u,d]=r;this.outputShape=[p,u,d,l];let h=n==="bilinear"?1:0,[c,f]=[`${i-1}.0`,`${o-1}.0`],[m,g,y]=u>1?[`${(i-1)/(u-1)}`,"(y2-y1) * height_ratio",`y1*${c} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${c}`],[b,x,v]=d>1?[`${(o-1)/(d-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
const float height_ratio = float(${m});
const float width_ratio = float(${b});
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 >= ${s}) {
return;
}
float height_scale = ${g};
float width_scale = ${x};
float in_y = ${y};
if( in_y < 0.0 || in_y > ${c} ) {
setOutput(float(${a}));
return;
}
float in_x = ${v};
if( in_x < 0.0 || in_x > ${f} ) {
setOutput(float(${a}));
return;
}
vec2 sourceFracIndexCR = vec2(in_x,in_y);
if(${h} == 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);
}
}
`}},Ate=e=>{let{inputs:t,backend:r,attrs:n}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:p}=n,u=new $te(a.shape,s.shape,o,l,p);return r.runWebGLProgram(u,[a,s,i],"float32")},Fte={kernelName:ou,backendName:"webgl",kernelFunc:Ate},ld;(function(e){e.Prod="*",e.Sum="+"})(ld||(ld={}));var $1=class{constructor(e,t,r,n){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let a=this.outputShape.length,s=this.op===ld.Prod?"1.0":"0.0",i=r?s:`getX(${A1(a,"coords",this.op)})`,o=this.outputShape[this.outputShape.length-1],l="",p="";r?(l=n?`end != ${o-1}`:"end != 0",p=n?"end + 1":"end - 1"):(l=n?`end + pow2 < ${o}`:"end >= pow2",p=n?"end + pow2":"end - pow2"),this.userCode=`
void main() {
${pt(a)} coords = getOutputCoords();
int end = ${F1(a,"coords",this.op)};
float val = ${i};
int pow2 = int(pow(2.0, index));
if (${l}) {
int idx = ${p};
${F1(a,"coords",this.op)} = idx;
val ${this.op}= getX(${A1(a,"coords",this.op)});
}
setOutput(val);
}
`}};function A1(e,t,r){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw new Error(`Cumulative ${r} for rank ${e} is not yet supported`)}function F1(e,t,r){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw new Error(`Cumulative ${r} for rank ${e} is not yet supported`)}function VC(e,t,r,n,a,s){let i=t.shape.length,o=_.getAxesPermutation([n],i),l=t;o!=null&&(l=xr({inputs:{x:t},backend:r,attrs:{perm:o}}));let p=_.getInnerMostAxes(1,i)[0];if(p!==i-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let u=l.shape[p],d=Jr({inputs:{x:l},backend:r});for(let h=0;h<=Math.ceil(Math.log2(u))-1;h++){let c=new $1(e,l.shape,!1,s),f=[[h]],m=d;d=r.runWebGLProgram(c,[d],d.dtype,f),r.disposeIntermediateTensorInfo(m)}if(a){let h=new $1(e,l.shape,a,s),c=d;d=r.runWebGLProgram(h,[d],d.dtype),r.disposeIntermediateTensorInfo(c)}if(o!=null){let h=_.getUndoAxesPermutation(o),c=xr({inputs:{x:d},backend:r,attrs:{perm:h}});return r.disposeIntermediateTensorInfo(d),r.disposeIntermediateTensorInfo(l),c}return d}function Rte(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n;return VC(ld.Prod,a,r,s,i,o)}var Dte={kernelName:iu,backendName:"webgl",kernelFunc:Rte};function Mte(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n;return VC(ld.Sum,a,r,s,i,o)}var Ote={kernelName:qi,backendName:"webgl",kernelFunc:Mte};function Lte(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=n;if(a.shape.length===1){let l=r.readSync(a.dataId),p=r.readSync(s.dataId),u=wC(l,p,s.dtype,s.shape,i);return r.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=r.bufferSync(a),p=r.bufferSync(s),u=P9(l,p,i,o);return r.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var zte={kernelName:gd,backendName:"webgl",kernelFunc:Lte},Pte=class{constructor(e,t,r){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=r,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 / ${t};
int offset_h = imod(h, ${t});
int in_w = w / ${t};
int offset_w = imod(w, ${t});
int offset_d = (offset_h * ${t} + 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 Bte(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockSize:s,dataFormat:i}=n,o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],p=i==="NHWC"?a.shape[2]:a.shape[3],u=i==="NHWC"?a.shape[3]:a.shape[1],d=l*s,h=p*s,c=u/(s*s),f=i==="NHWC"?[o,d,h,c]:[o,c,d,h],m=new Pte(f,s,i);return r.runWebGLProgram(m,[a],a.dtype)}var Wte={kernelName:lu,backendName:"webgl",kernelFunc:Bte},GC=class{constructor(e,t=!1,r=null,n=!1,a=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=hr(this.outputShape.length);let s=e.filterHeight,i=e.filterWidth,o=e.outChannels/e.inChannels,l="",p="";r&&(n?l=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${r}
}`:a?l=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${r}
}`:l=`
float activation(float x) {
${r}
}
`,p="result = activation(result);");let u=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),a&&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 / ${o};
int q = d2 - d1 * ${o};
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 < ${s}; wR++) {
int xR = xRCorner + wR * dilations[0];
if (xR < 0 || xR >= inDims[0]) {
continue;
}
for (int wC = 0; wC < ${i}; 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;
${u}
${p}
setOutput(result);
}
`}},HC=class{constructor(e,t=!1,r=null,n=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=hr(this.outputShape.length);let s=e.outChannels/e.inChannels,i=e.padInfo.left,o=e.strideWidth,l=e.dilationWidth,p=e.filterHeight,u=e.filterWidth,d=u,h=`
int xR; int xC; int xCOffset;
vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g<u;g++)h+=`
vec4 xTexelC${g*2};
int xTexelC${g*2}Ready;
vec4 xTexelC${g*2+1};
int xTexelC${g*2+1}Ready;
vec4 xC${g};`;h+=`
for (int r = 0; r < ${p}; r++) {
`;for(let g=0;g<u;g++)h+=`
xTexelC${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);`;h+=`
xR = xRCorner + r * dilations[0];
if (xR >=0 && xR < inDims[0]) {
`;for(let g=0;g<(d+1)/2;g++){let y=g*2;if(h+=`
xC = xCCorner + ${y*l};
`,o===1){if(y<u&&(i%2===1?(h+=`
xCOffset = xC + 1;
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y}Ready == 0) {
xTexelC${y} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${y}.zw = vec2(0.0);
}
xTexelC${y}Ready = 1;
}
`,l===1&&y>0?h+=`
xC${y} = vec4(xTexelC${y-2}.zw, xTexelC${y}.xy);
`:h+=`
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${y} = vec4(previous.zw, xTexelC${y}.xy);
} else {
xC${y} = vec4(0.0, 0.0, xTexelC${y}.xy);
}
`):h+=`
if (xC >= 0 && xC < inDims[1] && xTexelC${y}Ready == 0) {
xTexelC${y} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${y}.zw = vec2(0.0);
}
xTexelC${y}Ready = 1;
}
xC${y} = xTexelC${y};
`,y+1<u)){let b=i%2===0?k.nearestLargerEven(l):l;l%2===0&&i%2===1||l%2!==0&&i%2!==1?(h+=`
xCOffset = xC + imod(pads[1], 2) + ${b};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) {
xTexelC${y+1} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${y+1}.zw = vec2(0.0);
}
xTexelC${y+1}Ready = 1;
}
`,l>1?h+=`
xCOffset -= 2;
if (xCOffset >= 0 && xCOffset < inDims[1]) {
previous = getX(batch, xR, xCOffset, d1);
xC${y+1} = vec4(previous.zw, xTexelC${y+1}.xy);
} else {
xC${y+1} = vec4(0.0, 0.0, xTexelC${y+1}.xy);
}
`:h+=`
xC${y+1} = vec4(xTexelC${y}.zw, xTexelC${y+1}.xy);
`):b===1?h+=`
xC${y+1} = xTexelC${y};
`:h+=`
xCOffset = xC + ${b};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) {
xTexelC${y+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${y+1}.zw = vec2(0.0);
}
xTexelC${y+1}Ready = 1;
}
xC${y+1} = xTexelC${y+1};
`}}else y<u&&(i%2===1?(h+=`
xCOffset = xC + 1 - strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y}Ready == 0) {
xTexelC${y} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${y}.zw = vec2(0.0);
}
xTexelC${y}Ready = 1;
}
if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${y+1}Ready == 0) {
xTexelC${y+1} = getX(batch, xR, xC + 1, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xC + 2 >= inDims[1]) {
xTexelC${y+1}.zw = vec2(0.0);
}
xTexelC${y+1}Ready = 1;
}
xC${y} = vec4(xTexelC${y}.zw, xTexelC${y+1}.zw);
`,y+1<u&&(h+=`
final = vec4(0.0);
xCOffset = xC + 1 + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1]) {
final = getX(batch, xR, xCOffset, d1);
}
xC${y+1} = vec4(xTexelC${y+1}.xy, final.xy);
`)):(h+=`
if(xC >= 0 && xC < inDims[1] && xTexelC${y}Ready == 0) {
xTexelC${y} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${y}.zw = vec2(0.0);
}
xTexelC${y}Ready = 1;
}
xCOffset = xC + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) {
xTexelC${y+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${y+1}.zw = vec2(0.);
}
xTexelC${y+1}Ready = 1;
}
xC${y} = vec4(
xTexelC${y}.xy, xTexelC${y+1}.xy);
`,y+1<u&&(h+=`
xC${y+1} = vec4(xTexelC${y}.zw, xTexelC${y+1}.zw);
`)));y<u&&(h+=`
wTexel = getW(r, ${y}, d1, q);
dotProd += xC${y} * vec4(wTexel.xz, wTexel.xz);
`,y+1<u&&(h+=`
wTexel = getW(r, ${y+1}, d1, q);
dotProd += xC${y+1} * vec4(wTexel.xz, wTexel.xz);
`))}h+=`
}
`,h+=`
}
`;let c="",f="";r&&(n?c=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${r}
}`:a?c=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${r}
}`:c=`vec4 activation(vec4 x) {
${r}
}`,f="result = activation(result);");let m=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${c}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
ivec2 xRCCorner = coords.yz * strides - pads;
int d2 = coords.w;
int d1 = d2 / ${s};
int q = d2 - d1 * ${s};
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);
${h}
vec4 result = dotProd - vec4(0.000000000000001);
${m}
${f}
setOutput(result);
}
`}};function Ute(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:p}=n,u=l;u==null&&(u=[1,1]),k.assert(_.eitherStridesOrDilationsAreOne(i,u),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let d=_.computeConv2DInfo(a.shape,s.shape,i,u,o,p,!0),h;j().getBool("WEBGL_PACK_DEPTHWISECONV")&&d.strideWidth<=2&&d.outChannels/d.inChannels===1?h=new HC(d):h=new GC(d);let c=[[d.padInfo.top,d.padInfo.left],[d.strideHeight,d.strideWidth],[d.dilationHeight,d.dilationWidth],[d.inHeight,d.inWidth]];return r.runWebGLProgram(h,[a,s],"float32",c)}var Vte={kernelName:Ki,backendName:"webgl",kernelFunc:Ute},Gte=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,r=e.strideWidth,n=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.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 * ${s} + dm;
float dotProd = 0.0;
// TO DO: Vec4 over the batch size
for (int b = 0; b < ${e.batchSize}; b++) {
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${t} - ${n};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${r} - ${a};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
setOutput(dotProd);
}
`}},Hte=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=r-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
const ivec2 pads = ivec2(${s}, ${i});
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 < ${t}; wR++) {
float dyR = float(dyRCorner + wR) / ${n}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${t} - 1 - wR;
for (int wC = 0; wC < ${r}; wC++) {
float dyC = float(dyCCorner + wC) / ${a}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${r} - 1 - wC;
// TO DO: Vec4 over the channelMul
for (int dm = 0; dm < ${o}; dm++) {
int d2 = d1 * ${o} + dm;
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, dm);
dotProd += xValue * wValue;
}
}
}
setOutput(dotProd);
}
`}};function jte(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:p,filterShape:u}=n,d=_.computeConv2DInfo(a.shape,u,i,o,l,p,!0),h=new Gte(d);return r.runWebGLProgram(h,[a,s],"float32")}var qte={kernelName:ef,backendName:"webgl",kernelFunc:jte};function Kte(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:p,inputShape:u}=n,d=_.computeConv2DInfo(u,s.shape,i,o,l,p,!0),h=new Hte(d);return r.runWebGLProgram(h,[a,s],"float32")}var Xte={kernelName:tf,backendName:"webgl",kernelFunc:Kte},Zte=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
setOutput(val);
}
`}};function Jte(e){let{inputs:t,backend:r}=e,{x:n}=t,a=[...n.shape,...n.shape],s=k.sizeFromShape(n.shape),i=ue({inputs:{x:n},backend:r,attrs:{shape:[s]}}),o=new Zte(s),l=r.runWebGLProgram(o,[i],i.dtype),p=ue({inputs:{x:l},backend:r,attrs:{shape:a}});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(l),p}var Yte={kernelName:yd,backendName:"webgl",kernelFunc:Jte},Qte=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:r,padInfo:n,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:p}=e,{top:u,left:d}=n;this.userCode=`
const ivec2 strides = ivec2(${a}, ${s});
const ivec2 pads = ivec2(${u}, ${d});
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 < ${i}; h++) {
int hIn = hBeg + h * ${l};
if (hIn >= 0 && hIn < ${t}) {
for (int w = 0; w < ${o}; w++) {
int wIn = wBeg + w * ${p};
if (wIn >= 0 && wIn < ${r}) {
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 ere(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=n,p=_.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),u,d=new Qte(p);u=r.runWebGLProgram(d,[a,s],"float32");let h=ue({inputs:{x:u},backend:r,attrs:{shape:p.outShape}});return r.disposeIntermediateTensorInfo(u),h}var tre={kernelName:Xi,backendName:"webgl",kernelFunc:ere};function rre(e){let{inputs:t,backend:r,attrs:n}=e,{equation:a}=n,s=t,{allDims:i,summedDims:o,idDims:l}=_.decodeEinsumEquation(a,s.length);_.checkEinsumDimSizes(i.length,l,s);let{path:p,steps:u}=_.getEinsumComputePath(o,l),d=u.length,h=null,c=i.length,f=[];for(let m=0;m<d;++m){for(let g of u[m]){let{permutationIndices:y,expandDims:b}=_.getEinsumPermutation(c,l[g]),x;_.isIdentityPermutation(y)?x=s[g]:(x=xr({inputs:{x:s[g]},backend:r,attrs:{perm:y}}),f.push(x));let v=x.shape.slice();for(let w=0;w<b.length;++w)v.splice(b[w],0,1);k.arraysEqual(x.shape,v)||(x=ue({inputs:{x},backend:r,attrs:{shape:v}}),f.push(x)),h===null?h=x:(h=dw({inputs:{a:x,b:h},backend:r}),f.push(h))}m<d-1&&(p[m]>=0&&(h=vm({inputs:{x:h},backend:r,attrs:{axis:p[m]-(i.length-c),keepDims:!1}}),f.push(h)),c--)}for(let m of f)m!==h&&r.disposeIntermediateTensorInfo(m);return h}var nre={kernelName:nf,backendName:"webgl",kernelFunc:rre},are="return (x >= 0.0) ? x : (exp(x) - 1.0);",sre=`
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;
`,ire=Ke({opSnippet:are,packedOpSnippet:sre}),ore={kernelName:Ji,backendName:"webgl",kernelFunc:ire},lre="return (b >= 0.0) ? a : a * (b + 1.0);",ure=`
vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,pre=e=>{let{inputs:t,backend:r}=e,{dy:n,y:a}=t,s=j().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new cp(ure,n.shape,a.shape):new Ni(lre,n.shape,a.shape);return r.runWebGLProgram(s,[n,a],n.dtype)},dre={kernelName:uu,backendName:"webgl",kernelFunc:pre},hre=`
return vec4(equal(a, b));
`,cre="return float(a == b);",fre=lr({opSnippet:cre,packedOpSnippet:hre,dtype:"bool",cpuKernelImpl:G9}),mre={kernelName:pu,backendName:"webgl",kernelFunc:fre},gre=`
// Error function is calculated approximately with elementary function.
// See "Handbook of Mathematical Functions with Formulas,
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
float p = ${_.ERF_P};
float a1 = ${_.ERF_A1};
float a2 = ${_.ERF_A2};
float a3 = ${_.ERF_A3};
float a4 = ${_.ERF_A4};
float a5 = ${_.ERF_A5};
float sign = sign(x);
x = abs(x);
float t = 1.0 / (1.0 + p * x);
return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,yre=Ke({opSnippet:gre}),bre={kernelName:Yi,backendName:"webgl",kernelFunc:yre},xre=fp+`
return exp(x);
`,vre=`
vec4 result = exp(x);
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : result.r;
result.g = isNaN.g ? x.g : result.g;
result.b = isNaN.b ? x.b : result.b;
result.a = isNaN.a ? x.a : result.a;
return result;
`,jC=Ke({opSnippet:xre,packedOpSnippet:vre,cpuKernelImpl:H9,dtype:"float32"}),wre={kernelName:Qi,backendName:"webgl",kernelFunc:jC};function Qg(e){let{inputs:t,attrs:r,backend:n}=e,{dim:a}=r,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(k.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),ue({inputs:{x:s},backend:n,attrs:{shape:o}})}var kre={kernelName:du,backendName:"webgl",kernelFunc:Qg},R1="return exp(x) - 1.0;",Ire=Ke({opSnippet:R1,packedOpSnippet:R1,cpuKernelImpl:j9}),Sre={kernelName:eo,backendName:"webgl",kernelFunc:Ire},D1=class{constructor(e,t,r){this.variableNames=["real","imag"];let n=t[1];this.outputShape=t;let a=r?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=r?`${n}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
const float exponentMultiplier = ${a};
float unaryOpComplex(float real, float expR, float imag, float expI) {
${i}
}
float mulMatDFT(int batch, int index) {
float indexRatio = float(index) / float(${n});
float exponentMultiplierTimesIndexRatio =
exponentMultiplier * indexRatio;
float result = 0.0;
for (int i = 0; i < ${n}; 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) / ${s};
}
return result;
}
void main() {
ivec2 coords = getOutputCoords();
setOutput(mulMatDFT(coords[0], coords[1]));
}
`}};function qC(e,t,r){let n=r.texData.get(e.dataId),a=k.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=ue({inputs:{x:e},backend:r,attrs:{shape:[i,s]}}),l=o.shape,p=new D1("real",l,t),u=new D1("imag",l,t),d=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:l},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:l}],h=r.runWebGLProgram(p,d,"float32"),c=r.runWebGLProgram(u,d,"float32"),f=Ls({inputs:{real:h,imag:c},backend:r});r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(c);let m=ue({inputs:{x:f},backend:r,attrs:{shape:e.shape}});return r.disposeIntermediateTensorInfo(o),r.disposeIntermediateTensorInfo(f),m}function Nre(e){let{inputs:t,backend:r}=e,{input:n}=t;return qC(n,!1,r)}var _re={kernelName:af,backendName:"webgl",kernelFunc:Nre},Tre=class{constructor(e,t){this.outputShape=[],this.customUniforms=[{name:"value",type:"float"}],this.variableNames=["x"],this.outputShape=e,this.userCode=`
void main() {
// Input can be obtained from uniform value.
setOutput(value);
}
`}};function dh(e){let{backend:t,attrs:r}=e,{shape:n,value:a}=r,{dtype:s}=r;if(s=s||k.inferDtype(a),s==="string"){let i=k.getArrayFromDType(s,k.sizeFromShape(n));return i.fill(a),t.makeTensorInfo(n,s,i)}else{let i=new Tre(n,a),o=[[a]];return t.runWebGLProgram(i,[],s,o)}}var Cre={kernelName:bd,backendName:"webgl",kernelFunc:dh},Ere=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int x = coords[2];
int coordX = ${t} - x - 1;
float outputValue;
if(coordX >= 0 && coordX < ${t}) {
outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
} else {
outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
}
setOutput(outputValue);
}
`}},$re={kernelName:hu,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:r}=e,n=t,a=new Ere(r.shape);return n.runWebGLProgram(a,[r],r.dtype)}},M1="return floor(x);",Are=Ke({opSnippet:M1,packedOpSnippet:M1,cpuKernelImpl:q9}),Fre={kernelName:to,backendName:"webgl",kernelFunc:Are},Rre=`
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;
}
`,Dre=`
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);
`,Mre=lr({opSnippet:Rre,packedOpSnippet:Dre,dtype:"int32"}),Ore={kernelName:ro,backendName:"webgl",kernelFunc:Mre},Lre=class{constructor(e){this.variableNames=["A"];let t=Sr(),[r,n]=e;this.outputShape=e,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(${n}.0, ${r}.0);
vec4 values = ${t.texture2D}(A, uv);
float value;
if (depth == 0) {
value = values.r;
} else if (depth == 1) {
value = values.g;
} else if (depth == 2) {
value = values.b;
} else if (depth == 3) {
value = values.a;
}
setOutput(floor(value * 255.0 + 0.5));
}
`}},zre=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=Sr(),[r,n]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec4 result = vec4(0.);
for(int row=0; row<=1; row++) {
for(int col=0; col<=1; col++) {
texC = coords[1] + row;
depth = coords[2] + col;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${n}.0, ${r}.0);
vec4 values = ${t.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);
}
}
${t.output} = result;
}
`}},Pre={kernelName:gc,backendName:"webgl",kernelFunc:Bre},hl,qm=j().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function Bre(e){let{inputs:t,backend:r,attrs:n}=e,{pixels:a}=t,{numChannels:s}=n,i=typeof HTMLVideoElement<"u"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement<"u"&&a instanceof HTMLImageElement,[l,p]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],u=[p,l],d=[p,l,s];if(o||i){let m=j().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(hl==null||m!==qm)&&(qm=m,hl=document.createElement("canvas").getContext("2d",{willReadFrequently:qm})),hl.canvas.width=l,hl.canvas.height=p,hl.drawImage(a,0,0,l,p),a=hl.canvas}let h=r.makeTensorInfo(u,"int32");r.texData.get(h.dataId).usage=on.PIXELS,r.gpgpu.uploadPixelDataToTexture(r.getTexture(h.dataId),a);let c=j().getBool("WEBGL_PACK")?new zre(d):new Lre(d),f=r.runWebGLProgram(c,[h],"int32");return r.disposeData(h.dataId),f}function Wre(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:p,dataFormat:u,dilations:d,dimRoundingMode:h,activation:c,leakyreluAlpha:f}=n,m=_.convertConv2DDataFormat(u),g=_.computeConv2DInfo(a.shape,s.shape,l,d,p,h,!1,m),y,b=[],x=i!=null,v=o!=null,w=c==="leakyrelu",N=()=>{let E=[a,s],$=(R,F)=>{if(F==="NCHW"&&R.shape.length===1&&R.shape[0]!==1){let S=ue({inputs:{x:R},backend:r,attrs:{shape:[R.shape[0],1,1]}});return b.push(S),S}return R};if(x&&E.push($(i,u)),v&&E.push($(o,u)),w){let R=r.makeTensorInfo([],"float32",k.createScalarValue(f,"float32"));E.push(R),b.push(R)}return E};if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))y=WC({x:a,filter:s,convInfo:g,backend:r,bias:i,activation:c,preluActivationWeights:o,leakyreluAlpha:f});else if(g.strideWidth<=2&&m==="channelsLast"&&j().getBool("WEBGL_EXP_CONV")){let E=c?id(c,!0):null,$=new BC(g,x,E,v,w),R=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],F=N();y=r.runWebGLProgram($,F,"float32",R)}else if(j().getBool("WEBGL_CONV_IM2COL"))y=UC({x:a,filter:s,convInfo:g,backend:r,bias:i,activation:c,preluActivationWeights:o,leakyreluAlpha:f});else{let E=c?id(c,!1):null,$=new PC(g,x,E,v,w),R=N();y=r.runWebGLProgram($,R,"float32")}let T=ue({inputs:{x:y},backend:r,attrs:{shape:g.outShape}});return b.push(y),b.forEach(E=>r.disposeIntermediateTensorInfo(E)),T}var Ure={kernelName:ui,backendName:"webgl",kernelFunc:Wre};function Vre(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:p,dilations:u,dimRoundingMode:d,activation:h,leakyreluAlpha:c}=n,f=[],m=u;m==null&&(m=[1,1]),k.assert(_.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let g=_.computeConv2DInfo(a.shape,s.shape,l,m,p,d,!0),y=j().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,b=h?id(h,y):null,x=[a,s],v=i!=null,w=o!=null,N=h==="leakyrelu";if(v&&x.push(i),w&&x.push(o),N){let R=r.makeTensorInfo([],"float32",k.createScalarValue(c,"float32"));x.push(R),f.push(R)}let T;y?T=new HC(g,v,b,w,N):T=new GC(g,v,b,w,N);let E=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],$=r.runWebGLProgram(T,x,"float32",E);return f.forEach(R=>r.disposeIntermediateTensorInfo(R)),$}var Gre={kernelName:pi,backendName:"webgl",kernelFunc:Vre},Hre=class{constructor(e,t,r,n){this.sliceDim=e,this.strides=t,this.paramsShape=n,this.variableNames=["x","indices"],this.outputShape=r;let a=pt(r.length),s=`
int index;`;for(let i=0;i<this.sliceDim;i++)s+=`
index = round(getIndices(coords[0], ${i}));
out_of_bounds = out_of_bounds || index < 0;
out_of_bounds = out_of_bounds || index >= ${this.paramsShape[i]};
flattenIndex += index * ${this.strides[i]};`;this.userCode=`
void main() {
${a} coords = getOutputCoords();
int flattenIndex = 0;
bool out_of_bounds = false;
${s}
setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));
}
`}};function jre(e){let{inputs:t,backend:r}=e,{params:n,indices:a}=t,s=a.shape,i=s[s.length-1],o=k.sizeFromShape(n.shape),[l,p,u,d]=_.prepareAndValidate(n,a),h=ue({inputs:{x:a},backend:r,attrs:{shape:[p,i]}}),c=ue({inputs:{x:n},backend:r,attrs:{shape:[k.sizeFromShape(n.shape)/u,u]}});if(r.shouldExecuteOnCPU([n,a])||n.dtype==="string"){let y=r.readSync(a.dataId),b=r.bufferSync(n),x=K9(y,b,n.dtype,p,i,u,d,n.shape,o);return r.makeTensorInfo(l,n.dtype,x.values)}let f=new Hre(i,d,[p,u],n.shape),m=r.runWebGLProgram(f,[c,h],c.dtype),g=ue({inputs:{x:m},backend:r,attrs:{shape:l}});return r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(c),r.disposeIntermediateTensorInfo(m),g}var qre={kernelName:fu,backendName:"webgl",kernelFunc:jre},Kre=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let r=pt(this.rank),n=Xre(e);this.userCode=`
void main() {
${r} resRC = getOutputCoords();
int index = int(getIndices(resRC.x, resRC.z));
float inBounds = (index >= 0) && (index < ${e[2]}) ? 1.0 : 0.0;
setOutput(inBounds * getA(${n}));
}
`}};function Xre(e,t){let r=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let a=0;a<e.length;a++)a===2?n.push("index"):n.push(`${r[a]}`);return n.join()}function KC(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=n,l=k.parseAxisParam(i,a.shape)[0];if(j().get("DEBUG")){let b=r.readSync(s.dataId),x=a.shape[l];for(let v=0;v<b.length;++v){let w=b[v];k.assert(w<=x-1&&w>=0,()=>`GatherV2: the index value ${w} is not in [0, ${x-1}]`)}}let p=_.segment_util.collectGatherOpShapeInfo(a,s,l,o),u=k.sizeFromShape(s.shape),d=[],h=ue({inputs:{x:a},backend:r,attrs:{shape:[p.batchSize,p.outerSize,p.dimSize,p.sliceSize]}}),c=ue({inputs:{x:s},backend:r,attrs:{shape:[p.batchSize,u/p.batchSize]}});d.push(h),d.push(c);let f=[p.batchSize,p.outerSize,u/p.batchSize,p.sliceSize];if(r.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let b=r.bufferSync(c),x=r.bufferSync(h),v=X9(x,b,f);return d.forEach(w=>r.disposeIntermediateTensorInfo(w)),r.makeTensorInfo(p.outputShape,v.dtype,v.values)}let m=new Kre(h.shape,f),g=r.runWebGLProgram(m,[h,c],h.dtype);d.push(g);let y=ue({inputs:{x:g},backend:r,attrs:{shape:p.outputShape}});return d.forEach(b=>r.disposeIntermediateTensorInfo(b)),y}var Zre={kernelName:cu,backendName:"webgl",kernelFunc:KC},Jre="return float(a > b);",Yre=`
return vec4(greaterThan(a, b));
`,Qre=lr({opSnippet:Jre,packedOpSnippet:Yre,cpuKernelImpl:Z9,dtype:"bool"}),ene={kernelName:mu,backendName:"webgl",kernelFunc:Qre},tne="return float(a >= b);",rne=`
return vec4(greaterThanEqual(a, b));
`,nne=lr({opSnippet:tne,packedOpSnippet:rne,dtype:"bool",cpuKernelImpl:J9}),ane={kernelName:ao,backendName:"webgl",kernelFunc:nne};function sne(e){let{inputs:t,backend:r}=e,{input:n}=t;return qC(n,!0,r)}var ine={kernelName:sf,backendName:"webgl",kernelFunc:sne},one="return float(!isnan(x) && !isinf(x));",lne=Ke({opSnippet:one,dtype:"bool"}),une={kernelName:io,backendName:"webgl",kernelFunc:lne},pne="return float(isinf(x));",dne=Ke({opSnippet:pne,dtype:"bool"}),hne={kernelName:oo,backendName:"webgl",kernelFunc:dne},cne="return float(isnan(x));",fne=Ke({opSnippet:cne,dtype:"bool"}),mne={kernelName:lo,backendName:"webgl",kernelFunc:fne},gne="return float(a < b);",yne=`
return vec4(lessThan(a, b));
`,bne=lr({opSnippet:gne,packedOpSnippet:yne,cpuKernelImpl:Y9,dtype:"bool"}),xne={kernelName:gu,backendName:"webgl",kernelFunc:bne},vne="return float(a <= b);",wne=`
return vec4(lessThanEqual(a, b));
`,kne=lr({opSnippet:vne,packedOpSnippet:wne,cpuKernelImpl:Q9,dtype:"bool"}),Ine={kernelName:yu,backendName:"webgl",kernelFunc:kne};function Sne(e){let{backend:t,attrs:r}=e,{start:n,stop:a,num:s}=r,i=eY(n,a,s);return t.makeTensorInfo([i.length],"float32",i)}var Nne={kernelName:bu,backendName:"webgl",kernelFunc:Sne},_ne=fp+`
return x < 0.0 ? 0./0. : log(x);
`,Tne=`
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;
`,Cne=Ke({opSnippet:_ne,packedOpSnippet:Tne,cpuKernelImpl:tY}),Ene={kernelName:po,backendName:"webgl",kernelFunc:Cne},$ne=fp+`
return log(1.0 + x);
`,Ane=Ke({opSnippet:$ne}),Fne={kernelName:ho,backendName:"webgl",kernelFunc:Ane},Rne="return float(a >= 1.0 && b >= 1.0);",Dne=`
return vec4(
vec4(greaterThanEqual(a, vec4(1.0))) *
vec4(greaterThanEqual(b, vec4(1.0))));
`,Mne=lr({opSnippet:Rne,packedOpSnippet:Dne,dtype:"bool"}),One={kernelName:xu,backendName:"webgl",kernelFunc:Mne},Lne="return float(!(x >= 1.0));",zne=Ke({opSnippet:Lne}),Pne={kernelName:vu,backendName:"webgl",kernelFunc:zne},Bne="return float(a >= 1.0 || b >= 1.0);",Wne=`
return min(
vec4(greaterThanEqual(a, vec4(1.0))) +
vec4(greaterThanEqual(b, vec4(1.0))),
vec4(1.0));
`,Une=lr({opSnippet:Bne,packedOpSnippet:Wne,dtype:"bool"}),Vne={kernelName:wu,backendName:"webgl",kernelFunc:Une},Gne=class{constructor(e,t,r,n,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${r}) + float(${n}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int r = coords[1];
int c = coords[2];
int d = coords[3];
float x = getX(b, r, c, d);
float sum = 0.0;
for (int j = -${s}; j <= ${s}; j++) {
int idx = d + j;
if (idx >= 0 && idx <= ${i}) {
float z = getX(b, r, c, idx);
sum += z * z;
}
}
float val = x * ${o};
setOutput(val);
}
`}},Hne=class{constructor(e,t,r,n,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${r}) + float(${n}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords.x;
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 - ${s};
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 = - ${s}; j <= ${s}; j++) {
ivec2 idx = depth + j;
bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${i}));
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 * ${o};
setOutput(result);
}
`}},jne=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n,p=j().getBool("WEBGL_PACK_NORMALIZATION")?new Hne(a.shape,s,i,o,l):new Gne(a.shape,s,i,o,l);return r.runWebGLProgram(p,[a],a.dtype)},qne={kernelName:co,backendName:"webgl",kernelFunc:jne},Kne=class{constructor(e,t,r,n,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=r,this.alpha=n,this.beta=a,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 - ${t})));
int depthEnd = int(min(float(${this.depth}),
float(d + ${t} + 1)));
const int MIN_DEPTH_BEGIN = 0;
const int MAX_DEPTH_END = ${this.depth};
float norm = 0.0;
for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd) {
norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
}
else {
break;
}
}
norm = float(${n}) * norm + float(${r});
for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd){
float dyi = -2.0 * float(${n})
* float(${a})
* getInputImage(b, r, c, k) * getOutputImage(b, r, c, d)
/ norm;
if (k == d) {
dyi += pow(norm, -1.0 * ${a});
}
if (k == coords[3]) {
dyi *= getDy(b, r, c, d);
result += dyi;
}
}
else {
break;
}
}
}
setOutput(result);
}
`}},Xne=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:p,beta:u}=n,d=new Kne(a.shape,o,l,p,u);return r.runWebGLProgram(d,[a,s,i],a.dtype)},Zne={kernelName:ku,backendName:"webgl",kernelFunc:Xne};function Jne(e,t,r,n){let a=k.sizeFromShape(t),s=k.sizeFromShape(e.shape)/a,i=ue({inputs:{x:e},attrs:{shape:[s,a]},backend:n}),o=sl(i,e.dtype,"max",n),l=ue({inputs:{x:o},attrs:{shape:r},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}function XC(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=n,o=a.shape.length,l=k.parseAxisParam(s,a.shape),p=l,u=_.getAxesPermutation(p,o),d=u!=null,h=r.shouldExecuteOnCPU([a]),c=a;if(d){if(h){let b=r.texData.get(c.dataId).values,x=new Array(o);for(let N=0;N<x.length;N++)x[N]=a.shape[u[N]];let v=lw(b,a.shape,a.dtype,u,x);c=r.makeTensorInfo(x,a.dtype);let w=r.texData.get(c.dataId);w.values=v}else c=xm(a,u,r);p=_.getInnerMostAxes(p.length,o)}_.assertAxesAreInnerMostDims("max",p,o);let[f,m]=_.computeOutAndReduceShapes(c.shape,p),g=f;i&&(g=_.expandShapeToKeepDim(f,l));let y;if(h){let b=r.texData.get(c.dataId).values,x=rY(b,k.sizeFromShape(m),g,a.dtype);y=r.makeTensorInfo(g,a.dtype);let v=r.texData.get(y.dataId);v.values=x}else y=Jne(c,m,g,r);return d&&r.disposeIntermediateTensorInfo(c),y}var Yne={kernelName:fo,backendName:"webgl",kernelFunc:XC},Qne=pw+`
return max(a, b);
`,eae=`
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);
`+al+`
return result;
`,tae=lr({opSnippet:Qne,packedOpSnippet:eae,cpuKernelImpl:nY}),rae={kernelName:mo,backendName:"webgl",kernelFunc:tae};function nae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t;lp(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,p=1;k.assert(_.eitherStridesOrDilationsAreOne(i,p),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${p}'`);let u=_.computePool2DInfo(a.shape,s,i,p,o,l);if(u.filterWidth===1&&u.filterHeight===1&&k.arraysEqual(u.inShape,u.outShape))return Jr({inputs:{x:a},backend:r});let d=new od(u,"max",!1);return r.runWebGLProgram(d,[a],a.dtype)}var aae={kernelName:go,backendName:"webgl",kernelFunc:nae};function sae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:p}=n,u=[1,1,1],d=_.computePool3DInfo(a.shape,s,i,u,o,p,l),h=new hw(d,"max",!1);return r.runWebGLProgram(h,[a],a.dtype)}var iae={kernelName:Iu,backendName:"webgl",kernelFunc:sae},oae=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,r=e.strideWidth,n=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
const ivec2 pads = ivec2(${i}, ${o});
void main() {
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 < ${a};
wR += ${n}) {
float dyR = float(dyRCorner + wR) / ${t}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${s}; wC++) {
float dyC = float(dyCCorner + wC) / ${r}.0;
if (dyC < 0.0 || dyC >= ${e.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 * ${s} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
setOutput(dotProd);
}
`}},lae=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,r=e.strideHeight,n=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,p=e.effectiveFilterWidth,u=o-1-e.padInfo.front,d=l-1-e.padInfo.top,h=p-1-e.padInfo.left,c=o*l*p-1;this.userCode=`
const ivec3 pads = ivec3(${u}, ${d}, ${h});
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 < ${o};
wD += ${a}) {
float dyD = float(dyDCorner + wD) / ${t}.0;
if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
continue;
}
int idyD = int(dyD);
for (int wR = 0; wR < ${l};
wR += ${s}) {
float dyR = float(dyRCorner + wR) / ${r}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${p};
wC += ${i}) {
float dyC = float(dyCCorner + wC) / ${n}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(batch, idyD, idyR, idyC, ch);
int maxPosValue = ${c} -
int(getMaxPos(batch, idyD, idyR, idyC, ch));
// Get the current value, check it against the value from the
// position matrix.
int curPosValue =
wD * ${l} * ${p} +
wR * ${p} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
}
setOutput(dotProd);
}
`}};function uae(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:p,dimRoundingMode:u}=n,d=[1,1,1],h=_.computePool3DInfo(i.shape,o,l,d,p,u),c=new hw(h,"max",!0),f=r.runWebGLProgram(c,[i],i.dtype),m=new lae(h),g=r.runWebGLProgram(m,[a,f],i.dtype);return r.disposeIntermediateTensorInfo(f),g}var pae={kernelName:vd,backendName:"webgl",kernelFunc:uae};function dae(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,input:s,output:i}=t,o=s;lp([s,i],"maxPoolGrad");let{filterSize:l,strides:p,pad:u,dimRoundingMode:d}=n,h=_.computePool2DInfo(o.shape,l,p,1,u,d),c=!0,f=new od(h,"max",c),m=r.runWebGLProgram(f,[o],o.dtype),g=new oae(h),y=r.runWebGLProgram(g,[a,m],o.dtype);return r.disposeIntermediateTensorInfo(m),y}var hae={kernelName:xd,backendName:"webgl",kernelFunc:dae};function cae(e,t,r,n){let a=new od(r,"max",!1),s=n.runWebGLProgram(a,[e],"float32");a=new od(r,"max",!0,!0,t);let i=n.runWebGLProgram(a,[e],"float32");return[s,i]}var fae={kernelName:wd,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:r})=>{let{x:n}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=r;k.assert(n.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${n.shape.length}.`);let p=[1,1];k.assert(_.eitherStridesOrDilationsAreOne(s,p),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${p}'`);let u=_.computePool2DInfo(n.shape,a,s,p,i),[d,h]=cae(n,o,u,l);return[d,h]}};function mae(e,t,r,n){let a=k.sizeFromShape(t),s=k.sizeFromShape(e.shape)/a,i=ue({inputs:{x:e},attrs:{shape:[s,a]},backend:n}),o=sl(i,"float32","mean",n),l=ue({inputs:{x:o},attrs:{shape:r},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}var gae={kernelName:yo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:r})=>{let{x:n}=e,{keepDims:a,axis:s}=t,i=r,o=n.shape.length,l=k.parseAxisParam(s,n.shape),p=l,u=_.getAxesPermutation(p,o),d=u!=null,h=i.shouldExecuteOnCPU([n]),c=[],f=n;if(d){if(h){let x=i.texData.get(f.dataId).values,v=new Array(o);for(let T=0;T<v.length;T++)v[T]=n.shape[u[T]];let w=lw(x,n.shape,n.dtype,u,v);f=i.makeTensorInfo(v,n.dtype);let N=i.texData.get(f.dataId);N.values=w}else f=xm(n,u,i);c.push(f),p=_.getInnerMostAxes(p.length,o)}_.assertAxesAreInnerMostDims("sum",p,o);let[m,g]=_.computeOutAndReduceShapes(f.shape,p),y=m;a&&(y=_.expandShapeToKeepDim(m,l));let b=mae(f,g,y,i);for(let x of c)i.disposeIntermediateTensorInfo(x);return b}};function yae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n,o=a.shape.length,l=k.parseAxisParam(s,a.shape),p=l,u=_.getAxesPermutation(p,o),d=a;u!=null&&(d=xr({inputs:{x:a},backend:r,attrs:{perm:u}}),p=_.getInnerMostAxes(p.length,a.shape.length)),_.assertAxesAreInnerMostDims("min",p,o);let[h,c]=_.computeOutAndReduceShapes(d.shape,p),f=k.sizeFromShape(c),m=ue({inputs:{x:d},backend:r,attrs:{shape:[-1,f]}}),g=sl(m,m.dtype,"min",r),y;if(i){let b=_.expandShapeToKeepDim(h,l);y=ue({inputs:{x:g},backend:r,attrs:{shape:b}})}else y=ue({inputs:{x:g},backend:r,attrs:{shape:h}});return r.disposeIntermediateTensorInfo(m),r.disposeIntermediateTensorInfo(g),u!=null&&r.disposeIntermediateTensorInfo(d),y}var bae={kernelName:bo,backendName:"webgl",kernelFunc:yae},xae=pw+`
return min(a, b);
`,vae=`
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);
`+al+`
return result;
`,wae=lr({opSnippet:xae,packedOpSnippet:vae,cpuKernelImpl:aY}),kae={kernelName:xo,backendName:"webgl",kernelFunc:wae},Iae=class{constructor(e,t,r){this.variableNames=["x"],this.outputShape=t.map((p,u)=>p[0]+e[u]+p[1]);let n=e.length,a=pt(n),s=t.map(p=>p[0]).join(","),i=t.map((p,u)=>p[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n),l=r==="reflect"?0:1;if(n===1){this.userCode=`
int start = ${s};
int end = ${i};
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=`
${a} start = ${a}(${s});
${a} end = ${a}(${i});
void main() {
${a} outC = getOutputCoords();
for (int i = 0; i < ${n}; 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};
}
}
${a} coords = outC - start;
setOutput(getX(${o}));
}
`}},Sae=class{constructor(e,t,r){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((c,f)=>c[0]+e[f]+c[1]);let n=e.length,a=pt(n),s=t.map(c=>c[0]).join(","),i=t.map((c,f)=>c[0]+e[f]).join(","),o=gr("rc",n),l=gr("source",n),p=`${o[n-1]} < ${this.outputShape[n-1]}`,u=n===1?"source":`vec2(${l.slice(-2).join()})`,d=r==="reflect"?0:1,h="";if(n===1){let c=`
${a} source = rc;
if (source < start) {
source = start * 2 - source - ${d};
} else if (source >= end) {
source = (end - 1) * 2 - source + ${d};
}
source -= start;
`;h=`
${a} rc = outputLoc;
${c}
result[0] = getChannel(getX(${l.join()}), ${u});
${o[n-1]} += 1;
if(${p}) {
${c}
result[1] = getChannel(getX(${l.join()}), ${u});
}
`}else{let c=`
${a} source = rc;
${a} lt = ${a}(lessThan(source, start));
${a} gte = ${a}(greaterThanEqual(source, end));
${a} orig = 1 - (lt + gte);
source = orig * source +
lt * (start * 2 - source - ${d}) +
gte * ((end - 1) * 2 - source + ${d});
source -= start;
`;h=`
${a} rc = outputLoc;
${c}
result[0] = getChannel(getX(${l.join()}), ${u});
${o[n-1]} += 1;
if(${p}) {
${c}
result[1] = getChannel(getX(${l.join()}), ${u});
}
rc = outputLoc;
${o[n-2]} += 1;
if(${o[n-2]} < ${this.outputShape[n-2]}) {
${c}
result[2] = getChannel(getX(${l.join()}), ${u});
${o[n-1]} += 1;
if(${p}) {
${c}
result[3] = getChannel(getX(${l.join()}), ${u});
}
}
`}this.userCode=`
const ${a} start = ${a}(${s});
const ${a} end = ${a}(${i});
void main() {
${a} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${h}
setOutput(result);
}
`}},Nae=({inputs:e,backend:t,attrs:r})=>{let{x:n}=e,{paddings:a,mode:s}=r,i=j().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Sae(n.shape,a,s):new Iae(n.shape,a,s);return t.runWebGLProgram(i,[n],n.dtype)},_ae={kernelName:vo,backendName:"webgl",kernelFunc:Nae},Tae=`if (b == 0.0) return NAN;
return mod(a, b);`,Cae=`
vec4 result = mod(a, b);
bvec4 isNaN = equal(b, vec4(0.0));
`+al+`
return result;
`,Eae=lr({opSnippet:Tae,packedOpSnippet:Cae}),$ae={kernelName:wo,backendName:"webgl",kernelFunc:Eae},Aae=class{constructor(e,t,r){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,r],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
float r = random(seed);
float cdf = 0.0;
for (int i = 0; i < ${t-1}; i++) {
cdf += getProbs(batch, i);
if (r < cdf) {
setOutput(float(i));
return;
}
}
// If no other event happened, last event happened.
setOutput(float(${t-1}));
}
`}},Fae=`
if (a == b) {
return 1.0;
};
return a / b;`,Rae=`
// 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;
`,ZC=lr({opSnippet:Fae,packedOpSnippet:Rae,checkOutOfBounds:!0}),Dae={kernelName:Zi,backendName:"webgl",kernelFunc:ZC},O1="return a - b;",JC=lr({opSnippet:O1,packedOpSnippet:O1,supportsComplex:!0,cpuKernelImpl:NY}),Mae={kernelName:jo,backendName:"webgl",kernelFunc:JC};function YC(e){let{inputs:t,backend:r,attrs:n}=e,{logits:a}=t,{dim:s}=n,i=k.parseAxisParam([s],a.shape),o=XC({inputs:{x:a},backend:r,attrs:{reductionIndices:i,keepDims:!1}}),l=_.expandShapeToKeepDim(o.shape,i),p=ue({inputs:{x:o},backend:r,attrs:{shape:l}}),u=JC({inputs:{a,b:p},backend:r}),d=jC({inputs:{x:u},backend:r}),h=vm({inputs:{x:d},backend:r,attrs:{axis:i,keepDims:!1}}),c=ue({inputs:{x:h},backend:r,attrs:{shape:l}}),f=ZC({inputs:{a:d,b:c},backend:r});return r.disposeIntermediateTensorInfo(o),r.disposeIntermediateTensorInfo(p),r.disposeIntermediateTensorInfo(u),r.disposeIntermediateTensorInfo(d),r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(c),f}var Oae={kernelName:Go,backendName:"webgl",kernelFunc:YC};function Lae(e){let{inputs:t,backend:r,attrs:n}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=n,l=o?a:YC({inputs:{logits:a},backend:r,attrs:{dim:a.shape.length-1}}),p=l.shape[0],u=l.shape[1],d=new Aae(p,u,s),h=[[i]],c=r.runWebGLProgram(d,[l],"int32",h);return o||r.disposeIntermediateTensorInfo(l),c}var zae={kernelName:Su,backendName:"webgl",kernelFunc:Lae},Pae=Cn+`
return -x;
`,Bae=`
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 Wae(e){let{inputs:t,backend:r}=e,{x:n}=t;if(r.shouldExecuteOnCPU([n])){let s=r.texData.get(n.dataId),[i,o]=iY(s.values,n.shape,n.dtype);return r.makeTensorInfo(o,n.dtype,i)}let a;return j().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new ss(n.shape,Bae):a=new aa(n.shape,Pae),r.runWebGLProgram(a,[n],n.dtype)}var Uae={kernelName:Nu,backendName:"webgl",kernelFunc:Wae},Vae=ga.nonMaxSuppressionV3Impl;function Gae(e){_.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:r,attrs:n}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=n,p=r.readSync(a.dataId),u=r.readSync(s.dataId),{selectedIndices:d}=Vae(p,u,i,o,l);return r.makeTensorInfo([d.length],"int32",new Int32Array(d))}var Hae={kernelName:Tu,backendName:"webgl",kernelFunc:Gae},jae=ga.nonMaxSuppressionV4Impl;function qae(e){_.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:r,attrs:n}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:p}=n,u=r.readSync(a.dataId),d=r.readSync(s.dataId),{selectedIndices:h,validOutputs:c}=jae(u,d,i,o,l,p);return[r.makeTensorInfo([h.length],"int32",new Int32Array(h)),r.makeTensorInfo([],"int32",new Int32Array([c]))]}var Kae={kernelName:Cu,backendName:"webgl",kernelFunc:qae},Xae=ga.nonMaxSuppressionV5Impl;function Zae(e){_.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:r,attrs:n}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:p}=n,u=r.readSync(a.dataId),d=r.readSync(s.dataId),h=i,c=o,f=l,m=p,{selectedIndices:g,selectedScores:y}=Xae(u,d,h,c,f,m);return[r.makeTensorInfo([g.length],"int32",new Int32Array(g)),r.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var Jae={kernelName:Eu,backendName:"webgl",kernelFunc:Zae},Yae=class{constructor(e,t,r,n){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int index = round(getIndices(coords.x));
setOutput(mix(float(${n}), float(${r}),
float(index == coords.y)));
}
`}},Qae=e=>{let{inputs:t,backend:r,attrs:n}=e,{indices:a}=t,{dtype:s,depth:i,onValue:o,offValue:l}=n,p=k.sizeFromShape(a.shape),u=new Yae(p,i,o,l),d=ue({inputs:{x:a},backend:r,attrs:{shape:[p]}}),h=r.runWebGLProgram(u,[d],s);r.disposeIntermediateTensorInfo(d);let c=[...a.shape,i],f=ue({inputs:{x:h},backend:r,attrs:{shape:c}});return r.disposeIntermediateTensorInfo(h),f},ese={kernelName:Io,backendName:"webgl",kernelFunc:Qae};function Pc(e){let{inputs:t,backend:r}=e,{x:n}=t;if(n.dtype==="complex64"){let a=ph({inputs:{input:n},backend:r}),s=Pc({inputs:{x:a},backend:r}),i=wm({inputs:{input:n},backend:r}),o=Pc({inputs:{x:i},backend:r}),l=Ls({inputs:{real:s,imag:o},backend:r});return r.disposeIntermediateTensorInfo(a),r.disposeIntermediateTensorInfo(s),r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}else return dh({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:r})}var tse={kernelName:Ku,backendName:"webgl",kernelFunc:Pc};function QC(e){let{inputs:t,backend:r}=e,{x:n}=t;if(n.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(n.dtype==="complex64"){let a=ph({inputs:{input:n},backend:r}),s=QC({inputs:{x:a},backend:r}),i=wm({inputs:{input:n},backend:r}),o=Pc({inputs:{x:i},backend:r}),l=Ls({inputs:{real:s,imag:o},backend:r});return r.disposeIntermediateTensorInfo(a),r.disposeIntermediateTensorInfo(s),r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}else return dh({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:r})}var rse={kernelName:$u,backendName:"webgl",kernelFunc:QC};function nse(e){let{inputs:t,backend:r,attrs:n}=e,{axis:a}=n;if(t.length===1)return Qg({inputs:{input:t[0]},backend:r,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(u=>{k.assertShapesMatch(s,u.shape,"All tensors passed to stack must have matching shapes"),k.assert(i===u.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(u=>{let d=Qg({inputs:{input:u},backend:r,attrs:{dim:a}});return o.push(d),d}),p=zC({inputs:l,backend:r,attrs:{axis:a}});return o.forEach(u=>r.disposeIntermediateTensorInfo(u)),p}var ase={kernelName:Au,backendName:"webgl",kernelFunc:nse},sse=class{constructor(e,t,r){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((l,p)=>l[0]+e[p]+l[1]);let n=e.length,a=pt(n),s=t.map(l=>l[0]).join(","),i=t.map((l,p)=>l[0]+e[p]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n);if(n===1){this.userCode=`
int start = ${s};
int end = ${i};
void main() {
int outC = getOutputCoords();
if (outC < start || outC >= end) {
setOutput(value);
} else {
setOutput(getX(outC - start));
}
}
`;return}this.userCode=`
${a} start = ${a}(${s});
${a} end = ${a}(${i});
void main() {
${a} outC = getOutputCoords();
if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
setOutput(value);
} else {
${a} coords = outC - start;
setOutput(getX(${o}));
}
}
`}},ise=class{constructor(e,t,r){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let n=e.length,a=pt(n),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=gr("rc",n),l=gr("source",n),p=`${o[n-1]} < ${this.outputShape[n-1]}`,u=n===1?"source":`vec2(${l.slice(-2).join()})`,d=[`${a} rc = outputLoc;`,`${o[n-1]} += 1;
if(${p}) {
`,n===1?"":`}
rc = outputLoc;
${o[n-2]} += 1;
if(${o[n-2]} < ${this.outputShape[n-2]}) {`,n===1?"":` ${o[n-1]} += 1;
if(${p}) {`],h=n===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",c="";for(let f=0,m=n===1?2:4;f<m;f++)c+=`
${d[f]}
if (${h}) {
result[${f}] = float(value);
} else {
${a} source = rc - start;
result[${f}] = getChannel(getX(${l.join()}), ${u});
}
`;c+=n===1?"} ":"}}",this.userCode=`
const ${a} start = ${a}(${s});
const ${a} end = ${a}(${i});
void main() {
${a} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${c}
setOutput(result);
}
`}},eE=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{paddings:s,constantValue:i}=n;if(k.sizeFromShape(a.shape)===0){let p=s.map((u,d)=>u[0]+a.shape[d]+u[1]);return dh({backend:r,attrs:{shape:p,value:i,dtype:a.dtype}})}let o=j().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new ise(a.shape,s,i):new sse(a.shape,s,i),l=[[i]];return r.runWebGLProgram(o,[a],a.dtype,l)},ose={kernelName:So,backendName:"webgl",kernelFunc:eE},lse=`
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);
`,use=`
// 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);
`+al+`
return result;
`,pse=lr({opSnippet:lse,packedOpSnippet:use}),dse={kernelName:No,backendName:"webgl",kernelFunc:pse};function hse(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n,o=a.shape.length,l=[],p=k.parseAxisParam(s,a.shape),u=p,d=_.getAxesPermutation(u,o),h=a;d!=null&&(h=xr({inputs:{x:a},backend:r,attrs:{perm:d}}),u=_.getInnerMostAxes(u.length,o),l.push(h)),_.assertAxesAreInnerMostDims("prod",u,o);let c;if(r.shouldExecuteOnCPU([h])){let f=r.texData.get(h.dataId).values,{outVals:m,outShape:g,outDtype:y}=lY(h.shape,h.dtype,f,u);c=r.makeTensorInfo(g,y,m)}else{let[f,m]=_.computeOutAndReduceShapes(h.shape,u),g=k.sizeFromShape(m),y=ue({inputs:{x:h},backend:r,attrs:{shape:[-1,g]}}),b=cf(a.dtype),x=sl(y,b,"prod",r);c=ue({inputs:{x},backend:r,attrs:{shape:f}}),l.push(y),l.push(x)}if(i){l.push(c);let f=_.expandShapeToKeepDim(c.shape,p);c=ue({inputs:{x:c},backend:r,attrs:{shape:f}})}return l.forEach(f=>r.disposeIntermediateTensorInfo(f)),c}var cse={kernelName:To,backendName:"webgl",kernelFunc:hse};function fse(e){let{inputs:t,backend:r,attrs:n}=e,{paramsNestedSplits:a,paramsDenseValues:s,indices:i}=t,{outputRaggedRank:o}=n,l=a.map(y=>r.readSync(y.dataId)),p=a.map(y=>y.shape),u=r.readSync(s.dataId),d=r.readSync(i.dataId),[h,c,f]=uY(l,p,u,s.shape,s.dtype,d,i.shape,o),m=h.map(y=>r.makeTensorInfo([y.length],"int32",y)),g=r.makeTensorInfo(f,s.dtype,c);return m.concat([g])}var mse={kernelName:lf,backendName:"webgl",kernelFunc:fse};function gse(e){let{inputs:t,backend:r}=e,{starts:n,limits:a,deltas:s}=t,i=r.readSync(n.dataId),o=r.readSync(a.dataId),l=r.readSync(s.dataId),[p,u]=pY(i,n.shape,n.dtype,o,a.shape,l,s.shape),d=r.makeTensorInfo([p.length],"int32",p),h=r.makeTensorInfo([u.length],n.dtype,u);return[d,h]}var yse={kernelName:uf,backendName:"webgl",kernelFunc:gse};function bse(e){let{inputs:t,backend:r,attrs:n}=e,{shape:a,values:s,defaultValue:i,rowPartitionTensors:o}=t,{rowPartitionTypes:l}=n,p=r.readSync(a.dataId),u=r.readSync(s.dataId),d=r.readSync(i.dataId),h=o.map(g=>r.readSync(g.dataId)),c=o.map(g=>g.shape),[f,m]=dY(p,a.shape,u,s.shape,s.dtype,d,i.shape,h,c,l);return r.makeTensorInfo(f,s.dtype,m)}var xse={kernelName:pf,backendName:"webgl",kernelFunc:bse},tE=e=>{let{backend:t,attrs:r}=e,{start:n,stop:a,step:s,dtype:i}=r,o=hY(n,a,s,i);return t.makeTensorInfo([o.length],i,o)},vse={kernelName:kd,backendName:"webgl",kernelFunc:tE},wse="return 1.0 / x;",kse=Ke({opSnippet:wse}),Ise={kernelName:Co,backendName:"webgl",kernelFunc:kse},Sse=Cn+`
return (x < 0.0) ? 0.0 : x;
`,Nse=`
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;
`,_se=Ke({opSnippet:Sse,packedOpSnippet:Nse}),Tse={kernelName:Eo,backendName:"webgl",kernelFunc:_se},Cse=Cn+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,Ese=`
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;
`,$se=Ke({opSnippet:Cse,packedOpSnippet:Ese}),Ase={kernelName:Fo,backendName:"webgl",kernelFunc:$se},Fse=class{constructor(e,t,r,n,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,r,l];let p=[n&&t>1?i-1:i,n&&r>1?o-1:o],u=[n&&t>1?t-1:t,n&&r>1?r-1:r],d;a?d="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${p[0]/u[0]},
${p[1]/u[1]});
const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 yRC = coords.yz;
// Fractional source index.
vec2 sourceFracIndexRC = ${d};
// 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);
}
`}},Rse=class{constructor(e,t,r,n,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,r,l];let p=[n&&t>1?i-1:i,n&&r>1?o-1:o],u=[n&&t>1?t-1:t,n&&r>1?r-1:r],d;a?d="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":d="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${p[0]/u[0]},
${p[1]/u[1]},
${p[1]/u[1]});
const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
${o}.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 = ${d};
// 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 < ${r-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 Dse(e){let{inputs:t,backend:r,attrs:n}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,p]=o,u=j().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Rse(a.shape,l,p,s,i):new Fse(a.shape,l,p,s,i);return r.runWebGLProgram(u,[a],"float32")}var Mse={kernelName:Ao,backendName:"webgl",kernelFunc:Dse},Ose=class{constructor(e,t,r){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,a]=t,[,s,i]=e,o=[r&&s>1?n-1:n,r&&i>1?a-1:a],l=[r&&s>1?s-1:s,r&&i>1?i-1:i],p=o[0]/l[0],u=o[1]/l[1],d=1/p,h=1/u,c=Math.ceil(d)*2+2,f=Math.ceil(h)*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(${p});
const float widthScale = float(${u});
const float invHeightScale = float(${d});
const float invWidthScale = float(${h});
const int winHeight = int(${c});
const int winWidth = int(${f});
// 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 >= ${s}) {
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 >= ${i}) {
continue;
}
float dxR = float(dyR) * heightScale;
int topDxRIndex = int(floor(dxR));
int bottomDxRIndex = int(min(ceil(dxR), ${n-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), ${a-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 Lse(e){let{inputs:t,backend:r,attrs:n}=e,{images:a,dy:s}=t,{alignCorners:i}=n,o=new Ose(s.shape,a.shape,i);return r.runWebGLProgram(o,[s],s.dtype)}var zse={kernelName:Du,backendName:"webgl",kernelFunc:Lse},Pse=class{constructor(e,t,r,n,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,r,l];let p=[n&&t>1?i-1:i,n&&r>1?o-1:o],u=[n&&t>1?t-1:t,n&&r>1?r-1:r],d=n?"0.5":"0.0",h;a?h="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${p[0]/u[0]},
${p[1]/u[1]});
const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 yRC = coords.yz;
// Fractional source index.
vec2 sourceFracIndexRC = ${h};
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestRC = ivec2(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${d})));
float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);
setOutput(newValue);
}
`}},Bse=class{constructor(e,t,r,n,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,r,l];let p=[n&&t>1?i-1:i,n&&r>1?o-1:o],u=[n&&t>1?t-1:t,n&&r>1?r-1:r],d=n?"0.5":"0.0",h;a?h="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${p[0]/u[0]},
${p[1]/u[1]},
${p[1]/u[1]});
const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
${o}.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 = ${h};
// Compute the coordinators of nearest neighbor point.
ivec3 sourceNearestRC = ivec3(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${d})));
// Should we calculate next column and row elements in 2x2 packed cell.
bool hasNextCol = d < ${l-1};
bool hasNextRow = coords.z < ${r-1};
vec4 newValue = vec4(
getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);
setOutput(newValue);
}
`}};function Wse(e){let{inputs:t,backend:r,attrs:n}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,p]=o,u=j().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Bse(a.shape,l,p,s,i):new Pse(a.shape,l,p,s,i);return r.runWebGLProgram(u,[a],a.dtype)}var Use={kernelName:$o,backendName:"webgl",kernelFunc:Wse},Vse=class{constructor(e,t,r){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,a]=t,[,s,i]=e,o=[r&&s>1?n-1:n,r&&i>1?a-1:a],l=[r&&s>1?s-1:s,r&&i>1?i-1:i],p=o[0]/l[0],u=o[1]/l[1],d=1/p,h=1/u,c=Math.ceil(d)*2+2,f=Math.ceil(h)*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(${p});
const float widthScale = float(${u});
const float invHeightScale = float(${d});
const float invWidthScale = float(${h});
const int winHeight = int(${c});
const int winWidth = int(${f});
// 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 >= ${s}) {
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 >= ${i}) {
continue;
}
float sourceFracRow =
float(${o[0]}) *
(float(dyR) / float(${l[0]}));
float sourceFracCol =
float(${o[1]}) *
(float(dyC) / float(${l[1]}));
int sourceNearestRow = int(min(
float(int(${n}) - 1),
${r} ? float(round(sourceFracRow)) :
float(floor(sourceFracRow))));
int sourceNearestCol = int(min(
float(int(${a}) - 1),
${r} ? float(round(sourceFracCol)) :
float(floor(sourceFracCol))));
if (r == sourceNearestRow && c == sourceNearestCol) {
accumulator += getDy(b, dyR, dyC, d);
}
}
}
// End loop over dy
setOutput(accumulator);
}
`}};function Gse(e){let{inputs:t,backend:r,attrs:n}=e,{images:a,dy:s}=t,{alignCorners:i}=n,o=new Vse(s.shape,a.shape,i);return r.runWebGLProgram(o,[s],s.dtype)}var Hse={kernelName:Ru,backendName:"webgl",kernelFunc:Gse},jse=class{constructor(e,t){this.variableNames=["x"];let r=e.length;if(r>4)throw new Error(`WebGL backend: Reverse of rank-${r} tensor is not yet supported`);if(this.outputShape=e,r===1){this.userCode=`
void main() {
int coord = getOutputCoords();
setOutput(getX(${e[0]} - coord - 1));
}
`;return}let n=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,a=e.map((i,o)=>n(o)).join(","),s=pt(r);this.userCode=`
void main() {
${s} coords = getOutputCoords();
setOutput(getX(${a}));
}
`}},qse=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let r=e.length;if(r>4)throw new Error(`WebGL backend: Reverse of rank-${r} tensor is not yet supported`);this.outputShape=e;let n=gr("rc",r),a=`${n[r-1]} + 1 < ${this.outputShape[r-1]}`,s=`${n[r-2]} + 1 < ${this.outputShape[r-2]}`,i=pt(r);r===1?this.userCode=`
void main(){
int rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = getChannel(getX(${e[0]} - rc - 1),
${e[0]} - rc - 1);
if(${a}){
result.g = getChannel(getX(${e[0]} - (rc + 1) - 1),
${e[0]} - (rc + 1) - 1);
}
setOutput(result);
}
`:this.userCode=`
void main() {
${i} rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = ${o(n.slice())};
if(${a}){
result.g = ${l(n.slice())};
}
if(${s}) {
result.b = ${p(n.slice())};
if(${a}) {
result.a = ${u(n.slice())};
}
}
setOutput(result);
}
`;function o(c){return d(c)}function l(c){return c[r-1]="("+c[r-1]+" + 1)",d(c)}function p(c){return c[r-2]="("+c[r-2]+" + 1)",d(c)}function u(c){return c[r-1]="("+c[r-1]+" + 1)",c[r-2]="("+c[r-2]+" + 1)",d(c)}function d(c){let f=e.map((y,b)=>h(b,c)),m=f.join(","),g=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${g}))`}function h(c,f){return t.indexOf(c)!==-1&&e[c]!==1?`${e[c]} - ${f[c]} - 1`:`${f[c]}`}}};function Kse(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{dims:s}=n,i=a.shape.length,o=k.parseAxisParam(s,a.shape);if(i===0)return Jr({inputs:{x:a},backend:r});let l=j().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new qse(a.shape,o):new jse(a.shape,o);return r.runWebGLProgram(l,[a],a.dtype)}var Xse={kernelName:Ro,backendName:"webgl",kernelFunc:Kse},Zse=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let r=e[1],n=e[2];this.outputShape=e;let a="";typeof t=="number"?a=`float outputValue = ${t.toFixed(2)};`:a=`
vec3 fill = vec3(${t.join(",")});
float outputValue = fill[coords[3]];`,this.userCode=`
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]));
${a}
if(coordX >= 0 && coordX < ${n} && coordY >= 0 && coordY < ${r}) {
outputValue = getImage(coords[0], coordY, coordX, coords[3]);
}
setOutput(outputValue);
}
`}},Jse={kernelName:Xu,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:r})=>{let{image:n}=e,{radians:a,fillValue:s,center:i}=t,o=r,l=new Zse(n.shape,s),[p,u]=_.getImageCenter(i,n.shape[1],n.shape[2]),d=[[p,u,Math.sin(a),Math.cos(a)]];return o.runWebGLProgram(l,[n],n.dtype,d)}},Yse=`
// OpenGL ES does not support round function.
// The algorithm is based on banker's rounding.
float base = floor(x);
if ((x - base) < 0.5) {
return floor(x);
} else if ((x - base) > 0.5) {
return ceil(x);
} else {
if (mod(base, 2.0) == 0.0) {
return base;
} else {
return base + 1.0;
}
}
`,Qse=Ke({opSnippet:Yse}),eie={kernelName:Do,backendName:"webgl",kernelFunc:Qse},tie="return inversesqrt(x);",rie=Ke({opSnippet:tie,cpuKernelImpl:cY}),nie={kernelName:Mo,backendName:"webgl",kernelFunc:rie},cw=class{constructor(e,t,r,n,a,s,i=!0,o=!1){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let l=pt(a.length),p=pt(s.length),u="";r===1?u="i":r===2&&(u="i, j");let d=`getIndices(${u})`,h="";n===1?h="i":n===2&&(h="i, coords[1]");let c=`getUpdates(${h})`,f="";o&&(f="coords[0], coords[1]");let m=`getDefaultValue(${f})`,g=t>1?"strides[j]":"strides";this.userCode=`
${l} strides = ${l}(${a});
void main() {
${p} coords = getOutputCoords();
float sum = 0.0;
bool found = false;
for (int i = 0; i < ${e}; i++) {
int flattenedIndex = 0;
for (int j = 0; j < ${t}; j++) {
int index = round(${d});
flattenedIndex += index * ${g};
}
if (flattenedIndex == coords[0]) {
sum += ${c};
found = true;
}
}
setOutput(mix(${m}, sum, float(found)));
}
`}},aie=class{constructor(e,t,r,n,a,s,i=!0,o=!1){this.variableNames=["updates","indices","defaultValue"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=s;let l=pt(a.length),p=pt(s.length),u="";r===1?u="i":r===2&&(u="i, j");let d=`getIndices(${u})`,h="";n===1?h="i":n===2&&(h="i, coords[1]");let c=`getUpdates(${h})`,f="";o&&(f="coords[0], coords[1]");let m=`getDefaultValue(${f})`,g=t>1?"strides[j]":"strides",y=t>1?"strides[j + 1]":"strides";this.userCode=`
${l} strides = ${l}(${a});
void main() {
${p} coords = getOutputCoords();
vec4 sum = vec4(0.);
vec4 found = vec4(0.);
for (int i = 0; i < ${e}; i+=2) {
ivec2 flattenedIndex = ivec2(0);
for (int j = 0; j < ${t}; j+=2) {
ivec4 index = round(${d});
flattenedIndex += index.xz * ${g};
if (j + 1 < ${t}) {
flattenedIndex += index.yw * ${y};
}
}
if (flattenedIndex[0] == coords[0] || flattenedIndex[1] == coords[0] ||
flattenedIndex[0] == coords[0] + 1 || flattenedIndex[1] == coords[0] + 1) {
vec4 updVals = ${c};
if (flattenedIndex[0] == coords[0]) {
sum.xy += updVals.xy;
found.xy = vec2(1.);
} else if (flattenedIndex[0] == coords[0] + 1) {
sum.zw += updVals.xy;
found.zw = vec2(1.);
}
if (flattenedIndex[1] == coords[0]) {
sum.xy += updVals.zw;
found.xy = vec2(1.);
} else if (flattenedIndex[1] == coords[0] + 1) {
sum.zw += updVals.zw;
found.zw = vec2(1.);
}
}
}
setOutput(mix(${m}, sum, found));
}
`}};function sie(e){let{inputs:t,backend:r,attrs:n}=e,{indices:a,updates:s}=t,{shape:i}=n,{sliceRank:o,numUpdates:l,sliceSize:p,strides:u,outputSize:d}=_.calculateShapes(s,a,i),h=[d/p,p];if(d===0)return r.makeTensorInfo(i,a.dtype);let c=ue({inputs:{x:a},backend:r,attrs:{shape:[l,o]}}),f=ue({inputs:{x:s},backend:r,attrs:{shape:[l,p]}}),m=r.makeTensorInfo([],"float32",new Float32Array([0])),g;j().getBool("WEBGL_PACK")?g=new aie(l,o,c.shape.length,f.shape.length,u,h):g=new cw(l,o,c.shape.length,f.shape.length,u,h);let y=r.runWebGLProgram(g,[f,c,m],f.dtype),b=ue({inputs:{x:y},backend:r,attrs:{shape:i}});return r.disposeIntermediateTensorInfo(c),r.disposeIntermediateTensorInfo(f),r.disposeIntermediateTensorInfo(y),r.disposeIntermediateTensorInfo(m),b}var iie={kernelName:Mu,backendName:"webgl",kernelFunc:sie},oie=class{constructor(e,t,r,n){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[e,r];let a="while (left < right) {",s=`for (int i = 0; i < ${Math.ceil(Math.log2(t+1))}; ++i) { if (left >= right) break;`,i=j().getNumber("WEBGL_VERSION")===2?a:s,o=n==="left"?"<":"<=";this.userCode=`
int findBound(int batch, float value) {
int left = 0;
int right = numInputs;
int mid;
${i}
mid = (left + right) / 2;
if (getSortedSequence(batch, mid) ${o} 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 lie(e){let{inputs:t,backend:r,attrs:n}=e,{sortedSequence:a,values:s}=t,{side:i}=n,o=new oie(a.shape[0],a.shape[1],s.shape[1],i),l=[[a.shape[1]]];return r.runWebGLProgram(o,[a,s],"int32",l)}var uie={kernelName:Lu,backendName:"webgl",kernelFunc:lie},pie=class{constructor(e,t,r){this.variableNames=["c","a","b"],this.outputShape=t;let n,a;if(r>4)throw Error(`Where for rank ${r} is not yet supported`);if(r===1)a="resRC",n="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let p=0;p<t.length;p++)l.push(`${i[p]}`),p<e&&o.push(`${i[p]}`);n=o.join(),a=l.join()}let s=pt(r);this.userCode=`
void main() {
${s} resRC = getOutputCoords();
float cVal = getC(${n});
if (cVal >= 1.0) {
setOutput(getA(${a}));
} else {
setOutput(getB(${a}));
}
}
`}};function die(e){let{inputs:t,backend:r}=e,{condition:n,t:a,e:s}=t,i=new pie(n.shape.length,a.shape,a.shape.length);return r.runWebGLProgram(i,[n,a,s],cn(a.dtype,s.dtype))}var hie={kernelName:zu,backendName:"webgl",kernelFunc:die},cie=`
// Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
// see: https://arxiv.org/abs/1706.02515
float scaleAlpha = ${_.SELU_SCALEALPHA};
float scale = ${_.SELU_SCALE};
return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,fie=Ke({opSnippet:cie}),mie={kernelName:Oo,backendName:"webgl",kernelFunc:fie},gie=fp+`
return 1.0 / (1.0 + exp(-1.0 * x));
`,yie=`
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;
`,bie=Ke({opSnippet:gie,packedOpSnippet:yie,cpuKernelImpl:mY}),xie={kernelName:Bo,backendName:"webgl",kernelFunc:bie},vie=`
if (isnan(x)) { return 0.0; }
return sign(x);
`,wie=Ke({opSnippet:vie}),kie={kernelName:Po,backendName:"webgl",kernelFunc:wie},Iie=fp+`
return sin(x);
`,Sie=`
vec4 result = sin(x);
bvec4 isNaN = isnan(x);
${al}
return result;
`,Nie=Ke({opSnippet:Iie,packedOpSnippet:Sie}),_ie={kernelName:Lo,backendName:"webgl",kernelFunc:Nie},Tie=`
float e2x = exp(x);
return (e2x - 1.0 / e2x) / 2.0;
`,Cie=Ke({opSnippet:Tie}),Eie={kernelName:zo,backendName:"webgl",kernelFunc:Cie},$ie=`
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;
`,Aie=Ke({opSnippet:$ie}),Fie={kernelName:Wo,backendName:"webgl",kernelFunc:Aie},Rie=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockShape:s,paddings:i}=n;k.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,b)=>y*b),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<a.shape.length;++y)l.push([0,0]);let p=[],u=eE({inputs:{x:a},backend:r,attrs:{paddings:l,constantValue:0}}),d=_.getReshaped(u.shape,s,o,!1),h=_.getPermuted(d.length,s.length,!1),c=_.getReshapedPermuted(u.shape,s,o,!1),f=ue({inputs:{x:u},backend:r,attrs:{shape:d}}),m=xr({inputs:{x:f},backend:r,attrs:{perm:h}}),g=ue({inputs:{x:m},backend:r,attrs:{shape:c}});return p.push(u),p.push(f),p.push(m),p.forEach(y=>r.disposeIntermediateTensorInfo(y)),g},Die={kernelName:Bu,backendName:"webgl",kernelFunc:Rie};function Mie(e){let{inputs:t,backend:r}=e,{indices:n,values:a,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(a.shape.length!==1)throw new Error(`Values must be a vector, saw:
${a.shape}`);if(i.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
${i.shape}`);let o=r.readSync(n.dataId),l=r.readSync(a.dataId),p=r.readSync(s.dataId),u=r.readSync(i.dataId)[0],[d,h,c,f,m]=yY(o,n.shape,n.dtype,l,a.dtype,p,u);return[r.makeTensorInfo(h,n.dtype,d),r.makeTensorInfo([h[0]],a.dtype,c),r.makeTensorInfo([f.length],"bool",new Uint8Array(f.map(g=>Number(g)))),r.makeTensorInfo([m.length],n.dtype,new Int32Array(m))]}var Oie={kernelName:Id,backendName:"webgl",kernelFunc:Mie};function Lie(e){let{inputs:t,backend:r}=e,{inputIndices:n,inputShape:a,newShape:s}=t;if(n.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${n.shape}`);if(a.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${a.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let i=Array.from(r.readSync(a.dataId)),o=r.readSync(n.dataId),l=Array.from(r.readSync(s.dataId)),[p,u,d]=bY(o,n.shape,n.dtype,i,l);return[r.makeTensorInfo(u,n.dtype,p),r.makeTensorInfo([d.length],s.dtype,new Int32Array(d))]}var zie={kernelName:Uu,backendName:"webgl",kernelFunc:Lie};function Pie(e){let{inputs:t,backend:r}=e,{data:n,indices:a,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(a.shape.length!==1)throw new Error(`Indices should be a vector but received shape
${a.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${s.shape}`);let i=r.readSync(n.dataId),o=r.readSync(a.dataId),l=r.readSync(s.dataId),[p,u]=IC(i,n.shape,n.dtype,o,l,!0);return r.makeTensorInfo(u,n.dtype,p)}var Bie={kernelName:Sd,backendName:"webgl",kernelFunc:Pie};function Wie(e){let{inputs:t,backend:r}=e,{data:n,indices:a,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(a.shape.length!==1)throw new Error(`Indices should be a vector but received shape
${a.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${s.shape}`);let i=r.readSync(n.dataId),o=r.readSync(a.dataId),l=r.readSync(s.dataId),[p,u]=IC(i,n.shape,n.dtype,o,l);return r.makeTensorInfo(u,n.dtype,p)}var Uie={kernelName:Nd,backendName:"webgl",kernelFunc:Wie};function Vie(e){let{inputs:t,backend:r,attrs:n}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=n,{sliceRank:l,numUpdates:p,sliceSize:u,strides:d,outputSize:h}=_.calculateShapes(s,a,o),c=!1;if(s.dtype==="string"){let y=r.bufferSync(a),b=r.bufferSync(s),x=k.decodeString(r.readSync(i.dataId)[0]),v=fY(y,b,o,h,u,p,l,d,x,c);return r.makeTensorInfo(o,v.dtype,v.values)}let f=new cw(p,l,a.shape.length,s.shape.length,d,[h,1],c),m=r.runWebGLProgram(f,[s,a,i],s.dtype),g=ue({inputs:{x:m},backend:r,attrs:{shape:o}});return r.disposeIntermediateTensorInfo(m),g}var Gie={kernelName:Vu,backendName:"webgl",kernelFunc:Vie};function Hie(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=n,o=k.parseAxisParam(i,a.shape)[0],l=_.prepareSplitSize(a,s,o),p=a.shape.length,u=new Array(p).fill(0),d=a.shape.slice();return l.map(h=>{let c=[...d];c[o]=h;let f=mp({inputs:{x:a},backend:r,attrs:{begin:u,size:c}});return u[o]+=h,f})}var jie={kernelName:Wu,backendName:"webgl",kernelFunc:Hie},L1="return sqrt(x);",qie=Ke({opSnippet:L1,packedOpSnippet:L1,cpuKernelImpl:xY}),Kie={kernelName:Uo,backendName:"webgl",kernelFunc:qie},Xie="return x * x;",Zie=Ke({opSnippet:Xie}),Jie={kernelName:_d,backendName:"webgl",kernelFunc:Zie},z1="return (a - b) * (a - b);",Yie=lr({opSnippet:z1,packedOpSnippet:z1}),Qie={kernelName:Ho,backendName:"webgl",kernelFunc:Yie};function eoe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");let s=r.readSync(a.dataId),i=_.fromUint8ToStringArray(s),o=vY(i,"string",n);return r.makeTensorInfo(a.shape,"string",o)}var toe={kernelName:Td,backendName:"webgl",kernelFunc:eoe};function roe({inputs:e,attrs:t,backend:r}){let{x:n}=e,a=Cn+`
return x > 0.0 ? 1.0 : float(${t.alpha});
`,s=new aa(n.shape,a);return r.runWebGLProgram(s,[n],n.dtype)}var noe={kernelName:$s,backendName:"webgl",kernelFunc:roe},aoe=class{constructor(e,t,r){this.variableNames=["x"],this.outputShape=r;let n=r.length,a=pt(r.length),s=pt(r.length),i="";if(n===1)i="coords * strides + begin";else{let o=0;i=r.map((l,p)=>(o++,r.length===1?`coords * strides[${p}] + begin[${p}]`:`coords[${o-1}] * strides[${p}] + begin[${p}]`)).join(",")}this.userCode=`
${a} begin = ${a}(${e});
${a} strides = ${a}(${t});
void main() {
${s} coords = getOutputCoords();
setOutput(getX(${i}));
}
`}};function soe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:p,ellipsisMask:u,newAxisMask:d,shrinkAxisMask:h}=n,{finalShapeSparse:c,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:b,end:x,strides:v}=Wt.sliceInfo(a.shape,s,i,o,l,p,u,d,h),w;if(m)w=ue({inputs:{x:a},backend:r,attrs:{shape:f}});else if(g||y){k.assert(a.shape.length>=1,()=>`Input must have rank at least 1, got: ${a.shape.length}`);let T=Wt.computeOutShape(b,x,v),E=mp({inputs:{x:a},backend:r,attrs:{begin:b,size:T}});w=ue({inputs:{x:E},backend:r,attrs:{shape:f}}),r.disposeIntermediateTensorInfo(E)}else if(r.shouldExecuteOnCPU([a])){let T=r.readSync(a.dataId),E=Le(a.shape,a.dtype,T),$=wY(c,E,v,b);w=r.makeTensorInfo(f,a.dtype,$.values)}else{let T=new aoe(b,v,c);w=r.runWebGLProgram(T,[a],a.dtype)}let N=ue({inputs:{x:w},backend:r,attrs:{shape:f}});return r.disposeIntermediateTensorInfo(w),N}var ioe={kernelName:Gu,backendName:"webgl",kernelFunc:soe};function ooe(e){let{inputs:t,backend:r,attrs:n}=e,{separator:a,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:p}=n,{data:u,dataSplits:d}=t,h=r.readSync(u.dataId),c=r.readSync(d.dataId),[f,m]=kY(h,c,a,s,i,o,l,p);return[r.makeTensorInfo([f.length],"string",f),r.makeTensorInfo(d.shape,"int32",m)]}var loe={kernelName:Cd,backendName:"webgl",kernelFunc:ooe};function uoe(e){let{inputs:t,backend:r,attrs:n}=e,{skipEmpty:a}=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: ${i.shape}`);let o=r.readSync(s.dataId),l=r.readSync(i.dataId)[0],[p,u,d]=IY(o,l,a),h=u.length;return[r.makeTensorInfo([h,2],"int32",p),r.makeTensorInfo([h],"string",u),r.makeTensorInfo([2],"int32",new Int32Array(d))]}var poe={kernelName:Ed,backendName:"webgl",kernelFunc:uoe};function doe(e){let{inputs:t,backend:r,attrs:n}=e,{numBuckets:a}=n,{input:s}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(a<=0)throw new Error("Number of buckets must be at least 1");let i=r.readSync(s.dataId),o=SY(i,a);return r.makeTensorInfo(s.shape,"int32",o)}var hoe={kernelName:$d,backendName:"webgl",kernelFunc:doe},coe="return tan(x);",foe=Ke({opSnippet:coe}),moe={kernelName:qo,backendName:"webgl",kernelFunc:foe},goe=`
float e2x = exp(-2.0 * abs(x));
return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,yoe=Ke({opSnippet:goe}),boe={kernelName:Ko,backendName:"webgl",kernelFunc:yoe};function xoe(e){let{inputs:t,backend:r,attrs:n}=e,{tensor:a,indices:s,updates:i}=t,{sliceRank:o,numUpdates:l,sliceSize:p,strides:u,outputSize:d}=_.calculateShapes(i,s,a.shape),h=[d/p,p];if(d===0)return r.makeTensorInfo(a.shape,s.dtype);let c=ue({inputs:{x:s},backend:r,attrs:{shape:[l,o]}}),f=ue({inputs:{x:i},backend:r,attrs:{shape:[l,p]}}),m=ue({inputs:{x:a},backend:r,attrs:{shape:h}}),g=new cw(l,o,c.shape.length,f.shape.length,u,h,!1,!0),y=r.runWebGLProgram(g,[f,c,m],m.dtype),b=ue({inputs:{x:y},backend:r,attrs:{shape:a.shape}});return r.disposeIntermediateTensorInfo(c),r.disposeIntermediateTensorInfo(f),r.disposeIntermediateTensorInfo(m),r.disposeIntermediateTensorInfo(y),b}var voe={kernelName:Ou,backendName:"webgl",kernelFunc:xoe},woe=class{constructor(e,t){this.variableNames=["A"];let r=new Array(e.length);for(let s=0;s<r.length;s++)r[s]=e[s]*t[s];this.outputShape=r,this.rank=r.length;let n=pt(this.rank),a=koe(e);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
setOutput(getA(${a}));
}
`}};function koe(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let r=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],n=[];for(let a=0;a<e.length;a++)n.push(`imod(${r[a]}, ${e[a]})`);return n.join()}function rE(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{reps:s}=n;if(a.dtype==="string"||a.shape.length>5){let o=r.readSync(a.dataId),l=a.dtype==="string"?o.map(d=>k.decodeString(d)):o,p=Le(a.shape,a.dtype,l),u=_Y(p,s);return r.makeTensorInfo(u.shape,u.dtype,u.values)}let i=new woe(a.shape,s);return r.runWebGLProgram(i,[a],a.dtype)}var Ioe={kernelName:Es,backendName:"webgl",kernelFunc:rE},Soe=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"negativeInf",type:"float"},{name:"dir",type:"int"},{name:"inc",type:"int"}],this.outputShape=e,this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
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));
}
}
`}},Noe=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"k",type:"int"}],this.outputShape=e,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 js(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function P1(e){let t=1;for(;t<e;)t*=2;return t}function _oe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{k:s,sorted:i}=n,o=j().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=j().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),p=a.shape,u=p[p.length-1];if(r.shouldExecuteOnCPU([a])||u<o||s>l){let $=r.readSync(a.dataId),[R,F]=TY($,p,a.dtype,s,i);return[r.makeTensorInfo(R.shape,R.dtype,R.values),r.makeTensorInfo(F.shape,F.dtype,F.values)]}if(s===0)return p[p.length-1]=0,[r.makeTensorInfo(p,a.dtype,[]),r.makeTensorInfo(p,"int32",[])];if(u===1)return[a,dh({attrs:{shape:p,dtype:"int32",value:0},backend:r})];let d=r.texData.get(a.dataId),h=d!==null&&d.isPacked,c=h?r.unpackTensor(a):a,f=k.sizeFromShape(p)/u,m=ue({inputs:{x:c},attrs:{shape:[f,u]},backend:r});h&&js(r,c);let g=P1(s),y=P1(u),b=null,x=()=>b===null?[m,m]:[m,b],v=($,R,F)=>{let S=x(),D=new Soe(F),P=[[u],[b===null?1:0],[Number.NEGATIVE_INFINITY],[$],[R]],U=b;b=r.runWebGLProgram(D,S,"int32",P),js(r,U)};for(let $=1;$<g;$*=2){let R=$*2;for(let F=$;F>=1;F/=2)v(R,F,[f,y])}for(let $=y;$>g;$/=2){let R=x(),F=new Noe([f,$/2]),S=[[u],[b===null?1:0],[g]],D=b;b=r.runWebGLProgram(F,R,"int32",S),js(r,D);let P=g/2,U=P*2;for(let H=P;H>=1;H/=2)v(U,H,b.shape)}let w=b;b=mp({inputs:{x:b},backend:r,attrs:{begin:0,size:[f,s]}}),js(r,w);let N=KC({inputs:{x:m,indices:b},backend:r,attrs:{axis:1,batchDims:1}});js(r,m);let T=p.slice(0,-1);T.push(s),w=b,b=ue({inputs:{x:b},attrs:{shape:T},backend:r}),js(r,w);let E=N;return N=ue({inputs:{x:N},attrs:{shape:T},backend:r}),js(r,E),[N,b]}var Toe={kernelName:Hu,backendName:"webgl",kernelFunc:_oe},Coe=class{constructor(e,t,r,n,a,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=r==="nearest"?1:2,o;switch(n){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
float mapCoord(float outCoord, float len) {
float inCoord = outCoord;
if(${o} == 2) {
if (inCoord < 0.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz2 = 2.0 * len;
if (inCoord < sz2) {
inCoord = sz2 * float(int(float(-inCoord / sz2))) +
inCoord;
}
inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;
}
} else if (inCoord > len - 1.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz2 = 2.0 * len;
inCoord -= sz2 * float(int(float(inCoord / sz2)));
if (inCoord >= len) {
inCoord = sz2 - inCoord - 1.0;
}
}
}
return clamp(inCoord, 0.0, len - 1.0);
} else if (${o} == 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 (${o} == 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 < ${e} && 0 <= coordX && coordX < ${t}) {
outputValue = getImage(batch, coordY, coordX, channel);
} else {
outputValue = float(${a});
}
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(${a});
} else {
float inX = (a1 * xf + a2 * yf + a3) / projection;
float inY = (b1 * xf + b2 * yf + b3) / projection;
float mapX = mapCoord(inX, float(${t}));
float mapY = mapCoord(inY, float(${e}));
if (${i} == 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 Eoe(e){let{inputs:t,backend:r,attrs:n}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:p}=n,[u,d,h,c]=a.shape,[f,m]=p??[d,h],g=[u,f,m,c],y=new Coe(d,h,i,o,l,g);return r.runWebGLProgram(y,[a,s],"float32")}var $oe={kernelName:ju,backendName:"webgl",kernelFunc:Eoe};function Aoe(e){let{inputs:t,attrs:r,backend:n}=e,{axis:a}=r,{x:s}=t;lp(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=n.readSync(s.dataId),{outputValues:o,outputShape:l,indices:p}=CY(i,a,s.shape,s.dtype);return[n.makeTensorInfo(l,s.dtype,o),n.makeTensorInfo([p.length],"int32",p)]}var Foe={kernelName:Ad,backendName:"webgl",kernelFunc:Aoe};function Roe(e){let{inputs:t,backend:r,attrs:n}=e,{value:a}=t,{axis:s}=n;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],p=new Array(o-1),u=0;for(let m=0;m<o;m++)m!==s&&(p[u++]=i.shape[m]);let d=[],h=new Array(o).fill(0),c=i.shape.slice();c[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){h[s]=m;let g=mp({inputs:{x:i},backend:r,attrs:{begin:h,size:c}}),y=ue({inputs:{x:g},backend:r,attrs:{shape:p}});f[m]=y,d.push(g)}return d.forEach(m=>r.disposeIntermediateTensorInfo(m)),f}var Doe={kernelName:qu,backendName:"webgl",kernelFunc:Roe},Moe=class{constructor(e,t){this.variableNames=["x","segmentIds"];let r=e.windowSize,n=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/r);this.outputShape=[n,i];let o="0.0",l="sumValue",p=Math.floor(r/4)*4,u=r%4,d=`
sumValue += dot(values, segFilter);
`,h="";a%r>0&&(h=`
if (inIdx < 0 || inIdx >= ${a}) {
return initializationValue;
}
`);let c="";a%r>0&&(c=`
if (inIdx < 0 || inIdx >= ${a}) {
return -1.0;
}
`),this.userCode=`
const float initializationValue = ${o};
float getValue(int batch, int inIdx) {
${h}
return getX(batch, inIdx);
}
float getSegmentIdAtIndex(int inIdx) {
${c}
return getSegmentIds(inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = int(floor(float(outIdx) / float(
${s})) * float(${r}));
int currentSeg = int(mod(float(outIdx), float(${s})));
float sumValue = 0.0;
for (int i = 0; i < ${p}; 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
);
${d}
}
int inIdx = inOffset + ${p};
if (${u===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
);
${d}
} else if (${u===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
);
${d}
} else if (${u===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
);
${d}
}
setOutput(${l});
}
`}};function Ooe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,segmentIds:s}=t,{numSegments:i}=n,o=a.shape.length,l=[],p=0,u=_.getAxesPermutation([p],o),d=a;u!=null&&(d=xr({inputs:{x:a},backend:r,attrs:{perm:u}}),l.push(d),p=_.getInnerMostAxes(1,o)[0]);let h=_.segment_util.computeOutShape(d.shape,p,i),c=k.sizeFromShape([d.shape[p]]),f=ue({inputs:{x:d},backend:r,attrs:{shape:[-1,c]}});l.push(f);let m=cf(a.dtype),g=(v,w,N,T,E)=>{let $=v.shape[0],R=v.shape[1],F=_.segment_util.segOpComputeOptimalWindowSize(R,E),S={windowSize:F,inSize:R,batchSize:$,numSegments:E},D=new Moe(S,w),P=r.compileAndRun(D,[v,N],T);if(l.push(P),P.shape[1]===E)return P;let U=tE({backend:r,attrs:{start:0,stop:E,step:1,dtype:"float32"}}),H=rE({inputs:{x:U},backend:r,attrs:{reps:[R/F]}});return l.push(U),l.push(H),g(P,w,H,T,E)},y=g(f,"unsortedSegmentSum",s,m,i),b=ue({inputs:{x:y},backend:r,attrs:{shape:h}}),x=b;if(u!=null){l.push(b);let v=_.getUndoAxesPermutation(u);x=xr({inputs:{x},backend:r,attrs:{perm:v}})}return l.forEach(v=>r.disposeIntermediateTensorInfo(v)),x}var Loe={kernelName:Fd,backendName:"webgl",kernelFunc:Ooe},zoe=[wQ,IQ,_Q,EQ,AQ,DQ,OQ,zQ,UQ,GQ,qQ,ZQ,QQ,nee,iee,lee,pee,fee,gee,bee,kee,Eee,Aee,Mee,Lee,Vee,Hee,Xee,aQ,Yee,nte,ote,cte,gte,bte,vte,kte,_te,Ete,Fte,Dte,Ote,zte,Wte,Vte,qte,Xte,Yte,tre,nre,ore,dre,mre,bre,wre,kre,Sre,_re,Cre,$re,Fre,Ore,Pre,Ure,Gre,qre,Zre,ene,ane,nQ,ine,tte,une,hne,mne,iQ,xne,Ine,Nne,Ene,Fne,One,Pne,Vne,qne,Zne,Yne,rae,aae,iae,pae,hae,fae,gae,bae,kae,_ae,$ae,zae,uQ,Uae,Hae,Kae,Jae,Pee,ese,rse,ase,ose,dse,lQ,cse,mse,yse,xse,vse,Bee,Dae,Ise,Tse,Ase,dQ,Mse,zse,Use,Hse,Xse,Jse,eie,nie,iie,uie,hie,mie,xie,kie,_ie,Eie,Tee,Oae,Fie,Die,Oie,zie,Bie,Uie,Gie,jie,Kie,Jie,Qie,toe,noe,ioe,loe,poe,hoe,Mae,bQ,moe,boe,voe,Ioe,Toe,$oe,xQ,Foe,Doe,Loe,tse];for(let e of zoe)Rd(e);var Ze;(function(e){e[e.float32=0]="float32",e[e.int32=1]="int32",e[e.bool=2]="bool",e[e.string=3]="string",e[e.complex64=4]="complex64"})(Ze||(Ze={}));var ud;(function(e){e[e.linear=0]="linear",e[e.relu=1]="relu",e[e.relu6=2]="relu6",e[e.prelu=3]="prelu",e[e.leakyrelu=4]="leakyrelu",e[e.sigmoid=5]="sigmoid",e[e.elu=6]="elu"})(ud||(ud={}));var nE;function Poe(e){nE=e.wasm.cwrap(li,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Boe(e){let{inputs:t,backend:r,attrs:n}=e,{a,b:s,bias:i,preluActivationWeights:o}=t;if(a.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:p,activation:u,leakyreluAlpha:d}=n,h=r.dataIdMap.get(a.dataId).id,c=r.dataIdMap.get(s.dataId).id,f=0;if(i!=null){let E=r.dataIdMap.get(i.dataId);if(E.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${E.shape.length}.`);f=E.id}let m=o==null?0:r.dataIdMap.get(o.dataId).id,g=ud[u];if(g==null)throw new Error(`${u} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?a.shape[2]:a.shape[1],b=p?s.shape[1]:s.shape[2],x=Zu.assertAndGetBroadcastShape(a.shape.slice(0,-2),s.shape.slice(0,-2)),v=r.makeOutput([...x,y,b],a.dtype),w=r.dataIdMap.get(v.dataId).id,N=new Uint8Array(new Int32Array(a.shape).buffer),T=new Uint8Array(new Int32Array(s.shape).buffer);return nE(h,N,a.shape.length,c,T,s.shape.length,l,p,g,f,m,d||0,w),v}var Woe={kernelName:li,backendName:"wasm",setupFunc:Poe,kernelFunc:Boe};function je(e,t){let r;function n(s){r=s.wasm.cwrap(e,null,["number","number","number"])}function a(s){let{backend:i,inputs:{x:o}}=s,l=i.dataIdMap.get(o.dataId).id,p=i.makeOutput(o.shape,t||o.dtype),u=i.dataIdMap.get(p.dataId).id;return k.sizeFromShape(p.shape)===0||r(l,Ze[o.dtype],u),p}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:a}}var Uoe=je(Kl),Voe=je($i),Goe=je(Ai);function zt(e,t,r){let n;function a(i){n=i.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function s(i){let{backend:o,inputs:l}=i,{a:p,b:u}=l,d=o.dataIdMap.get(p.dataId).id,h=o.dataIdMap.get(u.dataId).id,c=r??p.dtype,f=_.assertAndGetBroadcastShape(p.shape,u.shape),m=o.makeOutput(f,c);if(k.sizeFromShape(f)===0)return m;let g=new Uint8Array(new Int32Array(p.shape).buffer),y=new Uint8Array(new Int32Array(u.shape).buffer),b=o.dataIdMap.get(m.dataId).id;return n(d,g,p.shape.length,h,y,u.shape.length,Ze[p.dtype],b),m}return{kernelName:e,backendName:"wasm",setupFunc:a,kernelFunc:s}}var Hoe=zt(Ts),aE;function joe(e){aE=e.wasm.cwrap(Fi,null,["array","number","number","number"])}function qoe(e){let{inputs:t,backend:r}=e,n=r.makeOutput(t[0].shape,t[0].dtype);if(k.sizeFromShape(n.shape)===0)return n;let a=t.map(o=>r.dataIdMap.get(o.dataId).id),s=new Uint8Array(new Int32Array(a).buffer),i=r.dataIdMap.get(n.dataId).id;return aE(s,a.length,Ze[n.dtype],i),n}var Koe={kernelName:Fi,backendName:"wasm",setupFunc:joe,kernelFunc:qoe};function km(e){let{inputs:{x:t},backend:r}=e;if(t.dtype==="string")return yr(r.readSync(t.dataId),t.shape,t.dtype);let n=r.makeOutput(t.shape,t.dtype),a=r.typedArrayFromHeap(t);return r.typedArrayFromHeap(n).set(a),n}var Xoe={kernelName:so,backendName:"wasm",kernelFunc:km},sE;function Zoe(e){sE=e.wasm.cwrap(Ta,null,["number","array","number","number","number","array","number"])}function Ss(e){let{inputs:t,backend:r,attrs:n}=e,[a,s]=Yoe(t.x.shape,n.perm),i=!0;for(let f=0;f<s.length;f++)s[f]!==f&&(i=!1);let o=Joe(t.x.shape,n.perm),l={dataId:t.x.dataId,shape:a,dtype:t.x.dtype};if(i){let f=km({inputs:t,backend:r});return f.shape=o,f}let p=r.makeOutput(o,l.dtype),u=r.dataIdMap.get(l.dataId).id,d=r.dataIdMap.get(p.dataId).id,h=new Uint8Array(new Int32Array(s).buffer),c=new Uint8Array(new Int32Array(l.shape).buffer);return sE(u,c,l.shape.length,Ze[l.dtype],d,h,s.length),p}function Joe(e,t){let r=new Array(e.length);for(let n=0;n<r.length;n++)r[n]=e[t[n]];return r}function Yoe(e,t){let r=[],n=[];for(let a=0;a<e.length;++a)e[a]!==1&&r.push(e[a]),e[t[a]]!==1&&n.push(t[a]);for(let a=0;a<n.length;++a){let s=-1;for(let i=0;i<n.length;++i)n[i]>=a&&(s===-1||n[s]>n[i])&&(s=i);n[s]=a}return[r,n]}var Qoe={kernelName:Ta,backendName:"wasm",kernelFunc:Ss,setupFunc:Zoe};function zs(e,t,r){let n=e.shape,a=e.shape.length,s=k.parseAxisParam(t,n),i=s,o=_.getAxesPermutation(i,a),l=null,p=!1;if(o!=null){let u=new Array(a);for(let h=0;h<u.length;h++)u[h]=n[o[h]];i=_.getInnerMostAxes(i.length,a),l=Ss({inputs:{x:e},attrs:{perm:o},backend:r});let d=r.dataIdMap.get(e.dataId).id;r.dataIdMap.get(l.dataId).id!==d&&(p=!0)}return{transposed:l,originalAxes:s,axes:i,inputWasTransposed:p}}var iE;function ele(e){iE=e.wasm.cwrap(Xl,null,["number, number, number"])}function tle(e){let{backend:t,inputs:r,attrs:n}=e,{axis:a,keepDims:s}=n,{x:i}=r,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:p,axes:u,originalAxes:d,inputWasTransposed:h}=zs(i,a,t);if(h){let b=t.dataIdMap.get(p.dataId).id;l=p,o=b}let c=l.shape.length;_.assertAxesAreInnerMostDims("all",u,c);let[f,m]=_.computeOutAndReduceShapes(l.shape,u),g=k.sizeFromShape(m),y=t.makeOutput(f,i.dtype);if(k.sizeFromShape(l.shape)!==0){let b=t.dataIdMap.get(y.dataId).id;iE(o,g,b)}if(h&&t.disposeData(p.dataId),s){let b=_.expandShapeToKeepDim(y.shape,d);y.shape=b}return y}var rle={kernelName:Xl,backendName:"wasm",setupFunc:ele,kernelFunc:tle},oE;function nle(e){oE=e.wasm.cwrap(Zl,null,["number, number, number"])}function ale(e){let{backend:t,inputs:r,attrs:n}=e,{axis:a,keepDims:s}=n,{x:i}=r,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:p,axes:u,originalAxes:d,inputWasTransposed:h}=zs(i,a,t);if(h){let b=t.dataIdMap.get(p.dataId).id;l=p,o=b}let c=l.shape.length;_.assertAxesAreInnerMostDims("any",u,c);let[f,m]=_.computeOutAndReduceShapes(l.shape,u),g=k.sizeFromShape(m),y=t.makeOutput(f,i.dtype);if(k.sizeFromShape(l.shape)!==0){let b=t.dataIdMap.get(y.dataId).id;oE(o,g,b)}if(h&&t.disposeData(p.dataId),s){let b=_.expandShapeToKeepDim(y.shape,d);y.shape=b}return y}var sle={kernelName:Zl,backendName:"wasm",setupFunc:nle,kernelFunc:ale};function lE(e){let t;function r(a){t=a.wasm.cwrap(e,null,["number","number","number","number","number"])}function n(a){let{backend:s,inputs:i,attrs:o}=a,{axis:l}=o,{x:p}=i,u=s.dataIdMap.get(p.dataId).id,d=u,h=p,{transposed:c,axes:f,inputWasTransposed:m}=zs(p,l,s);if(m){let w=s.dataIdMap.get(c.dataId).id;w!==u&&(h=c,d=w)}let g=h.shape.slice(0,-1),y=s.makeOutput(g,"int32"),b=s.dataIdMap.get(y.dataId).id,x=k.sizeFromShape(y.shape),v=h.shape[f[0]];return t(d,Ze[h.dtype],x,v,b),m&&s.disposeData(c.dataId),y}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:n}}var ile=lE(Jl),ole=lE(Yl),lle=je(Ri),ule=je(Di),ple=je(Mi),dle=zt(Li),hle=je(Oi),uE;function cle(e){uE=e.wasm.cwrap(zi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function fle(e){let{inputs:t,attrs:r,backend:n}=e,a=t.x,s=n.dataIdMap.get(a.dataId).id,{filterSize:i,strides:o,pad:l,dimRoundingMode:p}=r,u=_.computePool2DInfo(a.shape,i,o,1,l,p),d=u.filterHeight,h=u.filterWidth,c=u.padInfo.top,f=u.padInfo.right,m=u.padInfo.bottom,g=u.padInfo.left,y=u.strideHeight,b=u.strideWidth,x=u.inChannels;if(u.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${u.dataFormat}'. Please use 'channelsLast'.`);if(u.dilationWidth!==1||u.dilationHeight!==1)throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${u.dilationHeight}, ${u.dilationWidth}].`);let v=n.makeOutput(u.outShape,"float32"),w=n.dataIdMap.get(v.dataId).id;return uE(s,a.shape[0],a.shape[1],a.shape[2],d,h,c,f,m,g,y,b,x,w),v}var mle={kernelName:zi,backendName:"wasm",setupFunc:cle,kernelFunc:fle},pE;function gle(e){pE=e.wasm.cwrap("AvgPool3D",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function yle(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:p}=n,u=_.computePool3DInfo(a.shape,s,i,1,o,l,p),d=r.makeOutput(u.outShape,a.dtype);return pE(r.dataIdMap.get(a.dataId).id,r.dataIdMap.get(d.dataId).id,u.batchSize,u.inChannels,u.inDepth,u.inHeight,u.inWidth,u.outDepth,u.outHeight,u.outWidth,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.effectiveFilterDepth,u.effectiveFilterHeight,u.effectiveFilterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left),d}var ble={kernelName:Ql,backendName:"wasm",setupFunc:gle,kernelFunc:yle},dE;function xle(e){dE=e.wasm.cwrap("AvgPool3DGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function vle(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:p}=n,u=_.computePool3DInfo(s.shape,i,o,1,l,p),d=r.makeOutput(s.shape,s.dtype);return dE(r.dataIdMap.get(a.dataId).id,r.dataIdMap.get(d.dataId).id,u.batchSize,u.inChannels,u.inDepth,u.inHeight,u.inWidth,u.outDepth,u.outHeight,u.outWidth,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.effectiveFilterDepth,u.effectiveFilterHeight,u.effectiveFilterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left,u.filterDepth,u.filterHeight,u.filterWidth),d}var wle={kernelName:cd,backendName:"wasm",setupFunc:xle,kernelFunc:vle},hE;function kle(e){hE=e.wasm.cwrap("AvgPoolGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Ile(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,input:s}=t,{filterSize:i,strides:o,pad:l}=n,p=_.computePool2DInfo(s.shape,i,o,1,l),u=r.makeOutput(s.shape,s.dtype);return hE(r.dataIdMap.get(a.dataId).id,r.dataIdMap.get(u.dataId).id,p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.top,p.padInfo.left,p.filterHeight,p.filterWidth),u}var Sle={kernelName:hd,backendName:"wasm",setupFunc:kle,kernelFunc:Ile};function Fr(e){let{inputs:t,attrs:r}=e,{x:n}=t,{shape:a}=r,s=k.sizeFromShape(n.shape),i=k.inferFromImplicitShape(a,s);return k.assert(s===k.sizeFromShape(i),()=>`new shape: ${i}, old shape: ${n.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(n.dataId),{dataId:n.dataId,shape:i,dtype:n.dtype}}var Nle={kernelName:Fu,backendName:"wasm",kernelFunc:Fr},cE;function _le(e){cE=e.wasm.cwrap(Pi,null,["number","array","number","number","array","number","number","number","number"])}function Tle(e){let{inputs:t,backend:r,attrs:n}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=n;if(a.dtype!=="float32"||s.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=a.shape.length,p=s.shape.length,u=i?a.shape[l-2]:a.shape[l-1],d=o?s.shape[p-1]:s.shape[p-2],h=i?a.shape[l-1]:a.shape[l-2],c=o?s.shape[p-2]:s.shape[p-1],f=a.shape.slice(0,-2),m=s.shape.slice(0,-2),g=k.sizeFromShape(f),y=k.sizeFromShape(m),b=Zu.assertAndGetBroadcastShape(a.shape.slice(0,-2),s.shape.slice(0,-2)).concat([h,c]);k.assert(u===d,()=>`Error in matMul: inner shapes (${u}) and (${d}) of Tensors with shapes ${a.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let x=i?[g,u,h]:[g,h,u],v=o?[y,c,d]:[y,d,c],w=Fr({inputs:{x:a},backend:r,attrs:{shape:x}}),N=Fr({inputs:{x:s},backend:r,attrs:{shape:v}}),T=r.dataIdMap.get(w.dataId).id,E=r.dataIdMap.get(N.dataId).id,$=i?w.shape[2]:w.shape[1],R=o?N.shape[1]:N.shape[2],F=Math.max(g,y),S=r.makeOutput([F,$,R],w.dtype),D=r.dataIdMap.get(S.dataId).id,P=new Uint8Array(new Int32Array(w.shape).buffer),U=new Uint8Array(new Int32Array(N.shape).buffer);return cE(T,P,w.shape.length,E,U,N.shape.length,i,o,D),r.disposeData(w.dataId),r.disposeData(N.dataId),S.shape=b,S}var Cle={kernelName:Pi,backendName:"wasm",setupFunc:_le,kernelFunc:Tle};function _i(e){let{inputs:{x:t},attrs:{begin:r,size:n},backend:a}=e,[s,i]=Wt.parseSliceParams(t,r,n),o=Wt.isSliceContinous(t.shape,s,i),l=a.readSync(t.dataId),p=a.makeOutput(i,t.dtype),u=k.computeStrides(t.shape),d=a.dataIdMap.get(p.dataId);if(o){let f=Wt.computeFlatOffset(s,u);return t.dtype==="string"?d.stringBytes=l.slice(f,f+k.sizeFromShape(i)):a.typedArrayFromHeap(p).set(l.subarray(f,f+k.sizeFromShape(i))),p}if(t.dtype==="string"){let f=Rc(l,s,i,t.shape,t.dtype);return d.stringBytes=f,p}let h=a.typedArrayFromHeap(p),c=t.shape.length;if(c===2)Ele(l,u[0],h,s,i);else if(c===3)$le(l,u[0],u[1],h,s,i);else if(c===4)Ale(l,u[0],u[1],u[2],h,s,i);else{let f=Rc(l,s,i,t.shape,t.dtype);h.set(f)}return p}function Ele(e,t,r,n,a){let s=0,i=n[0],o=n[1],l=i+a[0];for(let p=i;p<l;p++){let u=p*t+o;r.set(e.subarray(u,u+a[1]),s),s+=a[1]}}function $le(e,t,r,n,a,s){let i=0,o=a[0],l=a[1],p=a[2],u=o+s[0],d=l+s[1];for(let h=o;h<u;h++)for(let c=l;c<d;c++){let f=h*t+c*r+p;n.set(e.subarray(f,f+s[2]),i),i+=s[2]}}function Ale(e,t,r,n,a,s,i){let o=0,l=s[0],p=s[1],u=s[2],d=l+i[0],h=p+i[1],c=u+i[2],f=s[3];for(let m=l;m<d;m++)for(let g=p;g<h;g++)for(let y=u;y<c;y++){let b=m*t+g*r+y*n+f;a.set(e.subarray(b,b+i[3]),o),o+=i[3]}}var Fle={kernelName:Pu,backendName:"wasm",kernelFunc:_i};function Rle(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockShape:s,crops:i}=n,o=s.reduce((y,b)=>y*b),l=_.getReshaped(a.shape,s,o),p=_.getPermuted(l.length,s.length),u=_.getReshapedPermuted(a.shape,s,o),d=_.getSliceBeginCoords(i,s.length),h=_.getSliceSize(u,i,s.length),c=Fr({inputs:{x:a},backend:r,attrs:{shape:l}}),f=Ss({inputs:{x:c},backend:r,attrs:{perm:p}}),m=Fr({inputs:{x:f},backend:r,attrs:{shape:u}}),g=_i({inputs:{x:m},backend:r,attrs:{begin:d,size:h}});return r.disposeData(c.dataId),r.disposeData(f.dataId),r.disposeData(m.dataId),g}var Dle={kernelName:eu,backendName:"wasm",kernelFunc:Rle},fE;function Mle(e){fE=e.wasm.cwrap(tu,null,["number","number","boolean","number","number","number"])}function Ole(e){let{backend:t,inputs:r,attrs:n}=e,{x:a,weights:s}=r,{size:i}=n,o=s.shape.reduce((d,h)=>d*h,1)!==0,l=a.shape.length===1?[i]:[a.shape[0],i],p=t.makeOutput(l,s.dtype);function u(d){return t.dataIdMap.get(d.dataId).id}return fE(u(a),i,o,u(s),Ze[s.dtype],u(p)),p}var Lle={kernelName:tu,backendName:"wasm",setupFunc:Mle,kernelFunc:Ole},zle=zt(ru);function Ple(e){let{inputs:t,backend:r}=e,{s0:n,s1:a}=t,s=r.typedArrayFromHeap(n),i=r.typedArrayFromHeap(a),o=_.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return r.makeOutput([o.length],"int32",void 0,new Int32Array(o))}var Ble={kernelName:fd,backendName:"wasm",kernelFunc:Ple};function Ps(e){let{inputs:{x:t},attrs:{dtype:r},backend:n}=e,a=n.makeOutput(t.shape,r),s=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(a).set(s),a}var Wle={kernelName:Bi,backendName:"wasm",kernelFunc:Ps},Ule=je(Wi),mE;function Vle(e){mE=e.wasm.cwrap(Cs,null,["number","number","number","number"])}function Gle(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=n,o=r.dataIdMap.get(a.dataId).id,l=r.makeOutput(a.shape,a.dtype),p=r.dataIdMap.get(l.dataId).id;return mE(o,s,i,p),l}var Hle={kernelName:Cs,backendName:"wasm",setupFunc:Vle,kernelFunc:Gle};function gE(e){let{inputs:t,backend:r}=e,n=k.parseAxisParam(e.attrs.axis,t[0].shape)[0],a=t.map(c=>c.shape);_.assertParamsConsistent(a,n);let s=_.computeOutShape(t.map(c=>c.shape),n),i=t.filter(c=>k.sizeFromShape(c.shape)>0);if(i.length===1)return km({inputs:{x:i[0]},backend:r});let o=r.makeOutput(s,t[0].dtype);if(k.sizeFromShape(s)===0)return o;if(i[0].dtype==="string"){let c=i.map(x=>{let v=[-1,k.sizeFromShape(x.shape.slice(n))];return Fr({inputs:{x},backend:r,attrs:{shape:v}})}),f=c.map(x=>({vals:r.readSync(x.dataId),shape:x.shape}));s=_.computeOutShape(c.map(x=>x.shape),1);let m=c[0].shape[0]===1,g=Pv(f,s,t[0].dtype,m),y=_.computeOutShape(i.map(x=>x.shape),n);o.shape=y;let b=r.dataIdMap.get(o.dataId);return b.stringBytes=_.fromStringArrayToUint8(g),c.forEach(x=>r.disposeData(x.dataId)),o}let l=k.sizeFromShape(i[0].shape.slice(0,n)),p=0,u=i.map(c=>{let f=k.sizeFromShape(c.shape.slice(n));return p+=f,f}),d=i.map(c=>r.typedArrayFromHeap(c)),h=r.typedArrayFromHeap(o);for(let c=0;c<l;c++){let f=c*p;for(let m=0;m<d.length;m++){let g=u[m],y=c*g,b=d[m].subarray(y,y+g);h.set(b,f),f+=g}}return o}var jle={kernelName:nu,backendName:"wasm",kernelFunc:gE},yE;function qle(e){yE=e.wasm.cwrap(Ui,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Kle(e){let{inputs:t,attrs:r,backend:n}=e,{x:a,filter:s}=t,i=n.dataIdMap.get(a.dataId).id,o=n.dataIdMap.get(s.dataId).id,{strides:l,dilations:p,pad:u,dimRoundingMode:d,dataFormat:h}=r,c=_.convertConv2DDataFormat(h),f=_.computeConv2DInfo(a.shape,s.shape,l,p,u,d,!1,c),m=f.filterHeight,g=f.filterWidth,y=f.padInfo.top,b=f.padInfo.right,x=f.padInfo.bottom,v=f.padInfo.left,w=f.dilationHeight,N=f.dilationWidth,T=f.strideHeight,E=f.strideWidth,$=f.inChannels,R=f.outChannels,F=f.padInfo.type==="SAME"?1:0;if(f.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${f.dataFormat}'. Please use 'channelsLast'.`);let S=n.makeOutput(f.outShape,"float32"),D=n.dataIdMap.get(S.dataId).id;return yE(i,a.shape[0],a.shape[1],a.shape[2],o,m,g,y,b,x,v,F,w,N,T,E,$,R,D),S}var Xle={kernelName:Ui,backendName:"wasm",setupFunc:qle,kernelFunc:Kle},bE;function Zle(e){bE=e.wasm.cwrap(Vi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Jle(e){let{backend:t,inputs:r,attrs:n}=e,{dy:a,filter:s}=r,{strides:i,pad:o,dataFormat:l,dimRoundingMode:p,inputShape:u}=n,d=1,h=_.convertConv2DDataFormat(l),c=_.computeConv2DInfo(u,s.shape,i,d,o,p,!1,h),{batchSize:f,filterHeight:m,filterWidth:g,inChannels:y,inHeight:b,inWidth:x,outChannels:v,outHeight:w,outWidth:N,strideHeight:T,strideWidth:E}=c,$=m-1-c.padInfo.top,R=g-1-c.padInfo.left,F=c.dataFormat==="channelsLast",S=k.computeStrides(c.inShape),D=k.computeStrides(a.shape),[P,U,H]=k.computeStrides(s.shape),q=S[0],G=F?S[1]:S[2],Z=F?S[2]:1,ee=F?1:S[1],X=D[0],re=F?D[1]:D[2],te=F?D[2]:1,ae=F?1:D[1],ie=t.makeOutput(c.inShape,"float32"),ve=t.dataIdMap.get(ie.dataId).id,be=t.dataIdMap.get(a.dataId).id,he=t.dataIdMap.get(s.dataId).id;return bE(be,he,f,m,g,b,x,y,w,N,v,T,E,$,R,P,U,H,q,G,Z,ee,X,re,te,ae,ve),ie}var Yle={kernelName:Vi,backendName:"wasm",setupFunc:Zle,kernelFunc:Jle},xE;function Qle(e){xE=e.wasm.cwrap(Gi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function eue(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=n;if(a.dtype!=="float32")throw new Error(`Tensor x must have dtype float32, got ${a.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let p=_.computeConv3DInfo(a.shape,s.shape,i,l,o),u=r.makeOutput(p.outShape,a.dtype);return xE(r.dataIdMap.get(a.dataId).id,r.dataIdMap.get(s.dataId).id,r.dataIdMap.get(u.dataId).id,p.batchSize,p.inDepth,p.inHeight,p.inWidth,p.inChannels,p.outDepth,p.outHeight,p.outWidth,p.outChannels,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.filterDepth,p.filterHeight,p.filterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),u}var tue={kernelName:Gi,backendName:"wasm",setupFunc:Qle,kernelFunc:eue},vE;function rue(e){vE=e.wasm.cwrap(au,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function nue(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=n;if(a.dtype!=="float32")throw new Error(`Tensor dy must have dtype float32, got ${a.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let p=_.computeConv3DInfo(a.shape,l,i,1,o),u=r.makeOutput(p.filterShape,s.dtype);return vE(r.dataIdMap.get(a.dataId).id,r.dataIdMap.get(s.dataId).id,r.dataIdMap.get(u.dataId).id,p.batchSize,p.inDepth,p.inHeight,p.inWidth,p.inChannels,p.outDepth,p.outHeight,p.outWidth,p.outChannels,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.filterDepth,p.filterHeight,p.filterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),u}var aue={kernelName:au,backendName:"wasm",setupFunc:rue,kernelFunc:nue},wE;function sue(e){wE=e.wasm.cwrap(su,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function iue(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=n;if(a.dtype!=="float32")throw new Error(`Tensor dy must have dtype float32, got ${a.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let p=_.computeConv3DInfo(l,s.shape,o,1,i),u=r.makeOutput(p.inShape,a.dtype);return wE(r.dataIdMap.get(s.dataId).id,r.dataIdMap.get(a.dataId).id,r.dataIdMap.get(u.dataId).id,p.batchSize,p.inDepth,p.inHeight,p.inWidth,p.inChannels,p.outDepth,p.outHeight,p.outWidth,p.outChannels,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.filterDepth,p.filterHeight,p.filterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),u}var oue={kernelName:su,backendName:"wasm",setupFunc:sue,kernelFunc:iue},lue=je(Hi),uue=je(ji),ey;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(ey||(ey={}));var kE;function pue(e){kE=e.wasm.cwrap(ou,null,["number","number","number","number","array","number","number","number","number","number"])}function due(e){let{backend:t,inputs:r,attrs:n}=e,{method:a,extrapolationValue:s,cropSize:i}=n,{image:o,boxes:l,boxInd:p}=r,u=l.shape[0],[d,h]=i,c=[u,d,h,o.shape[3]],f=t.dataIdMap.get(o.dataId),m;o.dtype!=="float32"&&(m=Ps({backend:t,inputs:{x:o},attrs:{dtype:"float32"}}),f=t.dataIdMap.get(m.dataId));let g=f.id,y=t.dataIdMap.get(l.dataId).id,b=t.dataIdMap.get(p.dataId).id,x=t.makeOutput(c,"float32"),v=t.dataIdMap.get(x.dataId).id,w=new Uint8Array(new Int32Array(o.shape).buffer);return kE(g,y,b,u,w,d,h,ey[a],s,v),m!=null&&t.disposeData(m.dataId),x}var hue={kernelName:ou,backendName:"wasm",setupFunc:pue,kernelFunc:due},IE;function cue(e){IE=e.wasm.cwrap(iu,null,["number","number","number","number","number","number"])}function fue(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n,l=a.shape.length;k.assert(a.dtype==="float32"||a.dtype==="int32",()=>`cumprod does not support ${a.dtype} tensors in the WASM backend`);let p=_.getAxesPermutation([s],l),u=a;p!==null&&(u=Ss({inputs:{x:a},attrs:{perm:p},backend:r}));let d=_.getInnerMostAxes(1,l)[0];_.assertAxesAreInnerMostDims("cumprod",[d],l);let h=r.makeOutput(u.shape,u.dtype),c=u.shape[d],f=r.dataIdMap.get(u.dataId).id,m=r.dataIdMap.get(h.dataId).id;IE(f,i?1:0,o?1:0,c,m,Ze[a.dtype]);let g=h;if(p!==null){let y=_.getUndoAxesPermutation(p);g=Ss({inputs:{x:h},attrs:{perm:y},backend:r}),r.disposeData(u.dataId),r.disposeData(h.dataId)}return g}var mue={kernelName:iu,backendName:"wasm",setupFunc:cue,kernelFunc:fue},SE;function gue(e){SE=e.wasm.cwrap(qi,null,["number","number","number","number","number","number"])}function yue(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n,l=a.shape.length;k.assert(a.dtype==="float32"||a.dtype==="int32",()=>`cumsum does not support ${a.dtype} tensors in the WASM backend`);let p=_.getAxesPermutation([s],l),u=a;p!==null&&(u=Ss({inputs:{x:a},attrs:{perm:p},backend:r}));let d=_.getInnerMostAxes(1,l)[0];_.assertAxesAreInnerMostDims("cumsum",[d],l);let h=r.makeOutput(u.shape,u.dtype),c=u.shape[d],f=r.dataIdMap.get(u.dataId).id,m=r.dataIdMap.get(h.dataId).id;SE(f,i?1:0,o?1:0,c,m,Ze[a.dtype]);let g=h;if(p!==null){let y=_.getUndoAxesPermutation(p);g=Ss({inputs:{x:h},attrs:{perm:y},backend:r}),r.disposeData(u.dataId),r.disposeData(h.dataId)}return g}var bue={kernelName:qi,backendName:"wasm",setupFunc:gue,kernelFunc:yue},NE;function xue(e){NE=e.wasm.cwrap("DenseBincount",null,["number","array","number","number","boolean","number","number","boolean","number"])}function vue(e){let{backend:t,inputs:r,attrs:n}=e,{x:a,weights:s}=r,{size:i,binaryOutput:o}=n,l=s.shape.reduce((h,c)=>h*c,1)!==0,p=a.shape.length===1?[i]:[a.shape[0],i],u=t.makeOutput(p,s.dtype);function d(h){return t.dataIdMap.get(h.dataId).id}return NE(d(a),new Uint8Array(new Int32Array(a.shape).buffer),a.shape.length,i,l,d(s),Ze[s.dtype],o,d(u)),u}var wue={kernelName:gd,backendName:"wasm",setupFunc:xue,kernelFunc:vue},_E;function kue(e){_E=e.wasm.cwrap(lu,null,["number","number","number","array","number","array","array","number","number"])}function Iue(e){let{backend:t,inputs:r,attrs:n}=e,{x:a}=r,{blockSize:s,dataFormat:i}=n,o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],p=i==="NHWC"?a.shape[2]:a.shape[3],u=i==="NHWC"?a.shape[3]:a.shape[1],d=l*s,h=p*s,c=u/(s*s),f=i==="NHWC"?[o,d,h,c]:[o,c,d,h],m=t.makeOutput(f,"float32"),g=t.dataIdMap.get(a.dataId).id,y=new Uint8Array(new Int32Array(k.computeStrides(a.shape)).buffer),b=new Uint8Array(new Int32Array(f).buffer),x=new Uint8Array(new Int32Array(k.computeStrides(f)).buffer),v=t.dataIdMap.get(m.dataId).id;return _E(g,s,i==="NHWC"?1:0,y,a.shape.length-1,b,x,f.length,v),m}var Sue={kernelName:lu,backendName:"wasm",setupFunc:kue,kernelFunc:Iue},TE;function Nue(e){TE=e.wasm.cwrap(Ki,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function _ue(e){let{inputs:t,attrs:r,backend:n}=e,{x:a,filter:s}=t,i=n.dataIdMap.get(a.dataId).id,o=n.dataIdMap.get(s.dataId).id,{strides:l,dilations:p,pad:u,dimRoundingMode:d}=r,h=p??[1,1],c=_.computeConv2DInfo(a.shape,s.shape,l,h,u,d,!0),f=c.filterHeight,m=c.filterWidth,g=c.padInfo.top,y=c.padInfo.right,b=c.padInfo.bottom,x=c.padInfo.left,v=c.dilationHeight,w=c.dilationWidth,N=c.strideHeight,T=c.strideWidth,E=c.inChannels,$=c.outChannels,R=c.padInfo.type==="SAME"?1:0;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${c.dataFormat}'. Please use 'channelsLast'.`);let F=n.makeOutput(c.outShape,"float32"),S=n.dataIdMap.get(F.dataId).id;return TE(i,a.shape[0],a.shape[1],a.shape[2],o,f,m,g,y,b,x,R,v,w,N,T,E,$,S),F}var Tue={kernelName:Ki,backendName:"wasm",setupFunc:Nue,kernelFunc:_ue},CE;function Cue(e){CE=e.wasm.cwrap("Diag",null,["number","number","number","number"])}function Eue(e){let{inputs:t,backend:r}=e,{x:n}=t,a=k.sizeFromShape(n.shape),s=r.makeOutput([...n.shape,...n.shape],n.dtype);return CE(r.dataIdMap.get(n.dataId).id,Ze[n.dtype],a,r.dataIdMap.get(s.dataId).id),s}var $ue={kernelName:yd,backendName:"wasm",setupFunc:Cue,kernelFunc:Eue},EE;function Aue(e){EE=e.wasm.cwrap(Xi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Fue(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=n;if(a.dtype!==s.dtype)throw new Error(`Dilation2D error: x must have the same dtype as filter. 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Got ${a.dtype}, ${s.dtype}, and ${i.dtype}`);let u=_.computeDilation2DInfo(a.shape,s.shape,o,l,"NHWC",p),d=r.makeOutput(s.shape,s.dtype);return $E(r.dataIdMap.get(a.dataId).id,r.dataIdMap.get(s.dataId).id,r.dataIdMap.get(i.dataId).id,r.dataIdMap.get(d.dataId).id,Ze[a.dtype],u.batchSize,u.inChannels,u.inHeight,u.inWidth,u.outHeight,u.outWidth,u.strideHeight,u.strideWidth,u.dilationHeight,u.dilationWidth,u.filterHeight,u.filterWidth,u.padInfo.top,u.padInfo.left),d}var Oue={kernelName:Cl,backendName:"wasm",setupFunc:Due,kernelFunc:Mue},AE;function Lue(e){AE=e.wasm.cwrap(Tl,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function zue(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s,dy:i}=t,{strides:o,pad:l,dilations:p}=n;if(a.dtype!==s.dtype||a.dtype!==i.dtype)throw new Error(`Dilation2DBackpropInput error: x must have the same dtype as filter and dy. Got ${a.dtype}, ${s.dtype}, and ${i.dtype}`);let u=_.computeDilation2DInfo(a.shape,s.shape,o,l,"NHWC",p),d=r.makeOutput(a.shape,a.dtype);return AE(r.dataIdMap.get(a.dataId).id,r.dataIdMap.get(s.dataId).id,r.dataIdMap.get(i.dataId).id,r.dataIdMap.get(d.dataId).id,Ze[a.dtype],u.batchSize,u.inChannels,u.inHeight,u.inWidth,u.outHeight,u.outWidth,u.strideHeight,u.strideWidth,u.dilationHeight,u.dilationWidth,u.filterHeight,u.filterWidth,u.padInfo.top,u.padInfo.left),d}var Pue={kernelName:Tl,backendName:"wasm",setupFunc:Lue,kernelFunc:zue},Bue=je(Ji),FE;function Wue(e){FE=e.wasm.cwrap(uu,null,["number","number","number"])}function Uue(e){let{inputs:t,backend:r}=e,{dy:n,y:a}=t,s=r.makeOutput(a.shape,"float32"),i=o=>r.dataIdMap.get(o.dataId).id;return FE(i(a),i(n),i(s)),s}var Vue={kernelName:uu,backendName:"wasm",setupFunc:Wue,kernelFunc:Uue},Gue=!1,Hue=zt(pu,Gue,"bool"),jue=je(Yi),que=je(Qi,"float32");function ty(e){let{inputs:t,attrs:r,backend:n}=e,{input:a}=t,{dim:s}=r,i=a.shape.length,o=a.shape.slice(),l=s;return s<0&&(k.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),Fr({inputs:{x:a},backend:n,attrs:{shape:o}})}var Kue={kernelName:du,backendName:"wasm",kernelFunc:ty},Xue=je(eo,"float32");function RE(e){let{attrs:{shape:t,value:r},backend:n}=e,{attrs:{dtype:a}}=e;a=a||k.inferDtype(r);let s=n.makeOutput(t,a);return n.typedArrayFromHeap(s).fill(r),s}var Zue={kernelName:bd,backendName:"wasm",kernelFunc:RE},DE;function Jue(e){DE=e.wasm.cwrap(hu,null,["number","number","number","number","number","number"])}function Yue(e){let{inputs:t,backend:r}=e,{image:n}=t,a=r.makeOutput(n.shape,n.dtype),s=r.dataIdMap.get(n.dataId).id,i=r.dataIdMap.get(a.dataId).id,[o,l,p,u]=n.shape;return DE(s,o,l,p,u,i),a}var Que={kernelName:hu,backendName:"wasm",kernelFunc:Yue,setupFunc:Jue},epe=je(to),tpe=zt(ro),ME;function rpe(e){ME=e.wasm.cwrap(no,null,["number","number","number","number","number","number","number"])}function npe(e){let{backend:t,inputs:r,attrs:n}=e,{varianceEpsilon:a}=n,{x:s,mean:i,variance:o,offset:l,scale:p}=r,u=t.dataIdMap.get(s.dataId).id,d=t.dataIdMap.get(i.dataId).id,h=t.dataIdMap.get(o.dataId).id,c=l!=null?t.dataIdMap.get(l.dataId).id:0,f=p!=null?t.dataIdMap.get(p.dataId).id:0,m=t.makeOutput(s.shape,s.dtype);if(k.sizeFromShape(s.shape)===0)return m;let g=t.dataIdMap.get(m.dataId).id;return ME(u,d,h,c,f,a,g),m}var ape={kernelName:no,backendName:"wasm",setupFunc:rpe,kernelFunc:npe},OE;function spe(e){OE=e.wasm.cwrap(ui,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function ipe(e){let{inputs:t,attrs:r,backend:n}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:p,dilations:u,dataFormat:d,dimRoundingMode:h,activation:c,leakyreluAlpha:f}=r,m=_.computeConv2DInfo(a.shape,s.shape,l,u,p,h),g=ud[c];if(g==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let y=n.dataIdMap.get(a.dataId).id,b=n.dataIdMap.get(s.dataId).id,x=m.outChannels,v=0;if(i!=null){let te=n.dataIdMap.get(i.dataId);if(te.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${te.shape.length}.`);if(te.shape[0]!==x)throw new Error(`FusedConv2D bias shape (${te.shape}) does not match the number of output channels (${x})`);v=te.id}let w=m.filterHeight,N=m.filterWidth,T=m.padInfo.top,E=m.padInfo.right,$=m.padInfo.bottom,R=m.padInfo.left,F=m.dilationHeight,S=m.dilationWidth,D=m.strideHeight,P=m.strideWidth,U=m.inChannels,H=m.padInfo.type==="SAME"?1:0,q=m.batchSize,G=m.inHeight,Z=m.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${d}'. 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Please use 'NHWC'.`);let ee=n.makeOutput(m.outShape,"float32"),X=n.dataIdMap.get(ee.dataId).id,re=o==null?0:n.dataIdMap.get(o.dataId).id;return LE(y,q,G,Z,b,w,N,v,T,E,$,R,H,F,S,D,P,U,x,g,re,f||0,X),ee}var ppe={kernelName:pi,backendName:"wasm",setupFunc:lpe,kernelFunc:upe},zE;function dpe(e){zE=e.wasm.cwrap(fu,null,["number","number","number","number","number","number","array","number"])}function hpe(e){let{backend:t,inputs:r}=e,{params:n,indices:a}=r,[s,i,o,l]=Jb.prepareAndValidate(n,a),p=t.makeOutput(s,n.dtype);if(i===0)return p;let u=a.shape,d=u[u.length-1],h=t.dataIdMap.get(n.dataId).id,c=t.dataIdMap.get(a.dataId).id,f=new Uint8Array(new Int32Array(l).buffer),m=t.dataIdMap.get(p.dataId).id;return zE(h,Ze[n.dtype],c,i,d,o,f,m),p}var cpe={kernelName:fu,backendName:"wasm",setupFunc:dpe,kernelFunc:hpe},PE;function fpe(e){PE=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function mpe(e){let{backend:t,inputs:r,attrs:n}=e,{x:a,indices:s}=r,{axis:i,batchDims:o}=n,l=k.parseAxisParam(i,a.shape)[0],p=t.readSync(s.dataId),u=a.shape[l];for(let T=0;T<p.length;++T){let E=p[T];k.assert(E<=u-1&&E>=0,()=>`GatherV2: the index value ${E} is not in [0, ${u-1}]`)}let d=_.segment_util.collectGatherOpShapeInfo(a,s,l,o),h=Fr({inputs:{x:a},attrs:{shape:[d.batchSize,d.outerSize,d.dimSize,d.sliceSize]},backend:t}),c=k.sizeFromShape(s.shape),f=Fr({inputs:{x:s},attrs:{shape:[d.batchSize,c/d.batchSize]},backend:t}),m=[d.batchSize,d.outerSize,c/d.batchSize,d.sliceSize],g=t.makeOutput(m,a.dtype);if(k.sizeFromShape(a.shape)===0)return g;let y=h.shape.length-1,b=t.dataIdMap.get(h.dataId).id,x=t.dataIdMap.get(f.dataId).id,v=t.dataIdMap.get(g.dataId).id,w=new Uint8Array(new Int32Array(k.computeStrides(h.shape)).buffer),N=new Uint8Array(new Int32Array(k.computeStrides(m)).buffer);return PE(b,Ze[a.dtype],w,y,x,d.batchSize,N,v),t.disposeData(h.dataId),t.disposeData(f.dataId),g.shape=d.outputShape,g}var gpe={kernelName:cu,backendName:"wasm",setupFunc:fpe,kernelFunc:mpe},ype=!1,bpe=zt(mu,ype,"bool"),xpe=!1,vpe=zt(ao,xpe,"bool"),wpe=je(io,"bool"),kpe=je(oo,"bool"),Ipe=je(lo,"bool"),BE;function Spe(e){BE=e.wasm.cwrap(uo,null,["number","number","number","number"])}function Npe(e){let{inputs:{x:t},attrs:{alpha:r},backend:n}=e,a=n.dataIdMap.get(t.dataId).id,s=n.makeOutput(t.shape,"float32");if(k.sizeFromShape(t.shape)!==0){let i=n.dataIdMap.get(s.dataId).id;BE(a,Ze[t.dtype],r,i)}return s}var _pe={kernelName:uo,backendName:"wasm",setupFunc:Spe,kernelFunc:Npe},Tpe=!1,Cpe=zt(gu,Tpe,"bool"),Epe=!1,$pe=zt(yu,Epe,"bool"),WE;function Ape(e){WE=e.wasm.cwrap(bu,null,["number","number","number","number"])}function Fpe(e){let{attrs:t,backend:r}=e,{start:n,stop:a,num:s}=t,i=Math.floor(s),o=r.makeOutput([i],"float32");return WE(r.dataIdMap.get(o.dataId).id,n,a,i),o}var Rpe={kernelName:bu,backendName:"wasm",setupFunc:Ape,kernelFunc:Fpe},Dpe=je(po),Mpe=je(ho),Ope=!1,Lpe=zt(xu,Ope,"bool"),zpe=je(vu),Ppe=!1,Bpe=zt(wu,Ppe,"bool"),Wpe=!1,Upe=zt(Bk,Wpe,"bool"),UE;function Vpe(e){UE=e.wasm.cwrap(co,null,["number","number","number","number","number","number","number"])}function Gpe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n;if(a.dtype!=="float32")throw new Error("LRN error: x must have dtype float32");let p=r.makeOutput(a.shape,a.dtype);return UE(r.dataIdMap.get(a.dataId).id,r.dataIdMap.get(p.dataId).id,a.shape[3],s,i,o,l),p}var Hpe={kernelName:co,backendName:"wasm",setupFunc:Vpe,kernelFunc:Gpe},VE;function jpe(e){VE=e.wasm.cwrap(ku,null,["number","number","number","number","number","number","number","number","number"])}function qpe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:p,beta:u}=n;if(a.dtype!=="float32"||s.dtype!=="float32"||i.dtype!=="float32")throw new Error("LRNGrad error: x, y, and dy must have dtype float32");let d=r.makeOutput(a.shape,a.dtype);return VE(r.dataIdMap.get(a.dataId).id,r.dataIdMap.get(s.dataId).id,r.dataIdMap.get(i.dataId).id,r.dataIdMap.get(d.dataId).id,i.shape[3],o,l,p,u),d}var Kpe={kernelName:ku,backendName:"wasm",setupFunc:jpe,kernelFunc:qpe},GE;function Xpe(e){GE=e.wasm.cwrap(fo,null,["number","number","number","number"])}function Zpe(e){let{backend:t,inputs:r,attrs:n}=e,{reductionIndices:a,keepDims:s}=n,{x:i}=r,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:p,axes:u,originalAxes:d,inputWasTransposed:h}=zs(i,a,t);if(h){let b=t.dataIdMap.get(p.dataId).id;l=p,o=b}let c=l.shape.length;_.assertAxesAreInnerMostDims("max",u,c);let[f,m]=_.computeOutAndReduceShapes(l.shape,u),g=k.sizeFromShape(m),y=t.makeOutput(f,i.dtype);if(k.sizeFromShape(l.shape)!==0){let b=t.dataIdMap.get(y.dataId).id;GE(o,Ze[i.dtype],g,b)}if(h&&t.disposeData(p.dataId),s){let b=_.expandShapeToKeepDim(y.shape,d);y.shape=b}return y}var Jpe={kernelName:fo,backendName:"wasm",setupFunc:Xpe,kernelFunc:Zpe},Ype=zt(mo),HE;function Qpe(e){HE=e.wasm.cwrap(go,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function ede(e){let{inputs:t,attrs:r,backend:n}=e,a=t.x,s=n.dataIdMap.get(a.dataId).id;k.assert(a.dtype==="float32",()=>`Error in MaxPool: only float32 input is supported. Got ${a.dtype}.`);let{filterSize:i,strides:o,pad:l,dimRoundingMode:p}=r,u=_.computePool2DInfo(a.shape,i,o,1,l,p),d=u.filterHeight,h=u.filterWidth,c=u.padInfo.top,f=u.padInfo.right,m=u.padInfo.bottom,g=u.padInfo.left,y=u.dilationHeight,b=u.dilationWidth,x=u.strideHeight,v=u.strideWidth,w=u.inChannels,N=u.outChannels;if(u.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${u.dataFormat}'. 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v=t.dataIdMap.get(u.dataId).id;v!==o&&(p=u,l=v,f=_.getInnerMostAxes(f.length,p.shape.length))}_.assertAxesAreInnerMostDims("mean",f,p.shape.length);let[m,g]=_.computeOutAndReduceShapes(p.shape,f),y=k.sizeFromShape(g),b=p;p.dtype!=="float32"&&(b=Ps({backend:t,inputs:{x:p},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(b.dataId).id);let x=t.makeOutput(m,"float32");if(k.sizeFromShape(p.shape)!==0){let v=t.dataIdMap.get(x.dataId).id;ZE(l,y,v)}if(c&&t.disposeData(u.dataId),s){let v=_.expandShapeToKeepDim(x.shape,h);x.shape=v}return p.dtype!=="float32"&&t.disposeData(b.dataId),x}var gde={kernelName:yo,backendName:"wasm",setupFunc:fde,kernelFunc:mde},JE;function yde(e){JE=e.wasm.cwrap(bo,null,["number","number","number","number"])}function bde(e){let{backend:t,inputs:r,attrs:n}=e,{axis:a,keepDims:s}=n,{x:i}=r,o=t.dataIdMap.get(i.dataId).id,l=o,p=i,{transposed:u,axes:d,originalAxes:h,inputWasTransposed:c}=zs(i,a,t);if(c){let x=t.dataIdMap.get(u.dataId).id;x!==o&&(p=u,l=x)}let f=p.shape.length;_.assertAxesAreInnerMostDims("min",d,f);let[m,g]=_.computeOutAndReduceShapes(p.shape,d),y=k.sizeFromShape(g),b=t.makeOutput(m,p.dtype);if(k.sizeFromShape(p.shape)!==0){let x=t.dataIdMap.get(b.dataId).id;JE(l,Ze[i.dtype],y,x)}if(c&&t.disposeData(u.dataId),s){let x=_.expandShapeToKeepDim(b.shape,h);b.shape=x}return b}var xde={kernelName:bo,backendName:"wasm",setupFunc:yde,kernelFunc:bde},vde=zt(xo),ry;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(ry||(ry={}));var YE;function wde(e){YE=e.wasm.cwrap(vo,null,["number","array","number","number","array","array","number","number"])}function kde(e){let{inputs:{x:t},backend:r,attrs:{paddings:n,mode:a}}=e,s=n.map((f,m)=>f[0]+t.shape[m]+f[1]),i=r.dataIdMap.get(t.dataId).id,o=r.makeOutput(s,t.dtype),l=r.dataIdMap.get(o.dataId).id,p=new Uint8Array(new Int32Array(t.shape).buffer),u=n.map(f=>f[0]),d=n.map(f=>f[1]),h=new Uint8Array(new Int32Array(u).buffer),c=new Uint8Array(new Int32Array(d).buffer);return 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o$={kernelName:So,backendName:"wasm",kernelFunc:Jde,setupFunc:Zde},Yde=zt(No),l$;function Qde(e){l$=e.wasm.cwrap(_o,null,["number","number","number"])}function ehe(e){let{inputs:t,backend:r}=e,{x:n,alpha:a}=t,s=r.dataIdMap.get(n.dataId).id,i=r.dataIdMap.get(a.dataId).id,o=s,l=n,p=l;l.dtype!=="float32"&&(p=Ps({backend:r,inputs:{x:n},attrs:{dtype:"float32"}}),o=r.dataIdMap.get(p.dataId).id);let u=r.makeOutput(n.shape,"float32"),d=r.dataIdMap.get(u.dataId).id;return l$(o,i,d),l.dtype!=="float32"&&r.disposeData(p.dataId),u}var the={kernelName:_o,backendName:"wasm",setupFunc:Qde,kernelFunc:ehe},u$;function rhe(e){u$=e.wasm.cwrap(To,null,["number","number","number","number"])}function nhe(e){let{backend:t,inputs:r,attrs:n}=e,{axis:a,keepDims:s}=n,{x:i}=r,o=t.dataIdMap.get(i.dataId).id,l=o,p=i,{transposed:u,axes:d,originalAxes:h,inputWasTransposed:c}=zs(i,a,t),f=d;if(c){let 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n=r.map(({width:s,height:i})=>{let o=t/Math.max(i,s);return{width:s*o,height:i*o}}),a=n.length;return W(()=>{let s=(p,u)=>Mt([qr([68],p,"float32"),qr([68],u,"float32")],1).as2D(1,136).as1D(),i=(p,u)=>{let{width:d,height:h}=n[p];return u(d,h)?Math.abs(d-h)/2:0},o=p=>i(p,(u,d)=>u<d),l=p=>i(p,(u,d)=>d<u);return e.mul(qr([a,136],t,"float32")).sub(Mt(Array.from(Array(a),(p,u)=>s(o(u),l(u))))).div(Mt(Array.from(Array(a),(p,u)=>s(n[u].width,n[u].height))))})}forwardInput(e){return W(()=>{let t=this.runNet(e);return this.postProcess(t,e.inputSize,e.inputDimensions.map(([r,n])=>({height:r,width:n})))})}async forward(e){return this.forwardInput(await vr(e))}async detectLandmarks(e){let t=await vr(e),r=W(()=>Tt(this.forwardInput(t))),n=await Promise.all(r.map(async(a,s)=>{let i=Array.from(a.dataSync()),o=i.filter((p,u)=>sy(u)),l=i.filter((p,u)=>!sy(u));return new G$(Array(68).fill(0).map((p,u)=>new it(o[u],l[u])),{height:t.getInputHeight(s),width:t.getInputWidth(s)})}));return r.forEach(a=>a.dispose()),t.isBatchInput?n:n[0]}getClassifierChannelsOut(){return 136}},rme=class extends yA{constructor(e=new pA){super("FaceLandmark68Net",e)}getDefaultModelName(){return"face_landmark_68_model"}getClassifierChannelsIn(){return 256}};function nme(e){let t=[],{extractDenseBlock3Params:r}=uA(e,t),n={dense0:r("dense0",!0),dense1:r("dense1"),dense2:r("dense2")};return Ws(e,t),{params:n,paramMappings:t}}function ame(e){let t=[],{extractWeights:r,getRemainingWeights:n}=Us(e),{extractDenseBlock3Params:a}=oA(r,t),s=a(3,32,"dense0",!0),i=a(32,64,"dense1"),o=a(64,128,"dense2");if(n().length!==0)throw new Error(`weights remaing after extract: ${n().length}`);return{paramMappings:t,params:{dense0:s,dense1:i,dense2:o}}}var sme=class extends Bs{constructor(){super("TinyFaceFeatureExtractor")}forwardInput(e){let{params:t}=this;if(!t)throw new Error("TinyFaceFeatureExtractor - load model before inference");return W(()=>{let 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l=r(`${o}/sub`,1),p=r(`${o}/truediv`,1);return{sub:l,truediv:p}}function a(o){let l=r(`${o}/filters`,4),p=r(`${o}/bias`,1);return{filters:l,bias:p}}function s(o){let l=a(`${o}/conv`),p=n(`${o}/bn`);return{conv:l,bn:p}}let i=Nw(r);return{extractConvParams:a,extractConvWithBatchNormParams:s,extractSeparableConvParams:i}}function Ume(e,t){let r=[],{extractConvParams:n,extractConvWithBatchNormParams:a,extractSeparableConvParams:s}=Wme(e,r),i;if(t.withSeparableConvs){let o=t.filterSizes&&t.filterSizes.length||9;i={conv0:t.isFirstLayerConv2d?n("conv0"):s("conv0"),conv1:s("conv1"),conv2:s("conv2"),conv3:s("conv3"),conv4:s("conv4"),conv5:s("conv5"),conv6:o>7?s("conv6"):void 0,conv7:o>8?s("conv7"):void 0,conv8:n("conv8")}}else i={conv0:a("conv0"),conv1:a("conv1"),conv2:a("conv2"),conv3:a("conv3"),conv4:a("conv4"),conv5:a("conv5"),conv6:a("conv6"),conv7:a("conv7"),conv8:n("conv8")};return Ws(e,r),{params:i,paramMappings:r}}var Ew=class{constructor({inputSize:e,scoreThreshold:t}={}){if(this._name="TinyYolov2Options",this._inputSize=e||416,this._scoreThreshold=t||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)}get inputSize(){return this._inputSize}get scoreThreshold(){return this._scoreThreshold}},vA=class wA extends Bs{constructor(t){super("TinyYolov2"),zme(t),this._config=t}get config(){return this._config}get withClassScores(){return this.config.withClassScores||this.config.classes.length>1}get boxEncodingSize(){return 5+(this.withClassScores?this.config.classes.length:0)}runTinyYolov2(t,r){let n=Ha(t,r.conv0);return 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config`);return Bme(t,this.config,this.boxEncodingSize,r)}async extractBoxes(t,r,n){let{width:a,height:s}=r,i=Math.max(a,s),o=i/a,l=i/s,p=t.shape[1],u=this.config.anchors.length,[d,h,c]=W(()=>{let y=t.reshape([p,p,u,this.boxEncodingSize]),b=y.slice([0,0,0,0],[p,p,u,4]),x=y.slice([0,0,0,4],[p,p,u,1]),v=this.withClassScores?Ds(y.slice([0,0,0,5],[p,p,u,this.config.classes.length]),3):we(0);return[b,x,v]}),f=[],m=await h.array(),g=await d.array();for(let y=0;y<p;y++)for(let b=0;b<p;b++)for(let x=0;x<u;x++){let v=Km(m[y][b][x][0]);if(!n||v>n){let w=(b+Km(g[y][b][x][0]))/p*o,N=(y+Km(g[y][b][x][1]))/p*l,T=Math.exp(g[y][b][x][2])*this.config.anchors[x].x/p*o,E=Math.exp(g[y][b][x][3])*this.config.anchors[x].y/p*l,$=w-T/2,R=N-E/2,F={row:y,col:b,anchor:x},{classScore:S,label:D}=this.withClassScores?await this.extractPredictedClass(c,F):{classScore:1,label:0};f.push({box:new P$($,R,$+T,R+E),score:v,classScore:v*S,label:D,...F})}}return d.dispose(),h.dispose(),c.dispose(),f}async extractPredictedClass(t,r){let{row:n,col:a,anchor:s}=r,i=await t.array();return Array(this.config.classes.length).fill(0).map((o,l)=>i[n][a][s][l]).map((o,l)=>({classScore:o,label:l})).reduce((o,l)=>o.classScore>l.classScore?o:l)}};vA.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var kA=vA,Vme=class extends kA{constructor(e=!0){let t={withSeparableConvs:e,iouThreshold:Fme,classes:["face"],...e?{anchors:Dme,meanRgb:Mme}:{anchors:Rme,withClassScores:!0}};super(t)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(e,t){return(await this.detect(e,t)).map(r=>new Gn(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?Lme:Ome}extractParamsFromWeightMap(e){return super.extractParamsFromWeightMap(e)}},Gme=class extends Ew{constructor(){super(...arguments),this._name="TinyFaceDetectorOptions"}},fh=class{async then(e){return e(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};async function $w(e,t,r,n,a=({alignedRect:s})=>s){let s=e.map(l=>cA(l)?a(l):l.detection),i=n||(t instanceof ze?await nA(t,s):await rA(t,s)),o=await r(i);return i.forEach(l=>l instanceof ze&&l.dispose()),o}var Hme=.4,jme=[new it(1.603231,2.094468),new it(6.041143,7.080126),new it(2.882459,3.518061),new it(4.266906,5.178857),new it(9.041765,10.66308)],qme=[117.001,114.697,97.404],Kme=class extends kA{constructor(){let e={withSeparableConvs:!0,iouThreshold:Hme,classes:["face"],anchors:jme,meanRgb:qme,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(e)}get anchors(){return this.config.anchors}async locateFaces(e,t){return(await this.detect(e,t)).map(r=>new Gn(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(e){return super.extractParamsFromWeightMap(e)}},zn={ssdMobilenetv1:new Ame,tinyFaceDetector:new Kme,tinyYolov2:new Vme,faceLandmark68Net:new rme,faceLandmark68TinyNet:new ime,faceRecognitionNet:new cme,faceExpressionNet:new Pfe,ageGenderNet:new tme},Xme=class extends fh{constructor(e,t,r){super(),this.parentTask=e,this.input=t,this.extractedFaces=r}},Aw=class extends Xme{async run(){let e=await this.parentTask,t=await $w(e,this.input,async r=>Promise.all(r.map(n=>zn.faceExpressionNet.predictExpressions(n))),this.extractedFaces);return e.map((r,n)=>Wfe(r,t[n]))}withAgeAndGender(){return new Rw(this,this.input)}},Fw=class extends Aw{withAgeAndGender(){return new Dw(this,this.input)}withFaceDescriptors(){return new Mw(this,this.input)}},Zme=class extends fh{constructor(e,t,r){super(),this.parentTask=e,this.input=t,this.extractedFaces=r}},Rw=class extends Zme{async run(){let e=await this.parentTask,t=await $w(e,this.input,async r=>Promise.all(r.map(n=>zn.ageGenderNet.predictAgeAndGender(n))),this.extractedFaces);return e.map((r,n)=>{let{age:a,gender:s,genderProbability:i}=t[n];return 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Qme(this.runAndExtendWithFaceDetections(),this.input,e)}withFaceExpressions(){return new Aw(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new Rw(this.runAndExtendWithFaceDetections(),this.input)}};function rge(e,t=new Im){return new tge(e,t)}var nge=Hn('<a target="_blank"><img class="svelte-1lkxzkn"/></a>'),age=Hn('<img class="svelte-1lkxzkn"/>'),sge=Hn('<a target="_blank" class="view-profile-link svelte-1lkxzkn">View Profile</a>'),ige=Hn('<span class="no-profile-link svelte-1lkxzkn">No Profile</span>'),oge=Hn('<div class="cop svelte-1lkxzkn"><div class="cop-face"><!></div> <div class="cop-info svelte-1lkxzkn"><div class="name svelte-1lkxzkn"> </div> <div class="serial svelte-1lkxzkn"> </div> <div class="link svelte-1lkxzkn"><!></div></div></div>');function lge(e,t){my(t,!0);const 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N=nge(),T=Gr(N);bl(()=>{Ja(N,"href",Ye(s)),Ja(T,"src",Ye(a)),Ja(T,"alt",Ye(n))}),eg("error",T,()=>At(a,r)),Rn(w,N)},d=w=>{var N=age();bl(()=>{Ja(N,"src",Ye(a)),Ja(N,"alt",Ye(n))}),eg("error",N,()=>At(a,r)),Rn(w,N)};xl(p,w=>{Ye(s)?w(u):w(d,!1)})}var h=Fn(l,2),c=Gr(h),f=Gr(c),m=Fn(c,2),g=Gr(m),y=Fn(m,2),b=Gr(y);{var x=w=>{var N=sge();bl(()=>Ja(N,"href",Ye(s))),Rn(w,N)},v=w=>{var N=ige();Rn(w,N)};xl(b,w=>{Ye(s)&&Ye(i)?w(x):w(v,!1)})}bl(()=>{tg(f,Ye(n)),tg(g,`Serial: ${t.cop.serial||"N/A"}`)}),Rn(e,o),gy()}var uge=Hn('<div class="status svelte-4rj7r7">Loading...</div>'),pge=Hn('<div class="uploaded-face-section svelte-4rj7r7"><div class="cop uploaded-cop svelte-4rj7r7"><div class="cop-face"><img alt="Uploaded face" class="uploaded-face-img svelte-4rj7r7"/></div></div></div>'),dge=Hn('<hr class="results-divider svelte-4rj7r7"/>'),hge=Hn('<div class="cop svelte-4rj7r7"><!></div>'),cge=Hn('<form class="svelte-4rj7r7"><label for="image-input" class="svelte-4rj7r7">Select Photo</label> <input 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low-resolution photos will not match.</p> <!> <!></main>`);function mge(e,t){my(t,!0);let r,n,a,s=an(void 0),i=an(!1),o=an(!1),l=an(void 0),p=an(yl([])),u=_p(()=>Ye(i)&&Ye(o));async function d(w){try{const N=await fetch(w);if(!N.ok)throw new Error(`HTTP error! status: ${N.status}`);const T=await N.arrayBuffer(),$=new DataView(T).getUint32(0,!0),R=new Uint8Array(T,4,$),F=new TextDecoder().decode(R),S=JSON.parse(F),D=4+$,P=new Uint8Array(T,D);return{data:new Float32Array(P.buffer,P.byteOffset,P.byteLength/4),shape:S.shape,dtype:S.dtype}}catch(N){throw console.error("Error loading matrix:",N),N}}async function h(){At(s,"Loading...");try{const[w,N,T,E,$]=await Promise.all([zn.ssdMobilenetv1.loadFromUri("./models"),zn.faceLandmark68Net.loadFromUri("./models"),zn.faceRecognitionNet.loadFromUri("./models"),d("analysis/lapd_descriptors.bin"),fetch("analysis/lapd_metadata.json")]);if(!$.ok)throw new Error(`HTTP error! status: ${$.status}`);const R=await $.json();r=E,n=R,At(i,!0),At(o,!0),console.log("Face descriptors shape:",r.shape),console.log("Combined data length:",n.length),console.log("First few combined data entries:",n.slice(0,3)),At(s,"")}catch(w){console.error("Error loading models and database:",w),At(s,"Error loading face API models and database. Please make sure all model files and database files are available.")}}function c(w){const N=new FileReader;N.onload=function(T){At(l,T.target.result,!0)},N.readAsDataURL(w.target.files[0])}async function f(){try{const w=await rge(a).withFaceLandmarks().withFaceDescriptors();if(w.length===0){At(s,"No faces detected in image. Please try a different image with clearly visible faces."),At(p,[],!0);return}const N=w.reduce((X,re)=>{const te=re.detection.box.width*re.detection.box.height,ae=X.detection.box.width*X.detection.box.height;return te>ae?re:X}),T=N.descriptor,E=N.detection.box,$=document.createElement("canvas"),R=$.getContext("2d");$.width=a.naturalWidth,$.height=a.naturalHeight,R.drawImage(a,0,0);const F=document.createElement("canvas"),S=F.getContext("2d"),D=20,P=E.width+D*2,U=E.height+D*2,H=Math.max(0,E.x-D),q=Math.max(0,E.y-D);F.width=P,F.height=U,S.drawImage($,H,q,P,U,0,0,P,U),At(s,"Comparing with database...");const G=[],Z=r.shape[0],ee=r.shape[1];for(let X=0;X<Z;X++){const re=X*ee,te=r.data.slice(re,re+ee),ae=m(T,te);G.push({index:X,distance:ae,data:n[X]})}G.sort((X,re)=>X.distance-re.distance),At(p,G.slice(0,9),!0),F.remove(),$.remove(),At(s,"")}catch(w){console.error("Error in face recognition:",w)}}function m(w,N){let T=0;for(let E=0;E<w.length;E++){const $=w[E]-N[E];T+=$*$}return T}iR(()=>{h()});var g=fge(),y=Fn(Gr(g),6);{var b=w=>{var N=uge();Rn(w,N)};xl(y,w=>{Ye(u)||w(b)})}var x=Fn(y,2);{var v=w=>{var N=cge(),T=vF(N),E=Fn(Gr(T),2);E.__input=c;var $=Fn(T,2);eR($,"",{},{display:"none"}),sR($,q=>a=q,()=>a);var R=Fn($,2),F=Gr(R),S=Fn(R,2);{var D=q=>{var G=pge(),Z=Gr(G),ee=Gr(Z),X=Gr(ee);bl(()=>Ja(X,"src",Ye(l))),Rn(q,G)};xl(S,q=>{Ye(l)&&q(D)})}var P=Fn(S,2);{var U=q=>{var G=dge();Rn(q,G)};xl(P,q=>{Ye(p).length>0&&q(U)})}var H=Fn(P,2);XF(H,21,()=>Ye(p),qF,(q,G)=>{var Z=hge(),ee=Gr(Z);lge(ee,{get cop(){return Ye(G).data},get index(){return Ye(G).index},get distance(){return Ye(G).distance}}),Rn(q,Z)}),bl(()=>{Ja($,"src",Ye(l)),tg(F,Ye(s))}),eg("load",$,f),Rn(w,N)};xl(x,w=>{Ye(u)&&w(v)})}Rn(e,g),gy()}UF(["input"]);GF(mge,{target:document.getElementById("app")});
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