human/dist/tfjs.esm.js

/*
  Human
  homepage: <https://github.com/vladmandic/human>
  author: <https://github.com/vladmandic>'
*/

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n=this.backend.numDataIds(),s=0;o.forEach(p=>{s+=p.dtype==="complex64"?3:1});let a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=n-t-s-a;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,o=[],n=this.isTapeOn(),s=this.state.numBytes,a=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let p,u=Db(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(Db(e)){let{kernelName:f,inputs:h,attrs:g}=e;this.backendName==null&&this.backend;let x=qc(f,this.backendName);E(x!=null,()=>`Cannot find registered kernel '${f}' for backend '${this.backendName}'`),i=()=>{let b=this.backend.numDataIds();p=x.kernelFunc({inputs:h,attrs:g,backend:this.backend});let C=Array.isArray(p)?p:[p];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(f,b,C);let w=C.map(k=>k.rank!=null?k:this.makeTensorFromTensorInfo(k));if(n){let k=this.getTensorsForGradient(f,h,w);o=this.saveTensorsForBackwardMode(k)}return w}}else{let{forwardFunc:f}=e,h=g=>{!n||(o=g.map(x=>this.keep(this.clone(x))))};i=()=>{let g=this.backend.numDataIds();p=this.tidy(()=>f(this.backend,h));let x=Array.isArray(p)?p:[p];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(u,g,x),x}}let{inputs:c,attrs:l}=e,m=Db(e)?null:e.backwardsFunc,d;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(d=this.profiler.profileKernel(u,c,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),n&&this.addTapeNode(u,c,t,m,o,l),this.state.profiling&&this.state.activeProfile.kernels.push({name:u,bytesAdded:this.state.numBytes-s,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-a,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(c).map(f=>c[f]!=null?c[f].shape:null),outputShapes:t.map(f=>f.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(p)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(o=>this.keep(this.clone(o)))}getTensorsForGradient(e,t,o){let n=Cb(e);if(n!=null){let s=n.inputsToSave||[],a=n.outputsToSave||[],i;n.saveAllInputs?(E(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(u=>t[u])):i=s.map(u=>t[u]);let 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2 or rank 1 but got rank ${u.rank}.`),c!=null&&E(c.rank===2||c.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`),wi(a,i,p,c,u,s)}var A0=N({batchNorm2d_:QW});function ZW(r,e,t,o,n,s){let a=v(r,"x","batchNorm"),i=v(e,"mean","batchNorm"),p=v(t,"variance","batchNorm"),u;n!=null&&(u=v(n,"scale","batchNorm"));let c;return o!=null&&(c=v(o,"offset","batchNorm")),E(a.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${a.rank}.`),E(i.rank===3||i.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${i.rank}.`),E(p.rank===3||p.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${p.rank}.`),u!=null&&E(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${u.rank}.`),c!=null&&E(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`),wi(a,i,p,c,u,s)}var R0=N({batchNorm3d_:ZW});function JW(r,e,t,o,n,s){let a=v(r,"x","batchNorm"),i=v(e,"mean","batchNorm"),p=v(t,"variance","batchNorm"),u;n!=null&&(u=v(n,"scale","batchNorm"));let c;return o!=null&&(c=v(o,"offset","batchNorm")),E(a.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${a.rank}.`),E(i.rank===4||i.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${i.rank}.`),E(p.rank===4||p.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${p.rank}.`),u!=null&&E(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),c!=null&&E(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`),wi(a,i,p,c,u,s)}var F0=N({batchNorm4d_:JW});function eU(r,e,t){let o=v(r,"x","bincount"),n=v(e,"weights","bincount");E(o.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${o.dtype}`),E(t>=0,()=>`size must be non-negative, but got 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aq={fft:zp,ifft:hu,rfft:Wp,irfft:Fd},iq={hammingWindow:L1,hannWindow:Ld,frame:Bd,stft:B1},uq={flipLeftRight:z1,grayscaleToRGB:W1,resizeNearestNeighbor:J1,resizeBilinear:Z1,rotateWithOffset:U1,cropAndResize:V1,nonMaxSuppression:G1,nonMaxSuppressionAsync:K1,nonMaxSuppressionWithScore:j1,nonMaxSuppressionWithScoreAsync:X1,nonMaxSuppressionPadded:Y1,nonMaxSuppressionPaddedAsync:Q1,threshold:eN,transform:tN},pq={bandPart:rN,gramSchmidt:oN,qr:sN},cq={absoluteDifference:aN,computeWeightedLoss:sr,cosineDistance:iN,hingeLoss:uN,huberLoss:pN,logLoss:cN,meanSquaredError:lN,sigmoidCrossEntropy:mN,softmaxCrossEntropy:dN},lq={sparseFillEmptyRows:fN,sparseReshape:hN,sparseSegmentMean:gN,sparseSegmentSum:xN},mq={stringNGrams:yN,stringSplit:bN,stringToHashBucketFast:CN};var wr=class extends ol{minimize(e,t=!1,o){let{value:n,grads:s}=this.computeGradients(e,o);if(o!=null){let a=o.map(i=>({name:i.name,tensor:s[i.name]}));this.applyGradients(a)}else this.applyGradients(s);return Dt(s),t?n:(n.dispose(),null)}get iterations(){return this.iterations_==null&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return pC(e,t)}dispose(){this.iterations_!=null&&Dt(this.iterations_)}async saveIterations(){return this.iterations_==null&&(this.iterations_=0),{name:"iter",tensor:be(this.iterations_,"int32")}}async getWeights(){throw new Error("getWeights() is not implemented for this optimizer yet.")}async setWeights(e){throw new Error(`setWeights() is not implemented for this optimizer class ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(wr,Symbol.hasInstance,{value:r=>r.minimize!=null&&r.computeGradients!=null&&r.applyGradients!=null});var Ei=class extends wr{constructor(e,t,o=null){super(),this.learningRate=e,this.rho=t,this.epsilon=o,this.accumulatedGrads=[],this.accumulatedUpdates=[],o==null&&(this.epsilon=T.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let s=T.registeredVariables[o],a=!1;this.accumulatedGrads[n]==null&&(this.accumulatedGrads[n]={originalName:`${o}/accum_grad`,variable:Ee(()=>Ut(s).variable(a))}),this.accumulatedUpdates[n]==null&&(this.accumulatedUpdates[n]={originalName:`${o}/accum_var`,variable:Ee(()=>Ut(s).variable(a))});let i=Array.isArray(e)?e[n].tensor:e[o];if(i==null)return;let p=this.accumulatedGrads[n].variable,u=this.accumulatedUpdates[n].variable;Ee(()=>{let c=xe(ae(p,this.rho),ae(Qt(i),1-this.rho)),l=ae(Ge($r(xe(u,this.epsilon)),$r(xe(p,this.epsilon))),i),m=xe(ae(u,this.rho),ae(Qt(l),1-this.rho));p.assign(c),u.assign(m);let d=xe(ae(l,-this.learningRate),s);s.assign(d)})}),this.incrementIterations()}dispose(){this.accumulatedUpdates!=null&&(Dt(this.accumulatedGrads.map(e=>e.variable)),Dt(this.accumulatedUpdates.map(e=>e.variable)))}async getWeights(){let e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=e.length/2,o=!1;this.accumulatedGrads=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(o)})),this.accumulatedUpdates=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(o)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}};Ei.className="Adadelta";Er(Ei);var $i=class extends wr{constructor(e,t=.1){super(),this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let s=T.registeredVariables[o];this.accumulatedGrads[n]==null&&(this.accumulatedGrads[n]={originalName:`${o}/accumulator`,variable:Ee(()=>Ws(s.shape,this.initialAccumulatorValue).variable(!1))});let a=Array.isArray(e)?e[n].tensor:e[o];if(a==null)return;let i=this.accumulatedGrads[n].variable;Ee(()=>{let p=xe(i,Qt(a));i.assign(p);let u=xe(ae(Ge(a,$r(xe(p,T.backend.epsilon()))),-this.learningRate),s);s.assign(u)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&Dt(this.accumulatedGrads.map(e=>e.variable))}async getWeights(){return[await this.saveIterations()].concat(this.accumulatedGrads.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulatedGrads=e.map(o=>({originalName:o.name,variable:o.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}};$i.className="Adagrad";Er($i);var Ai=class extends wr{constructor(e,t,o,n=null){super(),this.learningRate=e,this.beta1=t,this.beta2=o,this.epsilon=n,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],Ee(()=>{this.accBeta1=be(t).variable(),this.accBeta2=be(o).variable()}),n==null&&(this.epsilon=T.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(o=>o.name):Object.keys(e);Ee(()=>{let o=Ne(1,this.accBeta1),n=Ne(1,this.accBeta2);t.forEach((s,a)=>{let i=T.registeredVariables[s],p=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${s}/m`,variable:Ee(()=>Ut(i).variable(p))}),this.accumulatedSecondMoment[a]==null&&(this.accumulatedSecondMoment[a]={originalName:`${s}/v`,variable:Ee(()=>Ut(i).variable(p))});let u=Array.isArray(e)?e[a].tensor:e[s];if(u==null)return;let c=this.accumulatedFirstMoment[a].variable,l=this.accumulatedSecondMoment[a].variable,m=xe(ae(c,this.beta1),ae(u,1-this.beta1)),d=xe(ae(l,this.beta2),ae(Qt(u),1-this.beta2)),f=Ge(m,o),h=Ge(d,n);c.assign(m),l.assign(d);let g=xe(ae(Ge(f,xe($r(h),this.epsilon)),-this.learningRate),i);i.assign(g)}),this.accBeta1.assign(ae(this.accBeta1,this.beta1)),this.accBeta2.assign(ae(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&Dt(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&Dt(this.accumulatedSecondMoment.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedFirstMoment,...this.accumulatedSecondMoment];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e),Ee(()=>{this.accBeta1.assign(Ra(this.beta1,this.iterations_+1)),this.accBeta2.assign(Ra(this.beta2,this.iterations_+1))});let t=e.length/2,o=!1;this.accumulatedFirstMoment=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(o)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(o)}))}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon)}};Ai.className="Adam";Er(Ai);var Ri=class extends wr{constructor(e,t,o,n=null,s=0){super(),this.learningRate=e,this.beta1=t,this.beta2=o,this.epsilon=n,this.decay=s,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],Ee(()=>{this.iteration=be(0).variable(),this.accBeta1=be(t).variable()}),n==null&&(this.epsilon=T.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(o=>o.name):Object.keys(e);Ee(()=>{let o=Ne(1,this.accBeta1),n=Ge(-this.learningRate,xe(ae(this.iteration,this.decay),1));t.forEach((s,a)=>{let i=T.registeredVariables[s],p=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${s}/m`,variable:Ut(i).variable(p)}),this.accumulatedWeightedInfNorm[a]==null&&(this.accumulatedWeightedInfNorm[a]={originalName:`${s}/v`,variable:Ut(i).variable(p)});let u=Array.isArray(e)?e[a].tensor:e[s];if(u==null)return;let c=this.accumulatedFirstMoment[a].variable,l=this.accumulatedWeightedInfNorm[a].variable,m=xe(ae(c,this.beta1),ae(u,1-this.beta1)),d=ae(l,this.beta2),f=Yt(u),h=Cd(d,f);c.assign(m),l.assign(h);let g=xe(ae(Ge(n,o),Ge(m,xe(h,this.epsilon))),i);i.assign(g)}),this.iteration.assign(xe(this.iteration,1)),this.accBeta1.assign(ae(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&Dt(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&Dt(this.accumulatedWeightedInfNorm.map(e=>e.variable))}async getWeights(){throw new Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}};Ri.className="Adamax";Er(Ri);var qs=class extends wr{constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let s=Array.isArray(e)?e[n].tensor:e[o];if(s==null)return;let a=T.registeredVariables[o];Ee(()=>{let i=xe(ae(this.c,s),a);a.assign(i)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=_r(be(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer does not have settable weights.")}getConfig(){return{learningRate:this.learningRate}}static fromConfig(e,t){return new e(t.learningRate)}};qs.className="SGD";Er(qs);var Fi=class extends qs{constructor(e,t,o=!1){super(e),this.learningRate=e,this.momentum=t,this.useNesterov=o,this.accumulations=[],this.m=be(this.momentum)}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let s=T.registeredVariables[o];this.accumulations[n]==null&&(this.accumulations[n]={originalName:`${o}/momentum`,variable:Ee(()=>Ut(s).variable(!1))});let a=this.accumulations[n].variable,i=Array.isArray(e)?e[n].tensor:e[o];i!=null&&Ee(()=>{let p,u=xe(ae(this.m,a),i);this.useNesterov?p=xe(ae(this.c,xe(i,ae(u,this.m))),s):p=xe(ae(this.c,u),s),a.assign(u),s.assign(p)})}),this.incrementIterations()}dispose(){this.m.dispose(),this.accumulations!=null&&Dt(this.accumulations.map(e=>e.variable))}setMomentum(e){this.momentum=e}async getWeights(){return[await this.saveIterations()].concat(this.accumulations.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulations=e.map(o=>({originalName:o.name,variable:o.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}}static fromConfig(e,t){return new e(t.learningRate,t.momentum,t.useNesterov)}};Fi.className="Momentum";Er(Fi);var Di=class extends wr{constructor(e,t=.9,o=0,n=null,s=!1){if(super(),this.learningRate=e,this.decay=t,this.momentum=o,this.epsilon=n,this.accumulatedMeanSquares=[],this.accumulatedMoments=[],this.accumulatedMeanGrads=[],this.centered=s,n==null&&(this.epsilon=T.backend.epsilon()),e==null)throw new Error("learningRate for RMSPropOptimizer must be defined.")}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let s=T.registeredVariables[o],a=!1;this.accumulatedMeanSquares[n]==null&&(this.accumulatedMeanSquares[n]={originalName:`${o}/rms`,variable:Ee(()=>Ut(s).variable(a))}),this.accumulatedMoments[n]==null&&(this.accumulatedMoments[n]={originalName:`${o}/momentum`,variable:Ee(()=>Ut(s).variable(a))}),this.accumulatedMeanGrads[n]==null&&this.centered&&(this.accumulatedMeanGrads[n]={originalName:`${o}/mg`,variable:Ee(()=>Ut(s).variable(a))});let i=Array.isArray(e)?e[n].tensor:e[o];if(i==null)return;let p=this.accumulatedMeanSquares[n].variable,u=this.accumulatedMoments[n].variable;Ee(()=>{let c=xe(ae(p,this.decay),ae(Qt(i),1-this.decay));if(this.centered){let l=this.accumulatedMeanGrads[n].variable,m=xe(ae(l,this.decay),ae(i,1-this.decay)),d=Ge(ae(i,this.learningRate),$r(Ne(c,xe(Qt(m),this.epsilon)))),f=xe(ae(u,this.momentum),d);p.assign(c),l.assign(m),u.assign(f);let h=Ne(s,f);s.assign(h)}else{let l=xe(ae(p,this.decay),ae(Qt(i),1-this.decay)),m=xe(ae(u,this.momentum),Ge(ae(i,this.learningRate),$r(xe(l,this.epsilon))));p.assign(l),u.assign(m);let d=Ne(s,m);s.assign(d)}})}),this.incrementIterations()}dispose(){this.accumulatedMeanSquares!=null&&Dt(this.accumulatedMeanSquares.map(e=>e.variable)),this.accumulatedMeanGrads!=null&&this.centered&&Dt(this.accumulatedMeanGrads.map(e=>e.variable)),this.accumulatedMoments!=null&&Dt(this.accumulatedMoments.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedMeanSquares,...this.accumulatedMoments];return this.centered&&e.push(...this.accumulatedMeanGrads),[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=this.centered?e.length/3:e.length/2,o=!1;this.accumulatedMeanSquares=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(o)})),this.accumulatedMoments=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(o)})),this.centered&&(this.accumulatedMeanGrads=e.slice(t*2,t*3).map(n=>({originalName:n.name,variable:n.tensor.variable(o)})))}getConfig(){return{learningRate:this.learningRate,decay:this.decay,momentum:this.momentum,epsilon:this.epsilon,centered:this.centered}}static fromConfig(e,t){return new e(t.learningRate,t.decay,t.momentum,t.epsilon,t.centered)}};Di.className="RMSProp";Er(Di);var ns=class{static sgd(e){return new qs(e)}static momentum(e,t,o=!1){return new Fi(e,t,o)}static rmsprop(e,t=.9,o=0,n=null,s=!1){return new Di(e,t,o,n,s)}static adam(e=.001,t=.9,o=.999,n=null){return new Ai(e,t,o,n)}static adadelta(e=.001,t=.95,o=null){return new Ei(e,t,o)}static adamax(e=.002,t=.9,o=.999,n=null,s=0){return new Ri(e,t,o,n,s)}static adagrad(e,t=.1){return new $i(e,t)}};var hMe={sgd:ns.sgd,momentum:ns.momentum,adadelta:ns.adadelta,adagrad:ns.adagrad,rmsprop:ns.rmsprop,adamax:ns.adamax,adam:ns.adam};var dq=(()=>typeof requestAnimationFrame!="undefined"?requestAnimationFrame:typeof setImmediate!="undefined"?setImmediate:r=>r())();function CC(){return new Promise(r=>dq(()=>r()))}var S={};Ue(S,{ERF_A1:()=>$q,ERF_A2:()=>Aq,ERF_A3:()=>Rq,ERF_A4:()=>Fq,ERF_A5:()=>Dq,ERF_P:()=>Eq,PARALLELIZE_THRESHOLD:()=>Ud,RowPartitionType:()=>Ks,SELU_SCALE:()=>_q,SELU_SCALEALPHA:()=>Tq,applyActivation:()=>yu,assertAndGetBroadcastShape:()=>Je,assertAxesAreInnerMostDims:()=>DU,assertParamsConsistent:()=>fq,assignToTypedArray:()=>Vq,axesAreInnerMostDims:()=>uC,calculateShapes:()=>Jv,checkEinsumDimSizes:()=>qq,checkPadOnDimRoundingMode:()=>Pt,combineLocations:()=>nk,combineRaggedTensorToTensorShapes:()=>gq,complexWithEvenIndex:()=>Mq,complexWithOddIndex:()=>Lq,computeConv2DInfo:()=>uu,computeConv3DInfo:()=>N0,computeDefaultPad:()=>iC,computeDilation2DInfo:()=>OW,computeOptimalWindowSize:()=>Cq,computeOutAndReduceShapes:()=>FU,computeOutShape:()=>hq,computePool2DInfo:()=>aC,computePool3DInfo:()=>PW,convertConv2DDataFormat:()=>T0,decodeEinsumEquation:()=>Gq,eitherStridesOrDilationsAreOne:()=>lr,expandShapeToKeepDim:()=>Aa,exponent:()=>Wq,exponents:()=>zq,fromStringArrayToUint8:()=>dK,fromUint8ToStringArray:()=>mK,getAxesPermutation:()=>OU,getBroadcastDims:()=>Xv,getComplexWithIndex:()=>Bq,getEinsumComputePath:()=>Kq,getEinsumPermutation:()=>Hq,getFusedBiasGradient:()=>xu,getFusedDyActivation:()=>gu,getImageCenter:()=>Sq,getInnerMostAxes:()=>MU,getPermuted:()=>Iq,getRaggedRank:()=>yq,getReductionAxes:()=>jm,getReshaped:()=>wq,getReshapedPermuted:()=>vq,getRowPartitionTypesHelper:()=>xq,getSliceBeginCoords:()=>kq,getSliceSize:()=>Nq,getSparseFillEmptyRowsIndicesDenseShapeMismatch:()=>Qq,getSparseFillEmptyRowsNegativeIndexErrorMessage:()=>Zq,getSparseFillEmptyRowsOutOfRangeIndexErrorMessage:()=>Jq,getSparseReshapeEmptyTensorZeroOutputDimErrorMessage:()=>rK,getSparseReshapeInputOutputMismatchErrorMessage:()=>nK,getSparseReshapeInputOutputMultipleErrorMessage:()=>oK,getSparseReshapeMultipleNegativeOneOutputDimErrorMessage:()=>eK,getSparseReshapeNegativeOutputDimErrorMessage:()=>tK,getSparseSegmentReductionIndicesOutOfRangeErrorMessage:()=>uK,getSparseSegmentReductionNegativeSegmentIdsErrorMessage:()=>sK,getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage:()=>aK,getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage:()=>iK,getUndoAxesPermutation:()=>PU,isIdentityPermutation:()=>jq,log:()=>GV,mergeRealAndImagArrays:()=>Oq,prepareAndValidate:()=>Zv,prepareSplitSize:()=>Yq,segment_util:()=>wC,shouldFuse:()=>bu,slice_util:()=>ut,splitRealAndImagArrays:()=>Pq,tupleValuesAreOne:()=>iu,upcastType:()=>dt,validateDefaultValueShape:()=>bq,validateInput:()=>Qm,validateUpdateShape:()=>tC,warn:()=>Os});function fq(r,e){let t=r[0].length;r.forEach((n,s)=>{E(n.length===t,()=>`Error in concat${t}D: rank of tensors[${s}] must be the same as the rank of the rest (${t})`)}),E(e>=0&&e<t,()=>`Error in concat${t}D: axis must be between 0 and ${t-1}.`);let o=r[0];r.forEach((n,s)=>{for(let a=0;a<t;a++)E(a===e||n[a]===o[a],()=>`Error in concat${t}D: Shape of tensors[${s}] (${n}) does not match the shape of the rest (${o}) along the non-concatenated axis ${s}.`)})}function hq(r,e){let t=r[0].slice();for(let o=1;o<r.length;o++)t[e]+=r[o][e];return t}var Ks;(function(r){r[r.FIRST_DIM_SIZE=0]="FIRST_DIM_SIZE",r[r.VALUE_ROWIDS=1]="VALUE_ROWIDS",r[r.ROW_LENGTHS=2]="ROW_LENGTHS",r[r.ROW_SPLITS=3]="ROW_SPLITS",r[r.ROW_LIMITS=4]="ROW_LIMITS",r[r.ROW_STARTS=5]="ROW_STARTS"})(Ks||(Ks={}));function gq(r,e,t){let o=new Array;if(t==null&&e==null)return o;if(e==null)for(;o.length<r+t.length;)o.push(-1);else o=e.slice();if(t==null)return o;if(r+t.length!==o.length)throw new Error(`rt input.shape and shape=${e} are incompatible: rt input.rank = ${r+t.length}, but shape.rank = ${o.length}`);for(let n=1;n<t.length;++n){let s=t[n],a=o[o.length-t.length+n],i=o[a];if(s>=0)if(i>=0){if(i!==s)throw new Error(`rt input.shape and shape=${e} are incompatible: rt input.shape[${n+r}] = ${s} but shape[${n+r}] = ${i}`)}else o[a]=s}return o}function xq(r){let e={FIRST_DIM_SIZE:Ks.FIRST_DIM_SIZE,VALUE_ROWIDS:Ks.VALUE_ROWIDS,ROW_LENGTHS:Ks.ROW_LENGTHS,ROW_SPLITS:Ks.ROW_SPLITS,ROW_LIMITS:Ks.ROW_LIMITS,ROW_STARTS:Ks.ROW_STARTS},t=[];for(let o of r)if(o in e)t.push(e[o]);else break;return t}function yq(r){return r.length===0?0:r[0]===Ks.FIRST_DIM_SIZE?r.length-1:r.length}function bq(r,e){if(r==null||e==null)return;let t=r.length,o=e.length;if(t>=o)throw new Error(`defaultValue.shape=${r} and ragged tensor flatValues.shape=${e}, are incompatible: defaultValue.rank = ${t} must be less than ragged tensor input flatValues.rank = ${o})`);for(let n=0;n<Math.min(t,o-1);++n){let s=r[n],a=e[n+1];if(s>=0&&a>=0&&s!==1&&s!==a)throw new Error(`defaultValue.shape=${r}, and ragged tensor input flatValues.shape=${e} are incompatible: defaultValue.shape[${n-r.length}] = ${s} but ragged tensor input.flatValues.shape[${n-r.length}] = ${a}`)}}var Ud=30;function Cq(r){return r<=Ud?r:sp(r,Math.floor(Math.sqrt(r)))}function Sq(r,e,t){let o=t*(typeof r=="number"?r:r[0]),n=e*(typeof r=="number"?r:r[1]);return[o,n]}function wq(r,e,t,o=!0){let n=[];if(o)n=n.concat(e.slice(0)),n.push(r[0]/t),n=n.concat(r.slice(1));else{n=n.concat(r[0]);let s=e.length;for(let a=0;a<s;++a)n=n.concat([r[a+1]/e[a],e[a]]);n=n.concat(r.slice(s+1))}return n}function Iq(r,e,t=!0){let o=[];if(t){o.push(e);for(let n=e+1;n<r;++n)n<=2*e?(o.push(n),o.push(n-(e+1))):o.push(n)}else{let n=[],s=[];for(let a=1;a<r;++a)a>=e*2+1||a%2===1?s.push(a):n.push(a);o.push(...n),o.push(0),o.push(...s)}return o}function vq(r,e,t,o=!0){let n=[];o?n.push(r[0]/t):n.push(r[0]*t);for(let 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o=I("elementShape",r,e,t),n=I("elementDType",r,e,t),s;r.op==="TensorListReserve"?s="numElements":s="maxNumElements";let a=I(s,r,e,t),i=r.op==="TensorListReserve"?-1:a,p=RN(o,n,a,i);return t.addTensorList(p),[p.idTensor]}case"TensorListGather":{let o=I("tensorListId",r,e,t),n=I("indices",r,e,t),s=I("elementShape",r,e,t),a=I("elementDType",r,e,t);return[t.getTensorList(o.id).gather(n,a,s)]}case"TensorListStack":{let o=I("tensorListId",r,e,t),n=I("elementShape",r,e,t),s=I("elementDType",r,e,t),a=I("numElements",r,e,t);return[t.getTensorList(o.id).stack(n,s,a)]}case"TensorListFromTensor":{let o=I("tensor",r,e,t),n=I("elementShape",r,e,t),s=I("elementDType",r,e,t),a=AN(o,n,s);return t.addTensorList(a),[a.idTensor]}case"TensorListConcat":case"TensorListConcatV2":{let o=I("tensorListId",r,e,t),n=t.getTensorList(o.id),s=I("dtype",r,e,t),a=I("elementShape",r,e,t);return[n.concat(s,a)]}case"TensorListPushBack":{let o=I("tensorListId",r,e,t),n=I("tensor",r,e,t),s=t.getTensorList(o.id);return 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n=I("strides",r,e,t),s=ul(r,e,t),a=I("dataFormat",r,e,t).toUpperCase(),i=I("dilations",r,e,t);return[o.conv2d(I("x",r,e,t),I("filter",r,e,t),[n[1],n[2]],s,a,[i[1],i[2]])]}case"_FusedConv2D":{let{stride:n,pad:s,dataFormat:a,dilations:i,biasArg:p,preluArg:u,activationFunc:c,leakyreluAlpha:l}=PN(r,e,t);return[o.fused.conv2d({x:I("x",r,e,t),filter:I("filter",r,e,t),strides:[n[1],n[2]],pad:s,dataFormat:a,dilations:[i[1],i[2]],bias:p,activation:c,preluActivationWeights:u,leakyreluAlpha:l})]}case"FusedDepthwiseConv2dNative":{let{stride:n,pad:s,dataFormat:a,dilations:i,biasArg:p,preluArg:u,activationFunc:c,leakyreluAlpha:l}=PN(r,e,t);return[o.fused.depthwiseConv2d({x:I("x",r,e,t),filter:I("filter",r,e,t),strides:[n[1],n[2]],pad:s,dataFormat:a,dilations:[i[1],i[2]],bias:p,activation:c,preluActivationWeights:u,leakyreluAlpha:l})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{let 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n=I("strides",r,e,t),s=I("pad",r,e,t),a=I("kernelSize",r,e,t),i=I("includeBatchInIndex",r,e,t),{result:p,indexes:u}=o.maxPoolWithArgmax(I("x",r,e,t),[a[1],a[2]],[n[1],n[2]],s,i);return[p,u]}case"AvgPool3D":{let n=I("strides",r,e,t),s=I("pad",r,e,t),a=I("kernelSize",r,e,t);return[o.avgPool3d(I("x",r,e,t),[a[1],a[2],a[3]],[n[1],n[2],n[3]],s)]}case"MaxPool3D":{let n=I("strides",r,e,t),s=I("pad",r,e,t),a=I("kernelSize",r,e,t);return[o.maxPool3d(I("x",r,e,t),[a[1],a[2],a[3]],[n[1],n[2],n[3]],s)]}case"Dilation2D":{let n=I("strides",r,e,t),s=I("pad",r,e,t),a=I("dilations",r,e,t),i=n[1],p=n[2],u=a[1],c=a[2];return[o.dilation2d(I("x",r,e,t),I("filter",r,e,t),[i,p],s,[u,c],"NHWC")]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var LN=(r,e,t,o=Ye)=>{switch(r.op){case"Fill":{let n=I("shape",r,e,t),s=I("dtype",r,e,t),a=I("value",r,e,t);return[o.fill(n,a,s)]}case"LinSpace":{let n=I("start",r,e,t),s=I("stop",r,e,t),a=I("num",r,e,t);return[o.linspace(n,s,a)]}case"Multinomial":{let n=I("logits",r,e,t),s=I("numSamples",r,e,t),a=I("seed",r,e,t);return[o.multinomial(n,s,a)]}case"OneHot":{let n=I("indices",r,e,t),s=I("depth",r,e,t),a=I("onValue",r,e,t),i=I("offValue",r,e,t),p=I("dtype",r,e,t);return[o.oneHot(n,s,a,i,p)]}case"Ones":return[o.ones(I("shape",r,e,t),I("dtype",r,e,t))];case"OnesLike":return[o.onesLike(I("x",r,e,t))];case"RandomStandardNormal":return[o.randomStandardNormal(I("shape",r,e,t),I("dtype",r,e,t),I("seed",r,e,t))];case"RandomUniform":return[o.randomUniform(I("shape",r,e,t),I("minval",r,e,t),I("maxval",r,e,t),I("dtype",r,e,t))];case"Range":{let n=I("start",r,e,t),s=I("stop",r,e,t),a=I("step",r,e,t);return[o.range(n,s,a,I("dtype",r,e,t))]}case"TruncatedNormal":{let n=I("shape",r,e,t),s=I("mean",r,e,t),a=I("stdDev",r,e,t),i=I("seed",r,e,t);return[o.truncatedNormal(n,s,a,I("dtype",r,e,t),i)]}case"Zeros":return[o.zeros(I("shape",r,e,t),I("dtype",r,e,t))];case"ZerosLike":return[o.zerosLike(I("x",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};function HC(r,e,t){let o=I("boxes",r,e,t),n=I("scores",r,e,t),s=I("maxOutputSize",r,e,t),a=I("iouThreshold",r,e,t),i=I("scoreThreshold",r,e,t),p=I("softNmsSigma",r,e,t);return{boxes:o,scores:n,maxOutputSize:s,iouThreshold:a,scoreThreshold:i,softNmsSigma:p}}var BN=async(r,e,t,o,n=Ye)=>{switch(r.op){case"NonMaxSuppressionV5":{let{boxes:s,scores:a,maxOutputSize:i,iouThreshold:p,scoreThreshold:u,softNmsSigma:c}=HC(r,e,t),l=await n.image.nonMaxSuppressionWithScoreAsync(s,a,i,p,u,c);return[l.selectedIndices,l.selectedScores]}case"NonMaxSuppressionV4":{let{boxes:s,scores:a,maxOutputSize:i,iouThreshold:p,scoreThreshold:u}=HC(r,e,t),c=I("padToMaxOutputSize",r,e,t),l=await n.image.nonMaxSuppressionPaddedAsync(s,a,i,p,u,c);return[l.selectedIndices,l.validOutputs]}case"NonMaxSuppressionV3":case"NonMaxSuppressionV2":{let{boxes:s,scores:a,maxOutputSize:i,iouThreshold:p,scoreThreshold:u}=HC(r,e,t);return[await n.image.nonMaxSuppressionAsync(s,a,i,p,u)]}case"Where":{let s=n.cast(I("condition",r,e,t),"bool"),a=[await n.whereAsync(s)];return s.dispose(),a}case"ListDiff":return n.setdiff1dAsync(I("x",r,e,t),I("y",r,e,t));default:throw TypeError(`Node type ${r.op} is not implemented`)}};var VN=(r,e,t,o=Ye)=>{switch(r.op){case"LowerBound":{let n=I("sortedSequence",r,e,t),s=I("values",r,e,t);return[o.lowerBound(n,s)]}case"TopKV2":{let n=I("x",r,e,t),s=I("k",r,e,t),a=I("sorted",r,e,t),i=o.topk(n,s,a);return[i.values,i.indices]}case"UpperBound":{let n=I("sortedSequence",r,e,t),s=I("values",r,e,t);return[o.upperBound(n,s)]}case"Unique":{let n=I("x",r,e,t),s=o.unique(n);return[s.values,s.indices]}case"UniqueV2":{let n=I("x",r,e,t),s=I("axis",r,e,t),a=o.unique(n,s);return[a.values,a.indices]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var zN=(r,e,t,o=Ye)=>{switch(r.op){case"Const":return e[r.name];case"PlaceholderWithDefault":let n=I("default",r,e,t);return[Gt(r.name,e,t)||n];case"Placeholder":return[Gt(r.name,e,t)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":{let c=I("x",r,e,t);return[as(c)]}case"IdentityN":return I("x",r,e,t).map(c=>as(c));case"Snapshot":let s=I("x",r,e,t);return[as(s)];case"Shape":return[o.tensor1d(I("x",r,e,t).shape,"int32")];case"ShapeN":return I("x",r,e,t).map(c=>o.tensor1d(c.shape));case"Size":return[o.scalar(I("x",r,e,t).size,"int32")];case"Rank":return[o.scalar(I("x",r,e,t).rank,"int32")];case"NoOp":return[o.scalar(1)];case"Print":let a=I("x",r,e,t),i=I("data",r,e,t),p=I("message",r,e,t),u=I("summarize",r,e,t);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(p);for(let c=0;c<i.length;c++)console.log(Array.prototype.slice.call(i[c].dataSync()).slice(0,u));return[a];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var sf=class{constructor(e,t){this.keyDType=e,this.valueDType=t,this.handle=be(0),this.tensorMap=new Map,_r(this.handle)}get id(){return this.handle.id}clearAndClose(){this.tensorMap.forEach(e=>e.dispose()),this.tensorMap.clear(),this.handle.dispose()}size(){return this.tensorMap.size}tensorSize(){return be(this.size(),"int32")}async import(e,t){this.checkKeyAndValueTensor(e,t);let o=await e.data();return this.tensorMap.forEach(n=>n.dispose()),this.tensorMap.clear(),Ee(()=>{let n=so(t),s=o.length,a=n.length;y.assert(s===a,()=>`The number of elements doesn't match, keys has ${s} elements, the values has ${a} elements.`);for(let i=0;i<s;i++){let p=o[i],u=n[i];_r(u),this.tensorMap.set(p,u)}return this.handle})}async find(e,t){this.checkKeyAndValueTensor(e,t);let o=await e.data();return Ee(()=>{let n=[];for(let s=0;s<o.length;s++){let a=o[s],i=this.findWithDefault(a,t);n.push(i)}return Sr(n)})}findWithDefault(e,t){let o=this.tensorMap.get(e);return o!=null?o:t}checkKeyAndValueTensor(e,t){if(e.dtype!==this.keyDType)throw new Error(`Expect key dtype ${this.keyDType}, but got ${e.dtype}`);if(t.dtype!==this.valueDType)throw new Error(`Expect value dtype ${this.valueDType}, but got ${t.dtype}`)}};var WN=async(r,e,t,o)=>{switch(r.op){case"HashTable":case"HashTableV2":{let n=o.getHashTableHandleByName(r.name);if(n!=null)return[n];{let s=I("keyDType",r,e,t),a=I("valueDType",r,e,t),i=new sf(s,a);return o.addHashTable(r.name,i),[i.handle]}}case"InitializeTable":case"InitializeTableV2":case"LookupTableImport":case"LookupTableImportV2":{let n=I("tableHandle",r,e,t,o),s=I("keys",r,e,t),a=I("values",r,e,t);return[await o.getHashTableById(n.id).import(s,a)]}case"LookupTableFind":case"LookupTableFindV2":{let n=I("tableHandle",r,e,t,o),s=I("keys",r,e,t),a=I("defaultValue",r,e,t);return[await o.getHashTableById(n.id).find(s,a)]}case"LookupTableSize":case"LookupTableSizeV2":{let n=I("tableHandle",r,e,t,o);return[o.getHashTableById(n.id).tensorSize()]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var UN=(r,e,t,o=Ye)=>{switch(r.op){case"ResizeBilinear":{let n=I("images",r,e,t),s=I("size",r,e,t),a=I("alignCorners",r,e,t),i=I("halfPixelCenters",r,e,t);return[o.image.resizeBilinear(n,[s[0],s[1]],a,i)]}case"ResizeNearestNeighbor":{let n=I("images",r,e,t),s=I("size",r,e,t),a=I("alignCorners",r,e,t),i=I("halfPixelCenters",r,e,t);return[o.image.resizeNearestNeighbor(n,[s[0],s[1]],a,i)]}case"CropAndResize":{let n=I("image",r,e,t),s=I("boxes",r,e,t),a=I("boxInd",r,e,t),i=I("cropSize",r,e,t),p=I("method",r,e,t),u=I("extrapolationValue",r,e,t);return[o.image.cropAndResize(n,s,a,i,p,u)]}case"ImageProjectiveTransformV3":{let n=I("images",r,e,t),s=I("transforms",r,e,t),a=I("outputShape",r,e,t),i=I("fillValue",r,e,t),p=I("interpolation",r,e,t),u=I("fillMode",r,e,t);return[o.image.transform(n,s,p.toLowerCase(),u.toLowerCase(),i,a)]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var GN=(r,e,t,o=Ye)=>{switch(r.op){case"Equal":return[o.equal(I("a",r,e,t),I("b",r,e,t))];case"NotEqual":return[o.notEqual(I("a",r,e,t),I("b",r,e,t))];case"Greater":return[o.greater(I("a",r,e,t),I("b",r,e,t))];case"GreaterEqual":return[o.greaterEqual(I("a",r,e,t),I("b",r,e,t))];case"Less":return[o.less(I("a",r,e,t),I("b",r,e,t))];case"LessEqual":return[o.lessEqual(I("a",r,e,t),I("b",r,e,t))];case"LogicalAnd":return[o.logicalAnd(I("a",r,e,t),I("b",r,e,t))];case"LogicalNot":return[o.logicalNot(I("a",r,e,t))];case"LogicalOr":return[o.logicalOr(I("a",r,e,t),I("b",r,e,t))];case"Select":case"SelectV2":return[o.where(I("condition",r,e,t),I("a",r,e,t),I("b",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var HN=(r,e,t,o=Ye)=>{switch(r.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[o.matMul(I("a",r,e,t),I("b",r,e,t),I("transposeA",r,e,t),I("transposeB",r,e,t))];case"Einsum":return[o.einsum(I("equation",r,e,t),...I("tensors",r,e,t))];case"Transpose":return[o.transpose(I("x",r,e,t),I("perm",r,e,t))];case"_FusedMatMul":let[n,s]=I("fusedOps",r,e,t),a=n==="biasadd",i=s==="prelu",p=I("numArgs",r,e,t),u=I("leakyreluAlpha",r,e,t);if(a){if(i&&p!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&p!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[c,l]=I("args",r,e,t);return[o.fused.matMul({a:I("a",r,e,t),b:I("b",r,e,t),transposeA:I("transposeA",r,e,t),transposeB:I("transposeB",r,e,t),bias:c,activation:s,preluActivationWeights:l,leakyreluAlpha:u})];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var qN=(r,e,t,o=Ye)=>{switch(r.op){case"EuclideanNorm":return[o.euclideanNorm(I("x",r,e,t),I("axis",r,e,t),I("keepDims",r,e,t))];case"FusedBatchNorm":case"FusedBatchNormV2":return[o.batchNorm(I("x",r,e,t),I("mean",r,e,t),I("variance",r,e,t),I("offset",r,e,t),I("scale",r,e,t),I("epsilon",r,e,t))];case"FusedBatchNormV3":return[o.batchNorm(I("x",r,e,t),I("mean",r,e,t),I("variance",r,e,t),I("offset",r,e,t),I("scale",r,e,t),I("epsilon",r,e,t))];case"LRN":return[o.localResponseNormalization(I("x",r,e,t),I("radius",r,e,t),I("bias",r,e,t),I("alpha",r,e,t),I("beta",r,e,t))];case"Softmax":return[o.softmax(I("x",r,e,t))];case"LogSoftmax":return[o.logSoftmax(I("x",r,e,t))];case"SparseToDense":return[o.sparseToDense(I("sparseIndices",r,e,t),I("outputShape",r,e,t),I("sparseValues",r,e,t),I("defaultValue",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var KN=(r,e,t,o=Ye)=>{switch(r.op){case"RaggedGather":{let{outputNestedSplits:n,outputDenseValues:s}=o.raggedGather(I("paramsNestedSplits",r,e,t),I("paramsDenseValues",r,e,t),I("indices",r,e,t),I("outputRaggedRank",r,e,t));return n.concat(s)}case"RaggedRange":{let{rtNestedSplits:n,rtDenseValues:s}=o.raggedRange(I("starts",r,e,t),I("limits",r,e,t),I("splits",r,e,t));return[n,s]}case"RaggedTensorToTensor":return[o.raggedTensorToTensor(I("shape",r,e,t),I("values",r,e,t),I("defaultValue",r,e,t),I("rowPartitionTensors",r,e,t),I("rowPartitionTypes",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var jN=(r,e,t,o=Ye)=>{switch(r.op){case"Max":{let i=I("axis",r,e,t),p=I("keepDims",r,e,t);return[o.max(I("x",r,e,t),i,p)]}case"Mean":{let i=I("axis",r,e,t),p=I("keepDims",r,e,t);return[o.mean(I("x",r,e,t),i,p)]}case"Min":{let i=I("axis",r,e,t),p=I("keepDims",r,e,t);return[o.min(I("x",r,e,t),i,p)]}case"Sum":{let i=I("axis",r,e,t),p=I("keepDims",r,e,t);return[o.sum(I("x",r,e,t),i,p)]}case"All":{let i=I("axis",r,e,t),p=I("keepDims",r,e,t);return[o.all(I("x",r,e,t),i,p)]}case"Any":{let i=I("axis",r,e,t),p=I("keepDims",r,e,t);return[o.any(I("x",r,e,t),i,p)]}case"ArgMax":{let i=I("axis",r,e,t);return[o.argMax(I("x",r,e,t),i)]}case"ArgMin":{let i=I("axis",r,e,t);return[o.argMin(I("x",r,e,t),i)]}case"Prod":{let i=I("axis",r,e,t),p=I("keepDims",r,e,t);return[o.prod(I("x",r,e,t),i,p)]}case"Cumprod":{let i=I("axis",r,e,t),p=I("exclusive",r,e,t),u=I("reverse",r,e,t);return[o.cumprod(I("x",r,e,t),i,p,u)]}case"Cumsum":{let i=I("axis",r,e,t),p=I("exclusive",r,e,t),u=I("reverse",r,e,t);return[o.cumsum(I("x",r,e,t),i,p,u)]}case"Bincount":let n=I("x",r,e,t),s=I("weights",r,e,t),a=I("size",r,e,t);return[o.bincount(n,s,a)];case"DenseBincount":{let i=I("x",r,e,t),p=I("weights",r,e,t),u=I("size",r,e,t),c=I("binaryOutput",r,e,t);return[o.denseBincount(i,p,u,c)]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var XN=(r,e,t,o=Ye)=>{switch(r.op){case"ConcatV2":case"Concat":{let n=I("n",r,e,t),s=I("axis",r,e,t),a=I("tensors",r,e,t);return a=a.slice(0,n),[o.concat(a,s)]}case"Gather":{let n=I("x",r,e,t),s=I("indices",r,e,t);return[o.gather(n,o.cast(s,"int32"),0)]}case"GatherV2":{let n=I("axis",r,e,t),s=I("batchDims",r,e,t),a=I("x",r,e,t),i=I("indices",r,e,t);return[o.gather(a,o.cast(i,"int32"),n,s)]}case"Reverse":{let n=I("dims",r,e,t),s=[];for(let i=0;i<n.length;i++)n[i]&&s.push(i);let a=I("x",r,e,t);return[o.reverse(a,s)]}case"ReverseV2":{let n=I("axis",r,e,t),s=I("x",r,e,t);return[o.reverse(s,n)]}case"Slice":{let n=I("begin",r,e,t),s=I("size",r,e,t);return[o.slice(I("x",r,e,t),n,s)]}case"StridedSlice":{let n=I("begin",r,e,t),s=I("end",r,e,t),a=I("strides",r,e,t),i=I("beginMask",r,e,t),p=I("endMask",r,e,t),u=I("ellipsisMask",r,e,t),c=I("newAxisMask",r,e,t),l=I("shrinkAxisMask",r,e,t),m=I("x",r,e,t);return[o.stridedSlice(m,n,s,a,i,p,u,c,l)]}case"Pack":return Ee(()=>{let n=I("axis",r,e,t),s=I("tensors",r,e,t),a=s[0].shape,i=o.squeeze(s[0]).shape,p=s.map(u=>{let c=y.arraysEqual(u.shape,a);if(!c&&!y.arraysEqual(o.squeeze(u).shape,i))throw new Error("the input tensors shape does not match");return c?u:o.reshape(u,a)});return[o.stack(p,n)]});case"Unpack":{let n=I("axis",r,e,t),s=I("tensor",r,e,t);return o.unstack(s,n)}case"Tile":{let n=I("reps",r,e,t);return[o.tile(I("x",r,e,t),n)]}case"Split":case"SplitV":{let n=I("axis",r,e,t),s=I("numOrSizeSplits",r,e,t),a=I("x",r,e,t);return o.split(a,s,n)}case"ScatterNd":{let n=I("indices",r,e,t),s=I("values",r,e,t),a=I("shape",r,e,t);return[o.scatterND(n,s,a)]}case"GatherNd":{let n=I("x",r,e,t),s=I("indices",r,e,t);return[o.gatherND(n,s)]}case"SparseToDense":{let n=I("sparseIndices",r,e,t),s=I("outputShape",r,e,t),a=I("sparseValues",r,e,t),i=I("defaultValue",r,e,t);return[o.sparseToDense(n,a,s,a.dtype===i.dtype?i:o.cast(i,a.dtype))]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var YN=(r,e,t,o=Ye)=>{switch(r.op){case"SparseFillEmptyRows":{let{outputIndices:n,outputValues:s,emptyRowIndicator:a,reverseIndexMap:i}=o.sparse.sparseFillEmptyRows(I("indices",r,e,t),I("values",r,e,t),I("denseShape",r,e,t),I("defaultValue",r,e,t));return[n,s,a,i]}case"SparseReshape":{let{outputIndices:n,outputShape:s}=o.sparse.sparseReshape(I("inputIndices",r,e,t),I("inputShape",r,e,t),I("newShape",r,e,t));return[n,s]}case"SparseSegmentMean":return[o.sparse.sparseSegmentMean(I("data",r,e,t),I("indices",r,e,t),I("segmentIds",r,e,t))];case"SparseSegmentSum":return[o.sparse.sparseSegmentSum(I("data",r,e,t),I("indices",r,e,t),I("segmentIds",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var QN=(r,e,t,o=Ye)=>{switch(r.op){case"FFT":return[o.fft(I("x",r,e,t))];case"IFFT":return[o.ifft(I("x",r,e,t))];case"RFFT":return[o.rfft(I("x",r,e,t))];case"IRFFT":return[o.irfft(I("x",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var ZN=(r,e,t,o=Ye)=>{switch(r.op){case"StringNGrams":{let{nGrams:n,nGramsSplits:s}=o.string.stringNGrams(I("data",r,e,t),I("dataSplits",r,e,t),I("separator",r,e,t),I("nGramWidths",r,e,t),I("leftPad",r,e,t),I("rightPad",r,e,t),I("padWidth",r,e,t),I("preserveShortSequences",r,e,t));return[n,s]}case"StringSplit":{let{indices:n,values:s,shape:a}=o.string.stringSplit(I("input",r,e,t),I("delimiter",r,e,t),I("skipEmpty",r,e,t));return[n,s,a]}case"StringToHashBucketFast":return[o.string.stringToHashBucketFast(I("input",r,e,t),I("numBuckets",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var JN=(r,e,t,o=Ye)=>{switch(r.op){case"Cast":return[o.cast(I("x",r,e,t),I("dtype",r,e,t))];case"ExpandDims":{let n=I("axis",r,e,t);return[o.expandDims(I("x",r,e,t),n)]}case"Squeeze":{let n=I("axis",r,e,t);return[o.squeeze(I("x",r,e,t),n)]}case"Reshape":return[o.reshape(I("x",r,e,t),I("shape",r,e,t))];case"MirrorPad":return[o.mirrorPad(I("x",r,e,t),I("padding",r,e,t),I("mode",r,e,t))];case"PadV2":case"Pad":return[o.pad(I("x",r,e,t),I("padding",r,e,t),I("constantValue",r,e,t))];case"SpaceToBatchND":{let n=I("blockShape",r,e,t),s=I("paddings",r,e,t);return[o.spaceToBatchND(I("x",r,e,t),n,s)]}case"BatchToSpaceND":{let n=I("blockShape",r,e,t),s=I("crops",r,e,t);return[o.batchToSpaceND(I("x",r,e,t),n,s)]}case"DepthToSpace":{let n=I("blockSize",r,e,t),s=I("dataFormat",r,e,t).toUpperCase();return[o.depthToSpace(I("x",r,e,t),n,s)]}case"BroadcastTo":return[o.broadcastTo(I("x",r,e,t),I("shape",r,e,t))];case"BroadcastArgs":return[o.broadcastArgs(I("s0",r,e,t),I("s1",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};function qC(r,e,t,o,n=Ee){let s=((a,i,p)=>{switch(a.category){case"arithmetic":return n(()=>_N(a,i,p));case"basic_math":return n(()=>EN(a,i,p));case"control":return ON(a,i,p);case"convolution":return n(()=>MN(a,i,p));case"creation":return n(()=>LN(a,i,p));case"dynamic":return BN(a,i,p);case"evaluation":return n(()=>VN(a,i,p));case"image":return n(()=>UN(a,i,p));case"graph":return n(()=>zN(a,i,p));case"logical":return n(()=>GN(a,i,p));case"matrices":return n(()=>HN(a,i,p));case"normalization":return n(()=>qN(a,i,p));case"ragged":return n(()=>KN(a,i,p));case"reduction":return n(()=>jN(a,i,p));case"slice_join":return n(()=>XN(a,i,p));case"sparse":return n(()=>YN(a,i,p));case"spectral":return n(()=>QN(a,i,p));case"string":return n(()=>ZN(a,i,p));case"transformation":return n(()=>JN(a,i,p));case"hash_table":return WN(a,i,p,o);case"custom":let u=Gd(a.op);if(u&&u.customExecutor)return u.customExecutor(new rf(a,i,p));throw TypeError(`Custom op ${a.op} is not registered.`);default:throw TypeError(`Unknown op '${a.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`)}})(r,e,t);return y.isPromise(s)?s.then(a=>[].concat(a)):[].concat(s)}var cl=class{constructor(e={},t={},o={},n={}){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=o,this.functionMap=n,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}newFrame(e,t){return{id:e,frameName:t,iterationId:0}}set currentContext(e){this.contexts!==e&&(this.contexts=e,this.generateCurrentContextIds())}get currentContext(){return this.contexts}get currentContextId(){return this._currentContextIds[0]}get currentContextIds(){return this._currentContextIds}generateCurrentContextIds(){let e=[];for(let t=0;t<this.contexts.length-1;t++){let o=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(o))}e.push(""),this._currentContextIds=e}contextIdforContexts(e){return e?e.map(t=>t.id===0&&t.iterationId===0?"":`${t.frameName}-${t.iterationId}`).join("/"):""}enterFrame(e){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,e)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))}exitFrame(){if(this.contexts&&this.contexts.length>1)this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift();else throw new Error("Cannot exit frame, the context is empty")}nextIteration(){if(this.contexts&&this.contexts.length>0){this.contexts=this.contexts.slice(),this.lastId++;let e=Object.assign({},this.contexts[this.contexts.length-1]);e.iterationId+=1,e.id=this.lastId,this.contexts.splice(-1,1,e),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}else throw new Error("Cannot increase frame iteration, the context is empty")}getWeight(e){return this.weightMap[e]}addTensorArray(e){this.tensorArrayMap[e.id]=e}getTensorArray(e){return this.tensorArrayMap[e]}addTensorList(e){this.tensorListMap[e.id]=e}getTensorList(e){return this.tensorListMap[e]}dispose(e){for(let t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(let t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}};function KC(r,e,t,o){let n=new Set,s=[],a=null,i=null,p=new Set,u=Object.keys(r).map(m=>Ir(m)[0]),c=[];o!=null&&(c=o.map(m=>Ir(m.name)[0]));let l=[...e];for(;l.length>0;){let m=l.pop();if((jC(m)||i6(m)||u6(m))&&a==null&&(a=m,i=a.children.map(d=>d.name).filter(d=>n.has(d))),n.add(m.name),t[m.name]==null&&u.indexOf(m.name)===-1&&c.indexOf(m.name)===-1){if(m.inputs.length===0){s.push(m.name);continue}m.inputs.forEach(d=>{p.has(d.name)||(p.add(d.name),l.push(d))})}}return{inputs:r,outputs:e,usedNodes:n,missingInputs:s,dynamicNode:a,syncInputs:i}}function eT(r,e,t){let{usedNodes:o,inputs:n}=t,s=[],a=Object.keys(n).map(c=>Ir(c)[0]).map(c=>r.nodes[c]),i=r.initNodes;a.forEach(c=>{o.has(c.name)&&s.push(c)}),r.weights.forEach(c=>{o.has(c.name)&&s.push(c)}),i!=null&&i.forEach(c=>{o.has(c.name)&&s.push(c)});let p=new Set,u=[];for(;s.length>0;){let c=s.pop();p.add(c.name),e[c.name]||u.push(c),c.children.forEach(l=>{!p.has(l.name)&&o.has(l.name)&&l.inputs.every(m=>p.has(m.name))&&s.push(l)})}return u}var n6=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],s6=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],a6=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function jC(r){return n6.indexOf(r.op)>=0}function i6(r){return s6.indexOf(r.op)>=0}function u6(r){return a6.indexOf(r.op)>=0}var Cu=class{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this.keepIntermediateTensors=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,e.functions!=null&&Object.keys(e.functions).forEach(o=>{this._functionExecutorMap[o]=new Cu(e.functions[o],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(o=>e[o].map(n=>n.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(e=>e.signatureKey||e.name)}get outputNodes(){return this._outputs.map(e=>{let t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}getCompilationKey(e,t){let o=e.map(s=>s.name).sort(),n=t.map(s=>s.name).sort();return o.join(this.SEPERATOR)+"--"+n.join(this.SEPERATOR)}compile(e,t){let o=KC(e,t,this.weightMap,this._initNodes),{missingInputs:n,dynamicNode:s,syncInputs:a}=o;if(s!=null)throw new Error(`This execution contains the node '${s.name}', which has the dynamic op '${s.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${a}]`);if(n.length>0){let i=t.map(u=>u.name),p=Object.keys(e);throw new Error(`Cannot compute the outputs [${i}] from the provided inputs [${p}]. Missing the following inputs: [${n}]`)}return eT(this.graph,this.weightMap,o)}cloneAndKeepTensor(e){if(e==null)return null;let t=e.clone();return _r(t),t}cloneTensorList(e){return e?e.map(o=>this.cloneAndKeepTensor(o)):null}cloneTensorMap(e){return Object.fromEntries(Object.entries(e).map(([t,o])=>[t,this.cloneTensorList(o)]))}execute(e,t){this.disposeIntermediateTensors(),e=this.mapInputs(e);let o=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let n=o.map(l=>this.graph.nodes[Ir(l)[0]]),s=t.map(l=>Ir(l)[0]),a=s.map(l=>this.graph.nodes[l]);a.length===0&&(a=this._outputs);let i=this.getCompilationKey(n,a),p=this.compiledMap.get(i);p==null&&(p=this.compile(e,a),this.compiledMap.set(i,p));try{this.keepIntermediateTensors=O().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(l){this.keepIntermediateTensors=!1,console.warn(l.message)}let u={},c={};return Ee(()=>{let l=new cl(this.weightMap,u,c,this.functionExecutorMap),m=Object.assign({},this.weightMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap)),Object.keys(e).forEach(h=>{let[g,x]=Ir(h),b=[];b[x]=e[h],m[g]=b,this.keepIntermediateTensors&&(this.clonedTensorsMap[g]=this.cloneTensorList(b))});let d=this.getFrozenTensorIds(m),f={};for(let h=0;h<p.length;h++){let g=p[h];if(!m[g.name]){let x=qC(g,m,l,this._resourceManager);if(y.isPromise(x))throw new Error(`The execution of the op '${g.op}' returned a promise. Please use model.executeAsync() instead.`);m[g.name]=x,this.keepIntermediateTensors&&(this.clonedTensorsMap[g.name]=this.cloneTensorList(x)),this.checkTensorForDisposal(g.name,g,m,l,d,s,f)}}return this.parent==null&&l.dispose(d),t.map(h=>Gt(h,m,l))})}getFrozenTensorIds(e){let t=[].concat.apply([],Object.keys(e).map(o=>e[o]).map(o=>o.map(n=>n.id)));return new Set(t)}checkTensorForDisposal(e,t,o,n,s,a,i){t.category==="control"||a.indexOf(e)!==-1||(o[e].forEach(p=>{p!=null&&(i[p.id]=(i[p.id]||0)+t.children.length)}),t.inputs.forEach(p=>{if(p.category!=="control"){let u=vN(p.name,o,n);u!=null&&u.forEach(c=>{if(c&&!c.kept&&!s.has(c.id)){let l=i[c.id];l===1?(c.dispose(),delete i[c.id]):l!=null&&i[c.id]--}})}}))}async executeAsync(e,t){return this._executeAsync(e,t)}disposeIntermediateTensors(){!this.clonedTensorsMap||(Object.values(this.clonedTensorsMap).forEach(e=>{for(let t of e)t&&!t.isDisposed&&t.dispose()}),this.clonedTensorsMap=null)}getIntermediateTensors(){return this.clonedTensorsMap}async _executeAsync(e,t,o=!1,n={},s={}){this.disposeIntermediateTensors(),o||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));try{this.keepIntermediateTensors=O().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(m){this.keepIntermediateTensors=!1,console.warn(m.message)}let a=new cl(this.weightMap,n,s,this.functionExecutorMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap));let i=await this.executeWithControlFlow(e,a,t,o),p=t.map(m=>Gt(m,i,a)),u=p.map(m=>m.id),c=Object.keys(e).map(m=>e[m].id),l=new Set([...u,...c,...this.weightIds]);return Object.values(i).forEach(m=>{m.forEach(d=>{d&&!d.isDisposed&&!l.has(d.id)&&d.dispose()})}),this.parent==null&&a.dispose(l),p}async executeFunctionAsync(e,t,o){let n=e.reduce((s,a,i)=>(s[this.inputs[i].name]=a,s),{});return this._executeAsync(n,this.outputNodes,!0,t,o)}async executeWithControlFlow(e,t,o,n){let s=Object.keys(e),a=s.map(C=>this.graph.nodes[Ir(C)[0]]),i=o.map(C=>Ir(C)[0]),p=i.map(C=>this.graph.nodes[C]);p.length===0&&(p=this._outputs);let{usedNodes:u,missingInputs:c,dynamicNode:l,syncInputs:m}=KC(e,p,this.weightMap,this._initNodes),d=[...a,...this.graph.weights,...this._initNodes||[]].map(C=>({node:C,contexts:t.currentContext})),f=Object.assign({},this.weightMap);Object.keys(e).forEach(C=>{let[w,k]=Ir(C),_=[];_[k]=e[C],f[w]=_});let h={},g=this.getFrozenTensorIds(f),x={};for(;d.length>0;){let C=this.processStack(a,d,t,f,x,g,i,h,u);await Promise.all(C)}l==null&&!n&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let b=p.filter(C=>!jC(C)&&!Gt(C.name,f,t)).map(C=>C.name);if(b.length>0){let C="";throw l!=null&&(C=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${m}]`),new Error(`Cannot compute the outputs [${b}] from the provided inputs [${s}]. Consider providing the following inputs: [${c}]. ${C}`)}return f}processStack(e,t,o,n,s,a,i,p,u){let c=[];for(;t.length>0;){let l=t.pop();o.currentContext=l.contexts;let m="";if(l.node.op==="Enter"&&I("isConstant",l.node,n,o)&&([m]=ss(l.node.name,o)),n[l.node.name]==null){let d=qC(l.node,n,o,this._resourceManager);m||([m]=ss(l.node.name,o));let f=o.currentContext;y.isPromise(d)?c.push(d.then(h=>(n[m]=h,this.keepIntermediateTensors&&(this.clonedTensorsMap[m]=this.cloneTensorList(h)),o.currentContext=f,this.checkTensorForDisposal(m,l.node,n,o,a,i,p),this.processChildNodes(l.node,t,o,n,s,u),h))):(n[m]=d,this.keepIntermediateTensors&&(this.clonedTensorsMap[m]=this.cloneTensorList(d)),this.checkTensorForDisposal(m,l.node,n,o,a,i,p),this.processChildNodes(l.node,t,o,n,s,u))}else this.processChildNodes(l.node,t,o,n,s,u)}return c}processChildNodes(e,t,o,n,s,a){e.children.forEach(i=>{let[p]=ss(i.name,o);s[p]||!a.has(i.name)||(i.op==="Merge"?i.inputNames.some(u=>!!Gt(u,n,o))&&(s[p]=!0,t.push({contexts:o.currentContext,node:i})):i.inputNames.every(u=>!!Gt(u,n,o))&&(s[p]=!0,t.push({contexts:o.currentContext,node:i})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let o=e[t],[n]=Ir(t),s=this.graph.nodes[n];if(s.attrParams.shape&&s.attrParams.shape.value){let a=s.attrParams.shape.value,i=a.length===o.shape.length&&o.shape.every((p,u)=>a[u]===-1||a[u]===p);y.assert(i,()=>`The shape of dict['${s.name}'] provided in model.execute(dict) must be [${a}], but was [${o.shape}]`)}s.attrParams.dtype&&s.attrParams.dtype.value&&y.assert(o.dtype===s.attrParams.dtype.value,()=>`The dtype of dict['${s.name}'] provided in model.execute(dict) must be ${s.attrParams.dtype.value}, but was ${o.dtype}`)})}mapInputs(e){var t,o;let n={};for(let s in e){let a=(o=(t=this._signature)===null||t===void 0?void 0:t.inputs)===null||o===void 0?void 0:o[s];a!=null?n[a.name]=e[s]:n[s]=e[s]}return n}checkInputs(e){let t=Object.keys(e).filter(o=>{let[n]=Ir(o);return this.graph.nodes[n]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map(t=>{var o,n;let s=(n=(o=this._signature)===null||o===void 0?void 0:o.outputs)===null||n===void 0?void 0:n[t];return s!=null?s.name:t},{})}checkOutputs(e){e.forEach(t=>{let[o]=Ir(t);if(!this.graph.nodes[o])throw new Error(`The output '${t}' is not found in the graph`)})}};var af=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}};var p6="?tfjs-format=file",c6="model.json",ll=class{constructor(e,t={},o=Ea){this.modelUrl=e,this.loadOptions=t,this.version="n/a",this.io=o,t==null&&(this.loadOptions={}),this.resourceManager=new af}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=this.io.browserHTTPRequest(e,this.loadOptions);else{let t=this.io.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(this.io.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=this.handler.load();return y.isPromise(e)?e.then(t=>this.loadSync(t)):this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,o=this.artifacts.signature;if(this.artifacts.userDefinedMetadata!=null){let s=this.artifacts.userDefinedMetadata;s.signature!=null&&(o=s.signature),s.structuredOutputKeys!=null&&(this.structuredOutputKeys=s.structuredOutputKeys)}this.signature=o,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let n=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new Cu(pl.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(n),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let s=pl.Instance.transformGraph(e.modelInitializer);this.initializer=new Cu(s),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializerSignature=e.initializerSignature}return!0}async save(e,t){if(typeof e=="string"){let o=this.io.getSaveHandlers(e);if(o.length===0)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(o.length>1)throw new Error(`Found more than one (${o.length}) save handlers for URL '${e}'`);e=o[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 it?[e]:e,o={};return t.forEach((n,s)=>o[this.structuredOutputKeys[s]]=n),o}return e}predict(e,t){let o=this.execute(e,this.outputNodes);return this.addStructuredOutputNames(o)}async predictAsync(e,t){let o=await this.executeAsync(e,this.outputNodes);return this.addStructuredOutputNames(o)}normalizeInputs(e){var t;if(!(e instanceof it)&&!Array.isArray(e)){let s=(t=this.signature)===null||t===void 0?void 0:t.inputs;if(s!=null)for(let a in s){let i=s[a];i.resourceId!=null&&(e[a]=this.resourceIdToCapturedInput[i.resourceId])}return e}e=Array.isArray(e)?e:[e];let o=Object.keys(this.resourceIdToCapturedInput).length;if(e.length+o!==this.inputNodes.length)throw new Error(`Input tensor count mismatch, the graph model has ${this.inputNodes.length-o} non-resource placeholders, while there are ${e.length} input tensors provided.`);let n=0;return this.inputNodes.reduce((s,a)=>{var i,p,u;let c=(u=(p=(i=this.signature)===null||i===void 0?void 0:i.inputs)===null||p===void 0?void 0:p[a])===null||u===void 0?void 0:u.resourceId;return c!=null?s[a]=this.resourceIdToCapturedInput[c]:s[a]=e[n++],s},{})}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,o=Object.keys(t);for(let n=0;n<o.length;n++){let s=o[n],a=t[s];this.resourceIdToCapturedInput[a.resourceId]=e[n]}}}execute(e,t){this.resourceIdToCapturedInput==null&&this.setResourceIdToCapturedInput(this.executeInitializerGraph()),e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let o=this.executor.execute(e,t);return o.length>1?o:o[0]}async executeAsync(e,t){this.resourceIdToCapturedInput==null&&this.setResourceIdToCapturedInput(await this.executeInitializerGraphAsync()),e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let o=await this.executor.executeAsync(e,t);return o.length>1?o:o[0]}getIntermediateTensors(){return this.executor.getIntermediateTensors()}disposeIntermediateTensors(){this.executor.disposeIntermediateTensors()}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,o)=>(t[o]=[e[o]],t),{})}dispose(){this.executor.dispose(),this.initializer&&(this.initializer.dispose(),this.resourceIdToCapturedInput&&Dt(this.resourceIdToCapturedInput)),this.resourceManager.dispose()}};async function l6(r,e={},t=Ea){if(r==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");e==null&&(e={}),e.fromTFHub&&typeof r=="string"&&(r=d6(r));let o=new ll(r,e,t);return await o.load(),o}function m6(r){if(r==null)throw new Error("modelUrl in loadGraphModelSync() cannot be null. Please provide model artifacts or an IOHandler that loads the model");let e;if(r instanceof Array){let[o,n]=r;if(!o)throw new Error("modelJSON must be the first element of the array");if(!n||!(n instanceof ArrayBuffer))throw new Error("An ArrayBuffer of weights must be the second element of the array");if(!("modelTopology"in o))throw new Error("Model JSON is missing 'modelTopology'");if(!("weightsManifest"in o))throw new Error("Model JSON is missing 'weightsManifest'");let s=Ea.getWeightSpecs(o.weightsManifest),a=Ea.getModelArtifactsForJSONSync(o,s,n);e=Ea.fromMemorySync(a)}else if("load"in r)e=r;else if("modelTopology"in r&&"weightSpecs"in r&&"weightData"in r)e=Ea.fromMemorySync(r);else throw new Error("Unknown model format");let t=new ll(e);return t.load(),t}function d6(r){return r.endsWith("/")||(r=r+"/"),`${r}${c6}${p6}`}var f6="4.1.0";function K(r,e){Array.isArray(r)||(r=[r]),r.forEach(t=>{t!=null&&y.assert(t.dtype!=="complex64",()=>`${e} does not support complex64 tensors in the CPU backend.`)})}var h6=Lt.whereImpl,Oi=class extends Zr{constructor(){super(),this.blockSize=48,this.firstUse=!0,this.data=new Do(this,cr())}nextDataId(){return Oi.nextDataId++}write(e,t,o){this.firstUse&&(this.firstUse=!1,O().get("IS_NODE")&&S.warn(`
============================
Hi, looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, visit https://github.com/tensorflow/tfjs-node for more details. 
============================`));let n={id:this.nextDataId()};return this.data.set(n,{values:e,dtype:o,refCount:1}),n}makeTensorInfo(e,t,o){let n;if(t==="string"&&o!=null&&o.length>0&&y.isString(o[0])){let s=o.map(a=>y.encodeString(a));n=this.write(s,e,t)}else n=this.write(o,e,t);return{dataId:n,shape:e,dtype:t}}refCount(e){return this.data.has(e)?this.data.get(e).refCount:0}incRef(e){let t=this.data.get(e);t.refCount++}decRef(e){if(this.data.has(e)){let t=this.data.get(e);t.refCount--}}move(e,t,o,n,s){this.data.set(e,{values:t,dtype:n,refCount:s})}numDataIds(){return this.data.numDataIds()}async read(e){return this.readSync(e)}readSync(e){let{dtype:t,complexTensorInfos:o}=this.data.get(e);if(t==="complex64"){let n=this.readSync(o.real.dataId),s=this.readSync(o.imag.dataId);return S.mergeRealAndImagArrays(n,s)}return this.data.get(e).values}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let o=t.map(n=>y.decodeString(n));return le(e.shape,e.dtype,o)}catch(o){throw new Error("Failed to decode encoded string bytes into utf-8")}return le(e.shape,e.dtype,t)}makeOutput(e,t,o){return cr().makeTensorFromTensorInfo(this.makeTensorInfo(t,o,e),this)}disposeData(e,t=!1){if(this.data.has(e)){if(this.data.get(e).refCount--,!t&&this.data.get(e).refCount>0)return!1;let{complexTensorInfos:o}=this.data.get(e);o!=null&&(this.disposeData(o.real.dataId,!0),this.disposeData(o.imag.dataId,!0)),this.data.delete(e)}return!0}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}async time(e){let t=y.now();return e(),{kernelMs:y.now()-t}}memory(){return{unreliable:!0,reasons:["The reported memory is an upper bound. Due to automatic garbage collection, the true allocated memory may be less."]}}where(e){K([e],"where");let t=this.readSync(e.dataId);return h6(e.shape,t)}dispose(){}floatPrecision(){return 32}epsilon(){return super.epsilon()}};Oi.nextDataId=0;var 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ko=S.RowPartitionType,Xp=class{constructor(e,t,o,n,s,a,i,p,u,c){this.shape=e,this.shapeShape=t,this.values=o,this.valuesShape=n,this.valuesDType=s,this.defaultValue=a,this.defaultValueShape=i,this.rowPartitionValues=p,this.rowPartitionValuesShapes=u,this.rowPartitionTypes=S.getRowPartitionTypesHelper(c),this.raggedRank=S.getRaggedRank(this.rowPartitionTypes)}getRowPartitionTypeByDimension(e){return this.rowPartitionTypes[0]===ko.FIRST_DIM_SIZE?this.rowPartitionTypes[e+1]:this.rowPartitionTypes[e]}getRowPartitionTensor(e){return this.rowPartitionTypes[0]===ko.FIRST_DIM_SIZE?this.rowPartitionValues[e+1]:this.rowPartitionValues[e]}getMaxWidth(e){let t=this.getRowPartitionTensor(e-1);switch(this.getRowPartitionTypeByDimension(e-1)){case ko.VALUE_ROWIDS:return Xp.getMaxWidthValueRowID(t);case ko.ROW_SPLITS:return Xp.getMaxWidthRowSplit(t);default:throw new Error(`Cannot handle partition type ${ko[this.getRowPartitionTypeByDimension(e-1)]}`)}}static getMaxWidthRowSplit(e){let 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firstDimension."),s}calculateOutputIndexRowSplit(e,t,o,n){let s=e.length,a=[];for(let i=0;i<s-1;++i){let p=e[i+1]-e[i],u=Math.min(n,p),c=t[i];c===-1&&(u=0);for(let l=0;l<u;++l)a.push(c),c+=o;for(let l=0;l<p-u;++l)a.push(-1)}if(s>0&&a.length!==e[s-1])throw new Error("Invalid row split size.");return a}calculateOutputIndexValueRowID(e,t,o,n){let s=e.length,a=[];if(s===0)return[];let i=0,p=e[0];if(p>=t.length)throw new Error(`Got currentValueRowId=${p}, which is not less than ${t.length}`);let u=t[p];a.push(u);for(let c=1;c<s;++c){let l=e[c];if(l===p)u>=0&&(++i,i<n?u+=o:u=-1);else{if(i=0,p=l,l>=t.length)throw new Error(`Got nextValueRowId=${l} which is not less than ${t.length}`);u=t[l]}a.push(u)}if(a.length!==e.length)throw new Error("Invalid row ids.");return a}calculateOutputIndex(e,t,o,n){let s=this.getRowPartitionTensor(e),a=this.getRowPartitionTypeByDimension(e);switch(a){case ko.VALUE_ROWIDS:return this.calculateOutputIndexValueRowID(s,t,o,n);case ko.ROW_SPLITS:if(s.length-1>t.length)throw new Error(`Row partition size is greater than output size: ${s.length-1} > ${t.length}`);return this.calculateOutputIndexRowSplit(s,t,o,n);default:throw new Error(`Unsupported partition type: ${ko[a]}`)}}getFirstDimensionSize(){let e=this.rowPartitionValues[0];if(this.rowPartitionTypes.length===0)throw new Error("No row_partition_types given.");let t=this.rowPartitionTypes[0];switch(t){case ko.FIRST_DIM_SIZE:return e[0];case ko.VALUE_ROWIDS:throw new Error("Cannot handle VALUE_ROWIDS in first dimension.");case ko.ROW_SPLITS:return this.rowPartitionValuesShapes[0][0]-1;default:throw new Error(`Cannot handle type ${ko[t]}`)}}compute(){if(this.rowPartitionValues[0].length<=0)throw new Error("Invalid first partition input. 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p=="number"?d.values.fill(p):typeof p=="boolean"&&d.values.fill(+p);for(let f=0;f<s;f++){let h=[],g=0;for(let x=0;x<a;x++){let b=l[f*a+x];h.push(b),g+=b*i[x]}if(g<0||g>=o/n)throw new Error(`Invalid indices: ${h} does not index into ${t}`);for(let x=0;x<n;x++)u?d.values[g*n+x]+=m[f*n+x]:d.values[g*n+x]=e.rank===0?m[0]:m[f*n+x]}return d}var ET=vr(r=>1/(1+Math.exp(-r))),gS=Ie(Un,r=>1/(1+Math.exp(-r))),$T={kernelName:Un,backendName:"cpu",kernelFunc:gS};function vu(r,e,t,o,n){let s=ut.isSliceContinous(o,e,t),a=y.sizeFromShape(t),i=y.computeStrides(o);if(s){let l=ut.computeFlatOffset(e,i);return n==="string"?r.slice(l,l+a):r.subarray(l,l+a)}let p=n==="string"?S.fromUint8ToStringArray(r):r,u=le(o,n,p),c=le(t,n);for(let l=0;l<c.size;++l){let m=c.indexToLoc(l),d=m.map((f,h)=>f+e[h]);c.set(u.get(...d),...m)}return n==="string"?S.fromStringArrayToUint8(c.values):c.values}function 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l=dt(u.dtype,"int32"),m=y.makeOnesTypedArray(y.sizeFromShape(u.shape),l),d=t.data.get(u.dataId).values,f=u.shape[u.shape.length-1],h=i?(x,b)=>x+f-b-1:(x,b)=>x+b;for(let x=0;x<d.length;x+=f)for(let b=0;b<f;b++){let C=h(x,b);if(b===0)m[C]=a?1:d[C];else{let w=h(x,b-1);m[C]=a?d[w]*m[w]:d[C]*m[w]}}let g=t.makeTensorInfo(u.shape,l,m);if(p!=null){let x=S.getUndoAxesPermutation(p),b=Ct({inputs:{x:g},backend:t,attrs:{perm:x}});return t.disposeIntermediateTensorInfo(g),t.disposeIntermediateTensorInfo(u),b}return g}var k2={kernelName:jo,backendName:"cpu",kernelFunc:Ij};function vj(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,exclusive:a,reverse:i}=o;K(n,"cumsum");let p=S.getAxesPermutation([s],n.shape.length),u=n;p!=null&&(u=Ct({inputs:{x:n},backend:t,attrs:{perm:p}}));let c=S.getInnerMostAxes(1,n.shape.length)[0];if(c!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${c}`);let l=dt(u.dtype,"int32"),m=y.makeZerosTypedArray(y.sizeFromShape(u.shape),l),d=t.data.get(u.dataId).values,f=u.shape[u.shape.length-1],h=i?(x,b)=>x+f-b-1:(x,b)=>x+b;for(let x=0;x<d.length;x+=f)for(let b=0;b<f;b++){let C=h(x,b);if(b===0)m[C]=a?0:d[C];else{let w=h(x,b-1);m[C]=a?d[w]+m[w]:d[C]+m[w]}}let g=t.makeTensorInfo(u.shape,l,m);if(p!=null){let x=S.getUndoAxesPermutation(p),b=Ct({inputs:{x:g},backend:t,attrs:{perm:x}});return t.disposeIntermediateTensorInfo(g),t.disposeIntermediateTensorInfo(u),b}return g}var N2={kernelName:Xo,backendName:"cpu",kernelFunc:vj};function kj(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a,binaryOutput:i}=o;if(n.shape.length===1){let p=t.data.get(n.dataId).values,u=t.data.get(s.dataId).values,c=Kp(p,u,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,c)}else if(n.shape.length===2){let p=t.bufferSync(n),u=t.bufferSync(s),c=uf(p,u,a,i);return t.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be 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Tj(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,dy:s}=e,{strides:a,dilations:i,pad:p,dimRoundingMode:u,filterShape:c}=o;K([n,s],"depthwiseConv2dNativeBackpropFilter");let l=S.computeConv2DInfo(n.shape,c,a,i,p,u,!0),{strideHeight:m,strideWidth:d,filterHeight:f,filterWidth:h}=l,g=new st(l.filterShape,"float32"),x=l.padInfo.left,b=l.padInfo.top,C=l.outChannels/l.inChannels,w=t.data.get(n.dataId).values,k=new st(n.shape,n.dtype,w),_=t.data.get(s.dataId).values,$=new st(s.shape,s.dtype,_);for(let A=0;A<f;++A){let R=Math.max(0,Math.ceil((b-A)/m)),D=Math.min(l.outHeight,(l.inHeight+b-A)/m);for(let P=0;P<h;++P){let M=Math.max(0,Math.ceil((x-P)/d)),L=Math.min(l.outWidth,(l.inWidth+x-P)/d);for(let W=0;W<l.outChannels;++W){let V=Math.trunc(W/C),U=W%C,q=0;for(let H=0;H<l.batchSize;++H)for(let j=R;j<D;++j){let X=A+j*m-b;for(let Z=M;Z<L;++Z){let ee=P+Z*d-x;q+=k.get(H,X,ee,V)*$.get(H,j,Z,W)}}g.set(q,A,P,V,U)}}}return t.makeTensorInfo(g.shape,g.dtype,g.values)}var $2={kernelName:dp,backendName:"cpu",kernelFunc:Tj};function _j(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{strides:a,dilations:i,pad:p,dimRoundingMode:u,inputShape:c}=o;K([n,s],"depthwiseConv2DNativeBackpropInput");let l=y.computeStrides(n.shape),m=y.computeStrides(s.shape),d=S.computeConv2DInfo(c,s.shape,a,i,p,u,!0),f=new st(d.inShape,"float32"),h=f.values,[g,x,b]=f.strides,C=t.data.get(n.dataId).values,[w,k,_]=l,$=t.data.get(s.dataId).values,[A,R,D]=m,{batchSize:P,filterHeight:M,filterWidth:L,inChannels:W,inHeight:V,inWidth:U,outChannels:q,outHeight:H,outWidth:j,strideHeight:X,strideWidth:Z}=d,ee=M-1-d.padInfo.top,Y=L-1-d.padInfo.left,J=q/W;for(let ie=0;ie<P;++ie)for(let pe=0;pe<W;++pe)for(let he=0;he<V;++he){let we=he-ee,ve=Math.max(0,Math.ceil(we/X)),$e=Math.min(H,(M+we)/X);for(let Le=0;Le<U;++Le){let nt=Le-Y,pt=Math.max(0,Math.ceil(nt/Z)),Oe=Math.min(j,(L+nt)/Z),mt=0;for(let at=ve;at<$e;++at){let ft=at*X-we;for(let wt=pt;wt<Oe;++wt){let 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F2={kernelName:gp,backendName:"cpu",kernelFunc:({inputs:r,backend:e,attrs:t})=>{let{x:o,filter:n}=r,{strides:s,pad:a,dilations:i}=t,p=e,u=p.data.get(o.dataId).values,c=o.shape.length,l=p.data.get(n.dataId).values,m=n.shape.length,{batchSize:d,inHeight:f,inWidth:h,inChannels:g,outHeight:x,outWidth:b,padInfo:C,strideHeight:w,strideWidth:k,filterHeight:_,filterWidth:$,dilationHeight:A,dilationWidth:R,outShape:D}=S.computeDilation2DInfo(o.shape,n.shape,s,a,"NHWC",i),P=y.sizeFromShape(D),M=D.length,L=y.getArrayFromDType(o.dtype,P);for(let V=0;V<d;++V)for(let U=0;U<x;++U){let q=U*w-C.top;for(let H=0;H<b;++H){let j=H*k-C.left;for(let X=0;X<g;++X){let Z=Number.MIN_SAFE_INTEGER;for(let Y=0;Y<_;++Y){let J=q+Y*A;if(J>=0&&J<f)for(let ie=0;ie<$;++ie){let pe=j+ie*R;if(pe>=0&&pe<h){let he=y.locToIndex([V,J,pe,X],c,y.computeStrides(o.shape)),we=y.locToIndex([Y,ie,X],m,y.computeStrides(n.shape)),ve=u[he]+l[we];ve>Z&&(Z=ve)}}}let 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D=y.toNestedArray(R,u.data.get(s.dataId).values),P=y.makeZerosNestedTypedArray(o.shape,o.dtype);for(let L=0;L<m;++L)for(let W=0;W<g;++W){let V=W*C-b.top;for(let U=0;U<x;++U){let q=U*w-b.left;for(let H=0;H<h;++H){let j=Number.MIN_SAFE_INTEGER,X=V<0?0:V,Z=q<0?0:q;for(let ee=0;ee<k;++ee){let Y=V+ee*$;if(Y>=0&&Y<d)for(let J=0;J<_;++J){let ie=q+J*A;if(ie>=0&&ie<f){let pe=c[L][Y][ie][H]+l[ee][J][H];pe>j&&(j=pe,X=Y,Z=ie)}}}P[L][X][Z][H]+=D[L][W][U][H]}}}return{dataId:u.write(y.toTypedArray(P,o.dtype),o.shape,o.dtype),shape:o.shape,dtype:o.dtype}}};function La(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o;K(n,"sum");let i;n.dtype==="bool"?i=Io({inputs:{x:n},backend:t,attrs:{dtype:"int32"}}):i=ar({inputs:{x:n},backend:t});let p=i.shape.length,u=y.parseAxisParam(s,i.shape),c=S.getAxesPermutation(u,p),l=u,m=i;c!=null&&(m=Ct({inputs:{x:i},backend:t,attrs:{perm:c}}),l=S.getInnerMostAxes(l.length,p)),S.assertAxesAreInnerMostDims("sum",l,m.shape.length);let[d,f]=S.computeOutAndReduceShapes(m.shape,l),h=S.upcastType(m.dtype,"int32"),g=Hp(t,d,h),x=y.sizeFromShape(f),b=t.data.get(g.dataId).values,C=t.data.get(m.dataId).values;for(let w=0;w<b.length;++w){let k=w*x,_=0;for(let $=0;$<x;++$)_+=C[k+$];b[w]=_}if(a){let w=S.expandShapeToKeepDim(g.shape,u),k=g;g=Me({inputs:{x:g},backend:t,attrs:{shape:w}}),t.disposeIntermediateTensorInfo(k)}return t.disposeIntermediateTensorInfo(i),c!=null&&t.disposeIntermediateTensorInfo(m),g}var P2={kernelName:Hn,backendName:"cpu",kernelFunc:La};function 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Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${r}.`)});Ce.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);Ce.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);Ce.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);Ce.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);Ce.registerFlag("WEBGL_EXP_CONV",()=>!1);Ce.registerFlag("SOFTWARE_WEBGL_ENABLED",()=>Ce.getBool("IS_TEST"));Ce.registerFlag("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE",()=>1/0);Ce.registerFlag("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE",()=>!1);Ce.registerFlag("WEBGL2_ISNAN_CUSTOM",()=>!1);Ce.registerFlag("ENGINE_COMPILE_ONLY",()=>!1);function St(){let r,e,t,o,n,s,a,i,p,u;return O().getNumber("WEBGL_VERSION")===2?(r="#version 300 es",e="in",t="out",o="in",n="texture",s="outputColor",a="out vec4 outputColor;",i=O().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)
    `:"",p="",u=`
      #define round(value) newRound(value)
      int newRound(float value) {
        return int(floor(value + 0.5));
      }

      ivec4 newRound(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `):(r="",e="attribute",t="varying",o="varying",n="texture2D",s="gl_FragColor",a="",i=`
      #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));
      }
    `,p=`
      uniform float INFINITY;

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

      ivec4 round(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `),{version:r,attribute:e,varyingVs:t,varyingFs:o,texture2D:n,output:s,defineOutput:a,defineSpecialNaN:i,defineSpecialInf:p,defineRound:u}}function us(r,e,t="index"){let o=y.computeStrides(e);return o.map((n,s)=>{let a=`int ${r[s]} = ${t} / ${n}`,i=s===o.length-1?`int ${r[s+1]} = ${t} - ${r[s]} * ${n}`:`index -= ${r[s]} * ${n}`;return`${a}; ${i};`}).join("")}function Au(r,e,t="index"){let o=y.computeStrides(e);return o.map((n,s)=>{let a=`int ${r[s]} = ${t} / outShapeStrides[${s}]`,i=s===o.length-1?`int ${r[s+1]} = ${t} - ${r[s]} * outShapeStrides[${s}]`:`index -= ${r[s]} * outShapeStrides[${s}]`;return`${a}; ${i};`}).join("")}function B5(r,e){let t=r.length,o=r.map(s=>`${e}[${s}]`),n=new Array(t-1);n[t-2]=o[t-1];for(let s=t-3;s>=0;--s)n[s]=`(${n[s+1]} * ${o[s+1]})`;return n}function kE(r,e,t="index"){let o=r.map((s,a)=>a),n=B5(o,e);return n.map((s,a)=>{let i=`int ${r[a]} = ${t} / ${n[a]}`,p=a===n.length-1?`int ${r[a+1]} = ${t} - ${r[a]} * ${n[a]}`:`index -= ${r[a]} * ${n[a]}`;return`${i}; ${p};`}).join("")}function nc(r){let e=y.computeStrides(r).map(t=>t.toString());return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * ${e[0]} + coords.y * ${e[1]} + coords.z;
  }
`}function sc(){return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
  }
`}var Df=`
  const float FLOAT_MAX = 1.70141184e38;
  const float FLOAT_MIN = 1.17549435e-38;

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

    highp float av = abs(v);

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

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

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

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

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

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

    return c / 255.0;
  }
`;var{getBroadcastDims:NE}=S;function TE(r,e,t){let o=[];if(r.forEach(d=>{let f=y.sizeFromShape(d.shapeInfo.logicalShape);if(d.shapeInfo.isUniform?o.push(`uniform float ${d.name}${f>1?`[${f}]`:""};`):(o.push(`uniform sampler2D ${d.name};`),o.push(`uniform int offset${d.name};`)),t.enableShapeUniforms){let{uniformShape:h}=Of(t.packedInputs,d.shapeInfo.logicalShape,d.shapeInfo.texShape);switch(h.length){case 1:o.push(`uniform int ${d.name}Shape;`);break;case 2:o.push(`uniform ivec2 ${d.name}Shape;`);break;case 3:o.push(`uniform ivec3 ${d.name}Shape;`);break;case 4:o.push(`uniform ivec4 ${d.name}Shape;`);break;default:break}o.push(`uniform ivec2 ${d.name}TexShape;`)}}),t.enableShapeUniforms){switch(e.logicalShape.length){case 1:o.push("uniform int outShape;");break;case 2:o.push("uniform ivec2 outShape;"),o.push("uniform int outShapeStrides;");break;case 3:o.push("uniform ivec3 outShape;"),o.push("uniform ivec2 outShapeStrides;");break;case 4:o.push("uniform ivec4 outShape;"),o.push("uniform ivec3 outShapeStrides;");break;default:break}o.push("uniform ivec2 outTexShape;")}t.customUniforms&&t.customUniforms.forEach(d=>{o.push(`uniform ${d.type} ${d.name}${d.arrayIndex?`[${d.arrayIndex}]`:""};`)});let n=o.join(`
`),s=r.map(d=>V5(d,e,t.packedInputs,t.enableShapeUniforms)).join(`
`),a=e.texShape,i=St(),p=U5(i),u,c,l=q5(i);return e.isPacked?(u=z5(e.logicalShape,a,t.enableShapeUniforms),c=H5(i)):(u=W5(e.logicalShape,a,t.enableShapeUniforms),c=G5(i)),t.packedInputs&&(l+=Y5),[l,p,c,n,u,s,t.userCode].join(`
`)}function ic(r,e=!1){let t=r.shapeInfo.logicalShape;switch(t.length){case 0:return u8(r,e);case 1:return c8(r,e);case 2:return m8(r,e);case 3:return f8(r,e);case 4:return g8(r,e);case 5:return x8(r);case 6:return y8(r);default:throw new Error(`${t.length}-D input sampling is not yet supported`)}}function _E(r,e){switch(r.shapeInfo.logicalShape.length){case 0:return i8(r);case 1:return p8(r,e);case 2:return l8(r,e);case 3:return d8(r,e);default:return h8(r,e)}}function V5(r,e,t=!1,o){let n="";t?n+=_E(r,o):n+=ic(r,o);let s=r.shapeInfo.logicalShape,a=e.logicalShape;return s.length<=a.length&&(t?n+=b8(r,e):n+=C8(r,e)),n}function z5(r,e,t){switch(r.length){case 0:return EE();case 1:return Q5(r,e,t);case 2:return s8(r,e,t);case 3:return J5(r,e,t);default:return t8(r,e,t)}}function W5(r,e,t){switch(r.length){case 0:return EE();case 1:return Z5(r,e,t);case 2:return a8(r,e,t);case 3:return e8(r,e,t);case 4:return r8(r,e,t);case 5:return o8(r,e);case 6:return n8(r,e);default:throw new Error(`${r.length}-D output sampling is not yet supported`)}}function U5(r){return`
    float sampleTexture(sampler2D textureSampler, vec2 uv) {
      return ${r.texture2D}(textureSampler, uv).r;
    }
  `}function G5(r){return`
    void setOutput(float val) {
      ${r.output} = vec4(val, 0, 0, 0);
    }
  `}function H5(r){return`
    void setOutput(vec4 val) {
      ${r.output} = val;
    }
  `}function q5(r){return`${r.version}
    precision highp float;
    precision highp int;
    precision highp sampler2D;
    ${r.varyingFs} vec2 resultUV;
    ${r.defineOutput}
    const vec2 halfCR = vec2(0.5, 0.5);

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

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

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

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

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

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

    ${K5}
    ${j5}
    ${X5}
  `}var K5=`
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);
}
`,j5=`
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);
}
`,X5=`
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);
}
`,Y5=`
  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 EE(){return`
    int getOutputCoords() {
      return 0;
    }
  `}function Q5(r,e,t){let o=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];return o[0]===1?t?`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
      }
    `:`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ${o[1]}.0);
      }
    `:o[1]===1?t?`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
      }
    `:`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ${o[0]}.0);
      }
    `:t?`
    int getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
    }
  `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${o[0]}, ${o[1]}));
      return 2 * (resTexRC.x * ${o[1]} + resTexRC.y);
    }
  `}function Z5(r,e,t){return e[0]===1?t?`
      int getOutputCoords() {
        return int(resultUV.x * float(outTexShape[1]));
      }
    `:`
      int getOutputCoords() {
        return int(resultUV.x * ${e[1]}.0);
      }
    `:e[1]===1?t?`
      int getOutputCoords() {
        return int(resultUV.y * float(outTexShape[0]));
      }
    `:`
      int getOutputCoords() {
        return int(resultUV.y * ${e[0]}.0);
      }
    `:t?`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(outTexShape[0], outTexShape[1]));
      return resTexRC.x * outTexShape[1] + resTexRC.y;
    }
  `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${e[0]}, ${e[1]}));
      return resTexRC.x * ${e[1]} + resTexRC.y;
    }
  `}function J5(r,e,t){if(t)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 o=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],n=Math.ceil(r[2]/2),s=n*Math.ceil(r[1]/2);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${o[0]}, ${o[1]}));
      int index = resTexRC.x * ${o[1]} + resTexRC.y;

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

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

      return ivec3(b, r, c);
    }
  `}function e8(r,e,t){if(t)return`
  ivec3 getOutputCoords() {
    ivec2 resTexRC = ivec2(resultUV.yx *
                           vec2(outTexShape[0], outTexShape[1]));
    int index = resTexRC.x * outTexShape[1] + resTexRC.y;
    ${Au(["r","c","d"],r)}
    return ivec3(r, c, d);
  }
`;let o=us(["r","c","d"],r);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${e[0]}, ${e[1]}));
      int index = resTexRC.x * ${e[1]} + resTexRC.y;
      ${o}
      return ivec3(r, c, d);
    }
  `}function t8(r,e,t){if(t)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 o=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],n=Math.ceil(r[r.length-1]/2),s=n*Math.ceil(r[r.length-2]/2),a=s,i="",p="b, r, c";for(let u=2;u<r.length-1;u++)a*=r[r.length-u-1],i=`
      int b${u} = index / ${a};
      index -= b${u} * ${a};
    `+i,p=`b${u}, `+p;return`
    ivec${r.length} getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${o[0]}, ${o[1]}));
      int index = resTexRC.x * ${o[1]} + resTexRC.y;

      ${i}

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

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

      return ivec${r.length}(${p});
    }
  `}function r8(r,e,t){if(t)return`
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(outTexShape[0], outTexShape[1]));
      int index = resTexRC.x * outTexShape[1] + resTexRC.y;
      ${Au(["r","c","d","d2"],r)}
      return ivec4(r, c, d, d2);
    }
  `;let o=us(["r","c","d","d2"],r);return`
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${e[0]}, ${e[1]}));
      int index = resTexRC.x * ${e[1]} + resTexRC.y;
      ${o}
      return ivec4(r, c, d, d2);
    }
  `}function o8(r,e){let t=us(["r","c","d","d2","d3"],r);return`
    ivec5 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx * vec2(${e[0]},
                             ${e[1]}));

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

      ${t}

      ivec5 outShape = ivec5(r, c, d, d2, d3);
      return outShape;
    }
  `}function n8(r,e){let t=us(["r","c","d","d2","d3","d4"],r);return`
    ivec6 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${e[0]}, ${e[1]}));
      int index = resTexRC.x * ${e[1]} + resTexRC.y;

      ${t}

      ivec6 result = ivec6(r, c, d, d2, d3, d4);
      return result;
    }
  `}function s8(r,e,t){let o=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(y.arraysEqual(r,e))return t?`
      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(${o[0]}, ${o[1]}));
      }
    `;let n=Math.ceil(r[1]/2);return t?`
    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(${o[0]}, ${o[1]}));

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

      return ivec2(r, c);
    }
  `}function a8(r,e,t){return y.arraysEqual(r,e)?t?`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
      }
    `:`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(${e[0]}, ${e[1]}));
      }
    `:r[1]===1?t?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(outTexShape[0], outTexShape[1]));
        int index = resTexRC.x * outTexShape[1] + resTexRC.y;
        return ivec2(index, 0);
      }
    `:`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${e[0]}, ${e[1]}));
        int index = resTexRC.x * ${e[1]} + resTexRC.y;
        return ivec2(index, 0);
      }
    `:r[0]===1?t?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(outTexShape[0], outTexShape[1]));
        int index = resTexRC.x * outTexShape[1] + resTexRC.y;
        return ivec2(0, index);
      }
    `:`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${e[0]}, ${e[1]}));
        int index = resTexRC.x * ${e[1]} + resTexRC.y;
        return ivec2(0, index);
      }
    `:t?`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(outTexShape[0], outTexShape[1]));
      int index = resTexRC.x * outTexShape[1] + resTexRC.y;
      int r = index / outShape[1];
      int c = index - r * outShape[1];
      return ivec2(r, c);
    }
  `:`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${e[0]}, ${e[1]}));
      int index = resTexRC.x * ${e[1]} + resTexRC.y;
      int r = index / ${r[1]};
      int c = index - r * ${r[1]};
      return ivec2(r, c);
    }
  `}function Ru(r){return`offset${r}`}function i8(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1),o=St();return`
    vec4 ${t}() {
      return ${o.texture2D}(${e}, halfCR);
    }
  `}function u8(r,e){let t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1);if(r.shapeInfo.isUniform)return`float ${o}() {return ${t};}`;let[n,s]=r.shapeInfo.texShape;if(n===1&&s===1)return`
      float ${o}() {
        return sampleTexture(${t}, halfCR);
      }
    `;let a=Ru(t);if(e)return`
    float ${o}() {
      vec2 uv = uvFromFlat(${t}TexShape[0], ${t}TexShape[1], ${a});
      return sampleTexture(${t}, uv);
    }
  `;let[i,p]=r.shapeInfo.texShape;return`
    float ${o}() {
      vec2 uv = uvFromFlat(${i}, ${p}, ${a});
      return sampleTexture(${t}, uv);
    }
  `}function p8(r,e){let t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=r.shapeInfo.texShape,s=St();if(e)return`
    vec4 ${o}(int index) {
      ivec2 packedTexShape = ivec2(ceil(float(${t}TexShape[0]) / 2.0), ceil(float(${t}TexShape[1]) / 2.0));
      vec2 uv = packedUVfrom1D(
        packedTexShape[0], packedTexShape[1], index);
      return ${s.texture2D}(${t}, uv);
    }
  `;let a=[Math.ceil(n[0]/2),Math.ceil(n[1]/2)];return`
    vec4 ${o}(int index) {
      vec2 uv = packedUVfrom1D(
        ${a[0]}, ${a[1]}, index);
      return ${s.texture2D}(${t}, uv);
    }
  `}function c8(r,e){let t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1);if(r.shapeInfo.isUniform)return`
      float ${o}(int index) {
        ${uc(r)}
      }
    `;let n=r.shapeInfo.texShape,s=n[0],a=n[1];if(a===1&&s===1)return`
      float ${o}(int index) {
        return sampleTexture(${t}, halfCR);
      }
    `;let i=Ru(t);return a===1?e?`
      float ${o}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / float(${t}TexShape[0]));
        return sampleTexture(${t}, uv);
      }
    `:`
      float ${o}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / ${s}.0);
        return sampleTexture(${t}, uv);
      }
    `:s===1?e?`
      float ${o}(int index) {
        vec2 uv = vec2((float(index + ${i}) + 0.5) / float(${t}TexShape[1]), 0.5);
        return sampleTexture(${t}, uv);
      }
    `:`
      float ${o}(int index) {
        vec2 uv = vec2((float(index + ${i}) + 0.5) / ${a}.0, 0.5);
        return sampleTexture(${t}, uv);
      }
    `:e?`
    float ${o}(int index) {
      vec2 uv = uvFromFlat(${t}TexShape[0], ${t}TexShape[1], index + ${i});
      return sampleTexture(${t}, uv);
    }
  `:`
    float ${o}(int index) {
      vec2 uv = uvFromFlat(${s}, ${a}, index + ${i});
      return sampleTexture(${t}, uv);
    }
  `}function l8(r,e){let t=r.shapeInfo.logicalShape,o=r.name,n="get"+o.charAt(0).toUpperCase()+o.slice(1),s=r.shapeInfo.texShape,a=s[0],i=s[1],p=St();if(s!=null&&y.arraysEqual(t,s))return e?`
      vec4 ${n}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${o}TexShape[1], ${o}TexShape[0]);

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

        return ${p.texture2D}(${o}, uv);
      }
    `;if(e)return`
    vec4 ${n}(int row, int col) {
      ivec2 packedTexShape = ivec2(ceil(float(${o}TexShape[0]) / 2.0), ceil(float(${o}TexShape[1]) / 2.0));
      int valuesPerRow = int(ceil(float(${o}Shape[1]) / 2.0));
      vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);
      return ${p.texture2D}(${o}, uv);
    }
  `;let u=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],c=Math.ceil(t[1]/2);return`
    vec4 ${n}(int row, int col) {
      vec2 uv = packedUVfrom2D(${c}, ${u[0]}, ${u[1]}, row, col);
      return ${p.texture2D}(${o}, uv);
    }
  `}function m8(r,e){let t=r.shapeInfo.logicalShape,o=r.name,n="get"+o.charAt(0).toUpperCase()+o.slice(1),s=r.shapeInfo.texShape;if(s!=null&&y.arraysEqual(t,s)){if(e)return`
      float ${n}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${o}TexShape[1], ${o}TexShape[0]);
        return sampleTexture(${o}, uv);
      }
    `;let m=s[0],d=s[1];return`
    float ${n}(int row, int col) {
      vec2 uv = (vec2(col, row) + halfCR) / vec2(${d}.0, ${m}.0);
      return sampleTexture(${o}, uv);
    }
  `}let{newShape:a,keptDims:i}=y.squeezeShape(t),p=a;if(p.length<t.length){let m=pc(r,p),d=["row","col"];return`
      ${ic(m,e)}
      float ${n}(int row, int col) {
        return ${n}(${cc(d,i)});
      }
    `}if(r.shapeInfo.isUniform)return`
      float ${n}(int row, int col) {
        int index = round(dot(vec2(row, col), vec2(${t[1]}, 1)));
        ${uc(r)}
      }
    `;let u=s[0],c=s[1],l=Ru(o);return c===1?e?`
      float ${n}(int row, int col) {
        float index = dot(vec3(row, col, ${l}), vec3(${o}Shape[1], 1, 1));
        vec2 uv = vec2(0.5, (index + 0.5) / float(${o}TexShape[0]));
        return sampleTexture(${o}, uv);
      }
    `:`
    float ${n}(int row, int col) {
      float index = dot(vec3(row, col, ${l}), vec3(${t[1]}, 1, 1));
      vec2 uv = vec2(0.5, (index + 0.5) / ${u}.0);
      return sampleTexture(${o}, uv);
    }
  `:u===1?e?`
      float ${n}(int row, int col) {
        float index = dot(vec3(row, col, ${l}), vec3(${o}Shape[1], 1, 1));
        vec2 uv = vec2((index + 0.5) / float(${o}TexShape[1]), 0.5);
        return sampleTexture(${o}, uv);
      }
    `:`
    float ${n}(int row, int col) {
      float index = dot(vec3(row, col, ${l}), vec3(${t[1]}, 1, 1));
      vec2 uv = vec2((index + 0.5) / ${c}.0, 0.5);
      return sampleTexture(${o}, uv);
    }
  `:e?`
      float ${n}(int row, int col) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${o}Shape[1] + col + ${l};
        vec2 uv = uvFromFlat(${o}TexShape[0], ${o}TexShape[1], index);
        return sampleTexture(${o}, uv);
      }
    `:`
  float ${n}(int row, int col) {
    // Explicitly use integer operations as dot() only works on floats.
    int index = row * ${t[1]} + col + ${l};
    vec2 uv = uvFromFlat(${u}, ${c}, index);
    return sampleTexture(${o}, uv);
  }
`}function d8(r,e){let t=r.shapeInfo.logicalShape,o=r.name,n="get"+o.charAt(0).toUpperCase()+o.slice(1),s=r.shapeInfo.texShape,a=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];if(t[0]===1){let m=t.slice(1),d=[1,2],f=pc(r,m),h=["b","row","col"];return`
        ${_E(f,e)}
        vec4 ${n}(int b, int row, int col) {
          return ${n}(${cc(h,d)});
        }
      `}let i=St();if(e)return`
    vec4 ${n}(int b, int row, int col) {
      ivec2 packedTexShape = ivec2(ceil(float(${o}TexShape[0]) / 2.0), ceil(float(${o}TexShape[1]) / 2.0));
      int valuesPerRow = int(ceil(float(${o}Shape[2]) / 2.0));
      int texelsInBatch = valuesPerRow * int(ceil(float(${o}Shape[1]) / 2.0));
      vec2 uv = packedUVfrom3D(
        packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);
      return ${i.texture2D}(${o}, uv);
    }
  `;let p=a[0],u=a[1],c=Math.ceil(t[2]/2),l=c*Math.ceil(t[1]/2);return`
    vec4 ${n}(int b, int row, int col) {
      vec2 uv = packedUVfrom3D(
        ${p}, ${u}, ${l}, ${c}, b, row, col);
      return ${i.texture2D}(${o}, uv);
    }
  `}function f8(r,e){let t=r.shapeInfo.logicalShape,o=r.name,n="get"+o.charAt(0).toUpperCase()+o.slice(1),s=t[1]*t[2],a=t[2],{newShape:i,keptDims:p}=y.squeezeShape(t),u=i;if(u.length<t.length){let h=pc(r,u),g=["row","col","depth"];return`
        ${ic(h,e)}
        float ${n}(int row, int col, int depth) {
          return ${n}(${cc(g,p)});
        }
      `}if(r.shapeInfo.isUniform)return`
      float ${n}(int row, int col, int depth) {
        int index = round(dot(vec3(row, col, depth),
                          vec3(${s}, ${a}, 1)));
        ${uc(r)}
      }
    `;let c=r.shapeInfo.texShape,l=c[0],m=c[1],d=r.shapeInfo.flatOffset;if(m===s&&d==null)return e?`
      float ${n}(int row, int col, int depth) {
        int stride1 = ${o}Shape[2];
        float texR = float(row);
        float texC = dot(vec2(col, depth), vec2(stride1, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${o}TexShape[1], ${o}TexShape[0]);
        return sampleTexture(${o}, uv);
      }
    `:`
        float ${n}(int row, int col, int depth) {
          float texR = float(row);
          float texC = dot(vec2(col, depth), vec2(${a}, 1));
          vec2 uv = (vec2(texC, texR) + halfCR) /
                     vec2(${m}.0, ${l}.0);
          return sampleTexture(${o}, uv);
        }
      `;if(m===a&&d==null)return e?`
      float ${n}(int row, int col, int depth) {
        float texR = dot(vec2(row, col), vec2(${o}Shape[1], 1));
        float texC = float(depth);
        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${o}TexShape[1], ${o}TexShape[0]);
        return sampleTexture(${o}, uv);
      }
    `:`
    float ${n}(int row, int col, int depth) {
      float texR = dot(vec2(row, col), vec2(${t[1]}, 1));
      float texC = float(depth);
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${m}.0, ${l}.0);
      return sampleTexture(${o}, uv);
    }
  `;let f=Ru(o);return e?`
    float ${n}(int row, int col, int depth) {
      // Explicitly use integer operations as dot() only works on floats.
      int stride0 = ${o}Shape[1] * ${o}Shape[2];
      int stride1 = ${o}Shape[2];
      int index = row * stride0 + col * stride1 + depth + ${f};
      vec2 uv = uvFromFlat(${o}TexShape[0], ${o}TexShape[1], index);
      return sampleTexture(${o}, uv);
    }
    `:`
      float ${n}(int row, int col, int depth) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${s} + col * ${a} + depth + ${f};
        vec2 uv = uvFromFlat(${l}, ${m}, index);
        return sampleTexture(${o}, uv);
      }
  `}function h8(r,e){let t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=St();if(e)return`
    vec4 ${o}(int b2, int b, int row, int col) {
      int valuesPerRow = int(ceil(float(${t}Shape[3]) / 2.0));
      int texelsInBatch = valuesPerRow * int(ceil(float(${t}Shape[2]) / 2.0));
      int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);
      texelsInBatch *= ${t}Shape[1];
      index = b2 * texelsInBatch + index;
      ivec2 packedTexShape = ivec2(ceil(float(${t}TexShape[0]) / 2.0), ceil(float(${t}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 ${n.texture2D}(${t}, uv);
    }
  `;let s=r.shapeInfo.logicalShape,a=s.length,i=r.shapeInfo.texShape,p=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)],u=p[0],c=p[1],l=Math.ceil(s[a-1]/2),m=l*Math.ceil(s[a-2]/2),d="int b, int row, int col",f=`b * ${m} + (row / 2) * ${l} + (col / 2)`;for(let h=2;h<a-1;h++)d=`int b${h}, `+d,m*=s[a-h-1],f=`b${h} * ${m} + `+f;return`
    vec4 ${o}(${d}) {
      int index = ${f};
      int texR = index / ${c};
      int texC = index - texR * ${c};
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${c}, ${u});
      return ${n.texture2D}(${t}, uv);
    }
  `}function g8(r,e){let t=r.shapeInfo.logicalShape,o=r.name,n="get"+o.charAt(0).toUpperCase()+o.slice(1),s=t[3],a=t[2]*s,i=t[1]*a,{newShape:p,keptDims:u}=y.squeezeShape(t);if(p.length<t.length){let b=pc(r,p),C=["row","col","depth","depth2"];return`
      ${ic(b,e)}
      float ${n}(int row, int col, int depth, int depth2) {
        return ${n}(${cc(C,u)});
      }
    `}if(r.shapeInfo.isUniform)return`
      float ${n}(int row, int col, int depth, int depth2) {
        int index = round(dot(vec4(row, col, depth, depth2),
                          vec4(${i}, ${a}, ${s}, 1)));
        ${uc(r)}
      }
    `;let c=r.shapeInfo.flatOffset,l=r.shapeInfo.texShape,m=l[0],d=l[1],f=`int stride2 = ${o}Shape[3];`,h=`int stride1 = ${o}Shape[2] * stride2;`,g=`int stride0 = ${o}Shape[1] * stride1;`;if(d===i&&c==null)return e?`
      float ${n}(int row, int col, int depth, int depth2) {
        ${f}
        ${h}
        float texR = float(row);
        float texC =
            dot(vec3(col, depth, depth2),
                vec3(stride1, stride2, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${o}TexShape[1], ${o}TexShape[0]);
        return sampleTexture(${o}, uv);
      }
    `:`
      float ${n}(int row, int col, int depth, int depth2) {
        float texR = float(row);
        float texC =
            dot(vec3(col, depth, depth2),
                vec3(${a}, ${s}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${d}.0, ${m}.0);
        return sampleTexture(${o}, uv);
      }
    `;if(d===s&&c==null)return e?`
      float ${n}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${o}Shape[1] * ${o}Shape[2], ${o}Shape[2], 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${o}TexShape[1], ${o}TexShape[0]);
        return sampleTexture(${o}, uv);
      }
    `:`
      float ${n}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${t[1]*t[2]}, ${t[2]}, 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${d}.0, ${m}.0);
        return sampleTexture(${o}, uv);
      }
    `;let x=Ru(o);return e?`
    float ${n}(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
      ${f}
      ${h}
      ${g}
      int index = row * stride0 + col * stride1 +
          depth * stride2 + depth2;
      vec2 uv = uvFromFlat(${o}TexShape[0], ${o}TexShape[1], index + ${x});
      return sampleTexture(${o}, uv);
    }
  `:`
    float ${n}(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${i} + col * ${a} +
          depth * ${s} + depth2;
      vec2 uv = uvFromFlat(${m}, ${d}, index + ${x});
      return sampleTexture(${o}, uv);
    }
  `}function x8(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=e[4],s=e[3]*n,a=e[2]*s,i=e[1]*a,{newShape:p,keptDims:u}=y.squeezeShape(e);if(p.length<e.length){let h=pc(r,p),g=["row","col","depth","depth2","depth3"];return`
      ${ic(h)}
      float ${o}(int row, int col, int depth, int depth2, int depth3) {
        return ${o}(${cc(g,u)});
      }
    `}if(r.shapeInfo.isUniform)return`
      float ${o}(int row, int col, int depth, int depth2, int depth3) {
        float index = dot(
          vec4(row, col, depth, depth2),
          vec4(${i}, ${a}, ${s}, ${n})) +
          depth3;
        ${uc(r)}
      }
    `;let c=r.shapeInfo.flatOffset,l=r.shapeInfo.texShape,m=l[0],d=l[1];if(d===i&&c==null)return`
      float ${o}(int row, int col, int depth, int depth2, int depth3) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
                         vec4(${a}, ${s}, ${n}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${d}.0, ${m}.0);
        return sampleTexture(${t}, uv);
      }
    `;if(d===n&&c==null)return`
      float ${o}(int row, int col, int depth, int depth2, int depth3) {
        float texR = dot(
          vec4(row, col, depth, depth2),
          vec4(${e[1]*e[2]*e[3]},
               ${e[2]*e[3]}, ${e[3]}, 1));
        int texC = depth3;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${d}.0, ${m}.0);
        return sampleTexture(${t}, uv);
      }
    `;let f=Ru(t);return`
    float ${o}(int row, int col, int depth, int depth2, int depth3) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${i} + col * ${a} + depth * ${s} +
          depth2 * ${n} + depth3 + ${f};
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      return sampleTexture(${t}, uv);
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      float ${o}(int row, int col, int depth,
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        int index = round(dot(
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            vec2(${a}, 1)));
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      float ${o}(int row, int col, int depth,
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        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
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               float(depth4);
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      float ${o}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        float texR = dot(vec4(row, col, depth, depth2),
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               ${e[2]*e[3]*e[4]},
               ${e[3]*e[4]},
               ${e[4]})) + float(depth3);
        int texC = depth4;
        vec2 uv = (vec2(texC, texR) + halfCR) /
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        return sampleTexture(${t}, uv);
      }
    `;let h=Ru(t);return`
    float ${o}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${c} + col * ${u} + depth * ${p} +
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      vec2 uv = uvFromFlat(${d}, ${f}, index);
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    }
  `}function uc(r){let e=r.name,t=y.sizeFromShape(r.shapeInfo.logicalShape);return t<2?`return ${e};`:`
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        return ${e}[i];
      }
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      ${c}
      vec4 outputValue = get${o}(${m});
      ${d}
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`);let f="";return p<2&&i>0?f="coords":f=r.shapeInfo.logicalShape.map((h,g)=>`coords.${d[g+l]}`).join(", "),`
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      ${m}
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        ${this.enableShapeUniforms?Au(["r","c","d"],e):us(["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;
      }
    `}};var Mf=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Mi.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=St();this.outputShape=e,this.enableShapeUniforms=ct(this.outputShape.length),this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${this.enableShapeUniforms?Au(["r","c","d"],e):us(["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;
      }
    `}};var Lf=class{constructor(e){this.variableNames=["A"],this.outTexUsage=ir.DOWNLOAD;let t=St();this.outputShape=e,this.userCode=`
      ${Df}

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

      void main() {
        ivec3 coords = getOutputCoords();
        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
        ${t.output} = encode_float(x);
      }
    `}};var I8={R:0,G:1,B:2,A:3},vl=class{constructor(e,t=!1,o="RGBA"){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=St();this.outputShape=e,this.enableShapeUniforms=ct(this.outputShape.length);let s="result";t&&(s="floor(result * 255. + 0.5)");let a="";for(let i=0;i<o.length;i++){let p=o[i];a+=`
          if(offset == ${i}) {
            result = values[${I8[p]}];
          }`}this.userCode=`
      ${this.enableShapeUniforms?sc():nc(e)}

      void main() {
        ivec3 coords = getOutputCoords();
        int flatIndex = getFlatIndex(coords);
        float result = 0.;
        int offset = imod(flatIndex, ${o.length});

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

            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 = ${o.texture2D}(A, uv);

            if (offset == 0) {
              result[${p}] = values[0];
            } else if (offset == 1) {
              result[${p}] = values[1];
            } else if (offset == 2) {
              result[${p}] = values[2];
            } else {
              result[${p}] = values[3];
            }
          }
        }
        `}this.userCode=`
        ${this.enableShapeUniforms?sc():nc(e)}

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

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

          ${n}

          ${o.output} = ${s};
        }
    `}};var yw={};Ue(yw,{bindVertexProgramAttributeStreams:()=>cw,createBufferFromOutputTexture:()=>dw,createFloat16MatrixTexture:()=>aw,createFloat16PackedMatrixTexture:()=>pw,createFloat32MatrixTexture:()=>sw,createIndexBuffer:()=>nw,createPackedMatrixTexture:()=>uw,createUnsignedBytesMatrixTexture:()=>iw,createVertexBuffer:()=>ow,createVertexShader:()=>rw,downloadByteEncodedFloatMatrixFromOutputTexture:()=>hw,downloadFloat32MatrixFromBuffer:()=>fw,downloadMatrixFromPackedOutputTexture:()=>xw,downloadPackedMatrixFromBuffer:()=>gw,getInternalFormatForFloat16MatrixTexture:()=>Wf,getInternalFormatForFloat16PackedMatrixTexture:()=>Hf,getInternalFormatForFloat32MatrixTexture:()=>zf,getInternalFormatForPackedMatrixTexture:()=>Gf,getInternalFormatForUnsignedBytesMatrixTexture:()=>Uf,uploadDenseMatrixToTexture:()=>lw,uploadPixelDataToTexture:()=>mw});function rw(r){let e=St(),t=`${e.version}
    precision highp float;
    ${e.attribute} vec3 clipSpacePos;
    ${e.attribute} vec2 uv;
    ${e.varyingVs} vec2 resultUV;

    void main() {
      gl_Position = vec4(clipSpacePos, 1);
      resultUV = uv;
    }`;return PS(r,t)}function ow(r){let e=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return VS(r,e)}function nw(r){let e=new Uint16Array([0,1,2,2,1,3]);return zS(r,e)}function kl(r,e,t,o,n,s){US(e,t);let a=WS(r),i=r.TEXTURE_2D;return ce(r,()=>r.bindTexture(i,a)),ce(r,()=>r.texParameteri(i,r.TEXTURE_WRAP_S,r.CLAMP_TO_EDGE)),ce(r,()=>r.texParameteri(i,r.TEXTURE_WRAP_T,r.CLAMP_TO_EDGE)),ce(r,()=>r.texParameteri(i,r.TEXTURE_MIN_FILTER,r.NEAREST)),ce(r,()=>r.texParameteri(i,r.TEXTURE_MAG_FILTER,r.NEAREST)),O().getNumber("WEBGL_VERSION")===1?ce(r,()=>r.texImage2D(i,0,o,e,t,0,n,s,null)):ce(r,()=>r.texStorage2D(i,1,o,e,t)),ce(r,()=>r.bindTexture(r.TEXTURE_2D,null)),{texture:a,texShape:[t,e]}}function zf(r){return r.internalFormatFloat}function sw(r,e,t,o){let[n,s]=$u(e,t);return kl(r,n,s,zf(o),o.textureFormatFloat,r.FLOAT)}function Wf(r){return r.internalFormatHalfFloat}function aw(r,e,t,o){let[n,s]=$u(e,t);return kl(r,n,s,Wf(o),o.textureFormatFloat,o.textureTypeHalfFloat)}function Uf(r){return r.downloadTextureFormat}function iw(r,e,t,o){let[n,s]=$u(e,t);return kl(r,n,s,Uf(o),r.RGBA,r.UNSIGNED_BYTE)}function Gf(r){return r.internalFormatPackedFloat}function uw(r,e,t,o){let[n,s]=Ys(e,t);return kl(r,n,s,Gf(o),r.RGBA,r.FLOAT)}function Hf(r){return r.internalFormatPackedHalfFloat}function pw(r,e,t,o){let[n,s]=Ys(e,t);return kl(r,n,s,Hf(o),r.RGBA,o.textureTypeHalfFloat)}function cw(r,e,t){return ce(r,()=>r.bindBuffer(r.ARRAY_BUFFER,t)),Af(r,e,"clipSpacePos",t,3,20,0)&&Af(r,e,"uv",t,2,20,12)}function lw(r,e,t,o,n,s){ce(r,()=>r.bindTexture(r.TEXTURE_2D,e));let a,i,p;n instanceof Uint8Array?(a=new Uint8Array(t*o*4),i=r.UNSIGNED_BYTE,p=r.RGBA):(a=new Float32Array(t*o*4),i=r.FLOAT,p=s.internalFormatPackedFloat),a.set(n),O().getNumber("WEBGL_VERSION")===2?ce(r,()=>r.texSubImage2D(r.TEXTURE_2D,0,0,0,t,o,r.RGBA,i,a)):ce(r,()=>r.texImage2D(r.TEXTURE_2D,0,p,t,o,0,r.RGBA,i,a)),ce(r,()=>r.bindTexture(r.TEXTURE_2D,null))}function mw(r,e,t){ce(r,()=>r.bindTexture(r.TEXTURE_2D,e)),t.data instanceof Uint8Array?O().getNumber("WEBGL_VERSION")===2?ce(r,()=>r.texSubImage2D(r.TEXTURE_2D,0,0,0,t.width,t.height,r.RGBA,r.UNSIGNED_BYTE,t.data)):ce(r,()=>r.texImage2D(r.TEXTURE_2D,0,r.RGBA,t.width,t.height,0,r.RGBA,r.UNSIGNED_BYTE,t.data)):O().getNumber("WEBGL_VERSION")===2?ce(r,()=>r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,t)):ce(r,()=>r.texImage2D(r.TEXTURE_2D,0,r.RGBA,r.RGBA,r.UNSIGNED_BYTE,t)),ce(r,()=>r.bindTexture(r.TEXTURE_2D,null))}function dw(r,e,t,o){let n=r.createBuffer();ce(r,()=>r.bindBuffer(r.PIXEL_PACK_BUFFER,n));let i=4*4*e*t;return ce(r,()=>r.bufferData(r.PIXEL_PACK_BUFFER,i,r.STREAM_READ)),ce(r,()=>r.readPixels(0,0,t,e,r.RGBA,r.FLOAT,0)),ce(r,()=>r.bindBuffer(r.PIXEL_PACK_BUFFER,null)),n}function fw(r,e,t){let o=r,n=new Float32Array(t);return o.bindBuffer(o.PIXEL_PACK_BUFFER,e),o.getBufferSubData(o.PIXEL_PACK_BUFFER,0,n),o.bindBuffer(o.PIXEL_PACK_BUFFER,null),n}function hw(r,e,t,o){let[n,s]=$u(e,t),a=4,i=new Uint8Array(bE(e*t,a));return ce(r,()=>r.readPixels(0,0,n,s,o.downloadTextureFormat,r.UNSIGNED_BYTE,i)),new Float32Array(i.buffer)}function gw(r,e,t,o,n,s,a,i){let p=r,u=new Float32Array(CE(s,a));return p.bindBuffer(p.PIXEL_PACK_BUFFER,e),p.getBufferSubData(p.PIXEL_PACK_BUFFER,0,u),p.bindBuffer(p.PIXEL_PACK_BUFFER,null),u}function xw(r,e,t){let o=new Float32Array(e*t*4);return ce(r,()=>r.readPixels(0,0,t,e,r.RGBA,r.FLOAT,o)),o}var Fu=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.itemsToPoll=[];let t=O().getNumber("WEBGL_VERSION");if(e!=null?(this.gl=e,RS(t,e)):this.gl=Wr(t),e=this.gl,O().getNumber("WEBGL_VERSION")===2){let s=e;this.createVertexArray=()=>ce(s,()=>s.createVertexArray()),this.bindVertexArray=a=>ce(s,()=>s.bindVertexArray(a)),this.deleteVertexArray=a=>ce(s,()=>s.deleteVertexArray(a)),this.getVertexArray=()=>ce(s,()=>s.getParameter(s.VERTEX_ARRAY_BINDING))}else if(e!=null){let s=e.getExtension("OES_vertex_array_object");if(s==null)throw new Error("All WebGL1 implementations are expected to offer OES_vertex_array_object.");this.createVertexArray=()=>ce(e,()=>s.createVertexArrayOES()),this.bindVertexArray=a=>ce(e,()=>s.bindVertexArrayOES(a)),this.deleteVertexArray=a=>ce(e,()=>s.deleteVertexArrayOES(a)),this.getVertexArray=()=>ce(e,()=>e.getParameter(s.VERTEX_ARRAY_BINDING_OES))}let o="WEBGL_color_buffer_float",n="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),O().getNumber("WEBGL_VERSION")===1){let s="OES_texture_float",a="OES_texture_half_float";if(this.textureFloatExtension=ec(this.gl,s),Ur(this.gl,a))this.textureHalfFloatExtension=ec(this.gl,a);else if(O().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(o),Ur(this.gl,n))this.colorBufferHalfFloatExtension=ec(this.gl,n);else if(O().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(o="EXT_color_buffer_float",Ur(this.gl,o))this.colorBufferFloatExtension=this.gl.getExtension(o);else if(Ur(this.gl,n))this.colorBufferHalfFloatExtension=this.gl.getExtension(n);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=ow(this.gl),this.indexBuffer=nw(this.gl),this.framebuffer=GS(this.gl),this.textureConfig=Sl(this.gl,this.textureHalfFloatExtension)}get debug(){return O().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;ce(e,()=>e.finish()),ce(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),ce(e,()=>e.deleteFramebuffer(this.framebuffer)),ce(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),ce(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),ce(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),sw(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),aw(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),iw(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),mw(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,o,n){this.throwIfDisposed(),lw(this.gl,e,t,o,n,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),pw(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),uw(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(Rf(this.gl,this.framebuffer),this.outputTexture=null),ce(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,o){return this.downloadMatrixDriver(e,()=>hw(this.gl,t,o,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,o,n,s,a){return gw(this.gl,e,t,o,n,s,a,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return fw(this.gl,e,t)}createBufferFromTexture(e,t,o){this.bindTextureToFrameBuffer(e);let n=dw(this.gl,t,o,this.textureConfig);return this.unbindTextureToFrameBuffer(),n}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,o;if(O().getBool("WEBGL_FENCE_API_ENABLED")){let n=e,s=n.fenceSync(n.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),o=()=>{let 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successful."),this.debug&&wl(t,n),this.setProgram(n),n}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&(ce(this.gl,()=>this.gl.deleteProgram(e)),this.deleteVertexArray(e.vao))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&(this.bindVertexArray(this.program.vao),this.debug&&wl(this.gl,this.program)),ce(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,o=!0){return this.throwIfDisposed(),o?HS(this.gl,e,t):qS(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),ce(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,o){this.throwIfDisposed(),this.throwIfNoProgram(),KS(this.gl,e,t,o)}setOutputMatrixTexture(e,t,o){this.setOutputMatrixTextureDriver(e,o,t)}setOutputPackedMatrixTexture(e,t,o){this.throwIfDisposed();let[n,s]=Ys(t,o);this.setOutputMatrixTextureDriver(e,n,s)}setOutputMatrixWriteRegion(e,t,o,n){this.setOutputMatrixWriteRegionDriver(o,e,n,t)}setOutputPackedMatrixWriteRegion(e,t,o,n){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&wl(this.gl,this.program),tc(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()}ce(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),ce(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=ec(this.gl,O().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(O().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let o=this.gl,n=this.getQueryTimerExtensionWebGL2(),s=o.createQuery();return o.beginQuery(n.TIME_ELAPSED_EXT,s),s}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(O().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,o=this.getQueryTimerExtensionWebGL2();t.endQuery(o.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await y.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,O().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,O().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let o=this.gl;return o.getQueryParameter(e,o.QUERY_RESULT)/1e6}else{let o=this.getQueryTimerExtensionWebGL1();return o.getQueryObjectEXT(e,o.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let o=this.gl,n=this.getQueryTimerExtensionWebGL2(),s=o.getQueryParameter(e,o.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),s&&!this.disjoint}else{let o=this.getQueryTimerExtensionWebGL1(),n=o.getQueryObjectEXT(e,o.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(o.GPU_DISJOINT_EXT)),n&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=v8(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:o}=this.itemsToPoll[t];o()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){if(this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),this.itemsToPoll.length>1)return;let o;"setTimeoutCustom"in O().platform&&(o=O().platform.setTimeoutCustom.bind(O().platform)),y.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0),()=>0,null,o)}bindTextureToFrameBuffer(e){this.throwIfDisposed(),Il(this.gl,e,this.framebuffer),this.debug&&tc(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(Il(this.gl,this.outputTexture,this.framebuffer),this.debug&&tc(this.gl)):Rf(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let o=t();return this.unbindTextureToFrameBuffer(),o}setOutputMatrixTextureDriver(e,t,o){this.throwIfDisposed();let n=this.gl;Il(n,e,this.framebuffer),this.debug&&tc(n),this.outputTexture=e,ce(n,()=>n.viewport(0,0,t,o)),ce(n,()=>n.scissor(0,0,t,o))}setOutputMatrixWriteRegionDriver(e,t,o,n){this.throwIfDisposed(),ce(this.gl,()=>this.gl.scissor(e,t,o,n))}throwIfDisposed(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(this.program==null)throw new Error("No GPU program is currently set.")}};function v8(r){let e=0;for(;e<r.length&&r[e]();++e);return e-1}var{addImpl:DE,bincountImpl:qf,bincountReduceImpl:OE,castImpl:PE,ceilImpl:ME,concatImpl:LE,equalImpl:BE,expImpl:VE,expm1Impl:zE,floorImpl:WE,gatherNdImpl:UE,gatherV2Impl:GE,greaterImpl:HE,greaterEqualImpl:qE,lessImpl:KE,lessEqualImpl:jE,linSpaceImpl:XE,logImpl:YE,maxImpl:QE,maximumImpl:ZE,minimumImpl:JE,multiplyImpl:e$,negImpl:t$,notEqualImpl:r$,prodImpl:o$,raggedGatherImpl:n$,raggedRangeImpl:s$,raggedTensorToTensorImpl:a$,rangeImpl:i$,rsqrtImpl:u$,scatterImpl:p$,sigmoidImpl:c$,simpleAbsImpl:Kf,sliceImpl:l$,sparseFillEmptyRowsImpl:m$,sparseReshapeImpl:d$,sparseSegmentReductionImpl:jf,sqrtImpl:f$,stridedSliceImpl:h$,stringNGramsImpl:g$,stringSplitImpl:x$,stringToHashBucketFastImpl:y$,subImpl:b$,tileImpl:C$,topKImpl:S$,transposeImpl:Du,uniqueImpl:w$}=Qp;function bw(r,e){return["x","y","z","w","u","v"].slice(0,e).map(t=>`${r}.${t}`)}function $t(r,e){return e===1?[r]:bw(r,e)}function I$(r,e){if(r===1)return"rc";let t="";for(let o=0;o<r;o++)t+=e[o],o<r-1&&(t+=",");return t}var Xf=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=ct(this.outputShape.length),this.rank===0)this.userCode=`
        void main() {
          setOutput(vec4(getA(), 0., 0., 0.));
        }
      `;else{let t=$t("rc",this.rank),o=_e(this.rank),n=this.getOutOfBoundsCondition(t),s=this.getSetup(t),a=this.getOutput(t);this.userCode=`
        void main() {
          ${o} rc = getOutputCoords();

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

            setOutput(vec4(${a}));
          }
        }
      `}}getSourceCoordsArr(e){let t=[];for(let o=0;o<=1;o++)for(let n=0;n<=1;n++){let s=`${o===0?"r":"rp1"}, ${n===0?"c":"cp1"}`;for(let a=2;a<this.rank;a++)s=`${e[e.length-1-a]},`+s;t.push(s)}return t}getOutOfBoundsCondition(e){if(this.rank===1)return`rc > ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let t="";for(let o=this.rank-2;o<this.rank;o++)t+=`${e[o]} >= ${this.enableShapeUniforms?`outShape[${o}]`:this.outputShape[o]}`,o<this.rank-1&&(t+="||");return t}getSetup(e){if(this.rank===1)return"";let t=e.slice(-2),o=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 >= ${o};
      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]})`}};var lc=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=ct(this.outputShape.length);let o="";for(let n=0;n<4;n++){let s="thisRC = rc;";n%2===1&&(s+="thisRC.z += 1;"),n>1&&(s+="thisRC.y += 1;"),o+=`
        ${s}
        ${n>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
          int flatIndex = getFlatIndex(thisRC);

          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=`
      ${k8(t,this.enableShapeUniforms)}
      ${this.enableShapeUniforms?sc():nc(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]};

        ${o}

        setOutput(result);
      }
    `}};function k8(r,e){return`
    ivec3 inputCoordsFromReshapedOutCoords(int index) {
      ${e?kE(["r","c","d"],"inputShape"):us(["r","c","d"],r)}
      return ivec3(r, c, d);
    }
  `}var Yf=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,o){let n=k$(t,o),s=N$(e,n,o);s in this.freeTextures||(this.freeTextures[s]=[]),s in this.usedTextures||(this.usedTextures[s]=[]);let a=v$(e,n,this.gpgpu.gl,this.gpgpu.textureConfig,o);if(this.freeTextures[s].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=a,this.log();let p=this.freeTextures[s].shift();return this.usedTextures[s].push(p),p}let i;return n===Zt.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):n===Zt.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):n===Zt.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):n===Zt.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):n===Zt.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[s].push(i),this.numUsedTextures++,this._numBytesAllocated+=a,this.log(),i}releaseTexture(e,t,o,n){if(this.freeTextures==null)return;let s=k$(o,n),a=N$(t,s,n);a in this.freeTextures||(this.freeTextures[a]=[]);let i=v$(t,s,this.gpgpu.gl,this.gpgpu.textureConfig,n),p=O().get("WEBGL_DELETE_TEXTURE_THRESHOLD");p!==-1&&this._numBytesAllocated>p?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=i):(this.freeTextures[a].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let u=this.usedTextures[a],c=u.indexOf(e);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");u.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.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 N8(r,e){let t=r;if(e===t.R32F)return 4;if(e===t.R16F)return 2;if(e===t.RGBA32F)return 16;if(e===r.RGBA)return 16;if(e===t.RGBA16F)return 8;if(e===t.RGBA8)return 4;throw new Error(`Unknown internal format ${e}`)}function v$(r,e,t,o,n){let s=T8(e,o),a;if(n){let[p,u]=Ys(r[0],r[1]);a=p*u}else{let[p,u]=$u(r[0],r[1]);a=p*u}let i=N8(t,s);return a*i}function T8(r,e){switch(r){case Zt.PACKED_2X2_FLOAT32:return Gf(e);case Zt.PACKED_2X2_FLOAT16:return Hf(e);case Zt.UNPACKED_FLOAT32:return zf(e);case Zt.UNPACKED_FLOAT16:return Wf(e);case Zt.PACKED_4X1_UNSIGNED_BYTE:return Uf(e);default:throw new Error(`Unknown physical texture type ${r}`)}}function _8(r){return O().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?r?Zt.PACKED_2X2_FLOAT32:Zt.UNPACKED_FLOAT32:r?Zt.PACKED_2X2_FLOAT16:Zt.UNPACKED_FLOAT16}function k$(r,e){if(r===ir.UPLOAD)return Zt.PACKED_2X2_FLOAT32;if(r===ir.RENDER||r==null)return _8(e);if(r===ir.DOWNLOAD||r===ir.PIXELS)return Zt.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${r}`)}function N$(r,e,t){return`${r[0]}_${r[1]}_${e}_${t}`}var Jt=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=ct(this.outputShape.length),this.userCode=`
      float unaryOperation(float x) {
        ${t}
      }

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

        setOutput(y);
      }
    `}},Bt="if (isnan(x)) return x;",T$="return x;",Cw="return abs(x);";var _$="return (x >= 0.0) ? x : (exp(x) - 1.0);",E$=Bt+`
  return (x < 0.0) ? 0.0 : x;
`,$$=Bt+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,Qs="return x;",A$="return 1.0 / (1.0 + exp(-1.0 * x));";var F$="return x;",D$=`
  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;
`,O$=`
  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;
`,P$=`
  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;
`,M$="return 1.0 / (1.0 + exp(-1.0 * x));",Ar=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=ct(this.outputShape.length),this.userCode=`
      vec4 unaryOperation(vec4 x) {
        ${t}
      }

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

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

        setOutput(getChannel(packedInput, ${i}));
      }
    `}};var $8=Lt.whereImpl,A8=1e-7,R8=1e-4,Zf={};function F8(r){return r in Zf||(Zf[r]={}),Zf[r]}var D8=O().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),O8=600;function P8(){return O().global.screen==null?1024:O().global.screen.height*O().global.screen.width*window.devicePixelRatio*O8/1024/1024}var Bi=class extends Zr{constructor(e){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!O().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let t;if(e!=null){if(e instanceof Fu)t=e;else{let o=Wr(O().getNumber("WEBGL_VERSION"),e);t=new Fu(o)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let o=Wr(O().getNumber("WEBGL_VERSION"));t=new Fu(o),this.binaryCache=F8(O().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=t,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new Yf(this.gpgpu),this.numMBBeforeWarning=P8(),this.texData=new Do(this,cr())}nextDataId(){return Bi.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}writeTexture(e,t,o,n,s,a){let i=this.makeTensorInfo(t,o),p=this.texData.get(i.dataId);p.isPacked=!1,p.texture={texture:e,texShape:[n,s]},p.texShape=[n,s];let u=rc(t),c=new vl(u,!1,a),l=this.runWebGLProgram(c,[i],o,[[n,s]]);return l.shape=t,p.texture=null,this.disposeIntermediateTensorInfo(i),l.dataId}write(e,t,o){if((O().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||O().getBool("DEBUG"))&&this.checkNumericalProblems(e),o==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let n={id:this.nextDataId()};return this.texData.set(n,{shape:t,dtype:o,values:e,usage:ir.UPLOAD,refCount:1}),n}refCount(e){return this.texData.has(e)?this.texData.get(e).refCount:0}incRef(e){let t=this.texData.get(e);t.refCount++}decRef(e){if(this.texData.has(e)){let t=this.texData.get(e);t.refCount--}}move(e,t,o,n,s){if(O().getBool("DEBUG")&&this.checkNumericalProblems(t),n==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:o,dtype:n,values:t,usage:ir.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:o,dtype:n,complexTensorInfos:s,slice:a,shape:i,isPacked:p}=t;if(a!=null){let m;p?m=new Ar(i,Qs):m=new Jt(i,Qs);let d=this.runWebGLProgram(m,[{dataId:e,shape:i,dtype:n}],n),f=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),f}if(o!=null)return this.convertAndCacheOnCPU(e);if(n==="string")return o;let u=this.activeTimers!=null,c;u&&(c=y.now());let l;if(n==="complex64"){let m=this.readSync(s.real.dataId),d=this.readSync(s.imag.dataId);l=S.mergeRealAndImagArrays(m,d)}else l=this.getValuesFromTexture(e);return u&&(this.downloadWaitMs+=y.now()-c),this.convertAndCacheOnCPU(e,l)}async read(e){if(this.pendingRead.has(e)){let f=this.pendingRead.get(e);return new Promise(h=>f.push(h))}let t=this.texData.get(e),{values:o,shape:n,slice:s,dtype:a,complexTensorInfos:i,isPacked:p}=t;if(s!=null){let f;p?f=new Ar(n,Qs):f=new Jt(n,Qs);let h=this.runWebGLProgram(f,[{dataId:e,shape:n,dtype:a}],a),g=this.read(h.dataId);return this.disposeIntermediateTensorInfo(h),g}if(o!=null)return this.convertAndCacheOnCPU(e);if(O().getBool("DEBUG")&&!O().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&O().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let u=null,c;if(a!=="complex64"&&O().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let f=this.texData.get(c.dataId);u=this.gpgpu.createBufferFromTexture(f.texture.texture,...Cl(n))}this.pendingRead.set(e,[]),a!=="complex64"&&await this.gpgpu.createAndWaitForFence();let l;if(a==="complex64"){let f=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),h=f[0],g=f[1];l=S.mergeRealAndImagArrays(h,g)}else if(u==null)l=this.getValuesFromTexture(e);else{let f=y.sizeFromShape(n);l=this.gpgpu.downloadFloat32MatrixFromBuffer(u,f)}if(c!=null&&this.disposeIntermediateTensorInfo(c),u!=null){let f=this.gpgpu.gl;ce(f,()=>f.deleteBuffer(u))}let m=this.convertAndCacheOnCPU(e,l),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(f=>f(m)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&cr().removeDataId(e,this),this.pendingDeletes--),m}readToGPU(e,t={}){let o=this.texData.get(e),{values:n,shape:s,slice:a,dtype:i,isPacked:p,texture:u}=o;if(i==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(a!=null){let d;p?d=new Ar(s,Qs):d=new Jt(s,Qs);let f=this.runWebGLProgram(d,[{dataId:e,shape:s,dtype:i}],i),h=this.readToGPU(f,t);return this.disposeIntermediateTensorInfo(f),h}if(u==null)throw n!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let c=this.decode(e,t.customTexShape),l=cr().makeTensorFromTensorInfo(c),m=this.texData.get(c.dataId);return Object.assign({tensorRef:l},m.texture)}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let o=t.map(n=>y.decodeString(n));return le(e.shape,e.dtype,o)}catch(o){throw new Error("Failed to decode encoded string bytes into utf-8")}return le(e.shape,e.dtype,t)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let o=e[t];if(!OS(o))throw O().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${o} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${o} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:o,isPacked:n}=this.texData.get(e),s=y.sizeFromShape(t);if(O().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let m=this.decode(e),d=this.texData.get(m.dataId),f=this.gpgpu.downloadMatrixFromPackedTexture(d.texture.texture,...Cl(t)).subarray(0,s);return this.disposeIntermediateTensorInfo(m),f}let a=O().getBool("WEBGL_PACK")&&n===!0,i=a?rc(t):t,p=a?new Bf(i):new Lf(i),u=this.runWebGLProgram(p,[{shape:i,dtype:o,dataId:e}],"float32"),c=this.texData.get(u.dataId),l=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture.texture,c.texShape[0],c.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(u),l}timerAvailable(){return O().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){let t=this.activeTimers,o=[],n=!1;this.programTimersStack==null?(this.programTimersStack=o,n=!0):this.activeTimers.push(o),this.activeTimers=o,e();let s=y.flatten(this.activeTimers.map(p=>p.query)).filter(p=>p!=null),a=y.flatten(this.activeTimers.map(p=>p.name)).filter(p=>p!=null);this.activeTimers=t,n&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(O().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let p=await Promise.all(s);i.kernelMs=y.sum(p),i.getExtraProfileInfo=()=>p.map((u,c)=>({name:a[c],ms:u})).map(u=>`${u.name}: ${u.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return O().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:y.now(),endMs:null}}endTimer(e){return O().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=y.now(),e)}async getQueryTime(e){if(O().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:o}=this.texData.get(e);return o!=null&&(this.disposeData(o.real.dataId,t),this.disposeData(o.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:o,texShape:n,usage:s,isPacked:a,slice:i}=this.texData.get(e),p=i&&i.origDataId||e,u=this.dataRefCount.get(p);u>1?this.dataRefCount.set(p,u-1):(this.dataRefCount.delete(p),t!=null&&(this.numBytesInGPU-=this.computeBytes(n,o),this.textureManager.releaseTexture(t,n,s,a)));let c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=D8){return O().getBool("WEBGL_CPU_FORWARD")&&e.every(o=>this.texData.get(o.dataId).texture==null&&y.sizeFromShape(o.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){S.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return $8(e.shape,t)}packedUnaryOp(e,t,o){let n=new Ar(e.shape,t),s=this.compileAndRun(n,[e],o);return cr().makeTensorFromTensorInfo(s)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let n=Kf(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,n)}if(O().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,Cw,e.dtype);let t=new Jt(e.shape,Cw),o=this.compileAndRun(t,[e]);return cr().makeTensorFromTensorInfo(o)}makeTensorInfo(e,t,o){let n;if(t==="string"&&o!=null&&o.length>0&&y.isString(o[0])){let s=o.map(a=>y.encodeString(a));n=this.write(s,e,t)}else n=this.write(o,e,t);return this.texData.get(n).usage=null,{dataId:n,shape:e,dtype:t}}makeOutput(e,t,o){return cr().makeTensorFromTensorInfo(this.makeTensorInfo(e,t,o),this)}unpackTensor(e){let t=new Qf(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new Xf(e.shape),o=!0;return this.runWebGLProgram(t,[e],e.dtype,null,o)}packedReshape(e,t){let o=[Va(e.shape),...za(e.shape)],n={dtype:e.dtype,shape:o,dataId:e.dataId},s=[Va(t),...za(t)],a=new lc(s,o),i=!0,p=[o],u=this.runWebGLProgram(a,[n],e.dtype,p,i);return{dataId:u.dataId,shape:t,dtype:u.dtype}}decode(e,t){let o=this.texData.get(e),{isPacked:n,shape:s,dtype:a}=o;if(t!=null){let m=y.sizeFromShape(s),d=t[0]*t[1]*4;y.assert(m<=d,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let i=rc(s),p;n?p=new Mf(i):p=new Pf(i);let u=!0,c=[t!=null?t:Cl(i)],l=this.runWebGLProgram(p,[{shape:i,dtype:a,dataId:e}],a,c,u,t);return{dtype:a,shape:s,dataId:l.dataId}}runWebGLProgram(e,t,o,n,s=!1,a){let i=this.makeTensorInfo(e.outputShape,o),p=this.texData.get(i.dataId);if(e.packedOutput&&(p.isPacked=!0),e.outPackingScheme===Mi.DENSE){let x=a!=null?a:Cl(e.outputShape);p.texShape=x.map(b=>b*2)}if(e.outTexUsage!=null&&(p.usage=e.outTexUsage),y.sizeFromShape(i.shape)===0)return p.values=y.getTypedArrayFromDType(i.dtype,0),i;let u=[],c=t.map(x=>{if(x.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let b=this.texData.get(x.dataId);if(b.texture==null){if(!e.packedInputs&&y.sizeFromShape(x.shape)<=O().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:x.shape,texData:null,isUniform:!0,uniformValues:b.values};e.packedInputs&&(b.isPacked=!0,b.shape=x.shape)}if(this.uploadToGPU(x.dataId),!!b.isPacked!=!!e.packedInputs)x=b.isPacked?this.unpackTensor(x):this.packTensor(x),u.push(x),b=this.texData.get(x.dataId);else if(b.isPacked&&!Li(b.shape,x.shape)){let C=x,w=x.shape;x.shape=b.shape,x=this.packedReshape(x,w),u.push(x),b=this.texData.get(x.dataId),C.shape=w}return{shape:x.shape,texData:b,isUniform:!1}});this.uploadToGPU(i.dataId);let l={shape:i.shape,texData:p,isUniform:!1},m=FE(e,c,l),d=this.getAndSaveBinary(m,()=>AE(this.gpgpu,e,c,l)),f=this.activeTimers!=null,h;f&&(h=this.startTimer()),O().get("ENGINE_COMPILE_ONLY")||RE(this.gpgpu,d,c,l,n),u.forEach(x=>this.disposeIntermediateTensorInfo(x)),f&&(h=this.endTimer(h),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(h)}));let g=O().get("WEBGL_FLUSH_THRESHOLD");if(g>0){let x=y.now();x-this.lastGlFlushTime>g&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=x)}if(!O().getBool("WEBGL_LAZILY_UNPACK")&&p.isPacked&&s===!1){let x=this.unpackTensor(i);return this.disposeIntermediateTensorInfo(i),x}return i}compileAndRun(e,t,o,n,s=!1){return o=o||t[0].dtype,this.runWebGLProgram(e,t,o,n,s)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(O().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(t=>{this.gpgpu.deleteProgram(this.binaryCache[t].webGLProgram),delete this.binaryCache[t]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=Ee(()=>{if(!O().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=O().getBool("DEBUG");O().set("DEBUG",!1);let t=this.abs(be(1e-8)).dataSync()[0];if(O().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?A8:R8}uploadToGPU(e){let t=this.texData.get(e),{shape:o,dtype:n,values:s,texture:a,usage:i,isPacked:p}=t;if(a!=null)return;let u=this.activeTimers!=null,c;u&&(c=y.now());let l=t.texShape;if(l==null&&(l=jS(o,p),t.texShape=l),s!=null){let m=rc(o),d,f=l[1],h=l[0],g=s instanceof Uint8Array||s instanceof Uint8ClampedArray;(p||!g)&&([f,h]=Ys(l[0],l[1])),p?d=new Vf(m,g):d=new vl(m,g);let x=g?[h,f]:l,b=this.makeTensorInfo(x,n),C=this.texData.get(b.dataId);g?C.usage=ir.PIXELS:C.usage=ir.UPLOAD,C.texShape=x,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(b.dataId),f,h,s);let w=[[h,f]],k=!0,_=this.runWebGLProgram(d,[b],n,w,k),$=this.texData.get(_.dataId);t.texShape=$.texShape,t.isPacked=$.isPacked,t.usage=$.usage,O().get("ENGINE_COMPILE_ONLY")?this.disposeData(_.dataId):(t.texture=$.texture,t.values=null,this.texData.delete(_.dataId)),this.disposeIntermediateTensorInfo(b),u&&(this.uploadWaitMs+=y.now()-c)}else{let m=this.acquireTexture(l,i,n,p);t.texture=m}}convertAndCacheOnCPU(e,t){let o=this.texData.get(e),{dtype:n}=o;return t!=null&&(o.values=M8(t,n)),o.values}acquireTexture(e,t,o,n){if(this.numBytesInGPU+=this.computeBytes(e,o),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let s=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${s} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,n)}computeBytes(e,t){return e[0]*e[1]*y.bytesPerElement(t)}checkCompileCompletion(){for(let[,e]of Object.entries(this.binaryCache))this.checkCompletion_(e)}async checkCompileCompletionAsync(){let e=[];if(this.gpgpu.parallelCompilationExtension){for(let[,t]of Object.entries(this.binaryCache))e.push(this.checkCompletionAsync_(t));return Promise.all(e)}else{for(let[,t]of Object.entries(this.binaryCache)){let o=new Promise(n=>{try{this.checkCompletion_(t),n(!0)}catch(s){throw s}});e.push(o)}return Promise.all(e)}}async checkCompletionAsync_(e){return this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(e):(await CC(),this.checkCompletionAsync_(e))}checkCompletion_(e){if(this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(e.webGLProgram)),this.gpgpu.gl.getShaderParameter(e.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?($f(e.source,this.gpgpu.gl.getShaderInfoLog(e.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let[,e]of Object.entries(this.binaryCache)){let{uniformLocations:t,customUniformLocations:o,infLoc:n,nanLoc:s,inShapesLocations:a,inTexShapesLocations:i,outShapeLocation:p,outShapeStridesLocation:u,outTexShapeLocation:c}=tw(this.gpgpu,e.program,e.webGLProgram);e.uniformLocations=t,e.customUniformLocations=o,e.infLoc=n,e.nanLoc=s,e.inShapesLocations=a,e.inTexShapesLocations=i,e.outShapeLocation=p,e.outShapeStridesLocation=u,e.outTexShapeLocation=c}}createTensorFromTexture(e,t,o){let{texture:n,height:s,width:a,channels:i}=e,p=cr().backend;if(!p.gpgpu.gl.isTexture(n))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 u=p.writeTexture(n,t,o,s,a,i);return cr().makeTensorFromDataId(u,t,o,p)}};Bi.nextDataId=0;function M8(r,e){if(e==="float32"||e==="complex64")return r;if(e==="int32"||e==="bool"){let t=e==="int32"?new Int32Array(r.length):new Uint8Array(r.length);for(let o=0;o<t.length;++o)t[o]=Math.round(r[o]);return t}else throw new Error(`Unknown dtype ${e}`)}var L8="4.1.0";function L$(){O().set("WEBGL_FORCE_F16_TEXTURES",!0)}yi.isBrowser()&&Ci("webgl",()=>new Bi,2);var L9e={forceHalfFloat:L$};var mc=`
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`;var io=class{constructor(e,t,o){this.variableNames=["A","B"],this.outputShape=S.assertAndGetBroadcastShape(t,o),this.enableShapeUniforms=ct(this.outputShape.length),this.userCode=`
      float binaryOperation(float a, float b) {
        ${e}
      }

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

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

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

        setOutput(result);
      }
    `}};function At(r){let{inputs:e,backend:t}=r,{x:o}=e;return t.incRef(o.dataId),{dataId:o.dataId,shape:o.shape,dtype:o.dtype}}var B$={kernelName:mo,backendName:"webgl",kernelFunc:At};function Rr(r){let{inputs:e,backend:t}=r,{real:o,imag:n}=e,s=t.makeTensorInfo(o.shape,"complex64"),a=t.texData.get(s.dataId),i=At({inputs:{x:o},backend:t}),p=At({inputs:{x:n},backend:t});return a.complexTensorInfos={real:i,imag:p},s}var V$={kernelName:ei,backendName:"webgl",kernelFunc:Rr};var Sw="return (a < 0.) ? b * a : a;",ww=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function B8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{alpha:s}=o,a=t.makeTensorInfo([],"float32",y.createScalarValue(s,"float32")),i=O().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new To(ww,n.shape,a.shape):new io(Sw,n.shape,a.shape),p=t.runWebGLProgram(i,[n,a],"float32");return t.disposeIntermediateTensorInfo(a),p}var z$={kernelName:mn,backendName:"webgl",kernelFunc:B8};var Iw="return (a < 0.) ? b * a : a;",vw=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function V8(r){let{inputs:e,backend:t}=r,{x:o,alpha:n}=e,s=O().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new To(vw,o.shape,n.shape):new io(Iw,o.shape,n.shape);return t.runWebGLProgram(s,[o,n],"float32")}var W$={kernelName:Rn,backendName:"webgl",kernelFunc:V8};var _o="if (isnan(x)) return x;";function ge({opSnippet:r,packedOpSnippet:e,cpuKernelImpl:t,dtype:o}){return({inputs:n,backend:s})=>{let{x:a}=n,i=s,p=o||a.dtype;if(i.shouldExecuteOnCPU([a])&&t!=null){let l=i.texData.get(a.dataId),m=t(l.values,p);return i.makeTensorInfo(a.shape,p,m)}let u=O().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&e!=null,c;return u?c=new Ar(a.shape,e):c=new Jt(a.shape,r),i.runWebGLProgram(c,[a],p)}}function tt({opSnippet:r,packedOpSnippet:e,checkOutOfBounds:t=!1,supportsComplex:o=!1,cpuKernelImpl:n,dtype:s}){return({inputs:a,backend:i})=>{let{a:p,b:u}=a,c=i;if(o&&p.dtype==="complex64"){let f=c.texData.get(p.dataId),h=c.texData.get(u.dataId),[g,x]=[[f.complexTensorInfos.real,h.complexTensorInfos.real],[f.complexTensorInfos.imag,h.complexTensorInfos.imag]].map(C=>{let[w,k]=C,_={dataId:w.dataId,dtype:w.dtype,shape:p.shape},$={dataId:k.dataId,dtype:k.dtype,shape:u.shape},A=new io(r,p.shape,u.shape);return c.runWebGLProgram(A,[_,$],dt(w.dtype,k.dtype))}),b=Rr({inputs:{real:g,imag:x},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(x),b}let l=s||dt(p.dtype,u.dtype);if((p.dtype==="string"||u.dtype==="string"||c.shouldExecuteOnCPU([p,u]))&&n!=null){let f=c.texData.get(p.dataId).values,h=c.texData.get(u.dataId).values,g=p.dtype==="string"?S.fromUint8ToStringArray(f):f,x=p.dtype==="string"?S.fromUint8ToStringArray(h):h,[b,C]=n(p.shape,u.shape,g,x,l),w=c.makeTensorInfo(C,l),k=c.texData.get(w.dataId);return k.values=b,w}let m=O().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&e!=null,d;return m?d=new To(e,p.shape,u.shape,t):d=new io(r,p.shape,u.shape),c.runWebGLProgram(d,[p,u],l)}}function Wa(r,e=!1){if(r==="linear")return e?F$:T$;if(r==="relu")return e?O$:E$;if(r==="elu")return e?D$:_$;if(r==="relu6")return e?P$:$$;if(r==="prelu")return e?vw:Iw;if(r==="leakyrelu")return e?ww:Sw;if(r==="sigmoid")return e?M$:A$;throw new Error(`Activation ${r} has not been implemented for the WebGL backend.`)}var dc=class{constructor(e,t,o,n=!1,s=!1,a=!1,i=null,p=!1,u=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=o,this.enableShapeUniforms=ct(this.outputShape.length);let c=n?e[1]:e[2],l=Math.ceil(c/2),m=n?"i * 2, rc.y":"rc.y, i * 2",d=s?"rc.z, i * 2":"i * 2, rc.z",f=n?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],h=s?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],g="",x="";i&&(p?g=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${i}
        }`:u?g=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${i}
        }`:g=`vec4 activation(vec4 x) {
          ${i}
        }`,x="result = activation(result);");let b=a?"result += getBiasAtOutCoords();":"";a&&this.variableNames.push("bias"),p&&this.variableNames.push("preluActivationWeights"),u&&this.variableNames.push("leakyreluAlpha");let C="rc.x",w="rc.x";e[0]<t[0]?C=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(w=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
      ${g}
      // Don't use uniform for sharedDimensionPacked for performance.
      const float sharedDimension = ${l}.0;

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

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

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

        ${b}

        ${x}

        setOutput(result);
      }
    `}};var kw={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},Nl=class{constructor(e,t,o){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=S.assertAndGetBroadcastShape(t,o),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));
      }
    `}};var U$="return a * b;";function Tl(r){let{inputs:e,backend:t}=r,{a:o,b:n}=e,s=S.upcastType(o.dtype,n.dtype);if(o.dtype==="complex64"){let i=t.texData.get(o.dataId),p=t.texData.get(n.dataId),u=new Nl(kw.REAL,o.shape,n.shape),c=new Nl(kw.IMAG,o.shape,n.shape),l=[{dataId:i.complexTensorInfos.real.dataId,dtype:i.complexTensorInfos.real.dtype,shape:o.shape},{dataId:i.complexTensorInfos.imag.dataId,dtype:i.complexTensorInfos.imag.dtype,shape:o.shape},{dataId:p.complexTensorInfos.real.dataId,dtype:p.complexTensorInfos.real.dtype,shape:n.shape},{dataId:p.complexTensorInfos.imag.dataId,dtype:p.complexTensorInfos.imag.dtype,shape:n.shape}],m=t.runWebGLProgram(u,l,"float32"),d=t.runWebGLProgram(c,l,"float32"),f=Rr({inputs:{real:m,imag:d},backend:t});return t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(d),f}if(t.shouldExecuteOnCPU([o,n])){let i=t.texData.get(o.dataId),p=t.texData.get(n.dataId),[u,c]=e$(o.shape,n.shape,i.values,p.values,s),l=t.makeTensorInfo(c,s),m=t.texData.get(l.dataId);return m.values=u,l}let a;return O().getBool("WEBGL_PACK_BINARY_OPERATIONS")?a=new To(U$,o.shape,n.shape):a=new io(U$,o.shape,n.shape),t.runWebGLProgram(a,[o,n],s)}var G$={kernelName:kn,backendName:"webgl",kernelFunc:Tl};function H$(r,e,t){let o=[Va(r.shape),...za(r.shape)],n={dtype:r.dtype,shape:o,dataId:r.dataId},s=[Va(e),...za(e)],a=new lc(s,o),i=!0,p=[o],u=t.runWebGLProgram(a,[n],r.dtype,p,i);return{dataId:u.dataId,shape:e,dtype:u.dtype}}function te(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{shape:s}=o,a=t,i=y.sizeFromShape(n.shape),p=y.inferFromImplicitShape(s,i),u=y.sizeFromShape(p);y.assert(i===u,()=>`The new shape (${p}) has ${u} elements and the old shape (${n.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`);let c=a.texData.get(n.dataId);return c.isPacked&&!Li(n.shape,p)&&!(c.texture!==null&&Li(c.shape,p))?H$(n,p,a):(a.incRef(n.dataId),{dataId:n.dataId,shape:p,dtype:n.dtype})}var q$={kernelName:Ns,backendName:"webgl",kernelFunc:te};var _l=class{constructor(e,t){this.variableNames=["x"];let{windowSize:o,batchSize:n,inSize:s,outSize:a}=e;this.outputShape=[n,a];let i=Math.floor(o/4)*4,p=o%4,u="sumValue += dot(values, ones);";if(t!=null){let l=1/t;u=`sumValue += dot(values * ${y.isInt(l)?l.toPrecision(2):l}, ones);`}let c="";s%o>0&&(c=`
        if (inIdx < 0 || inIdx >= ${s}) {
          return 0.0;
        }
      `),this.userCode=`
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

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

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

        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)
          );

          ${u}
        }

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

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

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

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

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

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

          ${m}
        }

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

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

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

          ${m}
        }
        setOutput(${u});
      }
    `}};function W8(r){let e=[];for(;e.length===0||e[e.length-1].outSize!==1;){let t=e.length?e[e.length-1].outSize:r[1],o=S.computeOptimalWindowSize(t);e.push({inSize:t,windowSize:o,outSize:Math.ceil(t/o)})}return e}function Gr(r,e,t,o){let n=W8(r.shape),s=r;for(let a=0;a<n.length;a++){let{inSize:i,windowSize:p,outSize:u}=n[a],c,l;t==="mean"?c=a===0?new _l({windowSize:p,inSize:i,batchSize:r.shape[0],outSize:u},i):new _l({windowSize:p,inSize:i,batchSize:r.shape[0],outSize:u}):c=new Jf({windowSize:p,inSize:i,batchSize:r.shape[0],outSize:u},t),l=s,s=o.runWebGLProgram(c,[s],e),l.dataId!==r.dataId&&o.disposeIntermediateTensorInfo(l)}return s}var eh=class{constructor(e,t){this.variableNames=["A"];let o=new Array(e.length);for(let a=0;a<o.length;a++)o[a]=e[t[a]];this.outputShape=o,this.rank=o.length;let n=_e(this.rank),s=U8(t);this.userCode=`
    void main() {
      ${n} resRC = getOutputCoords();
      setOutput(getA(${s}));
    }
    `}};function U8(r){let e=r.length;if(e>6)throw Error(`Transpose for rank ${e} is not yet supported`);let t=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],o=new Array(e);for(let n=0;n<r.length;n++)o[r[n]]=t[n];return o.join()}var th=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let o=new Array(e.length);for(let c=0;c<o.length;c++)o[c]=e[t[c]];if(this.outputShape=o,this.rank=o.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let n=_e(this.rank),s=bw("rc",this.rank),a=new Array(this.rank);for(let c=0;c<t.length;c++)a[t[c]]=s[c];let i=`vec2(${a.slice(-2).join()})`,p=`++${s[this.rank-1]} < ${o[this.rank-1]}`,u=`getChannel(getA(${a.join()}), ${i})`;this.userCode=`
    void main() {
      ${n} rc = getOutputCoords();
      vec4 result = vec4(0.);
      result[0] = ${u};
      if(${p}) {
        result[1] = ${u};
      }
      --${s[this.rank-1]};
      if(++${s[this.rank-2]} < ${o[this.rank-2]}) {
        result[2] = ${u};
        if(${p}) {
          result[3] = ${u};
        }
      }
      setOutput(result);
    }
    `}};function Vi(r,e,t){let o=O().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new th(r.shape,e):new eh(r.shape,e);return t.runWebGLProgram(o,[r],r.dtype)}function K$(r,e,t,o){let n=e,s=r.shape.length,a=y.parseAxisParam(n,r.shape),i=a,p=S.getAxesPermutation(i,s),u=p!=null,c=r;u&&(c=Vi(r,p,o),i=S.getInnerMostAxes(i.length,s)),S.assertAxesAreInnerMostDims("sum",i,s);let[l,m]=S.computeOutAndReduceShapes(c.shape,i),d=l;t&&(d=S.expandShapeToKeepDim(l,a));let f=y.sizeFromShape(m),g=y.sizeFromShape(r.shape)/f,x=te({inputs:{x:c},attrs:{shape:[g,f]},backend:o}),b=ka(r.dtype),C=Gr(x,b,"sum",o),w=te({inputs:{x:C},attrs:{shape:d},backend:o});return o.disposeIntermediateTensorInfo(x),o.disposeIntermediateTensorInfo(C),u&&o.disposeIntermediateTensorInfo(c),w}function Ou(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o;return K$(n,s,a,t)}var j$={kernelName:Hn,backendName:"webgl",kernelFunc:Ou};function xt(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{perm:s}=o,a=t,i=n.shape.length,p=new Array(i);for(let c=0;c<p.length;c++)p[c]=n.shape[s[c]];let u;if(a.shouldExecuteOnCPU([n])){let l=a.texData.get(n.dataId).values,m=Du(l,n.shape,n.dtype,s,p);u=a.makeTensorInfo(p,n.dtype);let d=a.texData.get(u.dataId);d.values=m}else u=Vi(n,s,a);return u}var X$={kernelName:ro,backendName:"webgl",kernelFunc:xt};var Nw=1e3;function Pu({a:r,b:e,transposeA:t,transposeB:o,backend:n,bias:s=null,preluActivationWeights:a=null,leakyreluAlpha:i=0,activation:p=null}){let u=r.shape.length,c=e.shape.length,l=t?r.shape[u-2]:r.shape[u-1],m=o?e.shape[c-1]:e.shape[c-2],d=t?r.shape[u-1]:r.shape[u-2],f=o?e.shape[c-2]:e.shape[c-1],h=r.shape.slice(0,-2),g=e.shape.slice(0,-2),x=y.sizeFromShape(h),b=y.sizeFromShape(g),w=br.assertAndGetBroadcastShape(r.shape.slice(0,-2),e.shape.slice(0,-2)).concat([d,f]);y.assert(l===m,()=>`Error in matMul: inner shapes (${l}) and (${m}) of Tensors with shapes ${r.shape} and ${e.shape} and transposeA=${t} and transposeB=${o} must match.`);let k=t?[x,l,d]:[x,d,l],_=o?[b,f,m]:[b,m,f],$=te({inputs:{x:r},backend:n,attrs:{shape:k}}),A=te({inputs:{x:e},backend:n,attrs:{shape:_}}),R=[$,A],D=Math.max(x,b),P=t?$.shape[1]:$.shape[2],M=s!=null,L=a!=null,W=p==="leakyrelu",V=p!=null?Wa(p,!0):null,U=M||L||W||V!=null,q;if((d===1||f===1)&&P>Nw&&U===!1){let j=$,X=A;t&&(j=xt({inputs:{x:$},backend:n,attrs:{perm:[0,2,1]}}),R.push(j)),o&&(X=xt({inputs:{x:A},backend:n,attrs:{perm:[0,2,1]}}),R.push(X));let Z=f!==1,ee=f===1,Y=j;Z&&(Y=te({inputs:{x:j},backend:n,attrs:{shape:[D,P,1]}}),R.push(Y));let J=f===1?2:1,ie=X;ee&&(ie=te({inputs:{x:X},backend:n,attrs:{shape:[D,1,P]}}),R.push(ie));let pe=Tl({inputs:{a:Y,b:ie},backend:n});q=Ou({inputs:{x:pe},backend:n,attrs:{axis:J,keepDims:!0}}),R.push(pe)}else{let j=dt(r.dtype,e.dtype),X=new dc(k,_,[D,d,f],t,o,M,V,L,W),Z=[$,A];if(s!=null&&Z.push(s),L&&Z.push(a),W){let ee=n.makeTensorInfo([],"float32",y.createScalarValue(i,"float32"));Z.push(ee),R.push(ee)}q=n.runWebGLProgram(X,Z,j)}let H=te({inputs:{x:q},backend:n,attrs:{shape:w}});R.push(q);for(let j of R)n.disposeIntermediateTensorInfo(j);return H}function G8(r){let{inputs:e,backend:t,attrs:o}=r,{a:n,b:s,bias:a,preluActivationWeights:i}=e,{transposeA:p,transposeB:u,activation:c,leakyreluAlpha:l}=o;return Pu({a:n,b:s,transposeA:p,transposeB:u,backend:t,bias:a,preluActivationWeights:i,leakyreluAlpha:l,activation:c})}var Y$={kernelName:fo,backendName:"webgl",kernelFunc:G8};var Q$="return abs(x);";function H8(r){let{inputs:e,backend:t}=r,{x:o}=e;if(t.shouldExecuteOnCPU([o])&&o.dtype!=="complex64"){let s=t.texData.get(o.dataId),a=Kf(s.values);return t.makeTensorInfo(o.shape,o.dtype,a)}let n;return O().getBool("WEBGL_PACK_UNARY_OPERATIONS")?n=new Ar(o.shape,Q$):n=new Jt(o.shape,Q$),t.runWebGLProgram(n,[o],o.dtype)}var Z$={kernelName:gs,backendName:"webgl",kernelFunc:H8};var q8=Bt+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return acos(x);
`,K8=ge({opSnippet:q8}),J$={kernelName:sa,backendName:"webgl",kernelFunc:K8};var j8=Bt+`
  if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,X8=ge({opSnippet:j8}),eA={kernelName:aa,backendName:"webgl",kernelFunc:X8};var tA="return a + b;",Y8=tt({opSnippet:tA,packedOpSnippet:tA,supportsComplex:!0,cpuKernelImpl:DE}),rA={kernelName:eo,backendName:"webgl",kernelFunc:Y8};var rh=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((s,a)=>`T${a}`);let o=[];this.variableNames.forEach(s=>{o.push(`float v${s} = get${s}AtOutCoords();`)});let n=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
      void main() {
        ${o.join(`
        `)}

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

        vec4 result = ${n};
        setOutput(result);
      }
    `}};function nh(r){let{inputs:e,backend:t}=r,o=e;if(o.length===1)return At({inputs:{x:o[0]},backend:t});if(o.length>O().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let p=Math.floor(o.length/2),u=nh({inputs:o.slice(0,p),backend:t}),c=nh({inputs:o.slice(p),backend:t});return nh({inputs:[u,c],backend:t})}let n=o.map(p=>p.dtype).reduce((p,u)=>dt(p,u)),s=o.map(p=>p.shape),i=O().getBool("WEBGL_PACK")?new oh(o[0].shape,s):new rh(o[0].shape,s);return t.runWebGLProgram(i,o,n)}var oA={kernelName:Mo,backendName:"webgl",kernelFunc:nh};function Q8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,p=y.parseAxisParam(s,n.shape),u=p,c=S.getAxesPermutation(u,i),l=n;c!=null&&(l=xt({inputs:{x:n},backend:t,attrs:{perm:c}}),u=S.getInnerMostAxes(u.length,i)),S.assertAxesAreInnerMostDims("all",u,i);let[m,d]=S.computeOutAndReduceShapes(l.shape,u),f=y.sizeFromShape(d),h=te({inputs:{x:l},backend:t,attrs:{shape:[-1,f]}}),g=Gr(h,h.dtype,"all",t),x;if(a){let b=S.expandShapeToKeepDim(m,p);x=te({inputs:{x:g},backend:t,attrs:{shape:b}})}else x=te({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(l),x}var nA={kernelName:Lo,backendName:"webgl",kernelFunc:Q8};function Z8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,p=y.parseAxisParam(s,n.shape),u=p,c=S.getAxesPermutation(u,i),l=n;c!=null&&(l=xt({inputs:{x:n},backend:t,attrs:{perm:c}}),u=S.getInnerMostAxes(u.length,i)),S.assertAxesAreInnerMostDims("any",u,i);let[m,d]=S.computeOutAndReduceShapes(l.shape,u),f=y.sizeFromShape(d),h=te({inputs:{x:l},backend:t,attrs:{shape:[-1,f]}}),g=Gr(h,h.dtype,"any",t),x;if(a){let b=S.expandShapeToKeepDim(m,p);x=te({inputs:{x:g},backend:t,attrs:{shape:b}})}else x=te({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(l),x}var sA={kernelName:Bo,backendName:"webgl",kernelFunc:Z8};var sh=class{constructor(e,t,o){this.variableNames=["A"];let{windowSize:n,batchSize:s,outSize:a}=e;o||this.variableNames.push("bestIndicesA"),this.outputShape=[s,a];let i=t==="max"?">":"<",p=o?"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 = ${p};
          float candidate = getA(batch, inIdx);
          if (candidate ${i} bestValue) {
            bestValue = candidate;
            bestIndex = inIdx;
          }
        }
        setOutput(float(bestIndex));
      }
    `}};var ah=class{constructor(e,t,o,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,y.assert(e.length>2,()=>`Packed arg${o.charAt(0).toUpperCase()+o.slice(1)} supports only inputs with rank above 2.`);let s=e[e.length-1],a=Math.ceil(s/t);this.outputShape=e.slice(0,-1),a>1&&this.outputShape.push(a),n||this.variableNames.push("bestIndicesA");let i=this.outputShape,p=i.length,u=_e(p),c=$t("coords",p),l,m;if(a===1){m=p+1;let A=_e(m);l=`
        ${A} sourceLocR = ${A}(${c.join()}, 0);
        ++${c[p-1]};
        ${A} sourceLocG = ${A}(${c.join()}, 0);
        ++${c[p-2]};
        ${A} sourceLocA = ${A}(${c.join()}, 0);
        --${c[p-1]};
        ${A} sourceLocB = ${A}(${c.join()}, 0);
        --${c[p-2]};`}else m=p,l=`
        ${u} sourceLocR = coords;
        ++${c[p-1]};
        ${u} sourceLocG = coords;
        ++${c[p-2]};
        ${u} sourceLocA = coords;
        --${c[p-1]};
        ${u} sourceLocB = coords;
        --${c[p-2]};`;let d=["x","y","z","w","u","v"].slice(0,m),f="."+d[m-1],h=d.map(A=>"int "+A),g=$t("sourceLocR",m-1).concat("inIdx.r"),x=$t("sourceLocG",m-1).concat("inIdx.g"),b=$t("sourceLocB",m-1).concat("inIdx.b"),C=$t("sourceLocA",m-1).concat("inIdx.a"),w=o==="max"?"greaterThan":"lessThan",k=n?"":`
          inIdx = round(vec4(getBestIndicesAChannel(${g.join()}),
                             getBestIndicesAChannel(${x.join()}),
                             getBestIndicesAChannel(${b.join()}),
                             getBestIndicesAChannel(${C.join()})));`,_=`vec4(
            getAChannel(${g.join()}),
            hasNextCol ? getAChannel(${x.join()}) : 0.,
            hasNextRow ? getAChannel(${b.join()}) : 0.,
            hasNextRow && hasNextCol ? getAChannel(${C.join()}) : 0.)`,$=n?"":`
      float getBestIndicesAChannel(${h.join()}) {
        return getChannel(getBestIndicesA(${d.join()}),
                                          vec2(${d.slice(-2).join()}));
      }`;this.userCode=`
      float getAChannel(${h.join()}) {
        return getChannel(getA(${d.join()}),
                               vec2(${d.slice(-2).join()}));
      }
      ${$}
      void main() {
        ${u} coords = getOutputCoords();
        bool hasNextCol = ${c[p-1]} < ${i[p-1]-1};
        bool hasNextRow = ${c[p-2]} < ${i[p-2]-1};
        ${l}
        ivec4 srcIdx = ivec4(sourceLocR${f}, sourceLocG${f},
          sourceLocB${f}, sourceLocA${f}) * ${t};
        ivec4 inIdx = srcIdx;
        vec4 bestIndex = vec4(inIdx);
        vec4 bestValue = ${_};

        for (int i = 0; i < ${t}; i++) {
          inIdx = srcIdx;
          ${k}
          vec4 candidate = ${_};
          bvec4 nan = isnan(candidate);
          bvec4 replace = bvec4(
            vec4(${w}(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 aA(r,e,t,o=null){let n=e.shape[0],s=e.shape[1];o!=null&&(n=o.shape[0],s=o.shape[1]);let a=S.computeOptimalWindowSize(s),i={windowSize:a,inSize:s,batchSize:n,outSize:Math.ceil(s/a)},p=new sh(i,t,o==null),u=[e];o!=null&&u.push(o);let c=r.runWebGLProgram(p,u,"int32");if(c.shape[1]===1)return c;let l=aA(r,e,t,c);return r.disposeIntermediateTensorInfo(c),l}function iA(r,e,t,o=null){let n=o!=null?o.shape:e.shape,s=n[n.length-1],a=S.computeOptimalWindowSize(s),i=new ah(n,a,t,o==null),p=o==null?[e]:[e,o],u=r.runWebGLProgram(i,p,"int32");if(u.shape.length===e.shape.length){let c=iA(r,e,t,u);return r.disposeIntermediateTensorInfo(u),c}return u}function ih(r,e,t,o){let n=[t];if(S.assertAxesAreInnerMostDims("arg"+o.charAt(0).toUpperCase()+o.slice(1),n,e.shape.length),!O().getBool("WEBGL_PACK_REDUCE")||e.shape.length<=2){let s=[],a=r.texData.get(e.dataId),i=a!==null&&a.isPacked,p=e;i&&(p=r.unpackTensor(e),s.push(p));let[u,c]=S.computeOutAndReduceShapes(p.shape,n),l=y.sizeFromShape(c),m=te({inputs:{x:p},backend:r,attrs:{shape:[-1,l]}});s.push(m);let d=aA(r,m,o);s.push(d);let f=te({inputs:{x:d},backend:r,attrs:{shape:u}});return s.forEach(h=>r.disposeIntermediateTensorInfo(h)),f}return iA(r,e,o)}function J8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s}=o,a=y.parseAxisParam(s,n.shape),i=S.getAxesPermutation(a,n.shape.length),p=n,u=[];i!=null&&(p=xt({inputs:{x:n},backend:t,attrs:{perm:i}}),u.push(p),a=S.getInnerMostAxes(a.length,p.shape.length)),S.assertAxesAreInnerMostDims("argMax",[a[0]],p.shape.length);let c=ih(t,p,a[0],"max");return u.forEach(l=>t.disposeIntermediateTensorInfo(l)),c}var uA={kernelName:Vo,backendName:"webgl",kernelFunc:J8};function eY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s}=o,a=y.parseAxisParam(s,n.shape),i=S.getAxesPermutation(a,n.shape.length),p=n,u=[];i!=null&&(p=xt({inputs:{x:n},backend:t,attrs:{perm:i}}),u.push(p),a=S.getInnerMostAxes(a.length,p.shape.length)),S.assertAxesAreInnerMostDims("argMin",[a[0]],p.shape.length);let c=ih(t,p,a[0],"min");return u.forEach(l=>t.disposeIntermediateTensorInfo(l)),c}var pA={kernelName:Za,backendName:"webgl",kernelFunc:eY};var tY=Bt+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return asin(x);
`,rY=ge({opSnippet:tY}),cA={kernelName:ia,backendName:"webgl",kernelFunc:rY};var oY=Bt+"return log(x + sqrt(x * x + 1.0));",nY=ge({opSnippet:oY}),lA={kernelName:ua,backendName:"webgl",kernelFunc:nY};var sY=Bt+`
  return atan(x);
`,aY=ge({opSnippet:sY}),mA={kernelName:pa,backendName:"webgl",kernelFunc:aY};var iY=mc+`
  return atan(a, b);
`,uY=`
  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);
  `+Zs+`
  return result;
`,pY=tt({opSnippet:iY,packedOpSnippet:uY}),dA={kernelName:la,backendName:"webgl",kernelFunc:pY};var cY=Bt+`
  if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,lY=ge({opSnippet:cY}),fA={kernelName:ca,backendName:"webgl",kernelFunc:lY};var ps=class{constructor(e,t,o,n=!1,s=!1){if(this.variableNames=["x"],t==="avg"&&o)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,i=e.strideHeight,p=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,l=e.effectiveFilterHeight,m=e.effectiveFilterWidth,d=e.padInfo.top,f=e.padInfo.left;this.outputShape=e.outShape;let h=t==="avg",g=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,x=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,b="0.0";if(h||(b="-1.0 / 1e-20"),o){let A=">=";this.userCode=`
        const ivec2 strides = ivec2(${i}, ${p});
        const ivec2 pads = ivec2(${d}, ${f});

        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 < ${l};
              wR += ${u}) {
            int xR = xRCorner + wR;

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

            for (int wC = 0; wC < ${m};
                wC += ${c}) {
              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 ${A} currMinMaxValue) {
                minMaxValue = value;
                minMaxValueFound = 1.0;
                minMaxPosition = ${n?s?g:x:`wR * ${m} + wC`};
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let C="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / count");let k=Math.floor(a/4)*4,_=a%4,$=`
      if (${h}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${C}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec2 strides = ivec2(${i}, ${p});
      const ivec2 pads = ivec2(${d}, ${f});
      const float initializationValue = ${b};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float count = 0.0;

      float getValue(int batch, int xR, int xC, int d) {
        if (xC < 0 || xC >= ${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(${b});
        float avgValue = 0.0;
        count = 0.0;

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

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

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

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

            ${$}
          }

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

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

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

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

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

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

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

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

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

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

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

              for (int wC = 0; wC < ${h};
                  wC += ${m}) {
                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 ${D} currMinMaxValue) {
                  minMaxValue = value;
                  minMaxValueFound = 1.0;
                  minMaxPosition = ${n?s?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${f} * ${h} +
                      wR * ${h} + wC`};
                }
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let k="max",_=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(_="avgValue / count");let $=Math.floor(a/4)*4,A=a%4,R=`
      if (${C}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${k}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec3 strides =
        ivec3(${i}, ${p}, ${u});
      const ivec3 pads = ivec3(${g}, ${x}, ${b});
      const float initializationValue = ${w};
      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(${w});
        float avgValue = 0.0;
        count = 0.0;

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

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

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

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

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

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

              ${R}
            }

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

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

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

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

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

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

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${p};
            wR += ${a}) {
          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 < ${u};
            wC+= ${i}) {
            float dyC = float(dyCCorner + wC) / ${s}.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);
      }
    `}},ph=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,o=e.filterHeight,n=e.filterWidth,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,p=e.dilationDepth,u=e.dilationHeight,c=e.dilationWidth,l=e.effectiveFilterDepth,m=e.effectiveFilterHeight,d=e.effectiveFilterWidth,f=l-1-e.padInfo.front,h=m-1-e.padInfo.top,g=d-1-e.padInfo.left,x=1/(t*o*n);this.userCode=`
      const ivec3 pads = ivec3(${f}, ${h}, ${g});
      const float avgMultiplier = float(${x});

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

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

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

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

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

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

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

            for (int wC = 0; wC < ${d};
                wC += ${c}) {
              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 fY(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s,{filterSize:i,strides:p,pad:u,dimRoundingMode:c}=o,l=[1,1,1],m=S.computePool3DInfo(a.shape,i,p,l,u,c),d=new ph(m);return t.runWebGLProgram(d,[n],a.dtype)}var xA={kernelName:Im,backendName:"webgl",kernelFunc:fY};function hY(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s;is([n,s],"avgPoolGrad");let{filterSize:i,strides:p,pad:u}=o,c=S.computePool2DInfo(a.shape,i,p,1,u),l=new uh(c);return t.runWebGLProgram(l,[n],a.dtype)}var yA={kernelName:wm,backendName:"webgl",kernelFunc:hY};function gY(r){let{inputs:e,backend:t,attrs:o}=r,{a:n,b:s}=e,{transposeA:a,transposeB:i}=o;return Pu({a:n,b:s,transposeA:a,transposeB:i,backend:t})}var bA={kernelName:Wo,backendName:"webgl",kernelFunc:gY};var ch=class{constructor(e,t,o,n,s,a){this.outputShape=[],this.variableNames=["x","mean","variance"],S.assertAndGetBroadcastShape(e,t),S.assertAndGetBroadcastShape(e,o);let i="0.0";n!=null&&(S.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let p="1.0";s!=null&&(S.assertAndGetBroadcastShape(e,s),this.variableNames.push("scale"),p="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
      void main() {
        float x = getXAtOutCoords();
        float mean = getMeanAtOutCoords();
        float variance = getVarianceAtOutCoords();
        float offset = ${i};
        float scale = ${p};
        float inv = scale * inversesqrt(variance + float(${a}));
        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
      }
    `}};var lh=class{constructor(e,t,o,n,s,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],S.assertAndGetBroadcastShape(e,t),S.assertAndGetBroadcastShape(e,o);let i="vec4(0.0)";n!=null&&(S.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let p="vec4(1.0)";s!=null&&(S.assertAndGetBroadcastShape(e,s),this.variableNames.push("scale"),p="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
      void main() {
        vec4 offset = ${i};
        vec4 scale = ${p};

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

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

        setOutput((x - mean) * inv + offset);
      }
    `}};var xY=({inputs:r,backend:e,attrs:t})=>{let{x:o,mean:n,variance:s,offset:a,scale:i}=r;y.assert(n.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),y.assert(a==null||n.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),y.assert(i==null||n.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:p}=t;p==null&&(p=.001);let u=[o,n,s],c=null;a!=null&&(c=a.shape,u.push(a));let l=null;i!=null&&(l=i.shape,u.push(i));let m=O().getBool("WEBGL_PACK_NORMALIZATION")?new lh(o.shape,n.shape,s.shape,c,l,p):new ch(o.shape,n.shape,s.shape,c,l,p);return e.runWebGLProgram(m,u,u[0].dtype)},CA={kernelName:an,backendName:"webgl",kernelFunc:xY};var mh=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=_e(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let o=yY(this.rank),n,s=e.map((a,i)=>`sourceLoc.${Tw[i]} = start[${i}] + coords.${Tw[i]};`);n=`
        ${t} sourceLoc;
        ${t} coords = getOutputCoords();
        ${s.join(`
`)}
      `,this.userCode=`
      void main() {
        ${n}
        setOutput(getSource(${o}));
      }
    `}},Tw=["x","y","z","w","u","v"];function yY(r){if(r===1)return"sourceLoc";if(r<=6)return Tw.slice(0,r).map(e=>"sourceLoc."+e).join(",");throw Error(`Slicing for rank ${r} is not yet supported`)}var dh=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=_e(this.rank),o=$t("coords",this.rank),n=$t("sourceLoc",this.rank),s=this.rank===1?"sourceLoc":`vec2(${n.slice(-2).join()})`,a=`getChannel(getSource(${n.join()}), ${s})`,i=`
      result.x = ${a};
      if (++${o[this.rank-1]} < ${e[this.rank-1]}) {
        ++${n[this.rank-1]};
        result.y = ${a};
        --${n[this.rank-1]};
      }
    `,p=this.rank===1?"":`
      --${o[this.rank-1]};
      if (++${o[this.rank-2]} < ${e[this.rank-2]}) {
        ++${n[this.rank-2]};
        result.z = ${a};
        if (++${o[this.rank-1]} < ${e[this.rank-1]}) {
          ++${n[this.rank-1]};
          result.w = ${a};
        }
      }
    `,u=this.rank<=4?`sourceLoc = coords +
            ${t}(${e.map((c,l)=>`start[${l}]`).join()});`:e.map((c,l)=>`${n[l]} = ${o[l]} + start[${l}];`).join(`
`);this.userCode=`
      void main() {
        ${t} coords = getOutputCoords();
        ${t} sourceLoc;
        ${u}
        vec4 result = vec4(0.);
        ${i}
        ${p}
        setOutput(result);
      }
    `}};function bY(r,e,t,o){let n=o.texData.get(r.dataId),s=o.makeTensorInfo(t,r.dtype),a=o.texData.get(s.dataId);Object.assign(a,n),a.refCount=1,a.shape=t,a.dtype=r.dtype;let i=ut.computeFlatOffset(e,y.computeStrides(r.shape));n.slice&&(i+=n.slice.flatOffset),a.slice={flatOffset:i,origDataId:n.slice&&n.slice.origDataId||r.dataId};let p=o.dataRefCount.get(a.slice.origDataId)||1;return o.dataRefCount.set(a.slice.origDataId,p+1),s}function cs(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{begin:s,size:a}=o,[i,p]=ut.parseSliceParams(n,s,a);if(ut.assertParamsValid(n,i,p),y.sizeFromShape(p)===0)return t.makeTensorInfo(p,n.dtype,[]);if(t.shouldExecuteOnCPU([n])||n.dtype==="string"){let l=t.texData.get(n.dataId),m=l$(l.values,i,p,n.shape,n.dtype);return t.makeTensorInfo(p,n.dtype,m)}let{isPacked:u}=t.texData.get(n.dataId),c=ut.isSliceContinous(n.shape,i,p);if(u||!c){let l=O().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new dh(p):new mh(p),m=[i];return t.runWebGLProgram(l,[n],n.dtype,m)}return t.uploadToGPU(n.dataId),bY(n,i,p,t)}var SA={kernelName:_s,backendName:"webgl",kernelFunc:cs};var CY=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockShape:s,crops:a}=o;y.assert(n.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let i=s.reduce((b,C)=>b*C),p=S.getReshaped(n.shape,s,i),u=S.getPermuted(p.length,s.length),c=S.getReshapedPermuted(n.shape,s,i),l=S.getSliceBeginCoords(a,s.length),m=S.getSliceSize(c,a,s.length),d=[],f=te({inputs:{x:n},backend:t,attrs:{shape:p}}),h=xt({inputs:{x:f},backend:t,attrs:{perm:u}}),g=te({inputs:{x:h},backend:t,attrs:{shape:c}}),x=cs({inputs:{x:g},backend:t,attrs:{begin:l,size:m}});return d.push(f),d.push(h),d.push(g),d.forEach(b=>t.disposeIntermediateTensorInfo(b)),x},wA={kernelName:xs,backendName:"webgl",kernelFunc:CY};function SY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a}=o,i=t.readSync(n.dataId),p=t.readSync(s.dataId),u=qf(i,p,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,u)}var IA={kernelName:Ja,backendName:"webgl",kernelFunc:SY};function wY(r){let{inputs:e,backend:t}=r,{s0:o,s1:n}=e,s=t.readSync(o.dataId),a=t.readSync(n.dataId),i=S.assertAndGetBroadcastShape(Array.from(s),Array.from(a));return t.makeTensorInfo([i.length],"int32",Int32Array.from(i))}var vA={kernelName:up,backendName:"webgl",kernelFunc:wY};var IY="return float(a != b);",_w=tt({opSnippet:IY,cpuKernelImpl:r$,dtype:"bool"}),kA={kernelName:Nn,backendName:"webgl",kernelFunc:_w};function Ua(r){let{inputs:e,backend:t}=r,{input:o}=e,n=t.texData.get(o.dataId);return At({inputs:{x:n.complexTensorInfos.real},backend:t})}var NA={kernelName:ai,backendName:"webgl",kernelFunc:Ua};var vY="return float(int(x));";function TA(r,e){let t=new Jt(r.shape,vY),o=e.runWebGLProgram(t,[r],"int32");return{dataId:o.dataId,shape:o.shape,dtype:o.dtype}}function Ew(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{dtype:s}=o;if(s==="complex64"){if(n.dtype==="complex64")return At({inputs:{x:n},backend:t});let a=Vr(n.shape),i=Ew({inputs:{x:n},backend:t,attrs:{dtype:"float32"}}),p=Rr({inputs:{real:i,imag:a},backend:t});return a.dispose(),t.disposeIntermediateTensorInfo(i),p}if(n.dtype==="complex64"){let a=Ua({inputs:{input:n},backend:t}),i=Ew({inputs:{x:a},backend:t,attrs:{dtype:s}});return t.disposeIntermediateTensorInfo(a),i}if(!y.hasEncodingLoss(n.dtype,s)){let a=At({inputs:{x:n},backend:t});return{dataId:a.dataId,shape:a.shape,dtype:s}}if(t.shouldExecuteOnCPU([n])){let a=t.texData.get(n.dataId).values,[i,p,u]=PE(a,n.shape,n.dtype,s);return t.makeTensorInfo(i,p,u)}if(s==="int32")return TA(n,t);if(s==="bool"){let a=t.makeTensorInfo([],"bool",y.getTypedArrayFromDType("bool",1)),p=_w({inputs:{a:n,b:a},backend:t});return t.disposeIntermediateTensorInfo(a),p}throw new Error(`Error in Cast: failed to cast ${n.dtype} to ${s}`)}var _A={kernelName:co,backendName:"webgl",kernelFunc:Ew};var EA="return ceil(x);",kY=ge({opSnippet:EA,packedOpSnippet:EA,cpuKernelImpl:ME}),$A={kernelName:Uo,backendName:"webgl",kernelFunc:kY};var fh=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));
      }
    `}};var hh=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 NY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{clipValueMin:s,clipValueMax:a}=o,i;O().getBool("WEBGL_PACK_CLIP")?i=new hh(n.shape):i=new fh(n.shape);let p=[[s],[a]];return t.runWebGLProgram(i,[n],n.dtype,p)}var AA={kernelName:lo,backendName:"webgl",kernelFunc:NY};var gh=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 RA(r,e){return{dataId:e.dataId,dtype:e.dtype,shape:r.shape}}function TY(r){let{inputs:e,backend:t}=r,{x:o}=e,n=t.texData.get(o.dataId),s=new gh(o.shape),a=[RA(o,n.complexTensorInfos.real),RA(o,n.complexTensorInfos.imag)];return t.runWebGLProgram(s,a,a[0].dtype)}var FA={kernelName:pp,backendName:"webgl",kernelFunc:TY};var xh=class{constructor(e){this.outputShape=[],this.outputShape=S.computeOutShape(e,1),this.variableNames=e.map((a,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let a=1;a<t.length;a++)t[a]=t[a-1]+e[a][1];let o=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let a=1;a<t.length;a++){let i=t[a-1];o.push(`else if (yC < ${t[a]}) setOutput(getT${a}(yR, yC-${i}));`)}let n=t.length,s=t[t.length-1];o.push(`else setOutput(getT${n}(yR, yC-${s}));`),this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int yR = coords.x;
        int yC = coords.y;

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

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

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

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

        ${a[n-1]} = ${a[n-1]} - 1;
        if (${a[n-2]} < ${o[n-2]} &&
            ${a[n-1]} < ${o[n-1]}) {
          result.b = getValue(${a});
        }
        setOutput(result);
      }
    `}};function yh(r,e,t){let o=r.indexOf(e);return r.map((s,a)=>a===o?`${s} - ${t}`:s).join()}function Mu(r){let{inputs:e,backend:t}=r,{input:o}=e,n=t.texData.get(o.dataId);return At({inputs:{x:n.complexTensorInfos.imag},backend:t})}var DA={kernelName:si,backendName:"webgl",kernelFunc:Mu};function fc(r,e,t){let o=r[0].dtype;if(o==="complex64"){let d=r.map(b=>Ua({inputs:{input:b},backend:t})),f=r.map(b=>Mu({inputs:{input:b},backend:t})),h=fc(d,e,t),g=fc(f,e,t),x=Rr({inputs:{real:h,imag:g},backend:t});return d.forEach(b=>t.disposeIntermediateTensorInfo(b)),f.forEach(b=>t.disposeIntermediateTensorInfo(b)),t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),x}let n=t.shouldExecuteOnCPU(r);if(o==="string"&&(n=!0),n){let d=r.map(w=>{let _=[-1,y.sizeFromShape(w.shape.slice(e))];return te({inputs:{x:w},backend:t,attrs:{shape:_}})}),f=d.map(w=>({vals:t.readSync(w.dataId),shape:w.shape})),h=S.computeOutShape(d.map(w=>w.shape),1),g=d[0].shape[0]===1,x=LE(f,h,o,g),b=S.computeOutShape(r.map(w=>w.shape),e),C=t.makeTensorInfo(b,o,x);return d.forEach(w=>t.disposeIntermediateTensorInfo(w)),C}let s=r.filter(d=>y.sizeFromShape(d.shape)>0),a=O().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&s[0].shape.length>1;if(s.length===1){let d=a?new Jt(r[0].shape,Qs):new Ar(r[0].shape,Qs);return t.runWebGLProgram(d,r,o)}let i=O().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(s.length>i){let d=[];for(let h=0;h<s.length;h+=i){let g=s.slice(h,h+i);d.push(fc(g,e,t))}let f=fc(d,e,t);for(let h of d)t.disposeIntermediateTensorInfo(h);return f}if(a){let d=new bh(s.map(f=>f.shape),e);return t.runWebGLProgram(d,s,o)}let{tensors2D:p,outShape:u}=_Y(s,e,t),c=new xh(p.map(d=>d.shape)),l=t.runWebGLProgram(c,p,o);p.forEach(d=>t.disposeIntermediateTensorInfo(d));let m=te({inputs:{x:l},attrs:{shape:u},backend:t});return t.disposeIntermediateTensorInfo(l),m}function _Y(r,e,t){let o=S.computeOutShape(r.map(s=>s.shape),e);return{tensors2D:r.map(s=>te({inputs:{x:s},attrs:{shape:[-1,y.sizeFromShape(s.shape.slice(e))]},backend:t})),outShape:o}}function $w(r){let{inputs:e,backend:t,attrs:o}=r,{axis:n}=o,s=y.parseAxisParam(n,e[0].shape)[0],a=e.map(u=>u.shape);S.assertParamsConsistent(a,s);let i=S.computeOutShape(e.map(u=>u.shape),s);if(y.sizeFromShape(i)===0)return t.makeTensorInfo(i,e[0].dtype,[]);let p=e.filter(u=>y.sizeFromShape(u.shape)>0);return p.length===1?At({inputs:{x:p[0]},backend:t}):fc(p,s,t)}var OA={kernelName:ys,backendName:"webgl",kernelFunc:$w};var hc=class{constructor(e,t=!1,o=null,n=!1,s=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.padInfo.top,i=e.padInfo.left,p=e.strideHeight,u=e.strideWidth,c=e.dilationHeight,l=e.dilationWidth,m=e.filterHeight,d=e.filterWidth,f=Math.floor(e.inChannels/4)*4,h=e.inChannels%4,g=e.dataFormat==="channelsLast",x=g?1:2,b=g?2:3,C=g?3:1,w="",k="";o&&(n?w=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${o}
        }`:s?w=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${o}
        }`:w=`
          float activation(float x) {
            ${o}
          }
        `,k="result = activation(result);");let _=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${w}

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

            }
          }
        }

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

      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 < ${l}; wF++) {
          int xF = xFCorner + wF * ${p};

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

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

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

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

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

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

                dotProd += dot(xValues, wValues);
              }

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

         ${m}

         vec4 result = dotProd - vec4(0.000000000000001);
         ${h}
         ${f}
         setOutput(result);
       }
     `}};var Sh=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=ct(this.outputShape.length);let{dataFormat:o}=t,n=St(),s=o==="channelsLast",a=s?1:2,i=s?2:3,p=this.enableShapeUniforms?"if(blockIndex < outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${e[2]} && pos < ${e[1]}) {`,u="";for(let c=0;c<=1;c++)for(let l=0;l<=1;l++)u+=`
          blockIndex = rc.z + ${l};
          pos = rc.y + ${c};

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

            if(d0 < inputShape[${a}] && 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 (${s}) {
                  innerDims = vec2(d1, ch);
                  result[${c*2+l}] = getChannel(
                    getA(rc.x, d0, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                } else {
                  innerDims = vec2(d0, d1);
                  result[${c*2+l}] = 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;

        ${u}

        ${n.output} = result;
      }
    `}};function wh(r,e){let t=r.length;return t>=3?e?[...r.slice(0,-3),r[t-3]*r[t-2],r[t-1]]:[...r.slice(0,-3),r[t-3],r[t-2]*r[t-1]]:!e&&t===1&&r[0]>1?[r[0],1]:null}function Ih({x:r,filter:e,convInfo:t,backend:o,bias:n=null,preluActivationWeights:s=null,leakyreluAlpha:a=0,activation:i=null}){let p=r.shape,u=o.texData.get(r.dataId),c=t.inChannels,l=p[0]*p[1]*p[2],m=t.outChannels,d=t.dataFormat==="channelsLast",f=!1,h=!1,g,x=[];if(s!=null){let w=wh(s.shape,d);w!=null&&(s=te({inputs:{x:s},backend:o,attrs:{shape:w}}),x.push(s))}if(n!=null){let w=wh(n.shape,d);w!=null&&(n=te({inputs:{x:n},backend:o,attrs:{shape:w}}),x.push(n))}if(!((l===1||m===1)&&c>Nw)&&u.isPacked&&d&&u.texture!=null&&p[2]%2!==0&&y.arraysEqual(u.shape.slice(-3),p.slice(-3))){let w=p[0]*p[1]*(p[2]+1),k={dataId:r.dataId,shape:[1,w,t.inChannels],dtype:r.dtype},_=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,y.assert(Li(u.shape,k.shape),()=>`packed reshape ${u.shape} to ${k.shape} isn't free`);let $=te({inputs:{x:e},backend:o,attrs:{shape:[1,t.inChannels,t.outChannels]}});x.push($);let A=Pu({a:k,b:$,backend:o,transposeA:f,transposeB:h,bias:n,activation:i,preluActivationWeights:s,leakyreluAlpha:a}),R=o.texData.get(A.dataId);y.assert(R.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=_,R.shape=t.outShape,g=At({inputs:{x:A},backend:o}),g.shape=t.outShape,x.push(A)}else{let w=t.outHeight*t.outWidth,k=te({inputs:{x:r},backend:o,attrs:{shape:d?[t.batchSize,w,t.inChannels]:[t.batchSize,t.inChannels,w]}}),_=te({inputs:{x:e},backend:o,attrs:{shape:[1,t.inChannels,t.outChannels]}}),$=Pu({a:d?k:_,b:d?_:k,transposeA:!d,transposeB:h,backend:o,bias:n,activation:i,preluActivationWeights:s,leakyreluAlpha:a});g=te({inputs:{x:$},backend:o,attrs:{shape:t.outShape}}),x.push(k),x.push(_),x.push($)}for(let w of x)o.disposeIntermediateTensorInfo(w);return g}function vh({x:r,filter:e,convInfo:t,backend:o,bias:n=null,preluActivationWeights:s=null,leakyreluAlpha:a=0,activation:i=null}){let{filterWidth:p,filterHeight:u,inChannels:c,outWidth:l,outHeight:m,dataFormat:d}=t,f=d==="channelsLast",h=p*u*c,g=m*l,x=[t.batchSize,h,g],b=!0,C=!1,w=[];if(s!=null){let H=wh(s.shape,f);H!=null&&(s=te({inputs:{x:s},backend:o,attrs:{shape:H}}),w.push(s))}if(n!=null){let H=wh(n.shape,f);H!=null&&(n=te({inputs:{x:n},backend:o,attrs:{shape:H}}),w.push(n))}let k=te({inputs:{x:e},backend:o,attrs:{shape:[1,h,y.sizeFromShape(e.shape)/h]}});w.push(k);let _=new Sh(x,t),$=[r.shape,[t.padInfo.top,t.padInfo.left],[t.strideHeight,t.strideWidth],[t.dilationHeight,t.dilationWidth],[t.inChannels],[t.filterWidth*t.inChannels],[t.outWidth]],A=o.runWebGLProgram(_,[r],"float32",$),R=te({inputs:{x:A},backend:o,attrs:{shape:x}});w.push(A),w.push(R);let D=n!=null,P=s!=null,M=i==="leakyrelu",L=i?Wa(i,!0):null,W=new dc(f?R.shape:k.shape,f?k.shape:R.shape,f?[t.batchSize,g,t.outChannels]:[t.batchSize,t.outChannels,g],b,C,D,L,P,M),V=f?[R,k]:[k,R];if(n&&V.push(n),P&&V.push(s),M){let H=o.makeTensorInfo([],"float32",y.createScalarValue(a,"float32"));V.push(H),w.push(H)}let U=o.runWebGLProgram(W,V,"float32"),q=te({inputs:{x:U},backend:o,attrs:{shape:t.outShape}});w.push(U);for(let H of w)o.disposeIntermediateTensorInfo(H);return q}function EY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dataFormat:p,dilations:u,dimRoundingMode:c}=o,l=S.convertConv2DDataFormat(p),m=S.computeConv2DInfo(n.shape,s.shape,a,u,i,c,!1,l),d;if(m.filterHeight===1&&m.filterWidth===1&&m.dilationHeight===1&&m.dilationWidth===1&&m.strideHeight===1&&m.strideWidth===1&&(m.padInfo.type==="SAME"||m.padInfo.type==="VALID"))d=Ih({x:n,filter:s,convInfo:m,backend:t});else if(m.strideWidth<=2&&l==="channelsLast"&&O().getBool("WEBGL_EXP_CONV")){let h=new gc(m),g=[[m.padInfo.top,m.padInfo.left],[m.strideHeight,m.strideWidth],[m.dilationHeight,m.dilationWidth],[m.inHeight,m.inWidth]];d=t.runWebGLProgram(h,[n,s],"float32",g)}else if(O().getBool("WEBGL_CONV_IM2COL"))d=vh({x:n,filter:s,convInfo:m,backend:t});else{let h=new hc(m);d=t.runWebGLProgram(h,[n,s],"float32")}let f=te({inputs:{x:d},backend:t,attrs:{shape:m.outShape}});return t.disposeIntermediateTensorInfo(d),f}var PA={kernelName:Go,backendName:"webgl",kernelFunc:EY};var kh=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,o=e.strideWidth,n=e.padInfo.top,s=e.padInfo.left,a=e.dataFormat==="channelsLast";this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int wR = coords.x;
        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 * ${o} - ${s};

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

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

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

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

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

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

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

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

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

              if (${a}) {
                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);
      }
    `}},Th=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,o=e.strideHeight,n=e.strideWidth,s=e.padInfo.front,a=e.padInfo.top,i=e.padInfo.left;this.userCode=`
      void main() {
        ivec5 coords = getOutputCoords();
        int wF = coords.x;
        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} - ${s};

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

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

              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);
      }
    `}},_h=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,o=e.filterHeight,n=e.filterWidth,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,p=t-1-e.padInfo.front,u=o-1-e.padInfo.top,c=n-1-e.padInfo.left;this.userCode=`
      const ivec3 pads = ivec3(${p}, ${u}, ${c});

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


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

        float dotProd = 0.0;
        for (int wF = 0; wF < ${t}; wF++) {
          float dyF = float(dyFCorner + wF) / ${s}.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 < ${o}; wR++) {
            float dyR = float(dyRCorner + wR) / ${a}.0;

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

            int wRPerm = ${o} - 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 $Y(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,dy:s}=e,{strides:a,pad:i,dataFormat:p,dimRoundingMode:u,filterShape:c}=o,l=S.convertConv2DDataFormat(p),m=S.computeConv2DInfo(n.shape,c,a,1,i,u,!1,l),d=new kh(m);return t.runWebGLProgram(d,[n,s],"float32")}var MA={kernelName:cp,backendName:"webgl",kernelFunc:$Y};function AY(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{inputShape:a,strides:i,pad:p,dataFormat:u,dimRoundingMode:c}=o,l=S.convertConv2DDataFormat(u),m=S.computeConv2DInfo(a,s.shape,i,1,p,c,!1,l),d=new Nh(m);return t.runWebGLProgram(d,[n,s],"float32")}var LA={kernelName:Ho,backendName:"webgl",kernelFunc:AY};function RY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:p}=o,u=S.computeConv3DInfo(n.shape,s.shape,a,p,i),c=new Ch(u);return t.runWebGLProgram(c,[n,s],"float32")}var BA={kernelName:lp,backendName:"webgl",kernelFunc:RY};function FY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,dy:s}=e,{strides:a,pad:i,filterShape:p}=o,u=S.computeConv3DInfo(n.shape,p,a,1,i),c=new Th(u);return t.runWebGLProgram(c,[n,s],"float32")}var VA={kernelName:vm,backendName:"webgl",kernelFunc:FY};function DY(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{pad:a,strides:i,inputShape:p}=o,u=S.computeConv3DInfo(p,s.shape,i,1,a),c=new _h(u);return t.runWebGLProgram(c,[n,s],"float32")}var zA={kernelName:mp,backendName:"webgl",kernelFunc:DY};var OY=_o+`
  return cos(x);
`,PY=ge({opSnippet:OY}),WA={kernelName:qo,backendName:"webgl",kernelFunc:PY};var MY=`
  float e2x = exp(-x);
  return (e2x + 1.0 / e2x) / 2.0;
`,LY=ge({opSnippet:MY}),UA={kernelName:Ko,backendName:"webgl",kernelFunc:LY};var Eh=class{constructor(e,t,o,n,s){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[a,i,p,u]=e,[c]=t,[l,m]=o;this.outputShape=[c,l,m,u];let d=n==="bilinear"?1:0,[f,h]=[`${i-1}.0`,`${p-1}.0`],[g,x,b]=l>1?[`${(i-1)/(l-1)}`,"(y2-y1) * height_ratio",`y1*${f} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${f}`],[C,w,k]=m>1?[`${(p-1)/(m-1)}`,"(x2-x1) * width_ratio",`x1*${h} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${h}`];this.userCode=`
      const float height_ratio = float(${g});
      const float width_ratio = float(${C});
      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 >= ${a}) {
          return;
        }

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

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

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

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

          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);

          float top = topLeft + (topRight - topLeft) * fracCR.x;
          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
          float newValue = top + (bottom - top) * fracCR.y;
          setOutput(newValue);
        } else {
          // Compute the coordinators of nearest neighbor point.
          ivec2 sourceNearestCR = ivec2(floor(
            sourceFracIndexCR + vec2(0.5,0.5)));
          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
          setOutput(newValue);
        }
      }
    `}};var BY=r=>{let{inputs:e,backend:t,attrs:o}=r,{image:n,boxes:s,boxInd:a}=e,{cropSize:i,method:p,extrapolationValue:u}=o,c=new Eh(n.shape,s.shape,i,p,u);return t.runWebGLProgram(c,[n,s,a],"float32")},GA={kernelName:Yo,backendName:"webgl",kernelFunc:BY};var Lu;(function(r){r.Prod="*",r.Sum="+"})(Lu||(Lu={}));var El=class{constructor(e,t,o,n){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let s=this.outputShape.length,a=this.op===Lu.Prod?"1.0":"0.0",i=o?a:`getX(${HA(s,"coords",this.op)})`,p=this.outputShape[this.outputShape.length-1],u="",c="";o?(u=n?`end != ${p-1}`:"end != 0",c=n?"end + 1":"end - 1"):(u=n?`end + pow2 < ${p}`:"end >= pow2",c=n?"end + pow2":"end - pow2"),this.userCode=`
      void main() {
        ${_e(s)} coords = getOutputCoords();
        int end = ${qA(s,"coords",this.op)};
        float val = ${i};
        int pow2 = int(pow(2.0, index));
        if (${u}) {
          int idx = ${c};
          ${qA(s,"coords",this.op)} = idx;
          val ${this.op}= getX(${HA(s,"coords",this.op)});
        }
        setOutput(val);
      }
    `}};function HA(r,e,t){if(r===1)return`${e}`;if(r===2)return`${e}.x, ${e}.y`;if(r===3)return`${e}.x, ${e}.y, ${e}.z`;if(r===4)return`${e}.x, ${e}.y, ${e}.z, ${e}.w`;throw new Error(`Cumulative ${t} for rank ${r} is not yet supported`)}function qA(r,e,t){if(r===1)return`${e}`;if(r===2)return`${e}.y`;if(r===3)return`${e}.z`;if(r===4)return`${e}.w`;throw new Error(`Cumulative ${t} for rank ${r} is not yet supported`)}function $h(r,e,t,o,n,s){let a=e.shape.length,i=S.getAxesPermutation([o],a),p=e;i!=null&&(p=xt({inputs:{x:e},backend:t,attrs:{perm:i}}));let u=S.getInnerMostAxes(1,a)[0];if(u!==a-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${e.shape.length-1} but got axis=${o}`);let c=p.shape[u],l=At({inputs:{x:p},backend:t});for(let m=0;m<=Math.ceil(Math.log2(c))-1;m++){let d=new El(r,p.shape,!1,s),f=[[m]],h=l;l=t.runWebGLProgram(d,[l],l.dtype,f),t.disposeIntermediateTensorInfo(h)}if(n){let m=new El(r,p.shape,n,s),d=l;l=t.runWebGLProgram(m,[l],l.dtype),t.disposeIntermediateTensorInfo(d)}if(i!=null){let m=S.getUndoAxesPermutation(i),d=xt({inputs:{x:l},backend:t,attrs:{perm:m}});return t.disposeIntermediateTensorInfo(l),t.disposeIntermediateTensorInfo(p),d}return l}function VY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,exclusive:a,reverse:i}=o;return $h(Lu.Prod,n,t,s,a,i)}var KA={kernelName:jo,backendName:"webgl",kernelFunc:VY};function zY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,exclusive:a,reverse:i}=o;return $h(Lu.Sum,n,t,s,a,i)}var jA={kernelName:Xo,backendName:"webgl",kernelFunc:zY};function WY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a,binaryOutput:i}=o;if(n.shape.length===1){let p=t.readSync(n.dataId),u=t.readSync(s.dataId),c=qf(p,u,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,c)}else if(n.shape.length===2){let p=t.bufferSync(n),u=t.bufferSync(s),c=OE(p,u,a,i);return t.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${n.shape.length}.`)}var XA={kernelName:ti,backendName:"webgl",kernelFunc:WY};var Ah=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=o,this.userCode=`
    void main() {
      ivec4 coords = getOutputCoords();
      int b = coords[0];
      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 UY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockSize:s,dataFormat:a}=o,i=n.shape[0],p=a==="NHWC"?n.shape[1]:n.shape[2],u=a==="NHWC"?n.shape[2]:n.shape[3],c=a==="NHWC"?n.shape[3]:n.shape[1],l=p*s,m=u*s,d=c/(s*s),f=a==="NHWC"?[i,l,m,d]:[i,d,l,m],h=new Ah(f,s,a);return t.runWebGLProgram(h,[n],n.dtype)}var YA={kernelName:Qo,backendName:"webgl",kernelFunc:UY};var xc=class{constructor(e,t=!1,o=null,n=!1,s=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=ct(this.outputShape.length);let a=e.filterHeight,i=e.filterWidth,p=e.outChannels/e.inChannels,u="",c="";o&&(n?u=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${o}
        }`:s?u=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${o}
        }`:u=`
          float activation(float x) {
            ${o}
          }
        `,c="result = activation(result);");let l=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${u}

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

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

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

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

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

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

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

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

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

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

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

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

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        ivec2 xRCCorner = coords.yz * strides - pads;
        int d2 = coords.w;
        int d1 = d2 / ${a};
        int q = d2 - d1 * ${a};
        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);
        ${g}
        ${h}
        setOutput(result);
      }
    `}};function GY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:p,dimRoundingMode:u}=o,c=p;c==null&&(c=[1,1]),y.assert(S.eitherStridesOrDilationsAreOne(a,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${a} and dilations '${c}'`);let l=S.computeConv2DInfo(n.shape,s.shape,a,c,i,u,!0),m;O().getBool("WEBGL_PACK_DEPTHWISECONV")&&l.strideWidth<=2&&l.outChannels/l.inChannels===1?m=new yc(l):m=new xc(l);let d=[[l.padInfo.top,l.padInfo.left],[l.strideHeight,l.strideWidth],[l.dilationHeight,l.dilationWidth],[l.inHeight,l.inWidth]];return t.runWebGLProgram(m,[n,s],"float32",d)}var QA={kernelName:Zo,backendName:"webgl",kernelFunc:GY};var Rh=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,o=e.strideWidth,n=e.padInfo.top,s=e.padInfo.left,a=e.outChannels/e.inChannels;this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int wR = coords.x;
        int wC = coords.y;
        int d1 = coords.z;
        int dm = coords.w;
        int d2 = d1 * ${a} + 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 * ${o} - ${s};

              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);
      }
    `}},Fh=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,o=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=t-1-e.padInfo.top,i=o-1-e.padInfo.left,p=e.outChannels/e.inChannels;this.userCode=`
      const ivec2 pads = ivec2(${a}, ${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 < ${o}; wC++) {
            float dyC = float(dyCCorner + wC) / ${s}.0;

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

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

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

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

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

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

              if (wIn >= 0 && wIn < ${o}) {
                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 jY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:p}=o,u=S.computeDilation2DInfo(n.shape,s.shape,a,i,"NHWC",p),c,l=new Oh(u);c=t.runWebGLProgram(l,[n,s],"float32");let m=te({inputs:{x:c},backend:t,attrs:{shape:u.outShape}});return t.disposeIntermediateTensorInfo(c),m}var tR={kernelName:gp,backendName:"webgl",kernelFunc:jY};function XY(r){let{inputs:e,backend:t,attrs:o}=r,{equation:n}=o,s=e,{allDims:a,summedDims:i,idDims:p}=S.decodeEinsumEquation(n,s.length);S.checkEinsumDimSizes(a.length,p,s);let{path:u,steps:c}=S.getEinsumComputePath(i,p),l=c.length,m=null,d=a.length,f=[];for(let h=0;h<l;++h){for(let g of c[h]){let{permutationIndices:x,expandDims:b}=S.getEinsumPermutation(d,p[g]),C;S.isIdentityPermutation(x)?C=s[g]:(C=xt({inputs:{x:s[g]},backend:t,attrs:{perm:x}}),f.push(C));let w=C.shape.slice();for(let k=0;k<b.length;++k)w.splice(b[k],0,1);y.arraysEqual(C.shape,w)||(C=te({inputs:{x:C},backend:t,attrs:{shape:w}}),f.push(C)),m===null?m=C:(m=Tl({inputs:{a:C,b:m},backend:t}),f.push(m))}h<l-1&&(u[h]>=0&&(m=Ou({inputs:{x:m},backend:t,attrs:{axis:u[h]-(a.length-d),keepDims:!1}}),f.push(m)),d--)}for(let h of f)h!==m&&t.disposeIntermediateTensorInfo(h);return m}var rR={kernelName:ri,backendName:"webgl",kernelFunc:XY};var YY="return (x >= 0.0) ? x : (exp(x) - 1.0);",QY=`
  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;
`,ZY=ge({opSnippet:YY,packedOpSnippet:QY}),oR={kernelName:en,backendName:"webgl",kernelFunc:ZY};var JY="return (b >= 1.0) ? a : a * (b + 1.0);",eQ=`
  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,tQ=r=>{let{inputs:e,backend:t}=r,{dy:o,y:n}=e,s=O().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new To(eQ,o.shape,n.shape):new io(JY,o.shape,n.shape);return t.runWebGLProgram(s,[o,n],o.dtype)},nR={kernelName:km,backendName:"webgl",kernelFunc:tQ};var rQ=`
  return vec4(equal(a, b));
`,oQ="return float(a == b);",nQ=tt({opSnippet:oQ,packedOpSnippet:rQ,dtype:"bool",cpuKernelImpl:BE}),sR={kernelName:tn,backendName:"webgl",kernelFunc:nQ};var sQ=`
  // Error function is calculated approximately with elementary function.
  // See "Handbook of Mathematical Functions with Formulas,
  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
  float p = ${S.ERF_P};
  float a1 = ${S.ERF_A1};
  float a2 = ${S.ERF_A2};
  float a3 = ${S.ERF_A3};
  float a4 = ${S.ERF_A4};
  float a5 = ${S.ERF_A5};

  float sign = sign(x);
  x = abs(x);
  float t = 1.0 / (1.0 + p * x);
  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,aQ=ge({opSnippet:sQ}),aR={kernelName:ma,backendName:"webgl",kernelFunc:aQ};var iQ=_o+`
  return exp(x);
`,uQ=`
  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;
`,Aw=ge({opSnippet:iQ,packedOpSnippet:uQ,cpuKernelImpl:VE,dtype:"float32"}),iR={kernelName:rn,backendName:"webgl",kernelFunc:Aw};function Ph(r){let{inputs:e,attrs:t,backend:o}=r,{dim:n}=t,{input:s}=e,a=s.shape.length,i=s.shape.slice(),p=n;return n<0&&(y.assert(-(a+1)<=n,()=>`Axis must be in the interval [${-(a+1)}, ${a}]`),p=a+n+1),i.splice(p,0,1),te({inputs:{x:s},backend:o,attrs:{shape:i}})}var uR={kernelName:bs,backendName:"webgl",kernelFunc:Ph};var pR="return exp(x) - 1.0;",pQ=ge({opSnippet:pR,packedOpSnippet:pR,cpuKernelImpl:zE}),cR={kernelName:da,backendName:"webgl",kernelFunc:pQ};var $l=class{constructor(e,t,o){this.variableNames=["real","imag"];let n=t[1];this.outputShape=t;let s=o?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,a=o?`${n}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
      const float exponentMultiplier = ${s};

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

        return result;
      }

      void main() {
        ivec2 coords = getOutputCoords();
        setOutput(mulMatDFT(coords[0], coords[1]));
      }
    `}};function Mh(r,e,t){let o=t.texData.get(r.dataId),n=y.sizeFromShape(r.shape),s=r.shape[r.shape.length-1],a=n/s,i=te({inputs:{x:r},backend:t,attrs:{shape:[a,s]}}),p=i.shape,u=new $l("real",p,e),c=new $l("imag",p,e),l=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:p},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:p}],m=t.runWebGLProgram(u,l,"float32"),d=t.runWebGLProgram(c,l,"float32"),f=Rr({inputs:{real:m,imag:d},backend:t});t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(d);let h=te({inputs:{x:f},backend:t,attrs:{shape:r.shape}});return t.disposeIntermediateTensorInfo(i),t.disposeIntermediateTensorInfo(f),h}function cQ(r){let{inputs:e,backend:t}=r,{input:o}=e;return Mh(o,!1,t)}var lR={kernelName:oi,backendName:"webgl",kernelFunc:cQ};var Lh=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 Ga(r){let{backend:e,attrs:t}=r,{shape:o,value:n}=t,{dtype:s}=t;if(s=s||y.inferDtype(n),s==="string"){let a=y.getArrayFromDType(s,y.sizeFromShape(o));return a.fill(n),e.makeTensorInfo(o,s,a)}else{let a=new Lh(o,n),i=[[n]];return e.runWebGLProgram(a,[],s,i)}}var mR={kernelName:Cs,backendName:"webgl",kernelFunc:Ga};var Bh=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);
        }
    `}};var dR={kernelName:on,backendName:"webgl",kernelFunc:({inputs:r,backend:e})=>{let{image:t}=r,o=e,n=new Bh(t.shape);return o.runWebGLProgram(n,[t],t.dtype)}};var fR="return floor(x);",lQ=ge({opSnippet:fR,packedOpSnippet:fR,cpuKernelImpl:WE}),hR={kernelName:nn,backendName:"webgl",kernelFunc:lQ};var mQ=`
  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;
  }
`,dQ=`
  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);
`,fQ=tt({opSnippet:mQ,packedOpSnippet:dQ,dtype:"int32"}),gR={kernelName:sn,backendName:"webgl",kernelFunc:fQ};var Vh=class{constructor(e){this.variableNames=["A"];let t=St(),[o,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, ${o}.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));
      }
    `}};var zh=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=St(),[o,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, ${o}.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;
      }
    `}};var xR={kernelName:Zi,backendName:"webgl",kernelFunc:hQ},bc,Rw=O().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function hQ(r){let{inputs:e,backend:t,attrs:o}=r,{pixels:n}=e,{numChannels:s}=o,a=typeof HTMLVideoElement!="undefined"&&n instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&n instanceof HTMLImageElement,[p,u]=a?[n.videoWidth,n.videoHeight]:[n.width,n.height],c=[u,p],l=[u,p,s];if(i||a){let h=O().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(bc==null||h!==Rw)&&(Rw=h,bc=document.createElement("canvas").getContext("2d",{willReadFrequently:Rw})),bc.canvas.width=p,bc.canvas.height=u,bc.drawImage(n,0,0,p,u),n=bc.canvas}let m=t.makeTensorInfo(c,"int32");t.texData.get(m.dataId).usage=ir.PIXELS,t.gpgpu.uploadPixelDataToTexture(t.getTexture(m.dataId),n);let d=O().getBool("WEBGL_PACK")?new zh(l):new Vh(l),f=t.runWebGLProgram(d,[m],"int32");return t.disposeData(m.dataId),f}function gQ(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s,bias:a,preluActivationWeights:i}=e,{strides:p,pad:u,dataFormat:c,dilations:l,dimRoundingMode:m,activation:d,leakyreluAlpha:f}=o,h=S.convertConv2DDataFormat(c),g=S.computeConv2DInfo(n.shape,s.shape,p,l,u,m,!1,h),x,b=[],C=a!=null,w=i!=null,k=d==="leakyrelu",_=()=>{let A=[n,s],R=(D,P)=>{if(P==="NCHW"&&D.shape.length===1&&D.shape[0]!==1){let M=te({inputs:{x:D},backend:t,attrs:{shape:[D.shape[0],1,1]}});return b.push(M),M}return D};if(C&&A.push(R(a,c)),w&&A.push(R(i,c)),k){let D=t.makeTensorInfo([],"float32",y.createScalarValue(f,"float32"));A.push(D),b.push(D)}return A};if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))x=Ih({x:n,filter:s,convInfo:g,backend:t,bias:a,activation:d,preluActivationWeights:i,leakyreluAlpha:f});else if(g.strideWidth<=2&&h==="channelsLast"&&O().getBool("WEBGL_EXP_CONV")){let A=d?Wa(d,!0):null,R=new gc(g,C,A,w,k),D=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],P=_();x=t.runWebGLProgram(R,P,"float32",D)}else if(O().getBool("WEBGL_CONV_IM2COL"))x=vh({x:n,filter:s,convInfo:g,backend:t,bias:a,activation:d,preluActivationWeights:i,leakyreluAlpha:f});else{let A=d?Wa(d,!1):null,R=new hc(g,C,A,w,k),D=_();x=t.runWebGLProgram(R,D,"float32")}let $=te({inputs:{x},backend:t,attrs:{shape:g.outShape}});return b.push(x),b.forEach(A=>t.disposeIntermediateTensorInfo(A)),$}var yR={kernelName:ho,backendName:"webgl",kernelFunc:gQ};function xQ(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s,bias:a,preluActivationWeights:i}=e,{strides:p,pad:u,dilations:c,dimRoundingMode:l,activation:m,leakyreluAlpha:d}=o,f=[],h=c;h==null&&(h=[1,1]),y.assert(S.eitherStridesOrDilationsAreOne(p,h),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${p} and dilations '${h}'`);let g=S.computeConv2DInfo(n.shape,s.shape,p,h,u,l,!0),x=O().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,b=m?Wa(m,x):null,C=[n,s],w=a!=null,k=i!=null,_=m==="leakyrelu";if(w&&C.push(a),k&&C.push(i),_){let D=t.makeTensorInfo([],"float32",y.createScalarValue(d,"float32"));C.push(D),f.push(D)}let $;x?$=new yc(g,w,b,k,_):$=new xc(g,w,b,k,_);let A=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],R=t.runWebGLProgram($,C,"float32",A);return f.forEach(D=>t.disposeIntermediateTensorInfo(D)),R}var bR={kernelName:go,backendName:"webgl",kernelFunc:xQ};var Wh=class{constructor(e,t,o,n){this.sliceDim=e,this.strides=t,this.paramsShape=n,this.variableNames=["x","indices"],this.outputShape=o;let s=_e(o.length),a=`
    int index;`;for(let i=0;i<this.sliceDim;i++)a+=`
          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() {
          ${s} coords = getOutputCoords();
          int flattenIndex = 0;
          bool out_of_bounds = false;

          ${a}

          setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));
        }
      `}};function yQ(r){let{inputs:e,backend:t}=r,{params:o,indices:n}=e,s=n.shape,a=s[s.length-1],i=y.sizeFromShape(o.shape),[p,u,c,l]=S.prepareAndValidate(o,n),m=te({inputs:{x:n},backend:t,attrs:{shape:[u,a]}}),d=te({inputs:{x:o},backend:t,attrs:{shape:[y.sizeFromShape(o.shape)/c,c]}});if(t.shouldExecuteOnCPU([o,n])||o.dtype==="string"){let x=t.readSync(n.dataId),b=t.bufferSync(o),C=UE(x,b,o.dtype,u,a,c,l,o.shape,i);return t.makeTensorInfo(p,o.dtype,C.values)}let f=new Wh(a,l,[u,c],o.shape),h=t.runWebGLProgram(f,[d,m],d.dtype),g=te({inputs:{x:h},backend:t,attrs:{shape:p}});return t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(d),t.disposeIntermediateTensorInfo(h),g}var CR={kernelName:un,backendName:"webgl",kernelFunc:yQ};var Uh=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let o=_e(this.rank),n=bQ(e,2);this.userCode=`
      void main() {
        ${o} 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 bQ(r,e){let t=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[];for(let n=0;n<r.length;n++)n===2?o.push("index"):o.push(`${t[n]}`);return o.join()}function Fw(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,indices:s}=e,{axis:a,batchDims:i}=o,p=y.parseAxisParam(a,n.shape)[0];if(O().get("DEBUG")){let b=t.readSync(s.dataId),C=n.shape[p];for(let w=0;w<b.length;++w){let k=b[w];y.assert(k<=C-1&&k>=0,()=>`GatherV2: the index value ${k} is not in [0, ${C-1}]`)}}let u=S.segment_util.collectGatherOpShapeInfo(n,s,p,i),c=y.sizeFromShape(s.shape),l=[],m=te({inputs:{x:n},backend:t,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),d=te({inputs:{x:s},backend:t,attrs:{shape:[u.batchSize,c/u.batchSize]}});l.push(m),l.push(d);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(t.shouldExecuteOnCPU([n,s])||n.dtype==="string"){let b=t.bufferSync(d),C=t.bufferSync(m),w=GE(C,b,f);return l.forEach(k=>t.disposeIntermediateTensorInfo(k)),t.makeTensorInfo(u.outputShape,w.dtype,w.values)}let h=new Uh(m.shape,f),g=t.runWebGLProgram(h,[m,d],m.dtype);l.push(g);let x=te({inputs:{x:g},backend:t,attrs:{shape:u.outputShape}});return l.forEach(b=>t.disposeIntermediateTensorInfo(b)),x}var SR={kernelName:Ss,backendName:"webgl",kernelFunc:Fw};var CQ="return float(a > b);",SQ=`
  return vec4(greaterThan(a, b));
`,wQ=tt({opSnippet:CQ,packedOpSnippet:SQ,cpuKernelImpl:HE,dtype:"bool"}),wR={kernelName:pn,backendName:"webgl",kernelFunc:wQ};var IQ="return float(a >= b);",vQ=`
  return vec4(greaterThanEqual(a, b));
`,kQ=tt({opSnippet:IQ,packedOpSnippet:vQ,dtype:"bool",cpuKernelImpl:qE}),IR={kernelName:cn,backendName:"webgl",kernelFunc:kQ};function NQ(r){let{inputs:e,backend:t}=r,{input:o}=e;return Mh(o,!0,t)}var vR={kernelName:ni,backendName:"webgl",kernelFunc:NQ};var TQ="return float(!isnan(x) && !isinf(x));",_Q=ge({opSnippet:TQ,dtype:"bool"}),kR={kernelName:fa,backendName:"webgl",kernelFunc:_Q};var EQ="return float(isinf(x));",$Q=ge({opSnippet:EQ,dtype:"bool"}),NR={kernelName:ha,backendName:"webgl",kernelFunc:$Q};var AQ="return float(isnan(x));",RQ=ge({opSnippet:AQ,dtype:"bool"}),TR={kernelName:ln,backendName:"webgl",kernelFunc:RQ};var FQ="return float(a < b);",DQ=`
  return vec4(lessThan(a, b));
`,OQ=tt({opSnippet:FQ,packedOpSnippet:DQ,cpuKernelImpl:KE,dtype:"bool"}),_R={kernelName:dn,backendName:"webgl",kernelFunc:OQ};var PQ="return float(a <= b);",MQ=`
  return vec4(lessThanEqual(a, b));
`,LQ=tt({opSnippet:PQ,packedOpSnippet:MQ,cpuKernelImpl:jE,dtype:"bool"}),ER={kernelName:fn,backendName:"webgl",kernelFunc:LQ};function BQ(r){let{backend:e,attrs:t}=r,{start:o,stop:n,num:s}=t,a=XE(o,n,s);return e.makeTensorInfo([a.length],"float32",a)}var $R={kernelName:xp,backendName:"webgl",kernelFunc:BQ};var VQ=_o+`
  return x < 0.0 ? 0./0. : log(x);
`,zQ=`
  vec4 result = log(x);
  bvec4 isNaN = isnan(x);
  result.r = isNaN.r ? x.r : (x.r < 0.0 ? 0./0. : result.r);
  result.g = isNaN.g ? x.g : (x.g < 0.0 ? 0./0. : result.g);
  result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);
  result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);
  return result;
`,WQ=ge({opSnippet:VQ,packedOpSnippet:zQ,cpuKernelImpl:YE}),AR={kernelName:hn,backendName:"webgl",kernelFunc:WQ};var UQ=_o+`
  return log(1.0 + x);
`,GQ=ge({opSnippet:UQ}),RR={kernelName:ga,backendName:"webgl",kernelFunc:GQ};var HQ="return float(a >= 1.0 && b >= 1.0);",qQ=`
  return vec4(
    vec4(greaterThanEqual(a, vec4(1.0))) *
    vec4(greaterThanEqual(b, vec4(1.0))));
`,KQ=tt({opSnippet:HQ,packedOpSnippet:qQ,dtype:"bool"}),FR={kernelName:gn,backendName:"webgl",kernelFunc:KQ};var jQ="return float(!(x >= 1.0));",XQ=ge({opSnippet:jQ}),DR={kernelName:xn,backendName:"webgl",kernelFunc:XQ};var YQ="return float(a >= 1.0 || b >= 1.0);",QQ=`
  return min(
    vec4(greaterThanEqual(a, vec4(1.0))) +
    vec4(greaterThanEqual(b, vec4(1.0))),
    vec4(1.0));
`,ZQ=tt({opSnippet:YQ,packedOpSnippet:QQ,dtype:"bool"}),OR={kernelName:xa,backendName:"webgl",kernelFunc:ZQ};var Gh=class{constructor(e,t,o,n,s){this.variableNames=["x"],this.outputShape=[];let a=t,i=e[3]-1;this.outputShape=e;let p,u=`float(${o}) + float(${n}) * sum`;s===.5?p=`inversesqrt(${u})`:s===1?p=`1.0/(${u})`:p=`exp(log(${u}) * float(-${s}));`,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];
        int d = coords[3];
        float x = getX(b, r, c, d);
        float sum = 0.0;
        for (int j = -${a}; j <= ${a}; j++) {
          int idx = d + j;
          if (idx >= 0 && idx <=  ${i}) {
            float z = getX(b, r, c, idx);
            sum += z * z;
          }
        }
        float val = x * ${p};
        setOutput(val);
      }
    `}};var Hh=class{constructor(e,t,o,n,s){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let a=t,i=e[3]-1;this.outputShape=e;let p,u=`float(${o}) + float(${n}) * sum`;s===.5?p=`inversesqrt(${u})`:s===1?p=`1.0/(${u})`:p=`exp(log(${u}) * float(-${s}));`,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords.x;
        int r = coords.y;
        int c = coords.z;
        int d = coords.w;

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

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

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

        int firstChannel = d - ${a};
        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 = - ${a}; j <= ${a}; j++) {
          ivec2 idx = depth + j;
          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${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 * ${p};
        setOutput(result);
      }
    `}};var JQ=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{depthRadius:s,bias:a,alpha:i,beta:p}=o,u=O().getBool("WEBGL_PACK_NORMALIZATION")?new Hh(n.shape,s,a,i,p):new Gh(n.shape,s,a,i,p);return t.runWebGLProgram(u,[n],n.dtype)},PR={kernelName:yp,backendName:"webgl",kernelFunc:JQ};var qh=class{constructor(e,t,o,n,s){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=o,this.alpha=n,this.beta=s,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        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(${n}) * norm + float(${o});

          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(${n})
                * float(${s})
                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
                / norm;
              if (k == d) {
                dyi += pow(norm, -1.0 * ${s});
              }
              if (k == coords[3]) {
                dyi *= getDy(b, r, c, d);
                result += dyi;
              }
            }
            else {
              break;
            }
          }
      }
      setOutput(result);
      }
    `}};var e7=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n,y:s,dy:a}=e,{depthRadius:i,bias:p,alpha:u,beta:c}=o,l=new qh(n.shape,i,p,u,c);return t.runWebGLProgram(l,[n,s,a],n.dtype)},MR={kernelName:Nm,backendName:"webgl",kernelFunc:e7};function LR(r,e,t,o){let n=y.sizeFromShape(e),a=y.sizeFromShape(r.shape)/n,i=te({inputs:{x:r},attrs:{shape:[a,n]},backend:o}),p=Gr(i,r.dtype,"max",o),u=te({inputs:{x:p},attrs:{shape:t},backend:o});return o.disposeIntermediateTensorInfo(i),o.disposeIntermediateTensorInfo(p),u}function Dw(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{reductionIndices:s,keepDims:a}=o,i=n.shape.length,p=y.parseAxisParam(s,n.shape),u=p,c=S.getAxesPermutation(u,i),l=c!=null,m=t.shouldExecuteOnCPU([n]),d=n;if(l){if(m){let C=t.texData.get(d.dataId).values,w=new Array(i);for(let $=0;$<w.length;$++)w[$]=n.shape[c[$]];let k=Du(C,n.shape,n.dtype,c,w);d=t.makeTensorInfo(w,n.dtype);let _=t.texData.get(d.dataId);_.values=k}else d=Vi(n,c,t);u=S.getInnerMostAxes(u.length,i)}S.assertAxesAreInnerMostDims("max",u,i);let[f,h]=S.computeOutAndReduceShapes(d.shape,u),g=f;a&&(g=S.expandShapeToKeepDim(f,p));let x;if(m){let C=t.texData.get(d.dataId).values,w=QE(C,y.sizeFromShape(h),g,n.dtype);x=t.makeTensorInfo(g,n.dtype);let k=t.texData.get(x.dataId);k.values=w}else x=LR(d,h,g,t);return l&&t.disposeIntermediateTensorInfo(d),x}var BR={kernelName:yn,backendName:"webgl",kernelFunc:Dw};var t7=mc+`
  return max(a, b);
`,r7=`
  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);
  `+Zs+`
  return result;
`,o7=tt({opSnippet:t7,packedOpSnippet:r7,cpuKernelImpl:ZE}),VR={kernelName:bn,backendName:"webgl",kernelFunc:o7};function n7(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e;is(n,"maxPool");let{filterSize:s,strides:a,pad:i,dimRoundingMode:p}=o,u=1;y.assert(S.eitherStridesOrDilationsAreOne(a,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=S.computePool2DInfo(n.shape,s,a,u,i,p);if(c.filterWidth===1&&c.filterHeight===1&&y.arraysEqual(c.inShape,c.outShape))return At({inputs:{x:n},backend:t});let l=new ps(c,"max",!1);return t.runWebGLProgram(l,[n],n.dtype)}var zR={kernelName:Cn,backendName:"webgl",kernelFunc:n7};function s7(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{filterSize:s,strides:a,pad:i,dataFormat:p,dimRoundingMode:u}=o,c=[1,1,1],l=S.computePool3DInfo(n.shape,s,a,c,i,u,p),m=new zi(l,"max",!1);return t.runWebGLProgram(m,[n],n.dtype)}var WR={kernelName:bp,backendName:"webgl",kernelFunc:s7};var Kh=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,o=e.strideWidth,n=e.dilationHeight,s=e.effectiveFilterHeight,a=e.effectiveFilterWidth,i=s-1-e.padInfo.top,p=a-1-e.padInfo.left,u=s*a-1;this.userCode=`
      const ivec2 pads = ivec2(${i}, ${p});

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

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

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${s};
          wR += ${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 < ${a}; wC++) {
            float dyC = float(dyCCorner + wC) / ${o}.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 = ${u} - int(getMaxPos(b, idyR, idyC, d));

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

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

      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 < ${p};
           wD += ${s}) {
          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 < ${u};
              wR += ${a}) {
            float dyR = float(dyRCorner + wR) / ${o}.0;

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

            for (int wC = 0; wC < ${c};
                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 = ${f} -
                  int(getMaxPos(batch, idyD, idyR, idyC, ch));

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

              dotProd += dyValue * mask;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function a7(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s,{filterSize:i,strides:p,pad:u,dimRoundingMode:c}=o,l=[1,1,1],m=S.computePool3DInfo(a.shape,i,p,l,u,c),d=new zi(m,"max",!0),f=t.runWebGLProgram(d,[a],a.dtype),h=new jh(m),g=t.runWebGLProgram(h,[n,f],a.dtype);return t.disposeIntermediateTensorInfo(f),g}var UR={kernelName:_m,backendName:"webgl",kernelFunc:a7};function i7(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s,output:a}=e,i=s;is([s,a],"maxPoolGrad");let{filterSize:p,strides:u,pad:c,dimRoundingMode:l}=o,m=S.computePool2DInfo(i.shape,p,u,1,c,l),d=!0,f=new ps(m,"max",d),h=t.runWebGLProgram(f,[i],i.dtype),g=new Kh(m),x=t.runWebGLProgram(g,[n,h],i.dtype);return t.disposeIntermediateTensorInfo(h),x}var GR={kernelName:Tm,backendName:"webgl",kernelFunc:i7};function HR(r,e,t,o){let n=new ps(t,"max",!1),s=o.runWebGLProgram(n,[r],"float32");n=new ps(t,"max",!0,!0,e);let a=o.runWebGLProgram(n,[r],"float32");return[s,a]}var qR={kernelName:Cp,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{x:o}=r,{filterSize:n,strides:s,pad:a,includeBatchInIndex:i}=e,p=t;y.assert(o.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${o.shape.length}.`);let u=[1,1];y.assert(S.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let c=S.computePool2DInfo(o.shape,n,s,u,a),[l,m]=HR(o,i,c,p);return[l,m]}};function KR(r,e,t,o){let n=y.sizeFromShape(e),a=y.sizeFromShape(r.shape)/n,i=te({inputs:{x:r},attrs:{shape:[a,n]},backend:o}),p=Gr(i,"float32","mean",o),u=te({inputs:{x:p},attrs:{shape:t},backend:o});return o.disposeIntermediateTensorInfo(i),o.disposeIntermediateTensorInfo(p),u}var jR={kernelName:Sn,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{x:o}=r,{keepDims:n,axis:s}=e,a=t,i=o.shape.length,p=y.parseAxisParam(s,o.shape),u=p,c=S.getAxesPermutation(u,i),l=c!=null,m=a.shouldExecuteOnCPU([o]),d=[],f=o;if(l){if(m){let w=a.texData.get(f.dataId).values,k=new Array(i);for(let A=0;A<k.length;A++)k[A]=o.shape[c[A]];let _=Du(w,o.shape,o.dtype,c,k);f=a.makeTensorInfo(k,o.dtype);let $=a.texData.get(f.dataId);$.values=_}else f=Vi(o,c,a);d.push(f),u=S.getInnerMostAxes(u.length,i)}S.assertAxesAreInnerMostDims("sum",u,i);let[h,g]=S.computeOutAndReduceShapes(f.shape,u),x=h;n&&(x=S.expandShapeToKeepDim(h,p));let b=KR(f,g,x,a);for(let C of d)a.disposeIntermediateTensorInfo(C);return b}};function u7(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,p=y.parseAxisParam(s,n.shape),u=p,c=S.getAxesPermutation(u,i),l=n;c!=null&&(l=xt({inputs:{x:n},backend:t,attrs:{perm:c}}),u=S.getInnerMostAxes(u.length,n.shape.length)),S.assertAxesAreInnerMostDims("min",u,i);let[m,d]=S.computeOutAndReduceShapes(l.shape,u),f=y.sizeFromShape(d),h=te({inputs:{x:l},backend:t,attrs:{shape:[-1,f]}}),g=Gr(h,h.dtype,"min",t),x;if(a){let b=S.expandShapeToKeepDim(m,p);x=te({inputs:{x:g},backend:t,attrs:{shape:b}})}else x=te({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(l),x}var XR={kernelName:wn,backendName:"webgl",kernelFunc:u7};var p7=mc+`
  return min(a, b);
`,c7=`
  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);
  `+Zs+`
  return result;
`,l7=tt({opSnippet:p7,packedOpSnippet:c7,cpuKernelImpl:JE}),YR={kernelName:In,backendName:"webgl",kernelFunc:l7};var Xh=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=t.map((c,l)=>c[0]+e[l]+c[1]);let n=e.length,s=_e(n),a=t.map(c=>c[0]).join(","),i=t.map((c,l)=>c[0]+e[l]).join(","),p=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n),u=o==="reflect"?0:1;if(n===1){this.userCode=`
        int start = ${a};
        int end = ${i};

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

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

      void main() {
        ${s} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${d}
        setOutput(result);
      }
    `}};var m7=({inputs:r,backend:e,attrs:t})=>{let{x:o}=r,{paddings:n,mode:s}=t,a=O().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Yh(o.shape,n,s):new Xh(o.shape,n,s);return e.runWebGLProgram(a,[o],o.dtype)},QR={kernelName:vn,backendName:"webgl",kernelFunc:m7};var d7=`if (b == 0.0) return NAN;
  return mod(a, b);`,f7=`
  vec4 result = mod(a, b);
  bvec4 isNaN = equal(b, vec4(0.0));
  `+Zs+`
  return result;
`,h7=tt({opSnippet:d7,packedOpSnippet:f7}),ZR={kernelName:ya,backendName:"webgl",kernelFunc:h7};var Qh=class{constructor(e,t,o){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,o],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}));
      }
    `}};var g7=`
if (a == b) {
  return 1.0;
};
return a / b;`,x7=`
  // 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;
`,Ow=tt({opSnippet:g7,packedOpSnippet:x7,checkOutOfBounds:!0}),JR={kernelName:Jo,backendName:"webgl",kernelFunc:Ow};var eF="return a - b;",Pw=tt({opSnippet:eF,packedOpSnippet:eF,supportsComplex:!0,cpuKernelImpl:b$}),tF={kernelName:Xn,backendName:"webgl",kernelFunc:Pw};function Mw(r){let{inputs:e,backend:t,attrs:o}=r,{logits:n}=e,{dim:s}=o,a=y.parseAxisParam([s],n.shape),i=Dw({inputs:{x:n},backend:t,attrs:{reductionIndices:a,keepDims:!1}}),p=S.expandShapeToKeepDim(i.shape,a),u=te({inputs:{x:i},backend:t,attrs:{shape:p}}),c=Pw({inputs:{a:n,b:u},backend:t}),l=Aw({inputs:{x:c},backend:t}),m=Ou({inputs:{x:l},backend:t,attrs:{axis:a,keepDims:!1}}),d=te({inputs:{x:m},backend:t,attrs:{shape:p}}),f=Ow({inputs:{a:l,b:d},backend:t});return t.disposeIntermediateTensorInfo(i),t.disposeIntermediateTensorInfo(u),t.disposeIntermediateTensorInfo(c),t.disposeIntermediateTensorInfo(l),t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(d),f}var rF={kernelName:qn,backendName:"webgl",kernelFunc:Mw};function y7(r){let{inputs:e,backend:t,attrs:o}=r,{logits:n}=e,{numSamples:s,seed:a,normalized:i}=o,p=i?n:Mw({inputs:{logits:n},backend:t,attrs:{dim:n.shape.length-1}}),u=p.shape[0],c=p.shape[1],l=new Qh(u,c,s),m=[[a]],d=t.runWebGLProgram(l,[p],"int32",m);return i||t.disposeIntermediateTensorInfo(p),d}var oF={kernelName:Sp,backendName:"webgl",kernelFunc:y7};var b7=Bt+`
  return -x;
`,C7=`
  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 S7(r){let{inputs:e,backend:t}=r,{x:o}=e;if(t.shouldExecuteOnCPU([o])){let s=t.texData.get(o.dataId),[a,i]=t$(s.values,o.shape,o.dtype);return t.makeTensorInfo(i,o.dtype,a)}let n;return O().getBool("WEBGL_PACK_UNARY_OPERATIONS")?n=new Ar(o.shape,C7):n=new Jt(o.shape,b7),t.runWebGLProgram(n,[o],o.dtype)}var nF={kernelName:ws,backendName:"webgl",kernelFunc:S7};var w7=Lt.nonMaxSuppressionV3Impl;function I7(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:p}=o,u=t.readSync(n.dataId),c=t.readSync(s.dataId),{selectedIndices:l}=w7(u,c,a,i,p);return t.makeTensorInfo([l.length],"int32",new Int32Array(l))}var sF={kernelName:Tn,backendName:"webgl",kernelFunc:I7};var v7=Lt.nonMaxSuppressionV4Impl;function k7(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:p,padToMaxOutputSize:u}=o,c=t.readSync(n.dataId),l=t.readSync(s.dataId),{selectedIndices:m,validOutputs:d}=v7(c,l,a,i,p,u);return[t.makeTensorInfo([m.length],"int32",new Int32Array(m)),t.makeTensorInfo([],"int32",new Int32Array([d]))]}var aF={kernelName:ba,backendName:"webgl",kernelFunc:k7};var N7=Lt.nonMaxSuppressionV5Impl;function T7(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:p,softNmsSigma:u}=o,c=t.readSync(n.dataId),l=t.readSync(s.dataId),m=a,d=i,f=p,h=u,{selectedIndices:g,selectedScores:x}=N7(c,l,m,d,f,h);return[t.makeTensorInfo([g.length],"int32",new Int32Array(g)),t.makeTensorInfo([x.length],"float32",new Float32Array(x))]}var iF={kernelName:_n,backendName:"webgl",kernelFunc:T7};var Zh=class{constructor(e,t,o,n){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int index = round(getIndices(coords.x));
        setOutput(mix(float(${n}), float(${o}),
                      float(index == coords.y)));
      }
    `}};var _7=r=>{let{inputs:e,backend:t,attrs:o}=r,{indices:n}=e,{dtype:s,depth:a,onValue:i,offValue:p}=o,u=y.sizeFromShape(n.shape),c=new Zh(u,a,i,p),l=te({inputs:{x:n},backend:t,attrs:{shape:[u]}}),m=t.runWebGLProgram(c,[l],s);t.disposeIntermediateTensorInfo(l);let d=[...n.shape,a],f=te({inputs:{x:m},backend:t,attrs:{shape:d}});return t.disposeIntermediateTensorInfo(m),f},uF={kernelName:En,backendName:"webgl",kernelFunc:_7};function Al(r){let{inputs:e,backend:t}=r,{x:o}=e;if(o.dtype==="complex64"){let n=Ua({inputs:{input:o},backend:t}),s=Al({inputs:{x:n},backend:t}),a=Mu({inputs:{input:o},backend:t}),i=Al({inputs:{x:a},backend:t}),p=Rr({inputs:{real:s,imag:i},backend:t});return t.disposeIntermediateTensorInfo(n),t.disposeIntermediateTensorInfo(s),t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(i),p}else return Ga({attrs:{shape:o.shape,dtype:o.dtype,value:o.dtype==="string"?"":0},backend:t})}var pF={kernelName:Fs,backendName:"webgl",kernelFunc:Al};function cF(r){let{inputs:e,backend:t}=r,{x:o}=e;if(o.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(o.dtype==="complex64"){let n=Ua({inputs:{input:o},backend:t}),s=cF({inputs:{x:n},backend:t}),a=Mu({inputs:{input:o},backend:t}),i=Al({inputs:{x:a},backend:t}),p=Rr({inputs:{real:s,imag:i},backend:t});return t.disposeIntermediateTensorInfo(n),t.disposeIntermediateTensorInfo(s),t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(i),p}else return Ga({attrs:{shape:o.shape,dtype:o.dtype,value:1},backend:t})}var lF={kernelName:Is,backendName:"webgl",kernelFunc:cF};function E7(r){let{inputs:e,backend:t,attrs:o}=r,{axis:n}=o;if(e.length===1)return Ph({inputs:{input:e[0]},backend:t,attrs:{dim:n}});let s=e[0].shape,a=e[0].dtype;e.forEach(c=>{y.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),y.assert(a===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],p=e.map(c=>{let l=Ph({inputs:{input:c},backend:t,attrs:{dim:n}});return i.push(l),l}),u=$w({inputs:p,backend:t,attrs:{axis:n}});return i.forEach(c=>t.disposeIntermediateTensorInfo(c)),u}var mF={kernelName:vs,backendName:"webgl",kernelFunc:E7};var Jh=class{constructor(e,t,o){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let n=e.length,s=_e(n),a=t.map(u=>u[0]).join(","),i=t.map((u,c)=>u[0]+e[c]).join(","),p=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n);if(n===1){this.userCode=`
        int start = ${a};
        int end = ${i};

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

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

      void main() {
        ${s} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${f}
        setOutput(result);
      }
    `}};var Lw=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{paddings:s,constantValue:a}=o;if(y.sizeFromShape(n.shape)===0){let u=s.map((c,l)=>c[0]+n.shape[l]+c[1]);return Ga({backend:t,attrs:{shape:u,value:a,dtype:n.dtype}})}let i=O().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new eg(n.shape,s,a):new Jh(n.shape,s,a),p=[[a]];return t.runWebGLProgram(i,[n],n.dtype,p)},dF={kernelName:$n,backendName:"webgl",kernelFunc:Lw};var $7=`
  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);
`,A7=`
  // 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);
  `+Zs+`
  return result;
`,R7=tt({opSnippet:$7,packedOpSnippet:A7}),fF={kernelName:An,backendName:"webgl",kernelFunc:R7};function F7(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,p=[],u=y.parseAxisParam(s,n.shape),c=u,l=S.getAxesPermutation(c,i),m=n;l!=null&&(m=xt({inputs:{x:n},backend:t,attrs:{perm:l}}),c=S.getInnerMostAxes(c.length,i),p.push(m)),S.assertAxesAreInnerMostDims("prod",c,i);let d;if(t.shouldExecuteOnCPU([m])){let f=t.texData.get(m.dataId).values,{outVals:h,outShape:g,outDtype:x}=o$(m.shape,m.dtype,f,c);d=t.makeTensorInfo(g,x,h)}else{let[f,h]=S.computeOutAndReduceShapes(m.shape,c),g=y.sizeFromShape(h),x=te({inputs:{x:m},backend:t,attrs:{shape:[-1,g]}}),b=ka(n.dtype),C=Gr(x,b,"prod",t);d=te({inputs:{x:C},backend:t,attrs:{shape:f}}),p.push(x),p.push(C)}if(a){p.push(d);let f=S.expandShapeToKeepDim(d.shape,u);d=te({inputs:{x:d},backend:t,attrs:{shape:f}})}return p.forEach(f=>t.disposeIntermediateTensorInfo(f)),d}var hF={kernelName:Fn,backendName:"webgl",kernelFunc:F7};function D7(r){let{inputs:e,backend:t,attrs:o}=r,{paramsNestedSplits:n,paramsDenseValues:s,indices:a}=e,{outputRaggedRank:i}=o,p=n.map(x=>t.readSync(x.dataId)),u=n.map(x=>x.shape),c=t.readSync(s.dataId),l=t.readSync(a.dataId),[m,d,f]=n$(p,u,c,s.shape,s.dtype,l,a.shape,i),h=m.map(x=>t.makeTensorInfo([x.length],"int32",x)),g=t.makeTensorInfo(f,s.dtype,d);return h.concat([g])}var gF={kernelName:wp,backendName:"webgl",kernelFunc:D7};function O7(r){let{inputs:e,backend:t}=r,{starts:o,limits:n,deltas:s}=e,a=t.readSync(o.dataId),i=t.readSync(n.dataId),p=t.readSync(s.dataId),[u,c]=s$(a,o.shape,o.dtype,i,n.shape,p,s.shape),l=t.makeTensorInfo([u.length],"int32",u),m=t.makeTensorInfo([c.length],o.dtype,c);return[l,m]}var xF={kernelName:Ip,backendName:"webgl",kernelFunc:O7};function P7(r){let{inputs:e,backend:t,attrs:o}=r,{shape:n,values:s,defaultValue:a,rowPartitionTensors:i}=e,{rowPartitionTypes:p}=o,u=t.readSync(n.dataId),c=t.readSync(s.dataId),l=t.readSync(a.dataId),m=i.map(g=>t.readSync(g.dataId)),d=i.map(g=>g.shape),[f,h]=a$(u,n.shape,c,s.shape,s.dtype,l,a.shape,m,d,p);return t.makeTensorInfo(f,s.dtype,h)}var yF={kernelName:vp,backendName:"webgl",kernelFunc:P7};var Bw=r=>{let{backend:e,attrs:t}=r,{start:o,stop:n,step:s,dtype:a}=t,i=i$(o,n,s,a);return e.makeTensorInfo([i.length],a,i)},bF={kernelName:ks,backendName:"webgl",kernelFunc:Bw};var M7="return 1.0 / x;",L7=ge({opSnippet:M7}),CF={kernelName:Dn,backendName:"webgl",kernelFunc:L7};var B7=Bt+`
  return (x < 0.0) ? 0.0 : x;
`,V7=`
  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;
`,z7=ge({opSnippet:B7,packedOpSnippet:V7}),SF={kernelName:On,backendName:"webgl",kernelFunc:z7};var W7=Bt+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,U7=`
  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;
`,G7=ge({opSnippet:W7,packedOpSnippet:U7}),wF={kernelName:Ln,backendName:"webgl",kernelFunc:G7};var tg=class{constructor(e,t,o,n,s){this.variableNames=["A"],this.outputShape=[];let[a,i,p,u]=e;this.outputShape=[a,t,o,u];let c=[n&&t>1?i-1:i,n&&o>1?p-1:p],l=[n&&t>1?t-1:t,n&&o>1?o-1:o],m;s?m="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":m="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ${c[0]/l[0]},
          ${c[1]/l[1]});
      const vec2 inputShapeRC = vec2(${i}.0, ${p}.0);

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

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

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

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

        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);

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

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

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

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

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

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

        // Should we calculate next column and row elements in 2x2 packed cell.
        bool hasNextCol = d < ${u-1};
        bool hasNextRow = coords.z < ${o-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 H7(r){let{inputs:e,backend:t,attrs:o}=r,{images:n}=e,{alignCorners:s,halfPixelCenters:a,size:i}=o,[p,u]=i,c=O().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new rg(n.shape,p,u,s,a):new tg(n.shape,p,u,s,a);return t.runWebGLProgram(c,[n],"float32")}var IF={kernelName:Mn,backendName:"webgl",kernelFunc:H7};var og=class{constructor(e,t,o){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,s]=t,[,a,i]=e,p=[o&&a>1?n-1:n,o&&i>1?s-1:s],u=[o&&a>1?a-1:a,o&&i>1?i-1:i],c=p[0]/u[0],l=p[1]/u[1],m=1/c,d=1/l,f=Math.ceil(m)*2+2,h=Math.ceil(d)*2+2;this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        int r = coords[1];
        int c = coords[2];

        float accumulator = 0.0;

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

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

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

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

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

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

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ${a}) {
            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), ${s-1}.0));
            float dxCLerp = dxC - float(leftDxCIndex);
            float inverseDxCLerp = 1.0 - dxCLerp;

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

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

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

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

        setOutput(accumulator);
      }
    `}};function q7(r){let{inputs:e,backend:t,attrs:o}=r,{images:n,dy:s}=e,{alignCorners:a}=o,i=new og(s.shape,n.shape,a);return t.runWebGLProgram(i,[s],s.dtype)}var vF={kernelName:$m,backendName:"webgl",kernelFunc:q7};var ng=class{constructor(e,t,o,n,s){this.variableNames=["A"],this.outputShape=[];let[a,i,p,u]=e;this.outputShape=[a,t,o,u];let c=[n&&t>1?i-1:i,n&&o>1?p-1:p],l=[n&&t>1?t-1:t,n&&o>1?o-1:o],m=n?"0.5":"0.0",d;s?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ${c[0]/l[0]},
          ${c[1]/l[1]});
      const vec2 inputShapeRC = vec2(${i}.0, ${p}.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 coordinators of nearest neighbor point.
        ivec2 sourceNearestRC = ivec2(
          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${m})));
        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);

        setOutput(newValue);
      }
    `}};var sg=class{constructor(e,t,o,n,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[a,i,p,u]=e;this.outputShape=[a,t,o,u];let c=[n&&t>1?i-1:i,n&&o>1?p-1:p],l=[n&&t>1?t-1:t,n&&o>1?o-1:o],m=n?"0.5":"0.0",d;s?d="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":d="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec3 effectiveInputOverOutputRatioRC = vec3(
          ${c[0]/l[0]},
          ${c[1]/l[1]},
          ${c[1]/l[1]});
      const vec3 inputShapeRC = vec3(${i}.0, ${p}.0,
                                     ${p}.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 coordinators of nearest neighbor point.
        ivec3 sourceNearestRC = ivec3(
          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${m})));

        // Should we calculate next column and row elements in 2x2 packed cell.
        bool hasNextCol = d < ${u-1};
        bool hasNextRow = coords.z < ${o-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 K7(r){let{inputs:e,backend:t,attrs:o}=r,{images:n}=e,{alignCorners:s,halfPixelCenters:a,size:i}=o,[p,u]=i,c=O().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new sg(n.shape,p,u,s,a):new ng(n.shape,p,u,s,a);return t.runWebGLProgram(c,[n],n.dtype)}var kF={kernelName:Pn,backendName:"webgl",kernelFunc:K7};var ag=class{constructor(e,t,o){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,s]=t,[,a,i]=e,p=[o&&a>1?n-1:n,o&&i>1?s-1:s],u=[o&&a>1?a-1:a,o&&i>1?i-1:i],c=p[0]/u[0],l=p[1]/u[1],m=1/c,d=1/l,f=Math.ceil(m)*2+2,h=Math.ceil(d)*2+2;this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        int r = coords[1];
        int c = coords[2];

        float accumulator = 0.0;

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

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

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

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

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

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

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ${a}) {
            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(${p[0]}) *
                (float(dyR) / float(${u[0]}));

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

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

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

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

        setOutput(accumulator);
      }
    `}};function j7(r){let{inputs:e,backend:t,attrs:o}=r,{images:n,dy:s}=e,{alignCorners:a}=o,i=new ag(s.shape,n.shape,a);return t.runWebGLProgram(i,[s],s.dtype)}var NF={kernelName:Em,backendName:"webgl",kernelFunc:j7};var ig=class{constructor(e,t){this.variableNames=["x"];let o=e.length;if(o>4)throw new Error(`WebGL backend: Reverse of rank-${o} tensor is not yet supported`);if(this.outputShape=e,o===1){this.userCode=`
        void main() {
          int coord = getOutputCoords();
          setOutput(getX(${e[0]} - coord - 1));
        }
      `;return}let n=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,s=e.map((i,p)=>n(p)).join(","),a=_e(o);this.userCode=`
      void main() {
        ${a} coords = getOutputCoords();
        setOutput(getX(${s}));
      }
    `}};var ug=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let o=e.length;if(o>4)throw new Error(`WebGL backend: Reverse of rank-${o} tensor is not yet supported`);this.outputShape=e;let n=$t("rc",o),s=`${n[o-1]} + 1 < ${this.outputShape[o-1]}`,a=`${n[o-2]} + 1 < ${this.outputShape[o-2]}`,i=_e(o);o===1?this.userCode=`
        void main(){
          int rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = getChannel(getX(${e[0]} - rc - 1),
            ${e[0]} - rc - 1);
          if(${s}){
              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 = ${p(n.slice())};
          if(${s}){
            result.g = ${u(n.slice())};
          }
          if(${a}) {
            result.b = ${c(n.slice())};
            if(${s}) {
              result.a = ${l(n.slice())};
            }
          }
          setOutput(result);
        }
    `;function p(f){return m(f)}function u(f){return f[o-1]="("+f[o-1]+" + 1)",m(f)}function c(f){return f[o-2]="("+f[o-2]+" + 1)",m(f)}function l(f){return f[o-1]="("+f[o-1]+" + 1)",f[o-2]="("+f[o-2]+" + 1)",m(f)}function m(f){let h=e.map((b,C)=>d(C,f)),g=h.join(","),x=h.slice(-2).join(",");return`getChannel(getX(${g}), vec2(${x}))`}function d(f,h){return t.indexOf(f)!==-1&&e[f]!==1?`${e[f]} - ${h[f]} - 1`:`${h[f]}`}}};function X7(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{dims:s}=o,a=n.shape.length,i=y.parseAxisParam(s,n.shape);if(a===0)return At({inputs:{x:n},backend:t});let p=O().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new ug(n.shape,i):new ig(n.shape,i);return t.runWebGLProgram(p,[n],n.dtype)}var TF={kernelName:Bn,backendName:"webgl",kernelFunc:X7};var pg=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let o=e[1],n=e[2];this.outputShape=e;let s="";typeof t=="number"?s=`float outputValue = ${t.toFixed(2)};`:s=`
        vec3 fill = vec3(${t.join(",")});
        float outputValue = fill[coords[3]];`,this.userCode=`
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];
          int y = coords[1];
          float coordXFloat = (float(x) - params[0]) * params[3] -
            (float(y) - params[1]) * params[2];
          float coordYFloat = (float(x) - params[0]) * params[2] +
            (float(y) - params[1]) * params[3];
          int coordX = int(round(coordXFloat + params[0]));
          int coordY = int(round(coordYFloat + params[1]));
          ${s}
          if(coordX >= 0 && coordX < ${n} && coordY >= 0 && coordY < ${o}) {
            outputValue = getImage(coords[0], coordY, coordX, coords[3]);
          }
          setOutput(outputValue);
        }
    `}};var _F={kernelName:es,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{image:o}=r,{radians:n,fillValue:s,center:a}=e,i=t,p=new pg(o.shape,s),[u,c]=S.getImageCenter(a,o.shape[1],o.shape[2]),l=[[u,c,Math.sin(n),Math.cos(n)]];return i.runWebGLProgram(p,[o],o.dtype,l)}};var Y7=`
  // OpenGL ES does not support round function.
  // The algorithm is based on banker's rounding.
  float base = floor(x);
  if ((x - base) < 0.5) {
    return floor(x);
  } else if ((x - base) > 0.5) {
    return ceil(x);
  } else {
    if (mod(base, 2.0) == 0.0) {
      return base;
    } else {
      return base + 1.0;
    }
  }
`,Q7=ge({opSnippet:Y7}),EF={kernelName:Ca,backendName:"webgl",kernelFunc:Q7};var Z7="return inversesqrt(x);",J7=ge({opSnippet:Z7,cpuKernelImpl:u$}),$F={kernelName:Vn,backendName:"webgl",kernelFunc:J7};var Cc=class{constructor(e,t,o,n,s,a,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;let p=_e(s.length),u=_e(a.length),c="";o===1?c="i":o===2&&(c="i, j");let l=`getIndices(${c})`,m="";n===1?m="i":n===2&&(m="i, coords[1]");let d=`getUpdates(${m})`,f=t>1?"strides[j]":"strides";this.userCode=`
        ${p} strides = ${p}(${s});

        void main() {
          ${u} coords = getOutputCoords();
          float sum = 0.0;
          bool found = false;
          for (int i = 0; i < ${e}; i++) {
            int flattenedIndex = 0;
            for (int j = 0; j < ${t}; j++) {
              int index = round(${l});
              flattenedIndex += index * ${f};
            }
            if (flattenedIndex == coords[0]) {
              sum += ${d};
              found = true;
            }
          }
          setOutput(mix(getDefaultValue(), sum, float(found)));
        }
      `}};function eZ(r){let{inputs:e,backend:t,attrs:o}=r,{indices:n,updates:s}=e,{shape:a}=o,{sliceRank:i,numUpdates:p,sliceSize:u,strides:c,outputSize:l}=S.calculateShapes(s,n,a),m=[l/u,u];if(l===0)return t.makeTensorInfo(a,n.dtype);let d=te({inputs:{x:n},backend:t,attrs:{shape:[p,i]}}),f=te({inputs:{x:s},backend:t,attrs:{shape:[p,u]}}),h=t.makeTensorInfo([],"float32",new Float32Array([0])),g=new Cc(p,i,d.shape.length,f.shape.length,c,m),x=t.runWebGLProgram(g,[f,d,h],f.dtype),b=te({inputs:{x},backend:t,attrs:{shape:a}});return t.disposeIntermediateTensorInfo(d),t.disposeIntermediateTensorInfo(f),t.disposeIntermediateTensorInfo(x),t.disposeIntermediateTensorInfo(h),b}var AF={kernelName:zn,backendName:"webgl",kernelFunc:eZ};var cg=class{constructor(e,t,o,n){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[e,o];let s="while (left < right) {",a=`for (int i = 0; i < ${Math.ceil(Math.log2(t+1))}; ++i) { if (left >= right) break;`,i=O().getNumber("WEBGL_VERSION")===2?s:a,p=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) ${p} 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 tZ(r){let{inputs:e,backend:t,attrs:o}=r,{sortedSequence:n,values:s}=e,{side:a}=o,i=new cg(n.shape[0],n.shape[1],s.shape[1],a),p=[[n.shape[1]]];return t.runWebGLProgram(i,[n,s],"int32",p)}var RF={kernelName:ii,backendName:"webgl",kernelFunc:tZ};var lg=class{constructor(e,t,o){this.variableNames=["c","a","b"],this.outputShape=t;let n,s;if(o>4)throw Error(`Where for rank ${o} is not yet supported`);if(o===1)s="resRC",n="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],p=[],u=[];for(let c=0;c<t.length;c++)u.push(`${i[c]}`),c<e&&p.push(`${i[c]}`);n=p.join(),s=u.join()}let a=_e(o);this.userCode=`
      void main() {
        ${a} resRC = getOutputCoords();
        float cVal = getC(${n});
        if (cVal >= 1.0) {
          setOutput(getA(${s}));
        } else {
          setOutput(getB(${s}));
        }
      }
    `}};function rZ(r){let{inputs:e,backend:t}=r,{condition:o,t:n,e:s}=e,a=new lg(o.shape.length,n.shape,n.shape.length);return t.runWebGLProgram(a,[o,n,s],dt(n.dtype,s.dtype))}var FF={kernelName:Ts,backendName:"webgl",kernelFunc:rZ};var oZ=`
  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
  // see: https://arxiv.org/abs/1706.02515
  float scaleAlpha = ${S.SELU_SCALEALPHA};
  float scale = ${S.SELU_SCALE};
  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,nZ=ge({opSnippet:oZ}),DF={kernelName:Xi,backendName:"webgl",kernelFunc:nZ};var sZ=_o+`
  return 1.0 / (1.0 + exp(-1.0 * x));
`,aZ=`
  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;
`,iZ=ge({opSnippet:sZ,packedOpSnippet:aZ,cpuKernelImpl:c$}),OF={kernelName:Un,backendName:"webgl",kernelFunc:iZ};var uZ=`
  if (isnan(x)) { return 0.0; }
  return sign(x);
`,pZ=ge({opSnippet:uZ}),PF={kernelName:Yi,backendName:"webgl",kernelFunc:pZ};var cZ=_o+`
  return sin(x);
`,lZ=ge({opSnippet:cZ}),MF={kernelName:Wn,backendName:"webgl",kernelFunc:lZ};var mZ=`
  float e2x = exp(x);
  return (e2x - 1.0 / e2x) / 2.0;
`,dZ=ge({opSnippet:mZ}),LF={kernelName:Sa,backendName:"webgl",kernelFunc:dZ};var fZ=`
  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;
`,hZ=ge({opSnippet:fZ}),BF={kernelName:Qi,backendName:"webgl",kernelFunc:hZ};var gZ=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockShape:s,paddings:a}=o;y.assert(n.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let i=s.reduce((x,b)=>x*b),p=[[0,0]];p.push(...a);for(let x=1+s.length;x<n.shape.length;++x)p.push([0,0]);let u=[],c=Lw({inputs:{x:n},backend:t,attrs:{paddings:p,constantValue:0}}),l=S.getReshaped(c.shape,s,i,!1),m=S.getPermuted(l.length,s.length,!1),d=S.getReshapedPermuted(c.shape,s,i,!1),f=te({inputs:{x:c},backend:t,attrs:{shape:l}}),h=xt({inputs:{x:f},backend:t,attrs:{perm:m}}),g=te({inputs:{x:h},backend:t,attrs:{shape:d}});return u.push(c),u.push(f),u.push(h),u.forEach(x=>t.disposeIntermediateTensorInfo(x)),g},VF={kernelName:Es,backendName:"webgl",kernelFunc:gZ};function xZ(r){let{inputs:e,backend:t}=r,{indices:o,values:n,denseShape:s,defaultValue:a}=e;if(s.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
         ${s.shape}`);if(o.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
         ${o.shape}`);if(n.shape.length!==1)throw new Error(`Values must be a vector, saw:
         ${n.shape}`);if(a.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
        ${a.shape}`);let i=t.readSync(o.dataId),p=t.readSync(n.dataId),u=t.readSync(s.dataId),c=t.readSync(a.dataId)[0],[l,m,d,f,h]=m$(i,o.shape,o.dtype,p,n.dtype,u,c);return[t.makeTensorInfo(m,o.dtype,l),t.makeTensorInfo([m[0]],n.dtype,d),t.makeTensorInfo([f.length],"bool",new Uint8Array(f.map(g=>Number(g)))),t.makeTensorInfo([h.length],o.dtype,new Int32Array(h))]}var zF={kernelName:ui,backendName:"webgl",kernelFunc:xZ};function yZ(r){let{inputs:e,backend:t}=r,{inputIndices:o,inputShape:n,newShape:s}=e;if(o.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${o.shape}`);if(n.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${n.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let a=Array.from(t.readSync(n.dataId)),i=t.readSync(o.dataId),p=Array.from(t.readSync(s.dataId)),[u,c,l]=d$(i,o.shape,o.dtype,a,p);return[t.makeTensorInfo(c,o.dtype,u),t.makeTensorInfo([l.length],s.dtype,new Int32Array(l))]}var WF={kernelName:wa,backendName:"webgl",kernelFunc:yZ};function bZ(r){let{inputs:e,backend:t}=r,{data:o,indices:n,segmentIds:s}=e;if(o.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(n.shape.length!==1)throw new Error(`Indices should be a vector but received shape
              ${n.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
              ${s.shape}`);let a=t.readSync(o.dataId),i=t.readSync(n.dataId),p=t.readSync(s.dataId),[u,c]=jf(a,o.shape,o.dtype,i,p,!0);return t.makeTensorInfo(c,o.dtype,u)}var UF={kernelName:pi,backendName:"webgl",kernelFunc:bZ};function CZ(r){let{inputs:e,backend:t}=r,{data:o,indices:n,segmentIds:s}=e;if(o.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(n.shape.length!==1)throw new Error(`Indices should be a vector but received shape
             ${n.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
             ${s.shape}`);let a=t.readSync(o.dataId),i=t.readSync(n.dataId),p=t.readSync(s.dataId),[u,c]=jf(a,o.shape,o.dtype,i,p);return t.makeTensorInfo(c,o.dtype,u)}var GF={kernelName:ci,backendName:"webgl",kernelFunc:CZ};function SZ(r){let{inputs:e,backend:t,attrs:o}=r,{sparseIndices:n,sparseValues:s,defaultValue:a}=e,{outputShape:i}=o,{sliceRank:p,numUpdates:u,sliceSize:c,strides:l,outputSize:m}=S.calculateShapes(s,n,i),d=!1;if(s.dtype==="string"){let x=t.bufferSync(n),b=t.bufferSync(s),C=y.decodeString(t.readSync(a.dataId)[0]),w=p$(x,b,i,m,c,u,p,l,C,d);return t.makeTensorInfo(i,w.dtype,w.values)}let f=new Cc(u,p,n.shape.length,s.shape.length,l,[m,1],d),h=t.runWebGLProgram(f,[s,n,a],s.dtype),g=te({inputs:{x:h},backend:t,attrs:{shape:i}});return t.disposeIntermediateTensorInfo(h),g}var HF={kernelName:li,backendName:"webgl",kernelFunc:SZ};function wZ(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{numOrSizeSplits:s,axis:a}=o,i=y.parseAxisParam(a,n.shape)[0],p=S.prepareSplitSize(n,s,i),u=n.shape.length,c=new Array(u).fill(0),l=n.shape.slice();return p.map(m=>{let d=[...l];d[i]=m;let f=cs({inputs:{x:n},backend:t,attrs:{begin:c,size:d}});return c[i]+=m,f})}var qF={kernelName:$s,backendName:"webgl",kernelFunc:wZ};var KF="return sqrt(x);",IZ=ge({opSnippet:KF,packedOpSnippet:KF,cpuKernelImpl:f$}),jF={kernelName:Gn,backendName:"webgl",kernelFunc:IZ};var vZ="return x * x;",kZ=ge({opSnippet:vZ}),XF={kernelName:mi,backendName:"webgl",kernelFunc:kZ};var YF="return (a - b) * (a - b);",NZ=tt({opSnippet:YF,packedOpSnippet:YF}),QF={kernelName:Kn,backendName:"webgl",kernelFunc:NZ};function TZ({inputs:r,attrs:e,backend:t}){let{x:o}=r,n=Bt+`
    return x > 0.0 ? 1.0 : float(${e.alpha});
  `,s=new Jt(o.shape,n);return t.runWebGLProgram(s,[o],o.dtype)}var ZF={kernelName:Ds,backendName:"webgl",kernelFunc:TZ};var mg=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=o;let n=o.length,s=_e(o.length),a=_e(o.length),i="";if(n===1)i="coords * strides + begin";else{let p=0;i=o.map((u,c)=>(p++,o.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${p-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
      ${s} begin = ${s}(${e});
      ${s} strides = ${s}(${t});

      void main() {
        ${a} coords = getOutputCoords();
        setOutput(getX(${i}));
      }
    `}};function _Z(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{begin:s,end:a,strides:i,beginMask:p,endMask:u,ellipsisMask:c,newAxisMask:l,shrinkAxisMask:m}=o,{finalShapeSparse:d,finalShape:f,isIdentity:h,sliceDim0:g,isSimpleSlice:x,begin:b,end:C,strides:w}=ut.sliceInfo(n.shape,s,a,i,p,u,c,l,m),k;if(h)k=te({inputs:{x:n},backend:t,attrs:{shape:f}});else if(g||x){y.assert(n.shape.length>=1,()=>`Input must have rank at least 1, got: ${n.shape.length}`);let $=ut.computeOutShape(b,C,w),A=cs({inputs:{x:n},backend:t,attrs:{begin:b,size:$}});k=te({inputs:{x:A},backend:t,attrs:{shape:f}}),t.disposeIntermediateTensorInfo(A)}else if(t.shouldExecuteOnCPU([n])){let A=t.readSync(n.dataId),R=le(n.shape,n.dtype,A),D=h$(d,R,w,b);k=t.makeTensorInfo(f,n.dtype,D.values)}else{let A=new mg(b,w,d);k=t.runWebGLProgram(A,[n],n.dtype)}let _=te({inputs:{x:k},backend:t,attrs:{shape:f}});return t.disposeIntermediateTensorInfo(k),_}var JF={kernelName:jn,backendName:"webgl",kernelFunc:_Z};function EZ(r){let{inputs:e,backend:t,attrs:o}=r,{separator:n,nGramWidths:s,leftPad:a,rightPad:i,padWidth:p,preserveShortSequences:u}=o,{data:c,dataSplits:l}=e,m=t.readSync(c.dataId),d=t.readSync(l.dataId),[f,h]=g$(m,d,n,s,a,i,p,u);return[t.makeTensorInfo([f.length],"string",f),t.makeTensorInfo(l.shape,"int32",h)]}var eD={kernelName:As,backendName:"webgl",kernelFunc:EZ};function $Z(r){let{inputs:e,backend:t,attrs:o}=r,{skipEmpty:n}=o,{input:s,delimiter:a}=e;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(a.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${a.shape}`);let i=t.readSync(s.dataId),p=t.readSync(a.dataId)[0],[u,c,l]=x$(i,p,n),m=c.length;return[t.makeTensorInfo([m,2],"int32",u),t.makeTensorInfo([m],"string",c),t.makeTensorInfo([2],"int32",new Int32Array(l))]}var tD={kernelName:di,backendName:"webgl",kernelFunc:$Z};function AZ(r){let{inputs:e,backend:t,attrs:o}=r,{numBuckets:n}=o,{input:s}=e;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(n<=0)throw new Error("Number of buckets must be at least 1");let a=t.readSync(s.dataId),i=y$(a,n);return t.makeTensorInfo(s.shape,"int32",i)}var rD={kernelName:fi,backendName:"webgl",kernelFunc:AZ};var RZ="return tan(x);",FZ=ge({opSnippet:RZ}),oD={kernelName:Yn,backendName:"webgl",kernelFunc:FZ};var DZ=`
  float e2x = exp(-2.0 * abs(x));
  return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,OZ=ge({opSnippet:DZ}),nD={kernelName:Qn,backendName:"webgl",kernelFunc:OZ};var dg=class{constructor(e,t){this.variableNames=["A"];let o=new Array(e.length);for(let a=0;a<o.length;a++)o[a]=e[a]*t[a];this.outputShape=o,this.rank=o.length;let n=_e(this.rank),s=PZ(e);this.userCode=`
      void main() {
        ${n} resRC = getOutputCoords();
        setOutput(getA(${s}));
      }
    `}};function PZ(r){let e=r.length;if(e>5)throw Error(`Tile for rank ${e} is not yet supported`);if(e===1)return`imod(resRC, ${r[0]})`;let t=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],o=[];for(let n=0;n<r.length;n++)o.push(`imod(${t[n]}, ${r[n]})`);return o.join()}function Vw(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{reps:s}=o;if(n.dtype==="string"||n.shape.length>5){let p=t.readSync(n.dataId),u=n.dtype==="string"?p.map(m=>y.decodeString(m)):p,c=le(n.shape,n.dtype,u),l=C$(c,s);return t.makeTensorInfo(l.shape,l.dtype,l.values)}let a=new dg(n.shape,s);return t.runWebGLProgram(a,[n],n.dtype)}var sD={kernelName:to,backendName:"webgl",kernelFunc:Vw};var fg=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));
         }
       }
     `}},hg=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 Bu(r,e){e!==null&&r.disposeIntermediateTensorInfo(e)}function aD(r){let e=1;for(;e<r;)e*=2;return e}function MZ(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{k:s,sorted:a}=o,i=O().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),p=O().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=n.shape,c=u[u.length-1];if(t.shouldExecuteOnCPU([n])||c<i||s>p){let D=t.readSync(n.dataId),[P,M]=S$(D,u,n.dtype,s,a);return[t.makeTensorInfo(P.shape,P.dtype,P.values),t.makeTensorInfo(M.shape,M.dtype,M.values)]}if(s===0)return u[u.length-1]=0,[t.makeTensorInfo(u,n.dtype,[]),t.makeTensorInfo(u,"int32",[])];if(c===1)return[n,Ga({attrs:{shape:u,dtype:"int32",value:0},backend:t})];let l=t.texData.get(n.dataId),m=l!==null&&l.isPacked,d=m?t.unpackTensor(n):n,h=y.sizeFromShape(u)/c,g=te({inputs:{x:d},attrs:{shape:[h,c]},backend:t});m&&Bu(t,d);let x=aD(s),b=aD(c),C=null,w=()=>C===null?[g,g]:[g,C],k=(D,P,M)=>{let L=w(),W=new fg(M),U=[[c],[C===null?1:0],[Number.NEGATIVE_INFINITY],[D],[P]],q=C;C=t.runWebGLProgram(W,L,"int32",U),Bu(t,q)};for(let D=1;D<x;D*=2){let P=D*2;for(let M=D;M>=1;M/=2)k(P,M,[h,b])}for(let D=b;D>x;D/=2){let P=w(),M=new hg([h,D/2]),W=[[c],[C===null?1:0],[x]],V=C;C=t.runWebGLProgram(M,P,"int32",W),Bu(t,V);let U=x/2,q=U*2;for(let H=U;H>=1;H/=2)k(q,H,C.shape)}let _=C;C=cs({inputs:{x:C},backend:t,attrs:{begin:0,size:[h,s]}}),Bu(t,_);let $=Fw({inputs:{x:g,indices:C},backend:t,attrs:{axis:1,batchDims:1}});Bu(t,g);let A=u.slice(0,-1);A.push(s),_=C,C=te({inputs:{x:C},attrs:{shape:A},backend:t}),Bu(t,_);let R=$;return $=te({inputs:{x:$},attrs:{shape:A},backend:t}),Bu(t,R),[$,C]}var iD={kernelName:Zn,backendName:"webgl",kernelFunc:MZ};var gg=class{constructor(e,t,o,n,s,a){this.variableNames=["Image","Transforms"],this.outputShape=a;let i=o==="nearest"?1:2,p;switch(n){case"constant":p=1;break;case"reflect":p=2;break;case"wrap":p=3;break;case"nearest":p=4;break;default:p=1;break}this.userCode=`
            float mapCoord(float outCoord, float len) {
              float inCoord = outCoord;
              if(${p} == 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 (${p} == 3) {
                if (inCoord < 0.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz = len - 1.0;
                    inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
                  }
                } else if (inCoord > len - 1.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz = len - 1.0;
                    inCoord -= len * float(int(float(inCoord / sz)));
                  }
                }
                return clamp(inCoord, 0.0, len - 1.0);
              } else if (${p} == 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 < ${t}) {
                  outputValue = getImage(batch, coordY, coordX, channel);
              } else {
                outputValue = float(${s});
              }
              return outputValue;
            }

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

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

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

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

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

        float sumValue = 0.0;

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

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

          ${m}
        }

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

          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));

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

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

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

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

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

          ${m}
        }
        setOutput(${u});
      }
    `}};function zZ(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,segmentIds:s}=e,{numSegments:a}=o,i=n.shape.length,p=[],u=0,c=S.getAxesPermutation([u],i),l=n;c!=null&&(l=xt({inputs:{x:n},backend:t,attrs:{perm:c}}),p.push(l),u=S.getInnerMostAxes(1,i)[0]);let m=S.segment_util.computeOutShape(l.shape,u,a),d=y.sizeFromShape([l.shape[u]]),f=te({inputs:{x:l},backend:t,attrs:{shape:[-1,d]}});p.push(f);let h=ka(n.dtype),g=(w,k,_,$,A)=>{let R=w.shape[0],D=w.shape[1],P=S.segment_util.segOpComputeOptimalWindowSize(D,A),M={windowSize:P,inSize:D,batchSize:R,numSegments:A},L=new xg(M,k),W=t.compileAndRun(L,[w,_],$);if(p.push(W),W.shape[1]===A)return W;let V=Bw({backend:t,attrs:{start:0,stop:A,step:1,dtype:"float32"}}),U=Vw({inputs:{x:V},backend:t,attrs:{reps:[D/P]}});return p.push(V),p.push(U),g(W,k,U,$,A)},x=g(f,"unsortedSegmentSum",s,h,a),b=te({inputs:{x},backend:t,attrs:{shape:m}}),C=b;if(c!=null){p.push(b);let w=S.getUndoAxesPermutation(c);C=xt({inputs:{x:C},backend:t,attrs:{perm:w}})}return p.forEach(w=>t.disposeIntermediateTensorInfo(w)),C}var lD={kernelName:Np,backendName:"webgl",kernelFunc:zZ};var WZ=[Y$,Z$,J$,eA,rA,oA,nA,sA,uA,pA,cA,lA,mA,dA,fA,hA,gA,xA,yA,bA,CA,wA,IA,vA,_A,$A,AA,V$,FA,OA,PA,MA,LA,BA,VA,zA,WA,UA,GA,KA,jA,XA,YA,QA,ZA,JA,eR,tR,rR,oR,nR,sR,aR,iR,uR,cR,lR,mR,dR,hR,gR,xR,yR,bR,CR,SR,wR,IR,B$,vR,DA,kR,NR,TR,z$,_R,ER,$R,AR,RR,FR,DR,OR,PR,MR,BR,VR,zR,WR,UR,GR,qR,jR,XR,YR,QR,ZR,oF,G$,nF,sF,aF,iF,kA,uF,lF,mF,dF,fF,W$,hF,gF,xF,yF,bF,NA,JR,CF,SF,wF,q$,IF,vF,kF,NF,TF,_F,EF,$F,AF,RF,FF,DF,OF,PF,MF,LF,SA,rF,BF,VF,zF,WF,UF,GF,HF,qF,jF,XF,QF,ZF,JF,eD,tD,rD,tF,j$,oD,nD,sD,iD,uD,X$,pD,cD,lD,pF];for(let r of WZ)Ia(r);var Fe;(function(r){r[r.float32=0]="float32",r[r.int32=1]="int32",r[r.bool=2]="bool",r[r.string=3]="string",r[r.complex64=4]="complex64"})(Fe||(Fe={}));var Wi;(function(r){r[r.linear=0]="linear",r[r.relu=1]="relu",r[r.relu6=2]="relu6",r[r.prelu=3]="prelu",r[r.leakyrelu=4]="leakyrelu",r[r.sigmoid=5]="sigmoid",r[r.elu=6]="elu"})(Wi||(Wi={}));var mD;function UZ(r){mD=r.wasm.cwrap(fo,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function GZ(r){let{inputs:e,backend:t,attrs:o}=r,{a:n,b:s,bias:a,preluActivationWeights:i}=e;if(n.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:p,transposeB:u,activation:c,leakyreluAlpha:l}=o,m=t.dataIdMap.get(n.dataId).id,d=t.dataIdMap.get(s.dataId).id,f=0;if(a!=null){let A=t.dataIdMap.get(a.dataId);if(A.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${A.shape.length}.`);f=A.id}let h=i==null?0:t.dataIdMap.get(i.dataId).id,g=Wi[c];if(g==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let x=p?n.shape[2]:n.shape[1],b=u?s.shape[1]:s.shape[2],C=br.assertAndGetBroadcastShape(n.shape.slice(0,-2),s.shape.slice(0,-2)),w=t.makeOutput([...C,x,b],n.dtype),k=t.dataIdMap.get(w.dataId).id,_=new Uint8Array(new Int32Array(n.shape).buffer),$=new Uint8Array(new Int32Array(s.shape).buffer);return mD(m,_,n.shape.length,d,$,s.shape.length,p,u,g,f,h,l||0,k),w}var dD={kernelName:fo,backendName:"wasm",setupFunc:UZ,kernelFunc:GZ};function Ve(r,e){let t;function o(s){t=s.wasm.cwrap(r,null,["number","number","number"])}function n(s){let{backend:a,inputs:{x:i}}=s,p=a.dataIdMap.get(i.dataId).id,u=a.makeOutput(i.shape,e||i.dtype),c=a.dataIdMap.get(u.dataId).id;return y.sizeFromShape(u.shape)===0||t(p,Fe[i.dtype],c),u}return{kernelName:r,backendName:"wasm",setupFunc:o,kernelFunc:n}}var fD=Ve(gs);function rt(r,e,t){let o;function n(a){o=a.wasm.cwrap(r,null,["number","array","number","number","array","number","number","number"])}function s(a){let{backend:i,inputs:p}=a,{a:u,b:c}=p,l=i.dataIdMap.get(u.dataId).id,m=i.dataIdMap.get(c.dataId).id,d=t!=null?t:u.dtype,f=S.assertAndGetBroadcastShape(u.shape,c.shape),h=i.makeOutput(f,d);if(y.sizeFromShape(f)===0)return h;let g=new Uint8Array(new Int32Array(u.shape).buffer),x=new Uint8Array(new Int32Array(c.shape).buffer),b=i.dataIdMap.get(h.dataId).id;return(()=>o(l,g,u.shape.length,m,x,c.shape.length,Fe[u.dtype],b))(),h}return{kernelName:r,backendName:"wasm",setupFunc:n,kernelFunc:s}}var HZ=!0,hD=rt(eo,HZ);var gD;function qZ(r){gD=r.wasm.cwrap(Mo,null,["array","number","number","number"])}function KZ(r){let{inputs:e,backend:t}=r,o=t.makeOutput(e[0].shape,e[0].dtype);if(y.sizeFromShape(o.shape)===0)return o;let n=e.map(i=>t.dataIdMap.get(i.dataId).id),s=new Uint8Array(new Int32Array(n).buffer),a=t.dataIdMap.get(o.dataId).id;return gD(s,n.length,Fe[o.dtype],a),o}var xD={kernelName:Mo,backendName:"wasm",setupFunc:qZ,kernelFunc:KZ};function Vu(r){let{inputs:{x:e},backend:t}=r;if(e.dtype==="string")return nr(t.readSync(e.dataId),e.shape,e.dtype);let o=t.makeOutput(e.shape,e.dtype),n=t.typedArrayFromHeap(e);return t.typedArrayFromHeap(o).set(n),o}var yD={kernelName:mo,backendName:"wasm",kernelFunc:Vu};var bD;function jZ(r){bD=r.wasm.cwrap(ro,null,["number","array","number","number","number","array","number"])}function uo(r){let{inputs:e,backend:t,attrs:o}=r,[n,s]=YZ(e.x.shape,o.perm),a=!0;for(let f=0;f<s.length;f++)s[f]!==f&&(a=!1);let i=XZ(e.x.shape,o.perm),p={dataId:e.x.dataId,shape:n,dtype:e.x.dtype};if(a){let f=Vu({inputs:e,backend:t});return f.shape=i,f}let u=t.makeOutput(i,p.dtype),c=t.dataIdMap.get(p.dataId).id,l=t.dataIdMap.get(u.dataId).id,m=new Uint8Array(new Int32Array(s).buffer),d=new Uint8Array(new Int32Array(p.shape).buffer);return bD(c,d,p.shape.length,Fe[p.dtype],l,m,s.length),u}function XZ(r,e){let t=new Array(r.length);for(let o=0;o<t.length;o++)t[o]=r[e[o]];return t}function YZ(r,e){let t=[],o=[];for(let n=0;n<r.length;++n)r[n]!==1&&t.push(r[n]),r[e[n]]!==1&&o.push(e[n]);for(let n=0;n<o.length;++n){let s=-1;for(let a=0;a<o.length;++a)o[a]>=n&&(s===-1||o[s]>o[a])&&(s=a);o[s]=n}return[t,o]}var CD={kernelName:ro,backendName:"wasm",kernelFunc:uo,setupFunc:jZ};function kr(r,e,t){let o=r.shape,n=r.shape.length,s=y.parseAxisParam(e,o),a=s,i=S.getAxesPermutation(a,n),p=null,u=!1;if(i!=null){let c=new Array(n);for(let d=0;d<c.length;d++)c[d]=o[i[d]];a=S.getInnerMostAxes(a.length,n),p=uo({inputs:{x:r},attrs:{perm:i},backend:t});let l=t.dataIdMap.get(r.dataId).id;t.dataIdMap.get(p.dataId).id!==l&&(u=!0)}return{transposed:p,originalAxes:s,axes:a,inputWasTransposed:u}}var SD;function QZ(r){SD=r.wasm.cwrap(Lo,null,["number, number, number"])}function ZZ(r){let{backend:e,inputs:t,attrs:o}=r,{axis:n,keepDims:s}=o,{x:a}=t,p=e.dataIdMap.get(a.dataId).id,u=a,{transposed:c,axes:l,originalAxes:m,inputWasTransposed:d}=kr(a,n,e);if(d){let C=e.dataIdMap.get(c.dataId).id;u=c,p=C}let 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b.stringBytes=S.fromStringArrayToUint8(g),d.forEach(C=>t.disposeData(C.dataId)),i}let p=y.sizeFromShape(a[0].shape.slice(0,o)),u=0,c=a.map(d=>{let f=y.sizeFromShape(d.shape.slice(o));return u+=f,f}),l=a.map(d=>t.typedArrayFromHeap(d)),m=t.typedArrayFromHeap(i);for(let d=0;d<p;d++){let f=d*u;for(let h=0;h<l.length;h++){let g=c[h],x=d*g,b=l[h].subarray(x,x+g);m.set(b,f),f+=g}}return i}var LD={kernelName:ys,backendName:"wasm",kernelFunc:zw};var BD;function d9(r){BD=r.wasm.cwrap(Go,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function f9(r){let{inputs:e,attrs:t,backend:o}=r,{x:n,filter:s}=e,a=o.dataIdMap.get(n.dataId).id,i=o.dataIdMap.get(s.dataId).id,{strides:p,dilations:u,pad:c,dimRoundingMode:l,dataFormat:m}=t,d=S.convertConv2DDataFormat(m),f=S.computeConv2DInfo(n.shape,s.shape,p,u,c,l,!1,d),h=f.filterHeight,g=f.filterWidth,x=f.padInfo.top,b=f.padInfo.right,C=f.padInfo.bottom,w=f.padInfo.left,k=f.dilationHeight,_=f.dilationWidth,$=f.strideHeight,A=f.strideWidth,R=f.inChannels,D=f.outChannels,P=f.padInfo.type==="SAME"?1:0;if(f.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${f.dataFormat}'. 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g9(r){let{backend:e,inputs:t,attrs:o}=r,{dy:n,filter:s}=t,{strides:a,pad:i,dataFormat:p,dimRoundingMode:u,inputShape:c}=o,l=1,m=S.convertConv2DDataFormat(p),d=S.computeConv2DInfo(c,s.shape,a,l,i,u,!1,m),{batchSize:f,filterHeight:h,filterWidth:g,inChannels:x,inHeight:b,inWidth:C,outChannels:w,outHeight:k,outWidth:_,strideHeight:$,strideWidth:A}=d,R=h-1-d.padInfo.top,D=g-1-d.padInfo.left,P=d.dataFormat==="channelsLast",M=y.computeStrides(d.inShape),L=y.computeStrides(n.shape),[W,V,U]=y.computeStrides(s.shape),q=M[0],H=P?M[1]:M[2],j=P?M[2]:1,X=P?1:M[1],Z=L[0],ee=P?L[1]:L[2],Y=P?L[2]:1,J=P?1:L[1],ie=e.makeOutput(d.inShape,"float32"),pe=e.dataIdMap.get(ie.dataId).id,he=e.dataIdMap.get(n.dataId).id,we=e.dataIdMap.get(s.dataId).id;return zD(he,we,f,h,g,b,C,x,k,_,w,$,A,R,D,W,V,U,q,H,j,X,Z,ee,Y,J,pe),ie}var WD={kernelName:Ho,backendName:"wasm",setupFunc:h9,kernelFunc:g9};var UD=Ve(qo);var GD=Ve(Ko);var Ww;(function(r){r[r.bilinear=0]="bilinear",r[r.nearest=1]="nearest"})(Ww||(Ww={}));var HD;function x9(r){HD=r.wasm.cwrap(Yo,null,["number","number","number","number","array","number","number","number","number","number"])}function y9(r){let{backend:e,inputs:t,attrs:o}=r,{method:n,extrapolationValue:s,cropSize:a}=o,{image:i,boxes:p,boxInd:u}=t,c=p.shape[0],[l,m]=a,d=[c,l,m,i.shape[3]],f=e.dataIdMap.get(i.dataId),h;i.dtype!=="float32"&&(h=ls({backend:e,inputs:{x:i},attrs:{dtype:"float32"}}),f=e.dataIdMap.get(h.dataId));let g=f.id,x=e.dataIdMap.get(p.dataId).id,b=e.dataIdMap.get(u.dataId).id,C=e.makeOutput(d,"float32"),w=e.dataIdMap.get(C.dataId).id,k=new Uint8Array(new Int32Array(i.shape).buffer);return HD(g,x,b,c,k,l,m,Ww[n],s,w),h!=null&&e.disposeData(h.dataId),C}var qD={kernelName:Yo,backendName:"wasm",setupFunc:x9,kernelFunc:y9};var KD;function b9(r){KD=r.wasm.cwrap(jo,null,["number","number","number","number","number","number"])}function C9(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,exclusive:a,reverse:i}=o,p=n.shape.length;y.assert(n.dtype==="float32"||n.dtype==="int32",()=>`cumprod does not support ${n.dtype} tensors in the WASM backend`);let u=S.getAxesPermutation([s],p),c=n;u!==null&&(c=uo({inputs:{x:n},attrs:{perm:u},backend:t}));let l=S.getInnerMostAxes(1,p)[0];S.assertAxesAreInnerMostDims("cumprod",[l],p);let m=t.makeOutput(c.shape,c.dtype),d=c.shape[l],f=t.dataIdMap.get(c.dataId).id,h=t.dataIdMap.get(m.dataId).id;KD(f,a?1:0,i?1:0,d,h,Fe[n.dtype]);let g=m;if(u!==null){let x=S.getUndoAxesPermutation(u);g=uo({inputs:{x:m},attrs:{perm:x},backend:t}),t.disposeData(c.dataId),t.disposeData(m.dataId)}return g}var jD={kernelName:jo,backendName:"wasm",setupFunc:b9,kernelFunc:C9};var XD;function S9(r){XD=r.wasm.cwrap(Xo,null,["number","number","number","number","number","number"])}function w9(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,exclusive:a,reverse:i}=o,p=n.shape.length;y.assert(n.dtype==="float32"||n.dtype==="int32",()=>`cumsum does not support ${n.dtype} tensors in the WASM backend`);let u=S.getAxesPermutation([s],p),c=n;u!==null&&(c=uo({inputs:{x:n},attrs:{perm:u},backend:t}));let l=S.getInnerMostAxes(1,p)[0];S.assertAxesAreInnerMostDims("cumsum",[l],p);let m=t.makeOutput(c.shape,c.dtype),d=c.shape[l],f=t.dataIdMap.get(c.dataId).id,h=t.dataIdMap.get(m.dataId).id;XD(f,a?1:0,i?1:0,d,h,Fe[n.dtype]);let g=m;if(u!==null){let x=S.getUndoAxesPermutation(u);g=uo({inputs:{x:m},attrs:{perm:x},backend:t}),t.disposeData(c.dataId),t.disposeData(m.dataId)}return g}var YD={kernelName:Xo,backendName:"wasm",setupFunc:S9,kernelFunc:w9};var QD;function I9(r){QD=r.wasm.cwrap(Qo,null,["number","number","number","array","number","array","array","number","number"])}function v9(r){let{backend:e,inputs:t,attrs:o}=r,{x:n}=t,{blockSize:s,dataFormat:a}=o,i=n.shape[0],p=a==="NHWC"?n.shape[1]:n.shape[2],u=a==="NHWC"?n.shape[2]:n.shape[3],c=a==="NHWC"?n.shape[3]:n.shape[1],l=p*s,m=u*s,d=c/(s*s),f=a==="NHWC"?[i,l,m,d]:[i,d,l,m],h=e.makeOutput(f,"float32"),x=e.dataIdMap.get(n.dataId).id,b=new Uint8Array(new Int32Array(y.computeStrides(n.shape)).buffer),C=new Uint8Array(new Int32Array(f).buffer),w=new Uint8Array(new Int32Array(y.computeStrides(f)).buffer),k=e.dataIdMap.get(h.dataId).id;return QD(x,s,a==="NHWC"?1:0,b,n.shape.length-1,C,w,f.length,k),h}var ZD={kernelName:Qo,backendName:"wasm",setupFunc:I9,kernelFunc:v9};var JD;function k9(r){JD=r.wasm.cwrap(Zo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function 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`),E3(e.shape),u,Pee(e.shape.length)];t.atomic||c.push(Mee(e.shape,e.dtype,t.isVec4));let l=r.map((f,h)=>Dee(f,e.shape,t.variableTypes?t.variableTypes[h]==="vec4<f32>":t.isVec4,t.dispatchLayout.x.length===e.shape.length)).join(`
`);c.push(l),c.push(t.getUserCode());let m=$3(t);return c.push(T3(m)),c.join(`
`)}function R3(r,e,t,o){let n=r.shaderKey;if(r.isFromPixels)return n;let s=t.map(c=>c.dtype).concat(o.dtype),a=t.map(c=>S.getBroadcastDims(c.shape,o.shape)),i=t.map(c=>y.arraysEqual(c.shape,o.shape)).join("_"),p=a.map(c=>c.join("_")).join(";"),u=F3(r)?"flatDispatch":"";return n+="_"+(r.workgroupSize?r.workgroupSize.join(","):"")+e.map(c=>c.length).join(",")+s.join(",")+r.variableNames.join(",")+p+i+u,n}var _3=`
  struct vec5 {x: i32, y: i32, z: i32, w: i32, u: i32};
  struct vec6 {x: i32, y: i32, z: i32, w: i32, u: i32, v: i32};

  // Checks whether coordinates lie within the bounds of the shape.
  fn coordsInBounds2D(coord : vec2<i32>, shape : vec2<i32>) -> bool {
    return all(coord >= vec2<i32>(0)) && all(coord < shape);
  }
  fn coordsInBounds3D(coord : vec3<i32>, shape : vec3<i32>) -> bool {
    return all(coord >= vec3<i32>(0)) && all(coord < shape);
  }
  fn coordsInBounds4D(coord : vec4<i32>, shape : vec4<i32>) -> bool {
    return all(coord >= vec4<i32>(0)) && all(coord < shape);
  }

  fn getIndexFromCoords1D(coord : i32, shape : i32) -> i32 {
    return coord;
  }
  fn getIndexFromCoords2D(coords : vec2<i32>, shape : vec2<i32>) -> i32 {
    return dot(coords, vec2<i32>(shape.y, 1));
  }
  fn getIndexFromCoords3D(coords : vec3<i32>, shape : vec3<i32>) -> i32 {
    return dot(coords, vec3<i32>(shape.y * shape.z, shape.z, 1));
  }
  fn getIndexFromCoords4D(coords : vec4<i32>, shape : vec4<i32>) -> i32 {
    return dot(coords, vec4<i32>(
        shape.y * shape.z * shape.w, shape.z * shape.w, shape.w, 1));
  }
  fn getIndexFromCoords5D(coords : vec5, shape : vec5) -> i32 {
    let shapeStrides: vec5 = vec5(shape.y * shape.z * shape.w * shape.u, shape.z * shape.w * shape.u, shape.w * shape.u, shape.u, 1);
    return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u;
  }
  fn getIndexFromCoords6D(coords : vec6, shape : vec6) -> i32 {
    let shapeStrides: vec6 = vec6(shape.y * shape.z * shape.w * shape.u * shape.v, shape.z * shape.w * shape.u * shape.v, shape.w * shape.u * shape.v, shape.u * shape.v, shape.v, 1);
    return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u + coords.v*shapeStrides.v;
  }

  fn idiv(a: i32, b: i32, sign: f32) -> i32 {
    var res: i32 = a / b;
    let modulo: i32 = a % b;
    if (sign < 0. && modulo != 0) {
      res = res - 1;
    }
    return res;
  }

  // NaN defination in IEEE 754-1985 is :
  //   - sign = either 0 or 1.
  //   - biased exponent = all 1 bits.
  //   - fraction = anything except all 0 bits (since all 0 bits represents infinity).
  // https://en.wikipedia.org/wiki/IEEE_754-1985#Representation_of_non-numbers
  fn isnan(val: f32) -> bool {
    let floatToUint: u32 = bitcast<u32>(val);
    return (floatToUint & 0x7fffffffu) > 0x7f800000u;
  }
  fn isnanVec4(val : vec4<f32>) -> vec4<bool> {
    return vec4<bool>(isnan(val[0]), isnan(val[1]), isnan(val[2]), isnan(val[3]));
  }
`,Aee=`
  fn isinf(val: f32) -> bool {
    return abs(val) == uniforms.INFINITY;
  }
`;function E3(r){let e=r.length;if(e<=1)return"fn getCoordsFromIndex(index : i32) -> i32 { return index; }";let t=y.computeStrides(r),o=Rt(e),n=[];for(let a=0;a<e;a++)n.push(`d${a}`);if(t.length===1)return`    fn getCoordsFromIndex(index : i32) -> vec2<i32> {
      let d0 = index / uniforms.outShapeStrides; let d1 = index - d0 * uniforms.outShapeStrides;
      return vec2<i32>(d0, d1);
    }`;let s;return s="var index2 = index;"+t.map((a,i)=>{let p=`let ${n[i]} = index2 / uniforms.outShapeStrides.${$o(i)}`,u=i===t.length-1?`let ${n[i+1]} = index2 - ${n[i]} * uniforms.outShapeStrides.${$o(i)}`:`index2 = index2 - ${n[i]} * uniforms.outShapeStrides.${$o(i)}`;return`${p}; ${u};`}).join(""),`
    fn getCoordsFromIndex(index : i32) -> ${o} {
      ${s}
      return ${o}(${n.join(",")});
    }
  `}function Ree(r,e){let t=r.name,o=r.shape.length,n=Rt(o),s="get"+t.charAt(0).toUpperCase()+t.slice(1),a=["d0","d1","d2","d3","d4","d5"].slice(0,o),i=a.map(c=>`${c} : i32`).join(", ");if(o<1)return e?`
        fn ${s}() -> vec4<f32> {
          return vec4<f32>(${t}[0]);
        }
      `:`
      fn ${s}() ->f32 {
        return f32(${t}[0]);
      }
    `;let p=`uniforms.${t.charAt(0).toLowerCase()+t.slice(1)}Shape`,u=`${o}D`;return o===0&&(u="1D"),e?`
      fn ${s}(${i}) -> vec4<f32> {
        return vec4<f32>(${t}[getIndexFromCoords${u}(${n}(${a.join(",")}),
          ${p}) / 4]);
      }
      `:`
    fn ${s}(${i}) -> f32 {
      return f32(${t}[getIndexFromCoords${u}(${n}(${a.join(",")}),
        ${p})]);
    }
   `}function Fee(r,e,t,o){let n=r.name,s=n.charAt(0).toUpperCase()+n.slice(1),a="get"+s+"ByOutput",i=r.shape.length,p=e.length,u=Rt(p);if(y.arraysEqual(r.shape,e)&&o)return t?`
      fn ${a}Index(globalIndex : i32) -> vec4<f32> {
        return vec4<f32>(${n}[globalIndex]);
      }

      fn ${a}Coords(coords : ${u}) -> vec4<f32> {
        return vec4<f32>(${n}[${p>1?"getOutputIndexFromCoords(coords)":"coords"} / 4]);
      }
      `:`
    fn ${a}Index(globalIndex : i32) -> f32 {
      return f32(${n}[globalIndex]);
    }

    fn ${a}Coords(coords : ${u}) -> f32 {
      return f32(${n}[${p>1?"getOutputIndexFromCoords(coords)":"coords"}]);
    }
    `;let c=S.getBroadcastDims(r.shape,e),l=p-i,m="";if(i===0)return t?`
    fn ${a}Index(globalIndex : i32) -> vec4<f32> {
      return get${s}();
    }

    fn ${a}Coords(coords : ${u}) -> vec4<f32> {
      return get${s}();
    }
  `:`
    fn ${a}Index(globalIndex : i32) -> f32{
      return get${s}();
    }

    fn ${a}Coords(coords : ${u}) -> f32{
      return get${s}();
    }
  `;p<2&&c.length>=1?m="coords = 0;":m=c.map(g=>`coords.${$o(g+l)} = 0;`).join(`
`);let d="";if(p<2&&i>0)d="coords";else if(p>1){let g=Rt(i),x=r.shape.map((b,C)=>`coords.${$o(C+l)}`).join(", ");d=`${g}(${x})`}else d="coords";let f=`uniforms.${n.charAt(0).toLowerCase()+n.slice(1)}Shape`,h=`${i}D`;return t?`
    fn ${a}Index(globalIndex : i32) -> vec4<f32> {
      var coords = getCoordsFromIndex(globalIndex);
      ${m}
      return ${n}[getIndexFromCoords${h}(${d}, ${f}) / 4];
    }

    fn ${a}Coords(coordsIn : ${u}) -> vec4<f32> {
      var coords = coordsIn;
      ${m}
      return ${n}[getIndexFromCoords${h}(${d}, ${f}) / 4];
    }
  `:`
  fn ${a}Index(globalIndex : i32) -> f32 {
    var coords = getCoordsFromIndex(globalIndex);
    ${m}
    return f32(${n}[getIndexFromCoords${h}(${d}, ${f})]);
  }

  fn ${a}Coords(coordsIn : ${u}) -> f32 {
    var coords = coordsIn;
    ${m}
    return f32(${n}[getIndexFromCoords${h}(${d}, ${f})]);
  }
`}function Dee(r,e,t,o){let n=Ree(r,t);return r.shape.length<=e.length&&(n+=Fee(r,e,t,o)),n}function Oee(r,e){let{x:t,y:o=[],z:n=[]}=e,s=r.length,a=t.length+o.length+n.length;if(a!==s)return"";if(t.length===s)return`fn getOutputCoords() -> ${Rt(s)}{
    let globalIndex = getGlobalIndex();
    return getCoordsFromIndex(globalIndex);
  }
  `;let i="",p=[t,o,n];for(let m=0;m<p.length;m++){let d=p[m];if(d.length!==0)if(d.length===1)i+=`let d${d[0]} = i32(globalId[${m}]);`;else{let f=N3(d,"uniforms.outShape");i+=`var index${m} = i32(globalId[${m}]);`;for(let h=0;h<f.length;h++)i+=`let d${d[h]} = index${m} / ${f[h]};`,h===f.length-1?i+=`let d${d[h+1]} = index${m} - d${d[h]} * ${f[h]};`:i+=`index${m} = index${m} - d${d[h]} * ${f[h]};`}}let u=[];for(let m=0;m<a;m++)u.push(`d${m}`);let c=Rt(a),l=`fn getOutputCoords() -> ${c} {
  ${i}
`;return u.length===0?l+=`return ${c}(0); }`:l+=`return ${c}(${u.join(",")}); }`,l}function Pee(r){let e="";switch(r){case 0:case 1:e+=`
        fn getOutputIndexFromCoords(coords : i32) -> i32 {
          return coords;
        }
        `;break;case 2:e+=`
        fn getOutputIndexFromCoords(coords : vec2<i32>) -> i32 {
          return dot(coords, vec2<i32>(uniforms.outShapeStrides, 1));
        }
        `;break;case 3:e+=`
        fn getOutputIndexFromCoords(coords : vec3<i32>) -> i32 {
          return dot(coords, vec3<i32>(uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, 1));
        }
        `;break;case 4:e+=`
        fn getOutputIndexFromCoords(coords : vec4<i32>) -> i32 {
          return dot(coords, vec4<i32>(
            uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, uniforms.outShapeStrides.z, 1));
        }
        `;break;case 5:e+=`
        fn getOutputIndexFromCoords(coords : vec5) -> i32 {
          return coords.x * uniforms.outShapeStrides.x +
              coords.y * uniforms.outShapeStrides.y +
              coords.z * uniforms.outShapeStrides.z +
              coords.w * uniforms.outShapeStrides.w +
              coords.u;
        }
        `;break;case 6:e+=`
        fn getOutputIndexFromCoords(coords : vec6) -> i32 {
          return coords.x * uniforms.outShapeStrides.x +
              coords.y * uniforms.outShapeStrides.y +
              coords.z * uniforms.outShapeStrides.z +
              coords.w * uniforms.outShapeStrides.w +
              coords.u * uniforms.outShapeStrides.u +
              coords.v;
        }
        `;break;default:y.assert(!1,()=>`Unsupported ${r}D shape`);break}return e}function F3(r){return r.dispatch[1]===1&&r.dispatch[2]===1}function wc(r,e){return r==="float32"?e?"vec4<f32>":"f32":r==="int32"||r==="bool"?e?"vec4<i32>":"i32":r}function Mee(r,e,t){let o=r.length,n=wc(e,t),s;if(t?s=`fn setOutputAtIndex(flatIndex : i32, value : vec4<f32>) {
      result[flatIndex] = ${n}(value);
    }
    fn setOutputAtIndexI32(flatIndex : i32, value : vec4<i32>) {
      result[flatIndex] = ${n}(value);
    }`:s=`fn setOutputAtIndex(flatIndex : i32, value : f32) {
      result[flatIndex] = ${n}(value);
    }
    fn setOutputAtIndexI32(flatIndex : i32, value : i32) {
      result[flatIndex] = ${n}(value);
    }`,o>=2){let a=["d0","d1","d2","d3","d4","d5"].slice(0,o),i=Rt(o);t?s+=`
      fn setOutputAtCoords(${a.map(p=>`${p} : i32`).join(", ")}, value : vec4<f32>) {
        let flatIndex = getOutputIndexFromCoords(${i}(${a.join(", ")}));
        setOutputAtIndex(flatIndex / 4, value);
      }
      fn setOutputAtCoordsI32(${a.map(p=>`${p} : i32`).join(", ")}, value : vec4<i32>) {
        let flatIndex = getOutputIndexFromCoords(${i}(${a.join(", ")}));
        setOutputAtIndexI32(flatIndex / 4, value);
      }
    `:s+=`
      fn setOutputAtCoords(${a.map(p=>`${p} : i32`).join(", ")}, value : f32) {
        let flatIndex = getOutputIndexFromCoords(${i}(${a.join(", ")}));
        setOutputAtIndex(flatIndex, value);
      }
      fn setOutputAtCoordsI32(${a.map(p=>`${p} : i32`).join(", ")}, value : i32) {
        let flatIndex = getOutputIndexFromCoords(${i}(${a.join(", ")}));
        setOutputAtIndexI32(flatIndex, value);
      }
    `}return s}function Lee(r){let e=/(\w+)\s*:\s*vec(5|6)/g;r=r.replace(e,o=>"@align(16) "+o);let t=/vec(5|6)\s*,\s*(\w+)/g;return r=r.replace(t,(o,n,s)=>`vec${n}, @align(16) ${s}`),r}function $3(r){return!(r.dispatchLayout.hasOwnProperty("y")&&r.dispatchLayout.y.length!==0||r.dispatchLayout.hasOwnProperty("z")&&r.dispatchLayout.z.length!==0)}var nI={};Ue(nI,{ArrayBufferToTypedArray:()=>oI,GPUBytesPerElement:()=>rI,MatMulProgramType:()=>Ao,computeDispatch:()=>re,computeWorkPerThreadForConv2d:()=>Ll,computeWorkgroupInfoForMatMul:()=>tI,computeWorkgroupSizeForConv2d:()=>Ml,flatDispatchLayout:()=>ue,isWebGPUSupported:()=>Bl,tilesFitEvenlyIntoShape:()=>Vee});var zu=r=>{let e=1;for(let t=0;t<r.length;t++)e*=r[t];return e};function Vee(r,e){if(r.length!==e.length)throw new Error(`Cannot compute whether rank ${r.length} tiles fit evenly into rank ${e.length} shape - ranks must match.`);return e.every((t,o)=>t%r[o]===0)}function re(r,e,t=[1,1,1],o=[1,1,1]){let[n,s,a]=[Math.ceil(zu(r.x.map(i=>e[i]))/(t[0]*o[0])),r.y?Math.ceil(zu(r.y.map(i=>e[i]))/(t[1]*o[1])):1,r.z?Math.ceil(zu(r.z.map(i=>e[i]))/(t[2]*o[2])):1];return[n,s,a]}function tI(r,e,t,o=!1){let n=[8,8,1],s=[4,4,1];return o||(r<=8&&(s[1]=1),e<=16&&t<=16&&(n[0]=4)),{workgroupSize:n,elementsPerThread:s}}function Ml(r,e,t=!1){if(t)return[8,8,1];let o=zu(r.x.map(s=>e[s])),n=zu(r.y.map(s=>e[s]));return o<=4?[4,16,1]:n<=4?[16,4,1]:[16,16,1]}function Ll(r,e,t=!1){if(t)return[4,4,1];let o=zu(r.x.map(s=>e[s])),n=zu(r.y.map(s=>e[s]));return o<=4?[1,2,1]:n<=4?[2,1,1]:[2,2,1]}function ue(r){return{x:r.map((e,t)=>t)}}function rI(r){if(r==="float32"||r==="int32"||r==="bool"||r==="string")return 4;if(r==="complex64")return 8;throw new Error(`Unknown dtype ${r}`)}function oI(r,e){if(e==="float32")return new Float32Array(r);if(e==="int32")return new Int32Array(r);if(e==="bool"||e==="string")return Uint8Array.from(new Int32Array(r));throw new Error(`Unknown dtype ${e}`)}function Bl(){return(typeof window!="undefined"||typeof WorkerGlobalScope!="undefined")&&!!navigator.gpu}var Ao;(function(r){r[r.MatMulReduceProgram=0]="MatMulReduceProgram",r[r.MatMulSplitKProgram=1]="MatMulSplitKProgram",r[r.MatMulSmallOutputSizeProgram=2]="MatMulSmallOutputSizeProgram",r[r.MatMulPackedProgram=3]="MatMulPackedProgram",r[r.MatMulMax=4]="MatMulMax"})(Ao||(Ao={}));var zee=O().getNumber("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD"),Wee=(r,e)=>{let t=r.limits.maxComputeWorkgroupsPerDimension,o=e.dispatchLayout,n=e.dispatch;if(n.every(a=>a<=t))return n;y.assert(n[0]>t&&o.y===void 0&&o.z===void 0,()=>"Dispatch size exceeds WebGPU limits in Y or Z dimension.");let s=Math.ceil(Math.sqrt(n[0]));return s>t?(s=Math.ceil(Math.cbrt(n[0])),y.assert(s<=t,()=>"Total dispatch size exceeds WebGPU maximum."),[s,s,s]):[s,s,1]},Ui=class extends Zr{constructor(e,t){if(super(),this.commandQueueOwnedIds=new WeakSet,this.dispatchNumberInEncoder=0,this.disposed=!1,this.downloadWaitMs=0,this.tensorDataPendingDisposal=[],this.stagingPendingDisposal=[],this.uniformPendingDisposal=[],this.uploadWaitMs=0,!Bl())throw new Error("WebGPU is not supported on this device");this.pipelineCache={},this.device=e,this.queue=e.queue,this.currentCommandEncoder=null,this.currentComputePass=null,this.supportTimeQuery=e.features.has("timestamp-query-inside-passes"),this.adapterInfo=new kg(t),this.thresholdToIncreaseWorkgroups=this.adapterInfo.intelGPUGeneration>=12?16:8,this.bufferManager=new Ng(this.device),this.textureManager=new Tg(this.device),this.tensorMap=new Do(this,cr()),this.supportTimeQuery&&(this.querySet=this.device.createQuerySet({type:"timestamp",count:2})),O().getBool("WEBGPU_USE_PROFILE_TOOL")&&(this.dummyCanvas=document.createElement("canvas"),this.dummyCanvas.width=1,this.dummyCanvas.height=1,this.dummyContext=this.dummyCanvas.getContext("webgpu"),this.dummyContext.configure({device:e,format:"bgra8unorm"}),document.body.appendChild(this.dummyCanvas))}nextDataId(){return Ui.nextDataId++}floatPrecision(){return 32}defaultGpuBufferUsage(){return GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST}disposeData(e,t=!1){if(this.tensorDataPendingDisposal.indexOf(e)>=0)return!1;if(!this.tensorMap.has(e))return!0;let o=this.tensorMap.get(e);if(this.decRef(e),!t&&o.refCount>0)return!1;if(this.commandQueueOwnedIds.has(e))return this.tensorDataPendingDisposal.push(e),!1;let{complexTensorInfos:n}=this.tensorMap.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.releaseResource(e),this.tensorMap.delete(e),!0}memory(){return{numBytesInGPU:this.bufferManager.numBytesUsed,numBytesAllocatedInGPU:this.bufferManager.numBytesAllocated,unreliable:!1}}releaseResource(e){let t=this.tensorMap.get(e);if(!(!t||!t.resourceInfo)){if("texture"in t.resourceInfo){let o=t.resourceInfo;o.texture instanceof GPUTexture&&this.textureManager.releaseTexture(o.texture,o.width,o.height,o.format,o.usage),o.texture=null}else{let o=t.resourceInfo;this.bufferManager.releaseBuffer(o.buffer,o.size,o.usage),o.buffer=null}t.resourceInfo=null}}refCount(e){return this.tensorMap.has(e)?this.tensorMap.get(e).refCount:0}incRef(e){let t=this.tensorMap.get(e);t.refCount++}decRef(e){if(this.tensorMap.has(e)){let t=this.tensorMap.get(e);t.refCount--}}write(e,t,o){if(o==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let n={id:this.nextDataId()};return this.tensorMap.set(n,{dtype:o,shape:t,values:e,refCount:1}),n}move(e,t,o,n,s){if(n==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.tensorMap.set(e,{dtype:n,shape:o,values:t,refCount:s})}submitQueue(){this.ensureComputePassEnded(),this.queue.submit([this.currentCommandEncoder.finish()]),this.currentCommandEncoder=null,this.dispatchNumberInEncoder=0,this.commandQueueOwnedIds=new WeakSet,this.tensorDataPendingDisposal.forEach(e=>{this.releaseResource(e),this.tensorMap.delete(e)}),this.uniformPendingDisposal.forEach(e=>this.bufferManager.releaseBuffer(e.buffer,e.size,e.usage)),this.stagingPendingDisposal.forEach(e=>this.bufferManager.releaseUploadBuffer(e.buffer,e.size,e.usage)),this.tensorDataPendingDisposal=[],this.uniformPendingDisposal=[],this.stagingPendingDisposal=[]}ensureCommandEncoderReady(){this.currentCommandEncoder||(this.currentCommandEncoder=this.device.createCommandEncoder())}ensureComputePassEnded(){this.currentComputePass&&(this.currentComputePass.end(),this.currentComputePass=null)}getComputePass(){return this.currentComputePass||(this.currentComputePass=this.currentCommandEncoder.beginComputePass()),this.currentComputePass}async getBufferData(e,t){let o=this.bufferManager.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(e,0,o,0,t),this.submitQueue(),await o.mapAsync(GPUMapMode.READ);let n=o.getMappedRange().slice(0);return o.unmap(),o!=null&&this.bufferManager.releaseBuffer(o,t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ),O().getBool("WEBGPU_USE_PROFILE_TOOL")&&(y.assert(this.dummyContext!==void 0,()=>"Fail to get context for profiling tool"),this.dummyContext.getCurrentTexture()),n}convertAndCacheOnCPU(e,t){let o=this.tensorMap.get(e);return this.releaseResource(e),o.values=t,o.values}readSync(e){let t=this.tensorMap.get(e),{values:o}=t;if(o==null)throw new Error("WebGPU readSync is only available for CPU-resident tensors.");return o}async read(e){if(!this.tensorMap.has(e))throw new Error(`Tensor ${e} was not registered!`);let t=this.tensorMap.get(e),{values:o}=t;if(o!=null)return this.convertAndCacheOnCPU(e,o);let n;if(t.dtype==="complex64"){let s=await Promise.all([this.read(t.complexTensorInfos.real.dataId),this.read(t.complexTensorInfos.imag.dataId)]),a=s[0],i=s[1];n=S.mergeRealAndImagArrays(a,i)}else{let s=t.resourceInfo,a=await this.getBufferData(s.buffer,s.size);n=oI(a,t.dtype)}return this.convertAndCacheOnCPU(e,n),n}readToGPU(e){let t=this.tensorMap.get(e),{values:o,dtype:n,shape:s,resourceInfo:a}=t;if(n==="complex64")throw new Error("Does not support reading buffer for complex64 dtype.");if(a==null)throw o!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let i=a.size,p=this.bufferManager.acquireBuffer(i,a.usage);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(a.buffer,0,p,0,i),this.submitQueue();let u=this.makeTensorInfo(s,n),c=cr().makeTensorFromTensorInfo(u),l=this.tensorMap.get(u.dataId);return l.resourceInfo={size:i,usage:this.defaultGpuBufferUsage(),buffer:p},{tensorRef:c,buffer:p,bufSize:i}}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let o=t.map(n=>y.decodeString(n));return le(e.shape,e.dtype,o)}catch(o){throw new Error("Failed to decode encoded string bytes into utf-8")}return le(e.shape,e.dtype,t)}async time(e){this.supportTimeQuery||console.warn("This device doesn't support timestamp-query-inside-passes extension. Start Chrome browser with flag --disable-dawn-features=disallow_unsafe_apis then try again. Otherwise, zero will be shown for the kernel time when profiling mode is enabled. Using performance.now is not workable for webgpu since it doesn't support synchronous data read from GPU.");let t=this.activeTimers,o=[],n=!1;this.programTimersStack==null?(this.programTimersStack=o,n=!0):this.activeTimers.push(o),this.activeTimers=o,e();let s=y.flatten(this.activeTimers.map(u=>u.query)).filter(u=>u!=null),a=y.flatten(this.activeTimers.map(u=>u.name)).filter(u=>u!=null);this.activeTimers=t,n&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},p=await Promise.all(s);return i.kernelMs=y.sum(p),i.getExtraProfileInfo=()=>p.map((u,c)=>({name:a[c],ms:u})).map(u=>`${u.name}: ${u.ms}`).join(", "),this.uploadWaitMs=0,this.downloadWaitMs=0,i}makeTensorInfo(e,t,o){return t==="string"&&o!=null&&o.length>0&&y.isString(o[0])&&(o=o.map(s=>y.encodeString(s))),{dataId:this.write(o,e,t),shape:e,dtype:t}}tensorToBinding(e){if(!e)return null;let t=this.tensorMap.get(e.dataId);if("texture"in t.resourceInfo){let n=t.resourceInfo;return n.texture instanceof GPUExternalTexture?n.texture:n.texture.createView()}let o=t.resourceInfo;return{offset:0,size:o.size,buffer:o.buffer}}async getQueryTime(e){return this.supportTimeQuery?this.getTimeFromQuerySet(e):0}uploadToGPU(e){let t=this.tensorMap.get(e);if(t.resourceInfo)return;let o=rI(t.dtype)*y.sizeFromShape(t.shape),n=this.bufferManager.acquireBuffer(o,this.defaultGpuBufferUsage());if(t.resourceInfo={size:o,usage:this.defaultGpuBufferUsage(),buffer:n},t.values){let s=this.bufferManager.acquireUploadBuffer(o,GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC),a=s.getMappedRange();t.dtype==="int32"||t.dtype==="bool"?new Int32Array(a).set(t.values):new Float32Array(a).set(t.values),s.unmap(),this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(s,0,n,0,o);let i={size:o,usage:GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC,buffer:s};this.stagingPendingDisposal.push(i)}}makeUniforms(e){let t=0,o=0,n=[];e.forEach(p=>{p.data.length===0&&(p.data=[1]);let u;switch(p.data.length){case 1:u=4;break;case 2:u=8;break;case 3:u=16;break;case 4:u=16;break;case 5:u=16;break;case 6:u=16;break;default:y.assert(!1,()=>`Unsupported ${p.data.length}D shape`)}(o===5||o===6)&&(u=16),t=Math.ceil(t/u)*u,o=p.data.length,n.push(t),t+=p.data.length*4});let s=new ArrayBuffer(t);e.forEach((p,u)=>{let c=n[u];p.type==="int32"?new Int32Array(s,c,p.data.length).set(p.data):p.type==="uint32"?new Uint32Array(s,c,p.data.length).set(p.data):new Float32Array(s,c,p.data.length).set(p.data)});let a=this.bufferManager.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM);this.queue.writeBuffer(a,0,s,0,t);let i={size:t,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM,buffer:a};return this.uniformPendingDisposal.push(i),{offset:0,size:t,buffer:a}}runWebGPUProgram(e,t,o,n,s){if(s||(s=this.makeTensorInfo(e.outputShape,o)),y.sizeFromShape(s.shape)===0)return this.tensorMap.get(s.dataId).values=y.getTypedArrayFromDType(s.dtype,0),s;this.uploadToGPU(s.dataId),e.dispatch=Wee(this.device,e);let a=[],i=[];if(!e.isFromPixels){a.push({type:"float32",data:[NaN]},{type:"float32",data:[1/0]}),i=t.concat(s).map(x=>x.shape);let h="int32";i.map(x=>{a.push({type:h,data:x})});let g=y.computeStrides(s.shape);if(a.push({type:h,data:g}),e.size){let x=y.sizeFromShape(e.outputShape);a.push({type:h,data:[e.isVec4?x/4:x]})}}let p=t.map((h,g)=>{if(h.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");return this.uploadToGPU(h.dataId),{dtype:this.tensorMap.get(h.dataId).dtype,shape:h.shape,name:e.variableNames[g]}}),u=R3(e,i,p,s),c;u in this.pipelineCache?c=this.pipelineCache[u]:(c=A3(this.device,e,p,s),this.pipelineCache[u]=c),n&&(a=[...a,...n]);let l=[this.tensorToBinding(s),...t.map(h=>this.tensorToBinding(h)),this.makeUniforms(a)],m=this.device.createBindGroup({layout:c.getBindGroupLayout(0),entries:l.map((h,g)=>({binding:g,resource:h}))});this.ensureCommandEncoderReady();let d=this.getComputePass(),f=this.activeTimers!=null;return f&&this.supportTimeQuery&&d.writeTimestamp(this.querySet,0),d.setPipeline(c),d.setBindGroup(0,m),d.dispatchWorkgroups(e.dispatch[0],e.dispatch[1],e.dispatch[2]),f&&this.supportTimeQuery&&d.writeTimestamp(this.querySet,1),this.dispatchNumberInEncoder++,t.forEach(h=>{this.commandQueueOwnedIds.add(h.dataId)}),this.commandQueueOwnedIds.add(s.dataId),O().get("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE")<=this.dispatchNumberInEncoder&&this.submitQueue(),f&&this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(this.querySet)}),s}async getTimeFromQuerySet(e){let t=this.bufferManager.acquireBuffer(16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),o=this.bufferManager.acquireBuffer(16,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.resolveQuerySet(e,0,2,t,0),this.currentCommandEncoder.copyBufferToBuffer(t,0,o,0,16),this.submitQueue(),await o.mapAsync(GPUMapMode.READ);let n=new BigUint64Array(o.getMappedRange()),s=Number(n[1]-n[0]);return o.unmap(),this.bufferManager.releaseBuffer(o,16,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST),this.bufferManager.releaseBuffer(t,16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),s/1e6}shouldExecuteOnCPU(e,t=zee){return O().getBool("WEBGPU_CPU_FORWARD")&&e.every(o=>this.tensorMap.get(o.dataId).resourceInfo==null&&y.sizeFromShape(o.shape)<t)}numDataIds(){return this.tensorMap.numDataIds()-this.tensorDataPendingDisposal.length}dispose(){this.disposed||(this.bufferManager.dispose(),this.textureManager.dispose(),this.disposed=!0)}};Ui.nextDataId=0;Bl()&&Ci("webgpu",async()=>{O().set("CHECK_COMPUTATION_FOR_ERRORS",!1);let r={powerPreference:O().get("WEBGPU_USE_LOW_POWER_GPU")?"low-power":"high-performance"},e=await navigator.gpu.requestAdapter(r),t={};e.features.has("timestamp-query-inside-passes")&&(t.requiredFeatures=["timestamp-query-inside-passes"]);let o=e.limits;t.requiredLimits={maxComputeWorkgroupStorageSize:o.maxComputeWorkgroupStorageSize,maxComputeWorkgroupsPerDimension:o.maxComputeWorkgroupsPerDimension,maxStorageBufferBindingSize:o.maxStorageBufferBindingSize};let n=await e.requestDevice(t),s=await e.requestAdapterInfo();return new Ui(n,s)},3);var ye;(function(r){r[r.ADD=0]="ADD",r[r.ATAN2=1]="ATAN2",r[r.COMPLEX_MULTIPLY_IMAG=2]="COMPLEX_MULTIPLY_IMAG",r[r.COMPLEX_MULTIPLY_REAL=3]="COMPLEX_MULTIPLY_REAL",r[r.DIV=4]="DIV",r[r.EQUAL=5]="EQUAL",r[r.GREATER=6]="GREATER",r[r.GREATER_EQUAL=7]="GREATER_EQUAL",r[r.INT_DIV=8]="INT_DIV",r[r.LESS=9]="LESS",r[r.LESS_EQUAL=10]="LESS_EQUAL",r[r.LOGICAL_AND=11]="LOGICAL_AND",r[r.MAX=12]="MAX",r[r.MIN=13]="MIN",r[r.MOD=14]="MOD",r[r.MUL=15]="MUL",r[r.NOT_EQUAL=16]="NOT_EQUAL",r[r.POW=17]="POW",r[r.PRELU=18]="PRELU",r[r.SQUARED_DIFFERENCE=19]="SQUARED_DIFFERENCE",r[r.SUB=20]="SUB"})(ye||(ye={}));var D3=`
  if (isnan(a)) { return a; }
  if (isnan(b)) { return b; }
  `,O3=`
  if (isNaN.r) {
    resultTemp.r = valueForNaN;
  }
  if (isNaN.g) {
    resultTemp.g = valueForNaN;
  }
  if (isNaN.b) {
    resultTemp.b = valueForNaN;
  }
  if (isNaN.a) {
    resultTemp.a = valueForNaN;
  }
  `,aI=`
  let isNaN = isnanVec4(a) | isnanVec4(b);
  ${O3}
  `,Uee="return a + b;",Gee="return areal * breal - aimag * bimag;",Hee="return areal * bimag + aimag * breal;",qee="return a / b;",Kee="return f32(a == b);",jee="return vec4<f32>(a == b);",Xee="return f32(a > b);",Yee="return vec4<f32>(a > b);",Qee="return f32(a >= b);",Zee="return vec4<f32>(a >= b);",Jee=`
  let s = sign(a) * sign(b);
  let ia = i32(round(a));
  let ib = i32(round(b));
  return f32(idiv(ia, ib, s));
`,ete=`
  let ia = vec4<i32>(round(a));
  let ib = vec4<i32>(round(b));
  let cond = ib != vec4<i32>(0);
  var resultTemp = vec4<i32>(0);
  let s = sign(a) * sign(b);

  // Windows (D3D) wants guaranteed non-zero int division at compile-time.
  if (cond[0]) {
    resultTemp[0] = idiv(ia[0], ib[0], s[0]);
  }
  if (cond[1]) {
    resultTemp[1] = idiv(ia[1], ib[1], s[1]);
  }
  if (cond[2]) {
    resultTemp[2] = idiv(ia[2], ib[2], s[2]);
  }
  if (cond[3]) {
    resultTemp[3] = idiv(ia[3], ib[3], s[3]);
  }
  return vec4<f32>(resultTemp);
`,tte="return f32(a < b);",rte="return vec4<f32>(a < b);",ote="return f32(a <= b);",nte="return vec4<f32>(a <= b);",ste="return f32(f32(a) >= 1.0 && f32(b) >= 1.0);",ate=`return (vec4<f32>(a >= vec4<f32>(1.0)) *
  vec4<f32>(b >= vec4<f32>(1.0)));`,ite=`
  ${D3}
  if (b == 0.) {
    return uniforms.NAN;
  }
  var resultTemp = a % b;
  if ((a < 0. && b < 0.) || (a >= 0. && b > 0.)) {
    return resultTemp;
  } else {
    return (resultTemp + b) % b;
  }
`,ute=`
  let valueForNaN = uniforms.NAN;
  var resultTemp = vec4<f32>(a % b);
  ${aI}

  if (b[0] == 0.) {
    resultTemp[0] = uniforms.NAN;
  }
  if (b[1] == 0.) {
    resultTemp[1] = uniforms.NAN;
  }
  if (b[2] == 0.) {
    resultTemp[2] = uniforms.NAN;
  }
  if (b[3] == 0.) {
    resultTemp[3] = uniforms.NAN;
  }

  if (!((a[0] < 0. && b[0] < 0.) || (a[0] >= 0. && b[0] > 0.))) {
    resultTemp[0] = (resultTemp[0] + b[0]) % b[0];
  }
  if (!((a[1] < 0. && b[1] < 0.) || (a[1] >= 0. && b[1] > 0.))) {
    resultTemp[1] = (resultTemp[1] + b[1]) % b[1];
  }
  if (!((a[2] < 0. && b[2] < 0.) || (a[2] >= 0. && b[2] > 0.))) {
    resultTemp[2] = (resultTemp[2] + b[2]) % b[2];
  }
  if (!((a[3] < 0. && b[3] < 0.) || (a[3] >= 0. && b[3] > 0.))) {
    resultTemp[3] = (resultTemp[3] + b[3]) % b[3];
  }

  return resultTemp;
`,pte="return a * b;",cte=`
  if (isnan(a) || isnan(b)) {
    return 1.0;
  }
  return f32(a != b);
`,lte=`
  var resultTemp = vec4<f32>(a != b);
  let valueForNaN = 1.0;
  ${aI}

  return resultTemp;
`,mte=`
  if(a < 0.0 && floor(b) < b) {
    return uniforms.NAN;
  }
  if (b == 0.0) {
    return 1.0;
  }
  if (round(abs(b) % 2.0) != 1.0) {
    return pow(abs(a), b);
  }
  return sign(a) * pow(abs(a), b);
`,dte=`
  let isModRound1Bool = vec4<i32>(round(abs(b) % vec4<f32>(2.0))) == vec4<i32>(1);
  let isModRound1 = vec4<f32>(isModRound1Bool);
  let multiplier = sign(a) * isModRound1 + (vec4<f32>(1.0) - isModRound1);
  var resultTemp = multiplier * pow(abs(a), b);

  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS
  let isExpZero = b == vec4<f32>(0.0);
  if (isExpZero.r) {
    resultTemp.r = 1.0;
  }
  if (isExpZero.g) {
    resultTemp.g = 1.0;
  }
  if (isExpZero.b) {
    resultTemp.b = 1.0;
  }
  if (isExpZero.a) {
    resultTemp.a = 1.0;
  }
  let isNaN = (a < vec4<f32>(0.0)) & (floor(b) < b);
  let valueForNaN = uniforms.NAN;
  ${O3}
  return resultTemp;
`,fte="if (a < 0.0) { return b * a; }  return a;",hte=`
  let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
  return (aLessThanZero * (b * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
`,gte="return (a - b) * (a - b);",xte="return a - b;";function sI(r,e,t="uniforms.NAN"){let o=e?aI:D3;return e?`
    let valueForNaN = ${t};
    var resultTemp = vec4<f32>(${r}(a, b));
    `+o+`
    return resultTemp;
  `:o+`
    return ${r}(a, b);
  `}function Ic(r,e){switch(r){case ye.ADD:return Uee;case ye.ATAN2:return sI("atan2",e);case ye.COMPLEX_MULTIPLY_IMAG:return Hee;case ye.COMPLEX_MULTIPLY_REAL:return Gee;case ye.DIV:return qee;case ye.EQUAL:return e?jee:Kee;case ye.GREATER:return e?Yee:Xee;case ye.GREATER_EQUAL:return e?Zee:Qee;case ye.INT_DIV:return e?ete:Jee;case ye.LESS:return e?rte:tte;case ye.LESS_EQUAL:return e?nte:ote;case ye.LOGICAL_AND:return e?ate:ste;case ye.MAX:return sI("max",e);case ye.MIN:return sI("min",e);case ye.MOD:return e?ute:ite;case ye.MUL:return pte;case ye.NOT_EQUAL:return e?lte:cte;case ye.POW:return e?dte:mte;case ye.PRELU:return e?hte:fte;case ye.SQUARED_DIFFERENCE:return gte;case ye.SUB:return xte;default:throw new Error(`BinaryType ${r} is not implemented!`)}}var Q;(function(r){r[r.ABS=0]="ABS",r[r.ACOS=1]="ACOS",r[r.ACOSH=2]="ACOSH",r[r.ASIN=3]="ASIN",r[r.ASINH=4]="ASINH",r[r.ATAN=5]="ATAN",r[r.ATANH=6]="ATANH",r[r.CEIL=7]="CEIL",r[r.COS=8]="COS",r[r.COSH=9]="COSH",r[r.ELU=10]="ELU",r[r.ERF=11]="ERF",r[r.EXP=12]="EXP",r[r.EXPM1=13]="EXPM1",r[r.FLOOR=14]="FLOOR",r[r.IS_FINITE=15]="IS_FINITE",r[r.IS_INF=16]="IS_INF",r[r.IS_NAN=17]="IS_NAN",r[r.LINEAR=18]="LINEAR",r[r.LOG=19]="LOG",r[r.LOG1P=20]="LOG1P",r[r.LOGICAL_NOT=21]="LOGICAL_NOT",r[r.NEG=22]="NEG",r[r.RELU=23]="RELU",r[r.RELU6=24]="RELU6",r[r.LEAKYRELU=25]="LEAKYRELU",r[r.RECIPROCAL=26]="RECIPROCAL",r[r.RSQRT=27]="RSQRT",r[r.SIN=28]="SIN",r[r.SINH=29]="SINH",r[r.SIGMOID=30]="SIGMOID",r[r.SQRT=31]="SQRT",r[r.SQUARE=32]="SQUARE",r[r.TAN=33]="TAN",r[r.TANH=34]="TANH",r[r.TO_INT=35]="TO_INT"})(Q||(Q={}));var yte="return abs(a);",bte=`
  if (abs(a) > 1.) {
    return uniforms.NAN;
  }
  return acos(a);
`,Cte=`
  if (a < 1.) {
    return uniforms.NAN;
  }
  return acosh(a);
`,Ste=`
  if (abs(a) > 1.) {
    return uniforms.NAN;
  }
  return asin(a);
`,wte="return asinh(a);",Ite=`
  if (isnan(a)) {
    return uniforms.NAN;
  }
  return atan(a);
`,vte=`
  if (abs(a) > 1.) {
    return uniforms.NAN;
  }
  if (a == 1.) {
    return uniforms.INFINITY;
  }
  if (a == -1.) {
    return -uniforms.INFINITY;
  }
  return atanh(a);
`,kte="return ceil(a);",Nte="return cos(a);",Tte=`
  let e2x = exp(-a);
  return (e2x + 1.0 / e2x) / 2.0;
`,_te="return exp(a) - 1.0;",Ete="if (a >= 0.0) { return a; }  return (exp(a) - 1.0);",$te=`
  var resFloat = exp(a) - vec4<f32>(1.0);
  if (a.r >= 0.0) {
    resFloat.r = a.r;
  }
  if (a.g >= 0.0) {
    resFloat.g = a.g;
  }
  if (a.b >= 0.0) {
    resFloat.b = a.b;
  }
  if (a.a >= 0.0) {
    resFloat.a = a.a;
  }
  return resFloat;
`,Ate=`
  // Error function is calculated approximately with elementary function.
  // See "Handbook of Mathematical Functions with Formulas,
  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
  let p = ${S.ERF_P};
  let a1 = ${S.ERF_A1};
  let a2 = ${S.ERF_A2};
  let a3 = ${S.ERF_A3};
  let a4 = ${S.ERF_A4};
  let a5 = ${S.ERF_A5};

  let sign = sign(a);
  let absA = abs(a);
  let t = 1.0 / (1.0 + p * absA);
  return sign * (1.0 - (((((a5 * t + a4) * t) + a3) * t + a2) * t + a1) * t * exp(-absA * absA));
`,Rte="return exp(a);",Fte="return floor(a);",Dte="return f32(!isnan(a) && !isinf(a));",Ote="return f32(isinf(a));",Pte="return f32(isnan(a));",Mte="return a;",Lte=`if (a < 0.0) { return uniforms.NAN; }
  return log(a);`,Bte=`
  if (isnan(a)) { return a; }
  return log(1.0 + a);
`,Vte="return f32(!(a >= 1.0));",zte="return -a;",Wte="if (a < 0.0) { return uniforms.alpha * a; } return a;",Ute=`
  let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
  return (aLessThanZero * (uniforms.alpha * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
`,Gte="return 1.0 / a;",Hte="return select(a, 0.0, a < 0.0);",qte="return clamp(a, 0.0, 6.0);",Kte="return clamp(a, vec4<f32>(0.0, 0.0, 0.0, 0.0), vec4<f32>(6.0, 6.0, 6.0, 6.0));",jte=`
  return select(a, vec4<f32>(0.0), a < vec4<f32>(0.0));
`,Xte="return inverseSqrt(a);",Yte="return 1.0 / (1.0 + exp(-1.0 * a));",Qte="return sin(a);",Zte=`
  let e2x = exp(a);
  return (e2x - 1.0 / e2x) / 2.0;
`,Jte="return sqrt(a);",ere="return a * a;",tre="return tan(a);",rre=`
  let e2x = exp(-2.0 * abs(a));
  return sign(a) * (1.0 - e2x) / (1.0 + e2x);
`,ore="return f32(i32((a)));";function Ha(r,e){switch(r){case Q.ABS:return yte;case Q.ACOS:return bte;case Q.ACOSH:return Cte;case Q.ASIN:return Ste;case Q.ASINH:return wte;case Q.ATAN:return Ite;case Q.ATANH:return vte;case Q.COS:return Nte;case Q.COSH:return Tte;case Q.CEIL:return kte;case Q.ELU:return e?$te:Ete;case Q.ERF:return Ate;case Q.EXP:return Rte;case Q.EXPM1:return _te;case Q.FLOOR:return Fte;case Q.IS_FINITE:return Dte;case Q.IS_INF:return Ote;case Q.IS_NAN:return Pte;case Q.LINEAR:return Mte;case Q.LOG:return Lte;case Q.LOG1P:return Bte;case Q.LOGICAL_NOT:return Vte;case Q.NEG:return zte;case Q.LEAKYRELU:return e?Ute:Wte;case Q.RECIPROCAL:return Gte;case Q.RELU:return e?jte:Hte;case Q.RELU6:return e?Kte:qte;case Q.RSQRT:return Xte;case Q.SIGMOID:return Yte;case Q.SIN:return Qte;case Q.SINH:return Zte;case Q.SQRT:return Jte;case Q.SQUARE:return ere;case Q.TAN:return tre;case Q.TANH:return rre;case Q.TO_INT:return ore;default:throw new Error(`BinaryType ${r} is not implemented!`)}}var kt=r=>{switch(r){case 1:return"f32";case 2:return"vec2<f32>";case 3:return"vec3<f32>";case 4:return"vec4<f32>";default:throw new Error(`${r}-component is not supported.`)}};function ur(r,e=!1,t=!1,o=3){if(r===null)return"";let n="";if(r==="linear")n=Ha(Q.LINEAR);else if(r==="relu")n=Ha(Q.RELU,t);else if(r==="elu")n=Ha(Q.ELU,t);else if(r==="relu6")n=Ha(Q.RELU6,t);else if(r==="prelu")n=Ic(ye.PRELU,t);else if(r==="sigmoid")n=Ha(Q.SIGMOID,t);else if(r==="leakyrelu")n=Ha(Q.LEAKYRELU,t);else throw new Error(`Activation ${r} has not been implemented for the WebGPU backend.`);let a=kt(t?4:1),i="";return e?i=`
      fn activation(a : ${a}, coords : vec${o}<i32>) -> ${a} {
        let b = getPreluActivationWeightsByOutputCoords(coords);
        ${n}
      }`:i=`
      fn activation(a : ${a}, coords : vec${o}<i32>) -> ${a} {
        ${n}
      }`,i}function Hr(r,e){return`
      ${r?"value = value + getBiasByOutputCoords(coords);":""}
      ${e?"value = activation(value, coords);":""}
      `}function iI(r,e,t,o,n=!1,s=!1,a=!1,i=1){y.assert(t&&i===1||!t,()=>`transposeA ${t} is not compatible with component size ${i}`);let p=`
      let batch = ${r?"0":"batchIn"};
      ${t?"value = getA(batch, col, row);":"value = getA(batch, row, col);"}

    `,u=o?"value = getB(batch, col, row);":"value = getB(batch, row, col);";return`
  fn mm_readA(batchIn: i32, row: i32, colIn: i32) -> ${kt(i)} {
    var value = ${kt(i)}(0.0);
    let col = colIn * ${i};
    ${n&&a?p:`
    ${t?"if(row < uniforms.dimAOuter && col < uniforms.dimInner)":"if(row < uniforms.aShape[1] && col < uniforms.aShape[2])"}
    {
      ${p}
    }
    `}
    return value;
  }

  fn mm_readB(batchIn: i32, row: i32, colIn: i32) -> ${kt(i)} {
    let col = colIn * ${i};
    let batch = ${e?"0":"batchIn"};
    var value = ${kt(i)}(0.0);
    ${u}
    return value;
  }
  `}function Vl(r,e,t,o,n,s,a=!1,i=!1,p=!1,u=1){return`
  ${iI(t,o,n,s,a,i,p,u)}
  fn mm_write(batch: i32, row: i32, colIn: i32, valueIn: ${kt(u)}) {
    let col = colIn * ${u};
    ${a&&i?"":"if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)"}
    {
      var value = valueIn;
      let coords = vec3<i32>(batch, row, col);
      ${Hr(r,e)}
      setOutputAtCoords(coords[0], coords[1], coords[2], value);
    }
  }
  `}var nre=r=>r?`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          kStart + inputRow,
          globalRowStart / innerElementSize + inputCol);
        `:`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          globalRow + innerRow,
          kStart / innerElementSize + inputCol);
        `,sre=(r,e)=>r?`
        let ACached0 = mm_Asub[k * innerElementSize][localRow];
        let ACached1 = mm_Asub[k * innerElementSize + 1][localRow];
        let ACached2 = mm_Asub[k * innerElementSize + 2][localRow];
        ${e===3?"":"let ACached3 = mm_Asub[k * innerElementSize + 3][localRow];"}
        for (var i = 0; i < rowPerThread; i = i + 1) {
          acc[i] = BCached0 * ACached0[i] + acc[i];
          acc[i] = BCached1 * ACached1[i] + acc[i];
          acc[i] = BCached2 * ACached2[i] + acc[i];
          ${e===3?"":"acc[i] = BCached3 * ACached3[i] + acc[i];"}
        }`:`
        for (var i = 0; i < rowPerThread; i = i + 1) {
          let ACached = mm_Asub[tileRow + i][k];
          acc[i] = BCached0 * ACached.x + acc[i];
          acc[i] = BCached1 * ACached.y + acc[i];
          acc[i] = BCached2 * ACached.z + acc[i];
          ${e===3?"":"acc[i] = BCached3 * ACached.w + acc[i];"}
        }`;function Wu(r,e,t=!1,o=32,n=!1,s=32,a=!1){let i=e[1]*r[1],p=e[0]*r[0],u=t?i:o,c=t?o:i,l=u/e[0],m=o/e[1];return y.assert((t&&l===4&&r[1]===4||!t&&(l===3||l===4))&&u%e[0]===0&&o%e[1]===0&&r[0]===4,()=>`If transposeA ${t} is true, innerElementSize ${l} and workPerThread[1] ${r[1]} must be 4.
          Otherwise, innerElementSize ${l} must be 3 or 4.
      tileAWidth ${u} must be divisible by workgroupSize[0]${e[0]}. tileInner ${o} must be divisible by workgroupSize[1] ${e[1]}. colPerThread ${r[0]} must be 4.`),`
  var<workgroup> mm_Asub : array<array<vec${l}<f32>, ${u/l}>, ${c}>;
  var<workgroup> mm_Bsub : array<array<vec4<f32>, ${p/r[0]}>, ${o}>;

  const rowPerThread = ${r[1]};
  const colPerThread = ${r[0]};
  const innerElementSize = ${l};
  const tileInner = ${o};

  ${se()} {
    let localRow = i32(localId.y);
    let tileRow = ${a?"0":"localRow * rowPerThread"};
    let tileCol = i32(localId.x);

    let globalRow = ${a?"0":"i32(globalId.y) * rowPerThread"};
    let globalCol = i32(globalId.x);
    let batch = ${n?"0":"i32(globalId.z)"};
    let globalRowStart = i32(workgroupId.y) * ${i};

    let numTiles = ${n?`${Math.ceil(s/o)}`:"(uniforms.dimInner - 1) / tileInner + 1"};
    var kStart = ${n?`i32(globalId.z) * ${s}`:"0"};

    var acc: array<vec4<f32>, rowPerThread>;

    // Loop over shared dimension.
    let tileRowB = localRow * ${m};
    for (var t = 0; t < numTiles; t = t + 1) {
        // Load one tile of A into local memory.
        for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
            let inputRow = tileRow + innerRow;
            let inputCol = tileCol;
            ${nre(t)}
        }

        // Load one tile of B into local memory.
        for (var innerRow = 0; innerRow < ${m}; innerRow = innerRow + 1) {
            let inputRow = tileRowB + innerRow;
            let inputCol = tileCol;
            mm_Bsub[inputRow][inputCol] = mm_readB(batch, kStart + inputRow, globalCol);
        }
        kStart = kStart + tileInner;
        workgroupBarrier();

        // Compute acc values for a single thread.
        for (var k = 0; k < tileInner / innerElementSize; k = k + 1) {
            let BCached0 = mm_Bsub[k * innerElementSize][tileCol];
            let BCached1 = mm_Bsub[k * innerElementSize + 1][tileCol];
            let BCached2 = mm_Bsub[k * innerElementSize + 2][tileCol];
            ${l===3?"":"let BCached3 = mm_Bsub[k * innerElementSize + 3][tileCol];"}

            ${sre(t,l)}
        }

        workgroupBarrier();
    }

    for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
        mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]);
    }
  }`}var P3=r=>r?`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          kStart + inputRow,
          globalRowStart + inputCol);
        `:`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          globalRowStart + inputRow,
          kStart + inputCol);
        `,are=r=>r?"let ACached = mm_Asub[k][tileRow + innerRow];":"let ACached = mm_Asub[tileRow + innerRow][k];";function Uu(r,e,t=!1,o=32,n=!1,s=32,a=!1){let i=r[1]*e[1],p=r[0]*e[0],u=t?i:o,c=t?o:i;y.assert(c%e[1]===0&&u%e[0]===0&&o%e[1]===0,()=>`tileAHight ${c} must be divisible by workgroupSize[1]${e[1]}, tileAWidth ${u} must be divisible by workgroupSize[0]${e[0]}, tileInner ${o} must be divisible by workgroupSize[1]${e[1]}`);let l=c/e[1],m=u/e[0],d=o/e[1],f=a?`
      let localRow = i32(localId.y);
      let localCol = i32(localId.x);
      let globalRowStart = i32(workgroupId.y) * ${i};
      let globalColStart = i32(workgroupId.x) * ${p};

      // Loop over shared dimension.
      for (var t = 0; t < numTiles; t = t + 1) {
        // Load one tile of A into local memory.
        for (var inputRow = localRow; inputRow < ${c}; inputRow = inputRow + ${e[1]}) {
          for (var inputCol = localCol; inputCol < ${u}; inputCol = inputCol + ${e[0]}) {
            ${P3(t)}
          }
        }
        // Load one tile of B into local memory.
        for (var inputRow = localRow; inputRow < ${o}; inputRow = inputRow + ${e[1]}) {
              for (var inputCol = localCol; inputCol < ${p}; inputCol = inputCol + ${e[0]}) {
            mm_Bsub[inputRow][inputCol] = mm_readB(batch,
              kStart + inputRow,
              globalColStart + inputCol);
          }
        }
        kStart = kStart + tileInner;
        workgroupBarrier();

        // Compute acc values for a single thread.
        var BCached : array<f32, colPerThread>;
        for (var k = 0; k < tileInner; k = k + 1) {
          for (var inner = 0; inner < colPerThread; inner = inner + 1) {
            BCached[inner] = mm_Bsub[k][localCol + inner * ${e[0]}];
          }
          for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
            let ACached = ${t?`mm_Asub[k][localRow + innerRow * ${e[1]}];`:`mm_Asub[localRow + innerRow * ${e[1]}][k];`}
            for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) {
              acc[innerRow][innerCol] = acc[innerRow][innerCol] +
                  ACached * BCached[innerCol];
            }
          }
        }
        workgroupBarrier();
      }
      for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
        let gRow = globalRowStart + localRow + innerRow * ${e[1]};
        for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) {
          let gCol = globalColStart + localCol + innerCol * ${e[0]};
          mm_write(batch, gRow, gCol, acc[innerRow][innerCol]);
        }
      }
      `:`
  let tileRow = i32(localId.y) * rowPerThread;
  let tileCol = i32(localId.x) * colPerThread;

  let globalRow = i32(globalId.y) * rowPerThread;
  let globalCol = i32(globalId.x) * colPerThread;
  let globalRowStart = i32(workgroupId.y) * ${i};

  let tileRowA = i32(localId.y) * ${l};
  let tileColA = i32(localId.x) * ${m};
  let tileRowB = i32(localId.y) * ${d};
  // Loop over shared dimension.
  for (var t = 0; t < numTiles; t = t + 1) {
    // Load one tile of A into local memory.
    for (var innerRow = 0; innerRow < ${l}; innerRow = innerRow + 1) {
      for (var innerCol = 0; innerCol < ${m}; innerCol = innerCol + 1) {
        let inputRow = tileRowA + innerRow;
        let inputCol = tileColA + innerCol;
        ${P3(t)}
      }
    }

    // Load one tile of B into local memory.
    for (var innerRow = 0; innerRow < ${d}; innerRow = innerRow + 1) {
      for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) {
        let inputRow = tileRowB + innerRow;
        let inputCol = tileCol + innerCol;
        mm_Bsub[inputRow][inputCol] = mm_readB(batch,
          kStart + inputRow,
          globalCol + innerCol);
      }
    }
    kStart = kStart + tileInner;
    workgroupBarrier();

    // Compute acc values for a single thread.
    var BCached : array<f32, colPerThread>;
    for (var k = 0; k < tileInner; k = k + 1) {
      for (var inner = 0; inner < colPerThread; inner = inner + 1) {
        BCached[inner] = mm_Bsub[k][tileCol + inner];
      }

      for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
        ${are(t)}
        for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) {
          acc[innerRow][innerCol] = acc[innerRow][innerCol] + ACached * BCached[innerCol];
        }
      }
    }

    workgroupBarrier();
  }

  for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
    for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) {
      mm_write(batch, globalRow + innerRow, globalCol + innerCol,
          acc[innerRow][innerCol]);
    }
  }
  `;return`
    var<workgroup> mm_Asub : array<array<f32, ${u}>, ${c}>;
    var<workgroup> mm_Bsub : array<array<f32, ${p}>, ${o}>;
    const rowPerThread = ${r[1]};
    const colPerThread = ${r[0]};
    const tileInner = ${o};

    ${se()} {
      let batch = ${n?"0":"i32(globalId.z)"};
      let numTiles = ${n?`${Math.ceil(s/o)}`:"(uniforms.dimInner - 1) / tileInner + 1"};
      var kStart = ${n?`i32(globalId.z) * ${s}`:"0"};

      var acc : array<array<f32, colPerThread>, rowPerThread>;

      // Without this initialization strange values show up in acc.
      for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
        for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) {
          acc[innerRow][innerCol] = 0.0;
        }
      }
      ${f}
    }
  `}var ire=r=>r?`
      mm_readA(batch, colA, globalRow),
      mm_readA(batch, colA + 1, globalRow),
      mm_readA(batch, colA + 2, globalRow),
      mm_readA(batch, colA + 3, globalRow)
  `:`
      mm_readA(batch, globalRow, colA),
      mm_readA(batch, globalRow, colA + 1),
      mm_readA(batch, globalRow, colA + 2),
      mm_readA(batch, globalRow, colA + 3)
  `;function ure(r,e=!1){return y.assert(r[1]===1&&r[2]===1,()=>`A linear work group size is required. But got ${r}.`),`
    const tileSize = ${r[0]*4};
    var<workgroup> mm_Asub : array<vec4<f32>, ${r[0]}>;

    ${se()} {
      let tileCol = i32(localId.x);
      let globalCol = i32(globalId.x);
      let globalRow = i32(globalId.y);

      let numTiles = (uniforms.dimInner - 1) / tileSize + 1;
      let batch = i32(globalId.z);
      // Without this initialization strange values show up in acc.
      var acc = 0.0;

      // Loop over shared dimension.
      for (var t = 0; t < numTiles; t = t + 1) {
        // Load one tile of A into local memory.
        let colA = t * tileSize + tileCol * 4;
        mm_Asub[tileCol] = vec4<f32>(${ire(e)});
        workgroupBarrier();

        // Compute acc values for a single thread.
        for (var k = 0; k < tileSize / 4; k = k + 1) {
          let rowB = t * tileSize + k * 4;
          let BCached = vec4<f32>(mm_readB(batch, rowB, globalCol),
                              mm_readB(batch, rowB + 1, globalCol),
                              mm_readB(batch, rowB + 2, globalCol),
                              mm_readB(batch, rowB + 3, globalCol));

          let ACached = mm_Asub[k];
          acc = acc + dot(ACached, BCached);
        }

        workgroupBarrier();
      }

      mm_write(batch, globalRow, globalCol, acc);
    }
  `}var _g=class{constructor(e,t,o,n,s=!1,a=!1,i=null,p=null,u=null,c=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=t,this.dispatchLayout={x:[2],y:[1],z:[0]};let l=s?e[1]:e[2];if(this.isVec4=(l%4===0&&!s||t[1]%4===0&&s)&&t[2]%4===0&&!a,this.isVectorA=t[1]===1&&!s,!this.isVec4&&this.isVectorA)this.elementsPerThread=[1,1,1],this.workgroupSize=[32,1,1];else{let f=tI(t[1],l,t[2],s);this.workgroupSize=f.workgroupSize,this.elementsPerThread=f.elementsPerThread}this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread);let m=i!=null,d=u!=null;m&&this.variableNames.push("bias"),d&&this.variableNames.push("preluActivationWeights"),this.sequentialAccessByThreads=c,this.transposeA=s,this.transposeB=a,this.addBias=m,this.activation=p,this.hasPreluActivationWeights=d,this.batchAEqualOne=o,this.batchBEqualOne=n,[this.fitAOuter,this.fitBOuter,this.fitInner]=this.getShapeFit(t[1],t[2],l),this.shaderKey=`matMulPacked_${this.elementsPerThread}_${s}_${a}_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.isVectorA}_${this.batchAEqualOne}_${this.batchBEqualOne}_${this.sequentialAccessByThreads}`}getShapeFit(e,t,o){let n=this.workgroupSize[1]*this.elementsPerThread[1],s=this.workgroupSize[0]*this.elementsPerThread[0];!this.isVec4&&this.isVectorA?this.tileInner=this.workgroupSize[0]*4:this.tileInner=s;let a=e%n===0,i=t%s===0,p=o%this.tileInner===0;return[a,i,p]}getUserCode(){return`
      ${ur(this.activation,this.hasPreluActivationWeights,this.isVec4)}
      ${Vl(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,!1,this.transposeB,this.fitAOuter,this.fitBOuter,this.fitInner,this.isVec4?4:1)}
      ${this.isVec4?Wu(this.elementsPerThread,this.workgroupSize,this.transposeA,this.tileInner,!1,null,this.isVectorA):this.isVectorA?ure(this.workgroupSize,this.transposeA):Uu(this.elementsPerThread,this.workgroupSize,this.transposeA,this.tileInner,!1,null,this.sequentialAccessByThreads)}
    `}};function pre(){return`
    var<workgroup> sumValues : array<f32, workgroupSizeX>;
    ${se()} {
      let coords = getOutputCoords();
      let batch = coords[0];
      let row = coords[1];
      let col = coords[2];
      var sum = 0.0;
      let Length = uniforms.dimInner;
      for (var k = i32(localId.x); k < Length; k = k + i32(workgroupSizeX)) {
        let dataA = mm_readA(batch, row, k);
        let dataB = mm_readB(batch, k, col);
        sum = sum + dataA * dataB;
      }
      sumValues[localId.x] = sum;
      workgroupBarrier();

      for(var currentSize = workgroupSizeX / 2u; currentSize > 1u;
          currentSize = currentSize / 2u) {
        if (localId.x < currentSize)
        {
          sumValues[localId.x] = sumValues[localId.x] + sumValues[localId.x + currentSize];
        }
        workgroupBarrier();
      }

      if (localId.x == 0u) {
        sum = sumValues[0] + sumValues[1];
        mm_write(batch, row, col, sum);
      }
    }
  `}var Eg=class{constructor(e,t,o,n=!1,s=!1,a=null,i=null,p=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout={x:[],y:[1,2],z:[0]},this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize);let u=a!=null,c=p!=null;u&&this.variableNames.push("bias"),c&&this.variableNames.push("preluActivationWeights"),this.transposeA=n,this.transposeB=s,this.addBias=u,this.activation=i,this.hasPreluActivationWeights=c,this.batchAEqualOne=t,this.batchBEqualOne=o,this.shaderKey=`matMulReduce_${this.activation}_${n}_${s}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getUserCode(){return`
      ${ur(this.activation,this.hasPreluActivationWeights)}
      ${Vl(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,this.transposeA,this.transposeB)}
      ${pre()}
    `}};function cre(r){let e=r[1],t=r[0],o=e>t?e:t;return`
  var<workgroup> mm_Asub : array<array<f32, ${o}>, ${e}>;
  var<workgroup> mm_Bsub : array<array<f32, ${t}>, ${o}>;

  // If the output size is small for matrix multiplication, avoid to use vec4
  // and handle some elements per thread to optimally utilize the ALU.
  // Read data from global memory to registers firstly, then store them into
  // shared memory, so it is instruction-Level parallelism for arithmetic
  // operations and others handle IO operations between barrier api, makes ALU
  // and load/store units work simultaneously, could improves the performance.
  ${se()} {
    let tileRow = i32(localId.y);
    let tileCol = i32(localId.x);
    let globalRow = i32(globalId.y);
    let globalCol = i32(globalId.x);
    let batch = i32(globalId.z);

    // uniforms.dimInner should be greater than 0.
    let numTiles = (uniforms.dimInner - 1) / ${o} + 1;
    var acc = 0.0;

    var globalColA = tileCol;
    var globalRowB = 0;
    var regA = mm_readA(batch, globalRow, globalColA);
    var regB0 = mm_readB(batch, globalRowB + 2 * tileRow, globalCol);
    var regB1 = mm_readB(batch, globalRowB + 2 * tileRow + 1, globalCol);
    globalColA = globalColA + ${o};
    globalRowB = globalRowB + ${o};

    for (var t = 0; t < numTiles; t = t + 1) {
      mm_Asub[tileRow][tileCol] = regA;
      mm_Bsub[2 * tileRow][tileCol] = regB0;
      mm_Bsub[2 * tileRow + 1][tileCol] = regB1;

      workgroupBarrier();

      regA = mm_readA(batch, globalRow, globalColA);
      regB0 = mm_readB(batch, globalRowB + 2 * tileRow, globalCol);
      regB1 = mm_readB(batch, globalRowB + 2 * tileRow + 1, globalCol);
      globalColA = globalColA + ${o};
      globalRowB = globalRowB + ${o};

      for (var k = 0; k < ${o}; k = k + 1) {
        acc = acc + mm_Asub[tileRow][k] * mm_Bsub[k][tileCol];
      }
      workgroupBarrier();
    }

    mm_write(batch, globalRow, globalCol, acc);
  }
  `}var $g=class{constructor(e,t,o,n=!1,s=!1,a=null,i=null,p=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[16,8,1],this.outputShape=o,this.dispatchLayout={x:[2],y:[1],z:[0]},this.dispatch=[Math.ceil(o[2]/this.workgroupSize[0]),Math.ceil(o[1]/this.workgroupSize[1]),o[0]];let u=a!=null;u&&this.variableNames.push("bias");let c=p!=null;c&&this.variableNames.push("preluActivationWeights"),this.transposeA=n,this.transposeB=s,this.addBias=u,this.activation=i,this.hasPreluActivationWeights=c,this.batchAEqualOne=e[0]===1,this.batchBEqualOne=t[0]===1,this.shaderKey=`matMulSmallOutputSize_${this.activation}_${n}_${s}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getUserCode(){return`
      ${ur(this.activation,this.hasPreluActivationWeights)}
      ${Vl(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,this.transposeA,this.transposeB)}
      ${cre(this.workgroupSize)}
    `}};var Ag=class{constructor(e,t,o,n,s=!1,a=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[8,8,1],this.atomic=!0,this.isVec4=!1,this.splitedDimInner=128,y.assert(e[0]===1,()=>"MatMulSplitKProgram only supports batch = 1."),this.outputShape=e,this.dispatchLayout={x:[2],y:[1],z:[0,3]},this.isVec4=(s&&this.outputShape[1]%4===0||!s&&t%4===0)&&this.outputShape[2]%4===0,this.elementsPerThread=[4,4,this.splitedDimInner],this.isVec4||(this.outputShape[1]<16&&(this.elementsPerThread[1]=1),this.outputShape[2]<16&&(this.elementsPerThread[0]=1)),this.dispatch=re(this.dispatchLayout,[this.outputShape[0],this.outputShape[1],this.outputShape[2],t],this.workgroupSize,this.elementsPerThread),this.transposeA=s,this.transposeB=a,this.batchAEqualOne=o,this.batchBEqualOne=n,this.shaderKey=`matMulSplitK_${s}_${a}_${o}_${n}_${this.elementsPerThread}_${this.isVec4}`}getUserCode(){let e=n=>`
      for (var i = 0; i < ${n}; i = i + 1)
      {
        var oldValue = atomicLoad(&(result[flatIndex + i]));
        var exchanged = false;
        for (; !exchanged;) {
          let newValueF32 = bitcast<f32>(oldValue) + ${n>1?"value[i]":"value"};
          let newValue = bitcast<i32>(newValueF32);
          let res = atomicCompareExchangeWeak(&(result[flatIndex + i]), oldValue, newValue);
          oldValue = res.old_value;
          exchanged = res.exchanged;
        }
      }
      `,t=this.isVec4?4:1;return`
      ${iI(this.batchAEqualOne,this.batchBEqualOne,!1,this.transposeB,!1,!1,!1,t)}
      fn mm_write(batch: i32, row : i32, colIn : i32, value : ${kt(t)}) {
        let col = colIn * ${t};
        if (row < uniforms.dimAOuter && col < uniforms.dimBOuter) {
          let coords = vec3<i32>(batch, row, col);
          let flatIndex = getOutputIndexFromCoords(coords);
          // The problem is that we should initialize output to zero before using.
          // Otherwise, the original value will be added to the result.
          ${e(t)}
        }
      }
      ${this.isVec4?Wu(this.elementsPerThread,this.workgroupSize,this.transposeA,32,!0,this.splitedDimInner):Uu(this.elementsPerThread,this.workgroupSize,this.transposeA,32,!0,this.splitedDimInner)}
    `}},Rg=class{constructor(e,t=null,o=null,n=null){this.uniforms="",this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.addBias=t!=null,this.hasPreluActivationWeights=n!=null,this.activation=o,this.addBias&&this.variableNames.push("bias"),this.hasPreluActivationWeights&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`biasActivation_${o}`}getUserCode(){return`
    ${ur(this.activation,this.hasPreluActivationWeights)}
    ${se("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        var value = getXByOutputIndex(index);
        ${Hr(this.addBias,this.activation)}
        setOutputAtIndex(index, value);
      }
    }
    `}};var Fg=class{constructor(e){this.variableNames=[],this.outputShape=[],this.uniforms="value : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="fill"}getUserCode(){return`
    ${se("index")} {
      if (index < uniforms.size) {
        setOutputAtIndex(index, uniforms.value);
      }
    }
  `}};function dr(r){let{backend:e,attrs:t}=r,{shape:o,value:n}=t,{dtype:s}=t;if(s=s||y.inferDtype(n),s==="string"){let a=y.getArrayFromDType(s,y.sizeFromShape(o));return a.fill(n),e.makeTensorInfo(o,s,a)}else{let a=new Fg(o),i=[{type:"float32",data:[n]}];return e.runWebGPUProgram(a,[],s,i)}}var M3={kernelName:Cs,backendName:"webgpu",kernelFunc:dr};function de(r){let{inputs:e,attrs:t}=r,{x:o}=e,{shape:n}=t,s=y.sizeFromShape(o.shape),a=y.inferFromImplicitShape(n,s),i=y.sizeFromShape(a);return y.assert(s===i,()=>`The new shape (${a}) has ${i} elements and the old shape (${o.shape}) has ${s} elements. The new shape and old shape must have the same number of elements.`),r.backend.incRef(o.dataId),{dataId:o.dataId,shape:a,dtype:o.dtype}}var L3={kernelName:Ns,backendName:"webgpu",kernelFunc:de};function Gu({a:r,b:e,transposeA:t,transposeB:o,backend:n,bias:s=null,preluActivationWeights:a=null,leakyreluAlpha:i=0,activation:p=null}){let u=r.shape.length,c=e.shape.length,l=t?r.shape[u-2]:r.shape[u-1],m=o?e.shape[c-1]:e.shape[c-2],d=t?r.shape[u-1]:r.shape[u-2],f=o?e.shape[c-2]:e.shape[c-1],h=r.shape.slice(0,-2),g=e.shape.slice(0,-2),x=y.sizeFromShape(h),b=y.sizeFromShape(g),w=br.assertAndGetBroadcastShape(r.shape.slice(0,-2),e.shape.slice(0,-2)).concat([d,f]);y.assert(l===m,()=>`Error in matMul: inner shapes (${l}) and (${m}) of Tensors with shapes ${r.shape} and ${e.shape} and transposeA=${t} and transposeB=${o} must match.`);let k=t?[x,l,d]:[x,d,l],_=o?[b,f,m]:[b,m,f],$=de({inputs:{x:r},backend:n,attrs:{shape:k}}),A=de({inputs:{x:e},backend:n,attrs:{shape:_}}),R=[$,A],D=Math.max(x,b),P=x===1,M=b===1,L=[$,A],W=[{type:"int32",data:[d]},{type:"int32",data:[f]},{type:"int32",data:[l]}],V,U,q=[D,d,f],H=O().get("WEBGPU_MATMUL_PROGRAM_TYPE");if(H<0){let X=O().getNumber("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL"),Z=X>0?X:n.thresholdToIncreaseWorkgroups,ee=D*Math.ceil(d/32)*Math.ceil(f/32);ee<=Z||d<=8&&ee<=Z*2?D*d*f<=128?H=Ao.MatMulReduceProgram:D===1&&m>=2e3?H=Ao.MatMulSplitKProgram:H=Ao.MatMulSmallOutputSizeProgram:H=Ao.MatMulPackedProgram}switch(H){case Ao.MatMulReduceProgram:V=new Eg(q,P,M,t,o,s,p,a);break;case Ao.MatMulSplitKProgram:{if(U=dr({backend:n,attrs:{shape:q,value:0,dtype:r.dtype}}),V=new Ag(q,m,P,M,t,o),s||p){U=n.runWebGPUProgram(V,L,r.dtype,W,U);let Z=new Rg(U.shape,s,p,a),ee=null,Y=[U];s&&Y.push(s),a&&Y.push(a),p==="leakyrelu"&&(ee=[{type:"float32",data:[i]}],Z.uniforms+=" alpha : f32,");let J=n.runWebGPUProgram(Z,Y,U.dtype,ee);R.push(U);let ie=de({inputs:{x:J},backend:n,attrs:{shape:w}});R.push(J);for(let pe of R)n.disposeData(pe.dataId);return ie}break}case Ao.MatMulSmallOutputSizeProgram:V=new $g(k,_,q,t,o,s,p,a);break;case Ao.MatMulPackedProgram:let X=n.adapterInfo.isIntel();V=new _g(k,q,P,M,t,o,s,p,a,X);break;default:throw new Error(`Unsupported MatMulProgramType ${H}.`)}s&&L.push(s),a&&L.push(a),p==="leakyrelu"&&(W.push({type:"float32",data:[i]}),V.uniforms+=" alpha : f32,"),U=n.runWebGPUProgram(V,L,r.dtype,W,U);let j=de({inputs:{x:U},backend:n,attrs:{shape:w}});R.push(U);for(let X of R)n.disposeData(X.dataId);return j}function lre(r){let{inputs:e,backend:t,attrs:o}=r,{a:n,b:s,bias:a,preluActivationWeights:i}=e,{transposeA:p,transposeB:u,activation:c,leakyreluAlpha:l}=o;return Gu({a:n,b:s,transposeA:p,transposeB:u,backend:t,bias:a,preluActivationWeights:i,leakyreluAlpha:l,activation:c})}var B3={kernelName:fo,backendName:"webgpu",kernelFunc:lre};var zl=class{constructor(e,t,o){this.variableNames=["AReal","AImag","BReal","BImag"],this.workgroupSize=[128,1,1],this.size=!0,this.outputShape=S.assertAndGetBroadcastShape(t,o),this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`binaryOpComplex_${e}`,this.op=e}getUserCode(){return`
      fn binaryOpComplex(
          areal : f32, aimag : f32, breal : f32, bimag : f32) -> f32 {
        ${Ic(this.op,!1)}
      }

      ${se("index")} {
        if(index < uniforms.size) {
          let areal = getARealByOutputIndex(index);
          let aimag = getAImagByOutputIndex(index);
          let breal = getBRealByOutputIndex(index);
          let bimag = getBImagByOutputIndex(index);
          setOutputAtIndex(index, binaryOpComplex(areal, aimag, breal, bimag));
        }
      }
    `}};var Hu=class{constructor(e,t,o){this.size=!0,this.variableNames=["A","B"],this.outputShape=S.assertAndGetBroadcastShape(t,o),this.dispatchLayout=ue(this.outputShape),this.op=e,this.useSharedMemoryWithA=t.length<=1&&o.length>1&&t[0]<128,this.useSharedMemoryWithB=o.length<=1&&t.length>1&&o[0]<128,this.useSharedMemoryWithA||this.useSharedMemoryWithB?(this.isVec4=!1,this.lastDimensionSize=this.useSharedMemoryWithB?o[0]:t[0],this.shaderKey=`binary_${this.type}_${e}_${this.lastDimensionSize}_${this.useSharedMemoryWithB}`,this.type="shared",this.workgroupSize=[256,1,1],this.workPerThread=1):(y.arraysEqual(t,o)&&y.sizeFromShape(t)%4===0?(this.isVec4=!0,this.type="vec4",this.workPerThread=4):(this.isVec4=!1,this.type="plain",this.workPerThread=1),this.shaderKey=`binary_${this.type}_${e}`,this.workgroupSize=[128,1,1]),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1])}getUserCode(){let e,t=this.isVec4?"vec4<f32>":"f32",o=`
    fn binaryOperation(a : ${t}, b : ${t}) -> ${t} {
      ${Ic(this.op,this.isVec4)}
    };
    `;if(this.type==="shared"){let n=this.lastDimensionSize>1?`coords[${this.outputShape.length-1}]`:"0",s=this.useSharedMemoryWithB?`let a = getAByOutputIndex(index);
          let b = sharedBuf[${n}];`:`let a = sharedBuf[${n}];
          let b = getBByOutputIndex(index);`;e=`
        ${o}
        var<workgroup> sharedBuf : array<f32, ${this.lastDimensionSize}>;
        ${se("index")} {
          // Fill in the shared memory buffer.
          let localIndex = i32(localId.x);
          if(localIndex < ${this.lastDimensionSize}) {
            sharedBuf[localIndex] = f32(${this.useSharedMemoryWithB?"B":"A"}[localIndex]);
          }
          workgroupBarrier();

          if(index < uniforms.size) {
            let coords = getCoordsFromIndex(index);
            ${s}
            setOutputAtIndex(index, binaryOperation(a, b));
          }
        }
        `}else e=`
       ${o}
       ${se("index")} {
         if (index < uniforms.size) {
           let a = getAByOutputIndex(index);
           let b = getBByOutputIndex(index);
           setOutputAtIndex(index, binaryOperation(a, b));
         }
       }
       `;return e}};function Ft(r){let{inputs:e}=r,{x:t}=e;return r.backend.incRef(t.dataId),{dataId:t.dataId,shape:t.shape,dtype:t.dtype}}var V3={kernelName:mo,backendName:"webgpu",kernelFunc:Ft};function po(r){let{inputs:e,backend:t}=r,{real:o,imag:n}=e,s=t.makeTensorInfo(o.shape,"complex64"),a=t.tensorMap.get(s.dataId),i=Ft({inputs:{x:o},backend:t}),p=Ft({inputs:{x:n},backend:t});return a.complexTensorInfos={real:i,imag:p},s}var z3={kernelName:ei,backendName:"webgpu",kernelFunc:po};var Ro=class{constructor(e,t){this.variableNames=["A"],this.size=!0;let o=128;this.workgroupSize=[o,1,1],this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.op=t,this.shaderKey=`unary_${t}`}getUserCode(){return`
      fn unaryOperation(a : f32) -> f32 {
        ${Ha(this.op,!1)}
      }
      ${se("index")} {
        if (index < uniforms.size) {
          let a = getAByOutputIndex(index);
          setOutputAtIndex(index, unaryOperation(a));
        }
      }
      `}};function Se({opType:r,cpuKernelImpl:e,dtype:t}){return({inputs:o,backend:n})=>{let{x:s}=o,a=n,i=t||s.dtype;if(a.shouldExecuteOnCPU([s])&&e!=null){let u=a.tensorMap.get(s.dataId),c=e(u.values,i);return a.makeTensorInfo(s.shape,i,c)}let p=new Ro(s.shape,r);return a.runWebGPUProgram(p,[s],i)}}function ot({opType:r,cpuKernelImpl:e,supportsComplex:t=!1,dtype:o}){return({inputs:n,backend:s})=>{let{a,b:i}=n,p=s;if(t&&a.dtype==="complex64"){let l=p.tensorMap.get(a.dataId),m=p.tensorMap.get(i.dataId),d,f;if(r!==ye.MUL)[d,f]=[[l.complexTensorInfos.real,m.complexTensorInfos.real],[l.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(g=>{let[x,b]=g,C={dataId:x.dataId,dtype:x.dtype,shape:a.shape},w={dataId:b.dataId,dtype:b.dtype,shape:i.shape},k=new Hu(r,a.shape,i.shape);return p.runWebGPUProgram(k,[C,w],dt(x.dtype,b.dtype))});else{let g=new zl(ye.COMPLEX_MULTIPLY_REAL,a.shape,i.shape),x=new zl(ye.COMPLEX_MULTIPLY_IMAG,a.shape,i.shape),b=[{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},{dataId:m.complexTensorInfos.real.dataId,dtype:m.complexTensorInfos.real.dtype,shape:i.shape},{dataId:m.complexTensorInfos.imag.dataId,dtype:m.complexTensorInfos.imag.dtype,shape:i.shape}];d=p.runWebGPUProgram(g,b,"float32"),f=p.runWebGPUProgram(x,b,"float32")}let h=po({inputs:{real:d,imag:f},backend:p});return p.disposeData(d.dataId),p.disposeData(f.dataId),h}let u=o||dt(a.dtype,i.dtype);if((a.dtype==="string"||i.dtype==="string"||p.shouldExecuteOnCPU([a,i]))&&e!=null){let l=p.tensorMap.get(a.dataId).values,m=p.tensorMap.get(i.dataId).values,d=a.dtype==="string"?S.fromUint8ToStringArray(l):l,f=a.dtype==="string"?S.fromUint8ToStringArray(m):m,[h,g]=e(a.shape,i.shape,d,f,u);return p.makeTensorInfo(g,u,h)}let c=new Hu(r,a.shape,i.shape);return p.runWebGPUProgram(c,[a,i],u)}}var{addImpl:W3,castImpl:U3,ceilImpl:G3,concatImpl:H3,equalImpl:q3,expImpl:K3,expm1Impl:j3,floorImpl:X3,gatherNdImpl:Y3,gatherV2Impl:Q3,greaterEqualImpl:Z3,greaterImpl:J3,lessEqualImpl:eM,lessImpl:tM,logImpl:rM,maxImpl:oM,maximumImpl:nM,minimumImpl:sM,multiplyImpl:aM,negImpl:iM,notEqualImpl:uM,prodImpl:pM,rangeImpl:cM,rsqrtImpl:lM,scatterImpl:mM,simpleAbsImpl:dM,sliceImpl:fM,stridedSliceImpl:hM,stringNGramsImpl:gM,subImpl:xM,tileImpl:yM,topKImpl:bM,transposeImpl:CM,uniqueImpl:kNt}=Qp;var mre=Se({opType:Q.ABS,cpuKernelImpl:dM}),SM={kernelName:gs,backendName:"webgpu",kernelFunc:mre};var dre=Se({opType:Q.ACOS}),wM={kernelName:sa,backendName:"webgpu",kernelFunc:dre};var fre=Se({opType:Q.ACOSH}),IM={kernelName:aa,backendName:"webgpu",kernelFunc:fre};var hre=ot({opType:ye.ADD,cpuKernelImpl:W3,supportsComplex:!0}),vM={kernelName:eo,backendName:"webgpu",kernelFunc:hre};var Dg=class{constructor(e){this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e[0],this.variableNames=e.map((t,o)=>`T${o}`),this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.shaderKey="addN"}getUserCode(){let e=[];this.variableNames.forEach(n=>{e.push(`let v${n} = get${n}ByOutputCoords(coords);`)});let t=this.variableNames.map(n=>`v${n}`).join(" + ");return`
      ${se("index")} {
        for (var i = 0; i < ${this.workPerThread}; i = i + 1) {
          let flatIndex = index * ${this.workPerThread} + i;
          if (flatIndex < uniforms.size) {
            let coords = getCoordsFromIndex(flatIndex);
            ${e.join(`
        `)}
            setOutputAtIndex(flatIndex, ${t});
          }
        }
      }
    `}};function gre(r){let{inputs:e,backend:t}=r,o=e;if(o.length===1)return Ft({inputs:{x:o[0]},backend:t});let n=o.map(i=>i.dtype).reduce((i,p)=>dt(i,p)),s=o.map(i=>i.shape),a=new Dg(s);return t.runWebGPUProgram(a,o,n)}var kM={kernelName:Mo,backendName:"webgpu",kernelFunc:gre};var Og=class{constructor(e,t){this.variableNames=["A"],this.workgroupSize=[16,16,1];let o=new Array(e.length);for(let n=0;n<o.length;n++)o[n]=e[t[n]];this.outputShape=o,this.dispatchLayout={x:[0],y:[1]},this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize,[1,1,1]),this.shaderKey="transposeShared"}getUserCode(){return y.assert(this.workgroupSize[0]===this.workgroupSize[1],()=>`Must be a square tile, current tile shape is ${this.workgroupSize[0]} x ${this.workgroupSize[1]}`),`
      const tileSize = ${this.workgroupSize[0]};
      var<workgroup> tile : array<array<f32, ${this.workgroupSize[0]+1}>, ${this.workgroupSize[0]}>;
      ${se()} {
        var x = i32(workgroupId.x) * tileSize + i32(localId.x);
        var y = i32(workgroupId.y) * tileSize + i32(localId.y);
        let width = uniforms.outShape[0];
        let height = uniforms.outShape[1];
        if (x < width && y < height) {
          tile[localId.y][localId.x] = f32(A[y * width + x]);
        }
        workgroupBarrier();

        x = i32(workgroupId.y) * tileSize + i32(localId.x);
        y = i32(workgroupId.x) * tileSize + i32(localId.y);
        if (x < height && y < width) {
          setOutputAtIndex((y * height + x), tile[localId.x]
            [localId.y]);
        }
      }
    `}};var Pg=class{constructor(e,t){this.variableNames=["A"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0;let o=new Array(e.length);for(let n=0;n<o.length;n++)o[n]=e[t[n]];this.outputShape=o,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.newDim=t,this.shaderKey=`transpose_${t}`}getUserCode(){let e=Rt(this.outputShape.length),t=xre(this.newDim);return`
      ${se("index")} {
        for(var i = 0; i < ${this.workPerThread}; i = i + 1) {
          let flatIndex = index * ${this.workPerThread} + i;
          if(flatIndex < uniforms.size) {
            let resRC = getCoordsFromIndex(flatIndex);
            setOutputAtIndex(flatIndex, A[getIndexFromCoords${this.outputShape.length}D(
              ${e}(${t}), uniforms.aShape)]);
          }
        }
      }
    `}};function xre(r){let e=r.length;if(e>6)throw Error(`Transpose for rank ${e} is not yet supported`);let t=new Array(e);for(let o=0;o<r.length;o++)t[r[o]]=`resRC.${$o(o)}`;return t.join()}function Nr(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{perm:s}=o,a=t,i=n.shape.length,p=new Array(i);for(let c=0;c<p.length;c++)p[c]=n.shape[s[c]];if(t.shouldExecuteOnCPU([n])){let l=a.tensorMap.get(n.dataId).values,m=CM(l,n.shape,n.dtype,s,p);return t.makeTensorInfo(p,n.dtype,m)}if(n.shape.length===2&&y.arraysEqual(s,[1,0])){let c=new Og(n.shape,s);return a.runWebGPUProgram(c,[n],n.dtype)}let u=new Pg(n.shape,s);return a.runWebGPUProgram(u,[n],n.dtype)}var NM={kernelName:ro,backendName:"webgpu",kernelFunc:Nr};var Mg=class{constructor(e,t){this.workgroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="reduceSize : i32,",this.size=!0,this.inputShape=[e.batchSize,e.inSize];let[o]=S.computeOutAndReduceShapes(this.inputShape,[1]);this.outputShape=o.length===0?[1]:o,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,[1,1,1]),this.reduceType=t,this.shaderKey=`reduce_${t}`}getUserCode(){let e="",t="0.0";this.reduceType==="min"||this.reduceType==="max"?(e=`
         if (isnan(candidate)) {
          bestValue = uniforms.NAN;
         } else if (!isnan(bestValue) && candidate ${this.reduceType==="min"?"<":">"} bestValue)
           {  bestValue = candidate; }`,t="f32(x[offset])"):this.reduceType==="sum"||this.reduceType==="mean"?e=" bestValue = bestValue + candidate; ":this.reduceType==="prod"?(e=" bestValue = bestValue * candidate; ",t="1.0"):this.reduceType==="all"?(e=" bestValue = f32(bestValue >= 1.0 && candidate >= 1.0); ",t="1.0"):this.reduceType==="any"&&(e=" bestValue = f32(bestValue >= 1.0 || candidate >= 1.0); ",t="0.0");let o=this.reduceType==="mean"?"setOutputAtIndex(outputIndex, bestValue / f32(uniforms.reduceSize));":"setOutputAtIndex(outputIndex, bestValue);";return`
       fn DIV_CEIL(a : u32, b : u32) -> u32 {
        return ((a - 1u) / b + 1u);
       }

       ${`
         var<workgroup> xBestValues : array<f32, ${this.workgroupSize[0]}>;
       `}
       fn getOffset(outputIndex : i32) -> i32 {
         let outputCoords = getCoordsFromIndex(outputIndex);
         let offset = ${this.outputShape.length===1?"outputCoords":"outputCoords[0]"} * uniforms.reduceSize;
          return offset;
       }
       ${se("index")} {
         let outputIndex = index / i32(workgroupSizeX);
         let offset = getOffset(outputIndex);
         var bestValue = ${t};
         let Length = uniforms.reduceSize;
         let WorkPerThread = DIV_CEIL(u32(Length), workgroupSizeX);
         for (var k = i32(localId.x); k < Length && outputIndex < uniforms.size;
             k = k + i32(workgroupSizeX)) {
           let candidate = f32(x[offset + k]);
           ${e}
         }
         xBestValues[localId.x] = bestValue;
         workgroupBarrier();

         var reduceSize = min(u32(Length), workgroupSizeX);
         for (var currentSize = reduceSize / 2u; reduceSize > 1u;
             currentSize = reduceSize / 2u) {
           let interval = DIV_CEIL(reduceSize, 2u);
           if (localId.x < currentSize) {
            let candidate = xBestValues[localId.x + interval];
            ${e}
            xBestValues[localId.x] = bestValue;
           }
           reduceSize = interval;
           workgroupBarrier();
         }

         if (localId.x == 0u && outputIndex < uniforms.size) {
          ${o}
        }
       }
     `}};function qr(r,e,t,o,n){let s=r.shape.length,a=[],i=y.parseAxisParam(e,r.shape),p=i,u=S.getAxesPermutation(p,s),c=r;u!=null&&(c=Nr({inputs:{x:r},attrs:{perm:u},backend:n}),p=S.getInnerMostAxes(p.length,s),a.push(c)),S.assertAxesAreInnerMostDims(o,p,s);let[l,m]=S.computeOutAndReduceShapes(c.shape,p),d=l;t&&(d=S.expandShapeToKeepDim(l,i));let f;if((o==="max"||o==="prod")&&n.shouldExecuteOnCPU([c])){let h=n.tensorMap.get(c.dataId).values;switch(o){case"max":let g=oM(h,y.sizeFromShape(m),d,r.dtype);f=n.makeTensorInfo(d,r.dtype,g);break;case"prod":let{outVals:x,outShape:b,outDtype:C}=pM(c.shape,c.dtype,h,p);f=n.makeTensorInfo(b,C,x);break;default:throw new Error(`${o} CPU implementation is not yet supported.`)}}else{let h=y.sizeFromShape(m),x=y.sizeFromShape(c.shape)/h,b={windowSize:h,inSize:h,batchSize:x,outSize:1},C=o==="mean"?"float32":ka(r.dtype),w=[{type:"int32",data:[h]}],k=new Mg(b,o),_=n.runWebGPUProgram(k,[c],C,w);a.push(_),f=de({inputs:{x:_},attrs:{shape:d},backend:n})}return a.forEach(h=>n.disposeData(h.dataId)),f}function yre(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{keepDims:s,axis:a}=o;return qr(n,a,s,"all",t)}var TM={kernelName:Lo,backendName:"webgpu",kernelFunc:yre};function bre(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{keepDims:s,axis:a}=o;return qr(n,a,s,"any",t)}var _M={kernelName:Bo,backendName:"webgpu",kernelFunc:bre};var vc=class{constructor(e,t,o){this.workgroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="infinityValue : f32,",this.size=!0;let n=[t];this.op=o==="min"?"<":">";let[s,a]=S.computeOutAndReduceShapes(e,n);this.outputShape=s.length===0?[1]:s,this.dispatchLayout=ue(this.outputShape),y.sizeFromShape(a)<32||y.sizeFromShape(s)>1e3?(this.type="plain",this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize)):(this.type="shared",this.dispatch=re(this.dispatchLayout,this.outputShape,[1,1,1])),this.inputShape=e,this.shaderKey=`argMinMax_${this.op}_${this.type}`}getUserCode(){let e=()=>this.inputShape.length===1?"uniforms.xShape":`uniforms.xShape.${$o(this.inputShape.length-1)}`,t=()=>{let o="";if(this.outputShape.length===1)this.inputShape.length!==1&&(o+="outputCoords,");else for(let n=0;n<this.outputShape.length;n++)o+=`outputCoords.${$o(n)},`;return o};return this.type==="shared"?`
      fn DIV_CEIL(a : u32, b : u32) -> u32 {
        return ((a - 1u) / b + 1u);
      }

      ${`
      var<workgroup> xBestIndices : array<i32, ${this.workgroupSize[0]}>;
      var<workgroup> xBestValues : array<f32, ${this.workgroupSize[0]}>;
    `}

      ${se("index")} {
        let outputIndex = index / i32(workgroupSizeX);
        let reduceLength = ${e()};

        var bestIndex = i32(localId.x);
        var bestValue = uniforms.infinityValue;
        let outputCoords = getCoordsFromIndex(outputIndex);
        for (var k = i32(localId.x); k < reduceLength && outputIndex < uniforms.size;
            k = k + i32(workgroupSizeX)) {
          let candidate = getX(${t()} k);
          if (!isnan(candidate) && candidate ${this.op} bestValue) {
            bestValue = candidate;
            bestIndex = k;
          }
        }
        xBestValues[localId.x] = bestValue;
        xBestIndices[localId.x] = bestIndex;
        workgroupBarrier();

        var reduceSize = min(u32(reduceLength), workgroupSizeX);
        for (var currentSize = reduceSize / 2u; reduceSize > 1u;
            currentSize = reduceSize / 2u) {
          let interval = DIV_CEIL(reduceSize, 2u);
          if (localId.x < currentSize) {
            let candidate = xBestValues[localId.x + interval];
            if (candidate ${this.op} bestValue) {
              bestValue = candidate;
              xBestValues[localId.x] = bestValue;
              xBestIndices[localId.x] = xBestIndices[localId.x + interval];
            }
          }
          reduceSize = interval;
          workgroupBarrier();
        }

        if (localId.x == 0u && outputIndex < uniforms.size) {
          setOutputAtIndexI32(outputIndex, xBestIndices[localId.x]);
        }
      }
    `:`
      ${se("index")} {
        if (index < uniforms.size) {
          let outputCoords = getCoordsFromIndex(index);
          var bestIndex = 0;
          var bestValue = getX(${t()} 0);
          let reduceLength = ${e()};
          for (var i = 1; i < reduceLength; i++) {
            let candidate = getX(${t()} i);
            if (candidate ${this.op} bestValue) {
              bestValue = candidate;
              bestIndex = i;
            }
          }
          setOutputAtIndexI32(index, bestIndex);
        }
      }
      `}};function Cre(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s}=o,a=y.parseAxisParam(s,n.shape),i=S.getAxesPermutation(a,n.shape.length),p=n,u=[];i!=null&&(p=Nr({inputs:{x:n},backend:t,attrs:{perm:i}}),u.push(p),a=S.getInnerMostAxes(a.length,p.shape.length)),S.assertAxesAreInnerMostDims("argMax",[a[0]],p.shape.length);let c=new vc(p.shape,a[0],"max"),l=[{type:"float32",data:[Number.NEGATIVE_INFINITY]}],m=t.runWebGPUProgram(c,[p],"int32",l);return u.forEach(d=>t.disposeData(d.dataId)),m}var EM={kernelName:Vo,backendName:"webgpu",kernelFunc:Cre};function Sre(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s}=o,a=y.parseAxisParam(s,n.shape),i=S.getAxesPermutation(a,n.shape.length),p=n,u=[];i!=null&&(p=Nr({inputs:{x:n},backend:t,attrs:{perm:i}}),u.push(p),a=S.getInnerMostAxes(a.length,p.shape.length)),S.assertAxesAreInnerMostDims("argMin",[a[0]],p.shape.length);let c=new vc(p.shape,a[0],"min"),l=[{type:"float32",data:[Number.POSITIVE_INFINITY]}],m=t.runWebGPUProgram(c,[p],"int32",l);return u.forEach(d=>t.disposeData(d.dataId)),m}var $M={kernelName:Za,backendName:"webgpu",kernelFunc:Sre};var wre=Se({opType:Q.ASIN}),AM={kernelName:ia,backendName:"webgpu",kernelFunc:wre};var Ire=Se({opType:Q.ASINH}),RM={kernelName:ua,backendName:"webgpu",kernelFunc:Ire};var vre=Se({opType:Q.ATAN}),FM={kernelName:pa,backendName:"webgpu",kernelFunc:vre};var kre=ot({opType:ye.ATAN2}),DM={kernelName:la,backendName:"webgpu",kernelFunc:kre};var Nre=Se({opType:Q.ATANH}),OM={kernelName:ca,backendName:"webgpu",kernelFunc:Nre};var Wl=class{constructor(e,t){this.variableNames=["x"],this.uniforms="stride : vec2<i32>, pad : vec2<i32>, dilation : vec2<i32>, convDims : vec2<i32>, filterDims : vec2<i32>,",this.workgroupSize=[128,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`pool2D_${t}`,this.poolType=t}getUserCode(){let e="resultValue = max(value, resultValue);";this.poolType==="avg"&&(e="resultValue = resultValue + value; count = count + 1.0;");let t="resultValue";return this.poolType==="avg"&&(t="resultValue / count"),`
      ${se("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
          let batch = coords[0];
          let xRCCorner = vec2<i32>(coords.yz) * uniforms.stride - uniforms.pad;
          let xRCorner = xRCCorner.x;
          let xCCorner = xRCCorner.y;

          var resultValue = ${this.poolType==="avg"?"0.0":"-1.0 / pow(10.0, -20.0)"};
          var count = 0.0;

          for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + uniforms.dilation.x) {
            let xR = xRCorner + wR;

            if (xR < 0 || xR >= uniforms.convDims.x) {
              continue;
            }

            for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + uniforms.dilation.y) {
              let xC = xCCorner + wC;
              if (xC < 0 || xC >= uniforms.convDims.y) {
                continue;
              }

              let value = getX(batch, xR, xC, coords[3]);
              ${e}
            }
          }

          setOutputAtIndex(index, ${t});
        }
      }
    `}};var Lg=class{constructor(e){this.variableNames=["x"],this.uniforms="stride : vec2<i32>,",this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="poolWithFilterSizeEqualsOne"}getUserCode(){return`
      ${se("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let batch = coords[0];
          let d = coords[3];

          let xRCCorner = coords.yz * uniforms.stride;
          let xRCorner = xRCCorner.x;
          let xCCorner = xRCCorner.y;

          let value = getX(batch, xRCorner, xCCorner, d);
          setOutputAtIndex(index, value);
        }
      }
    `}};function Ul(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{reductionIndices:s,keepDims:a}=o;return qr(n,s,a,"max",t)}var PM={kernelName:yn,backendName:"webgpu",kernelFunc:Ul};function uI(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{keepDims:s,axis:a}=o;return qr(n,a,s,"mean",t)}var MM={kernelName:Sn,backendName:"webgpu",kernelFunc:uI};function Bg(r,e,t,o){if(e.filterWidth===1&&e.filterHeight===1&&y.arraysEqual(e.inShape,e.outShape))return Ft({inputs:{x:r},backend:o});if(e.filterWidth===e.inWidth&&e.filterHeight===e.inHeight&&e.batchSize===1&&e.padInfo.type==="VALID"){let a=r.shape.length,i=de({inputs:{x:r},backend:o,attrs:{shape:[r.shape[a-3]*r.shape[a-2],r.shape[a-1]]}}),p;t==="avg"?p=uI({inputs:{x:i},backend:o,attrs:{axis:0,keepDims:!1}}):(y.assert(t==="max",()=>`Invalid pool type ${t}`),p=Ul({inputs:{x:i},backend:o,attrs:{reductionIndices:0,keepDims:!1}}));let u=de({inputs:{x:p},backend:o,attrs:{shape:e.outShape}});return o.disposeData(i.dataId),o.disposeData(p.dataId),u}let n,s=[{type:"int32",data:[e.strideHeight,e.strideWidth]}];return e.filterHeight===1&&e.filterWidth===1?n=new Lg(e):(t==="avg"?n=new Wl(e,"avg"):(y.assert(t==="max",()=>`Invalid pool type ${t}`),n=new Wl(e,"max")),s.push({type:"int32",data:[e.padInfo.top,e.padInfo.left]},{type:"int32",data:[e.dilationHeight,e.dilationWidth]},{type:"int32",data:[e.inHeight,e.inWidth]},{type:"int32",data:[e.effectiveFilterHeight,e.effectiveFilterWidth]})),o.runWebGPUProgram(n,[r],r.dtype,s)}function Tre(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{filterSize:s,strides:a,pad:i,dimRoundingMode:p}=o,u=1,c=S.computePool2DInfo(n.shape,s,a,u,i,p);return Bg(n,c,"avg",t)}var LM={kernelName:zo,backendName:"webgpu",kernelFunc:Tre};function _re(r){let{inputs:e,backend:t,attrs:o}=r,{a:n,b:s}=e,{transposeA:a,transposeB:i}=o;return Gu({a:n,b:s,transposeA:a,transposeB:i,backend:t})}var BM={kernelName:Wo,backendName:"webgpu",kernelFunc:_re};var Vg=class{constructor(e,t){this.variableNames=["source"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.rank=t.length,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.start=e,this.uniforms=`start : ${Rt(e.length)}, `,this.shaderKey="slice"}getUserCode(){let e=Rt(this.rank),t=Ere(this.rank),o;return this.start.length===1?o=this.outputShape.map((s,a)=>"sourceLoc = uniforms.start + coords;"):o=this.outputShape.map((s,a)=>`sourceLoc.${pI[a]} = uniforms.start.${$o(a)} + coords.${pI[a]};`),`
      ${se("index")} {
        if (index < uniforms.size) {
          var sourceLoc : ${e};
          let coords = getCoordsFromIndex(index);
          ${o.join(`
`)}
          setOutputAtIndex(index, getSource(${t}));
        }
      }
    `}},pI=["x","y","z","w","u","v"];function Ere(r){if(r===1)return"sourceLoc";if(r<=6)return pI.slice(0,r).map(e=>`sourceLoc.${e}`).join(",");throw Error(`Slicing for rank ${r} is not yet supported`)}function ds(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{begin:s,size:a}=o,[i,p]=ut.parseSliceParams(n,s,a);if(ut.assertParamsValid(n,i,p),t.shouldExecuteOnCPU([n])||n.dtype==="string"){let l=t.tensorMap.get(n.dataId),m=fM(l.values,i,p,n.shape,n.dtype);return t.makeTensorInfo(p,n.dtype,m)}if(y.sizeFromShape(p)===0)return t.makeTensorInfo(p,n.dtype,[]);let u=new Vg(i,p),c=[{type:"int32",data:i}];return t.runWebGPUProgram(u,[n],n.dtype,c)}var VM={kernelName:_s,backendName:"webgpu",kernelFunc:ds};var $re=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockShape:s,crops:a}=o;y.assert(n.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGPU backend not implemented yet");let i=s.reduce((b,C)=>b*C),p=S.getReshaped(n.shape,s,i),u=S.getPermuted(p.length,s.length),c=S.getReshapedPermuted(n.shape,s,i),l=S.getSliceBeginCoords(a,s.length),m=S.getSliceSize(c,a,s.length),d=[],f=de({inputs:{x:n},backend:t,attrs:{shape:p}}),h=Nr({inputs:{x:f},backend:t,attrs:{perm:u}}),g=de({inputs:{x:h},backend:t,attrs:{shape:c}}),x=ds({inputs:{x:g},backend:t,attrs:{begin:l,size:m}});return d.push(f),d.push(h),d.push(g),d.forEach(b=>t.disposeData(b.dataId)),x},zM={kernelName:xs,backendName:"webgpu",kernelFunc:$re};var Are=`
  fn bincount_write(index: i32, value: f32) {
    var oldValue = atomicLoad(& (result[index]));
    var exchanged = false;
    for (; !exchanged;) {
      let newValueF32 = bitcast<f32>(oldValue) + value;
      let newValue = bitcast<i32>(newValueF32);
      let res = atomicCompareExchangeWeak(
          &(result[index]), oldValue, newValue);
      oldValue = res.old_value;
      exchanged = res.exchanged;
    }
  }
`,Rre=`
  fn bincount_write(index: i32, value: f32) {
    result[index] = value;
  }
`,kc=class{constructor(e,t,o=!1){this.outputShape=[],this.variableNames=["x"],this.uniforms="binCountSize : i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.hasWeights=!0,this.binaryOutput=!1,this.outputShape=e,this.rank=e.length,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.binaryOutput=o,o&&(this.atomic=!1),this.hasWeights=t,this.hasWeights&&this.variableNames.push("w"),this.shaderKey=`bincount_${this.hasWeights}_${this.binaryOutput}_${this.rank}`}getUserCode(){return`
    ${this.binaryOutput?Rre:Are}
  ${se("index")} {
    ${this.rank===1?`if (index < uniforms.xShape) {
      let indexVal = i32(getX(index));
      if (indexVal < uniforms.binCountSize) {
        let value = ${this.binaryOutput?1:this.hasWeights?"f32(getW(index))":"1."};
        bincount_write(indexVal, value);
      }
    }`:`let coord = getCoordsFromIndex(index);
    if (coordsInBounds2D(coord, uniforms.xShape)) {
      let indexVal = i32(getX(coord[0], coord[1]));
      if (indexVal < uniforms.binCountSize) {
        let value = ${this.binaryOutput?1:this.hasWeights?"f32(getW(coord[0], coord[1]))":"1."};
        bincount_write(coord.x * uniforms.binCountSize + indexVal, value);
      }
    }`}
  }
  `}};function Fre(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a}=o,i=y.sizeFromShape(n.shape),u=y.sizeFromShape(s.shape)>0,c=[a],l=s.dtype,m=dr({backend:t,attrs:{shape:c,value:0,dtype:l}}),d=new kc([i],u),f=[{type:"int32",data:[a]}],h=u?[n,s]:[n];return t.runWebGPUProgram(d,h,l,f,m)}var WM={kernelName:Ja,backendName:"webgpu",kernelFunc:Fre};var cI=ot({opType:ye.NOT_EQUAL,dtype:"bool",cpuKernelImpl:uM}),UM={kernelName:Nn,backendName:"webgpu",kernelFunc:cI};function qa(r){let{inputs:e,backend:t}=r,{input:o}=e,n=t.tensorMap.get(o.dataId);return Ft({inputs:{x:n.complexTensorInfos.real},backend:t})}var GM={kernelName:ai,backendName:"webgpu",kernelFunc:qa};function HM(r,e){let t=new Ro(r.shape,Q.TO_INT),o=e.runWebGPUProgram(t,[r],"int32");return{dataId:o.dataId,shape:o.shape,dtype:o.dtype}}function lI(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{dtype:s}=o;if(s==="complex64"){if(n.dtype==="complex64")return Ft({inputs:{x:n},backend:t});let a=Vr(n.shape),i=lI({inputs:{x:n},backend:t,attrs:{dtype:"float32"}}),p=po({inputs:{real:i,imag:a},backend:t});return a.dispose(),t.disposeData(i.dataId),p}if(n.dtype==="complex64"){let a=qa({inputs:{input:n},backend:t}),i=lI({inputs:{x:a},backend:t,attrs:{dtype:s}});return t.disposeData(a.dataId),i}if(!y.hasEncodingLoss(n.dtype,s)){let a=Ft({inputs:{x:n},backend:t});return{dataId:a.dataId,shape:a.shape,dtype:s}}if(t.shouldExecuteOnCPU([n])){let a=t.tensorMap.get(n.dataId).values,[i,p,u]=U3(a,n.shape,n.dtype,s);return t.makeTensorInfo(i,p,u)}if(s==="int32")return HM(n,t);if(s==="bool"){let a=t.makeTensorInfo([],"bool",y.getTypedArrayFromDType("bool",1)),p=cI({inputs:{a:n,b:a},backend:t});return t.disposeData(a.dataId),p}throw new Error(`Error in Cast: failed to cast ${n.dtype} to ${s}`)}var qM={kernelName:co,backendName:"webgpu",kernelFunc:lI};var Dre=Se({opType:Q.CEIL,cpuKernelImpl:G3}),KM={kernelName:Uo,backendName:"webgpu",kernelFunc:Dre};var zg=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workPerThread=4,this.workgroupSize=[64,1,1],this.isVec4=!0,this.size=!0,this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.shaderKey="clipVec4"}getUserCode(){return`
      ${se("index")} {
        if(index < uniforms.size) {
          let value = getAByOutputIndex(index);
          var clampedValue : vec4<f32>;
          for (var i = 0; i < 4; i = i + 1) {
            if (isnan(value[i])) {
              clampedValue[i] = value[i];
            } else {
              clampedValue[i] = clamp(value[i], uniforms.minVal, uniforms.maxVal);
            }
          }

          setOutputAtIndex(index, clampedValue);
        }
      }
    `}};var Wg=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="clip"}getUserCode(){return`
      ${se("index")} {
        if(index < uniforms.size) {
          let value = getAByOutputIndex(index);
          if (isnan(value)) {
            setOutputAtIndex(index, value);
            return;
          }
          setOutputAtIndex(index, clamp(value, uniforms.minVal, uniforms.maxVal));
        }
      }
    `}};function Ore(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{clipValueMin:s,clipValueMax:a}=o,i,p=[{type:"float32",data:[s]},{type:"float32",data:[a]}];return y.sizeFromShape(n.shape)%4===0?i=new zg(n.shape):i=new Wg(n.shape),t.runWebGPUProgram(i,[n],n.dtype,p)}var jM={kernelName:lo,backendName:"webgpu",kernelFunc:Ore};var Ug=class{constructor(e){this.uniforms="",this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=S.computeOutShape(e,1),this.variableNames=e.map((t,o)=>`T${o}`),this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.offsetLength=e.length-1;for(let t=0;t<this.offsetLength;t++)this.uniforms+=`offset${t} : i32,`;this.shaderKey="concat"}getUserCode(){let e=[];if(this.offsetLength>0){e.push("if (yC < uniforms.offset0){ setOutputAtCoords(coords.x, coords.y, getT0(yR, yC)); }");for(let s=1;s<this.offsetLength;s++)e.push(`else if (yC < uniforms.offset${[s]}){ setOutputAtCoords(coords.x, coords.y, getT${s}(yR, yC - uniforms.offset${s-1})); }`);let o=this.offsetLength,n=this.offsetLength-1;e.push(`else { setOutputAtCoords(coords.x, coords.y, getT${o}(yR, yC - uniforms.offset${n})); }`)}else e.push("setOutputAtCoords(coords.x, coords.y, getT0(yR, yC));");return`
      ${se("index")} {
        for(var i = 0; i < ${this.workPerThread}; i = i + 1) {
          let flatIndex = index * ${this.workPerThread} + i;
          if(flatIndex < uniforms.size) {
            let coords = getCoordsFromIndex(flatIndex);
            let yR = coords.x;
            let yC = coords.y;

            ${e.join(`
        `)}
          }
        }
      }
    `}};function qu(r){let{inputs:e,backend:t}=r,{input:o}=e,n=t.tensorMap.get(o.dataId);return Ft({inputs:{x:n.complexTensorInfos.imag},backend:t})}var XM={kernelName:si,backendName:"webgpu",kernelFunc:qu};function Nc(r,e,t){let o=r[0].dtype;if(o==="complex64"){let f=r.map(C=>qa({inputs:{input:C},backend:t})),h=r.map(C=>qu({inputs:{input:C},backend:t})),g=Nc(f,e,t),x=Nc(h,e,t),b=po({inputs:{real:g,imag:x},backend:t});return f.forEach(C=>t.disposeData(C.dataId)),h.forEach(C=>t.disposeData(C.dataId)),t.disposeData(g.dataId),t.disposeData(x.dataId),b}let n=t.shouldExecuteOnCPU(r);if(o==="string"&&(n=!0),n){let f=r.map(k=>{let $=[-1,y.sizeFromShape(k.shape.slice(e))];return de({inputs:{x:k},backend:t,attrs:{shape:$}})}),h=f.map(k=>({vals:t.readSync(k.dataId),shape:k.shape})),g=S.computeOutShape(f.map(k=>k.shape),1),x=f[0].shape[0]===1,b=H3(h,g,o,x),C=S.computeOutShape(r.map(k=>k.shape),e),w=t.makeTensorInfo(C,o,b);return f.forEach(k=>t.disposeData(k.dataId)),w}let s=t.device.limits.maxStorageBuffersPerShaderStage-1;if(r.length>s){let f=[];for(let g=0;g<r.length;g+=s){let x=r.slice(g,g+s);f.push(Nc(x,e,t))}let h=Nc(f,e,t);for(let g of f)t.disposeData(g.dataId);return h}let{tensors2D:a,outShape:i}=Pre(r,e,t),p=a.map(f=>f.shape),u=new Ug(p),c=[],l=new Array(p.length-1);if(l.length>0){l[0]=p[0][1],c.push({type:"int32",data:[l[0]]});for(let f=1;f<l.length;f++)l[f]=l[f-1]+p[f][1],c.push({type:"int32",data:[l[f]]})}let m=t.runWebGPUProgram(u,a,a[0].dtype,c);a.forEach(f=>t.disposeData(f.dataId));let d=de({inputs:{x:m},backend:t,attrs:{shape:i}});return t.disposeData(m.dataId),d}function Pre(r,e,t){let o=S.computeOutShape(r.map(s=>s.shape),e);return{tensors2D:r.map(s=>de({inputs:{x:s},backend:t,attrs:{shape:[y.sizeFromShape(s.shape.slice(0,e)),y.sizeFromShape(s.shape.slice(e))]}})),outShape:o}}function mI(r){let{inputs:e,backend:t,attrs:o}=r,{axis:n}=o,s=y.parseAxisParam(n,e[0].shape)[0],a=e.map(u=>u.shape);S.assertParamsConsistent(a,s);let i=S.computeOutShape(e.map(u=>u.shape),s);if(y.sizeFromShape(i)===0)return t.makeTensorInfo(i,e[0].dtype,[]);let p=e.filter(u=>y.sizeFromShape(u.shape)>0);return p.length===1?Ft({inputs:{x:p[0]},backend:t}):Nc(p,s,t)}var YM={kernelName:ys,backendName:"webgpu",kernelFunc:mI};function Mre(r,e,t,o,n=!1,s=null,a=!1,i=4,p=4,u=4){let c=R=>{switch(R){case 1:return"resData = x[xIndex];";case 3:return"resData = vec3<f32>(x[xIndex], x[xIndex + 1], x[xIndex + 2]);";case 4:return"resData = x[xIndex / 4];";default:throw new Error(`innerElementSize ${R} is not supported.`)}},l=R=>{switch(R){case 1:return"return W[row * uniforms.wShape[3] + colIn];";case 4:return"return W[row * uniforms.wShape[3] / 4 + colIn];";default:throw new Error(`innerElementSize ${R} is not supported.`)}},m=r?`
      let coord = vec4<i32>(batch, xRow, xCol, xCh);
      `:`
      let coord = vec4<i32>(batch, xCh, xRow, xCol);
      `,d=r?`
      let coords = vec4<i32>(
        batch,
        row / outWidth,
        row % outWidth,
        col);
      `:`
      let coords = vec4<i32>(
        batch,
        row,
        col / outWidth,
        col % outWidth);
      `,f=r?"uniforms.xShape[1]":"uniforms.xShape[2]",h=r?"uniforms.xShape[2]":"uniforms.xShape[3]",g=r?"row":"col",x=r?"col":"row",b=`
      let inChannels = uniforms.wShape[2];
      let outWidth = ${r?"uniforms.outShape[2]":"uniforms.outShape[3]"};
      let outRow = ${g} / outWidth;
      let outCol = ${g} % outWidth;

      let WRow = ${x} / (uniforms.filterDims[1] * inChannels);
      let WCol = ${x} / inChannels % uniforms.filterDims[1];
      let xRow = outRow * uniforms.stride[0] + uniforms.dilation[0] * WRow - uniforms.pad[0];
      let xCol = outCol * uniforms.stride[1] + uniforms.dilation[1] * WCol - uniforms.pad[1];
      let xCh = ${x} % inChannels;
      var resData = ${kt(i)}(0.0);
      // The bounds checking is always needed since we use it to pad zero for
      // the 'same' padding type.
      if (xRow >= 0 && xRow < ${f} && xCol >= 0 && xCol < ${h}) {
        ${m}
        let xIndex = getIndexFromCoords4D(coord, uniforms.xShape);
        ${c(i)}
      }
      return resData;`,C=r?e&&o?`
      let col = colIn * ${i};
      ${b}`:`
      let col = colIn * ${i};
      if (row < uniforms.dimAOuter && col < uniforms.dimInner) {
        ${b}
      }
      return ${kt(i)}(0.0);`:o&&t?`
      let col = colIn * ${i};
      ${b}`:`
      let col = colIn * ${i};
      if (row < uniforms.dimInner && col < uniforms.dimBOuter) {
        ${b}
      }
      return ${kt(i)}(0.0);`,w=`${l(p)}`,k=kt(u),_=r?kt(i):kt(p),$=r?kt(p):kt(i);return`
      ${ur(s,a,u===4,4)}
      fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${_} {
        ${r?C:w}
      }

      fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${$} {
        ${r?w:C}
      }

      fn mm_write(batch: i32, row : i32, colIn : i32, valueIn : ${k}) {
        let col = colIn * ${u};
        if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)
        {
        var value = valueIn;
        let outWidth = ${r?"uniforms.outShape[2]":"uniforms.outShape[3]"};
        ${d}
        ${Hr(n,s)}
        setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
        }
      }`}var Gg=class{constructor(e,t,o,n,s=!1,a=null,i=!1,p=!1){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.isVec4=((e.inChannels%4===0||e.inChannels%3===0)&&this.isChannelsLast||e.outWidth%4===0&&!this.isChannelsLast)&&e.outChannels%4===0,this.dispatchLayout=this.isChannelsLast?{x:[3],y:[1,2],z:[0]}:{x:[2,3],y:[1],z:[0]},this.workgroupSize=Ml(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=Ll(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread),this.isVec4?(this.isChannelsLast&&e.inChannels%4!==0?(this.innerElementSize=3,this.variableTypes=["f32","vec4<f32>"]):(this.innerElementSize=4,this.variableTypes=["vec4<f32>","vec4<f32>"]),s&&(this.variableNames.push("bias"),this.variableTypes.push("vec4<f32>")),i&&(this.variableNames.push("preluActivationWeights"),this.variableTypes.push("vec4<f32>"))):(this.innerElementSize=this.elementsPerThread[0],s&&this.variableNames.push("bias"),i&&this.variableNames.push("preluActivationWeights")),this.sequentialAccessByThreads=p,this.addBias=s,this.activation=a,this.hasPreluActivationWeights=i,this.tileAOuter=this.workgroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workgroupSize[0]*this.elementsPerThread[0],this.tileInner=Math.max(this.workgroupSize[0]*this.innerElementSize,this.workgroupSize[1]),this.fitAOuter=t%this.tileAOuter===0,this.fitBOuter=o%this.tileBOuter===0,this.fitInner=n%this.tileInner===0,this.shaderKey=`conv2DMM_${this.elementsPerThread}_${this.activation}}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.innerElementSize}_${this.isChannelsLast}_${this.sequentialAccessByThreads}`}getUserCode(){let e=this.isVec4?Wu(this.elementsPerThread,this.workgroupSize,!this.isChannelsLast,this.tileInner):Uu(this.elementsPerThread,this.workgroupSize,!this.isChannelsLast,this.tileInner,!1,null,this.sequentialAccessByThreads),t=this.isVec4?[this.innerElementSize,4,4]:[1,1,1];return`
    ${Mre(this.isChannelsLast,this.fitAOuter,this.fitBOuter,this.fitInner,this.addBias,this.activation,this.hasPreluActivationWeights,t[0],t[1],t[2])}
    ${e}
  `}};var Hg=class{constructor(e,t=!1,o=null,n=!1){this.variableNames=["x","W"],this.uniforms="filterDims: vec2<i32>, pad: vec2<i32>, stride: vec2<i32>, dilation: vec2<i32>,",this.workgroupSize=[4,4,8],this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.dispatchLayout=this.isChannelsLast?{x:[2],y:[1],z:[0,3]}:{x:[3],y:[2],z:[0,1]},this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.addBias=t,this.activation=o,this.hasPreluActivationWeights=n,t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`conv2dnaive_${this.activation}_${this.isChannelsLast}`}getUserCode(){return`
       ${ur(this.activation,this.hasPreluActivationWeights,!1,4)}
       fn readInp(batch : i32, row : i32, col : i32, chan : i32) -> f32{
         let coords = vec4<i32>(batch, row, col, chan);
         if (coordsInBounds4D(coords, uniforms.xShape)) {
           return  getX(batch, row, col, chan);
         } else {
          return 0.0;
         }
       }
       fn readFilt(row : i32, col : i32, xChannel : i32, outChannel : i32) -> f32{
         let coords = vec4<i32>(row, col, xChannel, outChannel);
         if(coordsInBounds4D(coords, uniforms.wShape)) {
           return getW(row, col, xChannel, outChannel);
          } else {
            return 0.0;
          }
       }
       fn writeResult(batch : i32, row : i32, col : i32, chan : i32, valueIn : f32) {
         let coords = ${this.isChannelsLast?"vec4<i32>(batch, row, col, chan);":"vec4<i32>(batch, chan, row, col);"}
         if (coordsInBounds4D(coords, uniforms.outShape)) {
           var value = valueIn;
           ${Hr(this.addBias,this.activation)}
           setOutputAtCoords(coords.x, coords.y, coords.z, coords.w, value);
         }
       }
       ${se("index")} {
         let coords = getOutputCoords();
         let batch = coords[0];
         let outChannel = ${this.isChannelsLast?"coords[3];":"coords[1];"}
         let outRow = ${this.isChannelsLast?"coords[1];":"coords[2];"}
         let outCol = ${this.isChannelsLast?"coords[2];":"coords[3];"}
         var acc : f32 = 0.0;
         for (var row = 0; row < uniforms.filterDims[0]; row = row + 1) {
           for (var col = 0; col < uniforms.filterDims[1]; col = col + 1) {
             let xRow = outRow * uniforms.stride[0] + uniforms.dilation[0] * row - uniforms.pad[0];
             let xCol = outCol * uniforms.stride[1] + uniforms.dilation[1] * col - uniforms.pad[1];
             for (var xChannel = 0; xChannel < ${this.isChannelsLast?"uniforms.xShape[3];":"uniforms.xShape[1];"} xChannel = xChannel + 1) {
               ${this.isChannelsLast?"let v = readInp(batch, xRow, xCol, xChannel);":"let v = readInp(batch, xChannel, xRow, xCol);"}
               let f = readFilt(row, col, xChannel, outChannel);
               acc = acc + v * f;
             }
           }
         }
         writeResult(batch, outRow, outCol, outChannel, acc);
       }
     `}};var qg=class{constructor(e,t){this.variableNames=["x"],this.uniforms=`pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>, outWidth : i32, itemsPerBlockRow : i32,
       inChannels : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=t,this.shaderKey=`im2col_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?1:2,t=this.isChannelsLast?2:3,o=this.isChannelsLast?"coords[1]":"coords[2]",n=this.isChannelsLast?"coords[2]":"coords[1]",s=this.isChannelsLast?"getX(batch, xRow, xCol, ch)":"getX(batch, ch, xRow, xCol)";return`
    ${se("index")} {
      let coords = getCoordsFromIndex(index);
      if(index < uniforms.size) {
        let batch = coords[0];
        let row = ${o};
        let col = ${n};
        let offsetY = (row / uniforms.outWidth) * uniforms.stride[0] - uniforms.pad[0];
        let xRow = offsetY + uniforms.dilation[0] * (col / uniforms.itemsPerBlockRow);
        var value = 0.0;
        if(xRow < uniforms.xShape[${e}] && xRow >= 0) {
          let offsetX = (row % uniforms.outWidth) * uniforms.stride[1] -
              uniforms.pad[1];
          let xCol = offsetX + uniforms.dilation[1] * ((col %
              uniforms.itemsPerBlockRow) / uniforms.inChannels);
          let ch = col % uniforms.inChannels;
          if(xCol < uniforms.xShape[${t}] && xCol >= 0) {
            value = ${s};
          }
        }
        setOutputAtIndex(index, value);
      }
    }
   `}};function Kg(r,e){let t=r.length;return t>=3?e?[...r.slice(0,-3),r[t-3]*r[t-2],r[t-1]]:[...r.slice(0,-3),r[t-3],r[t-2]*r[t-1]]:!e&&t===1&&r[0]>1?[r[0],1]:null}function Lre({x:r,filter:e,convInfo:t,backend:o,bias:n=null,preluActivationWeights:s=null,leakyreluAlpha:a=0,activation:i=null}){let p=t.dataFormat==="channelsLast",u=!p,c=!1,l=p&&t.filterHeight===t.inHeight&&t.filterWidth===t.inWidth&&t.padInfo.type==="VALID",m=[],d,f;if(l){let x=t.inHeight*t.inWidth*t.inChannels;d=de({inputs:{x:r},backend:o,attrs:{shape:[1,t.batchSize,x]}}),f=de({inputs:{x:e},backend:o,attrs:{shape:[1,x,t.outChannels]}})}else d=de({inputs:{x:r},backend:o,attrs:{shape:p?[t.batchSize,t.inHeight*t.inWidth,t.inChannels]:[t.batchSize,t.inChannels,t.inHeight*t.inWidth]}}),f=de({inputs:{x:e},backend:o,attrs:{shape:[1,t.inChannels,t.outChannels]}});if(m.push(d),m.push(f),s!=null){let x=Kg(s.shape,p);x!=null&&(s=de({inputs:{x:s},backend:o,attrs:{shape:x}}),m.push(s))}if(n!=null){let x=Kg(n.shape,p);x!=null&&(n=de({inputs:{x:n},backend:o,attrs:{shape:x}}),m.push(n))}let h=Gu({a:p?d:f,b:p?f:d,transposeA:u,transposeB:c,backend:o,bias:n,activation:i,preluActivationWeights:s,leakyreluAlpha:a}),g=de({inputs:{x:h},backend:o,attrs:{shape:t.outShape}});m.push(h);for(let x of m)o.disposeData(x.dataId);return g}function Bre({x:r,filter:e,convInfo:t,backend:o,bias:n=null,preluActivationWeights:s=null,leakyreluAlpha:a=0,activation:i=null}){let{filterWidth:p,filterHeight:u,inChannels:c,strideWidth:l,strideHeight:m,padInfo:d,outWidth:f,outHeight:h,dilationWidth:g,dilationHeight:x,dataFormat:b}=t,C=b==="channelsLast",w=p*u*c,k=h*f,_=C?[t.batchSize,k,w]:[t.batchSize,w,k],$=new qg(_,C),A=[{type:"int32",data:[d.top,d.left]},{type:"int32",data:[m,l]},{type:"int32",data:[x,g]},{type:"int32",data:[f]},{type:"int32",data:[c*p]},{type:"int32",data:[c]}],R=o.runWebGPUProgram($,[r],r.dtype,A),D=[];D.push(R);let P=de({inputs:{x:e},backend:o,attrs:{shape:[1,w,-1]}});if(D.push(P),s!=null){let U=Kg(s.shape,C);U!=null&&(s=de({inputs:{x:s},backend:o,attrs:{shape:U}}),D.push(s))}if(n!=null){let U=Kg(n.shape,C);U!=null&&(n=de({inputs:{x:n},backend:o,attrs:{shape:U}}),D.push(n))}let W=Gu({a:C?R:P,b:C?P:R,transposeA:!C,transposeB:!1,backend:o,bias:n,activation:i,preluActivationWeights:s,leakyreluAlpha:a}),V=de({inputs:{x:W},backend:o,attrs:{shape:t.outShape}});D.push(W);for(let U of D)o.disposeData(U.dataId);return V}function jg({x:r,filter:e,convInfo:t,backend:o,bias:n=null,preluActivationWeights:s=null,leakyreluAlpha:a=0,activation:i=null}){let p=n!=null,u=s!=null,c=t.dataFormat==="channelsLast",l=c&&t.filterHeight===t.inHeight&&t.filterWidth===t.inWidth&&t.padInfo.type==="VALID",m=O().getBool("WEBGPU_USE_NAIVE_CONV2D_DEBUG");if(!m&&(l||t.filterHeight===1&&t.filterWidth===1&&t.dilationHeight===1&&t.dilationWidth===1&&t.strideHeight===1&&t.strideWidth===1&&(t.padInfo.type==="SAME"||t.padInfo.type==="VALID")))return Lre({x:r,filter:e,convInfo:t,backend:o,bias:n,activation:i,preluActivationWeights:s,leakyreluAlpha:a});let d=O().getNumber("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL"),f=d>0?d:o.thresholdToIncreaseWorkgroups,h=t.batchSize*Math.ceil(t.outHeight*t.outWidth/32)*Math.ceil(t.outChannels/32);if(O().getBool("WEBGPU_CONV_SEPARATE_IM2COL_SHADER")||h<=f)return Bre({x:r,filter:e,convInfo:t,backend:o,bias:n,preluActivationWeights:s,leakyreluAlpha:a,activation:i});let g,x=[t.padInfo.top,t.padInfo.left],b=[{type:"int32",data:[t.filterHeight,t.filterWidth]},{type:"int32",data:[...x]},{type:"int32",data:[t.strideHeight,t.strideWidth]},{type:"int32",data:[t.dilationHeight,t.dilationWidth]}];if(m)g=new Hg(t,p,i,u);else{let _=c?t.outHeight*t.outWidth:t.outChannels,$=c?t.outChannels:t.outHeight*t.outWidth,A=t.filterHeight*t.filterWidth*t.inChannels;b.push({type:"int32",data:[_]},{type:"int32",data:[$]},{type:"int32",data:[A]});let R=o.adapterInfo.isIntel();g=new Gg(t,_,$,A,p,i,u,R)}let C=[],w=[r,e];p&&(!c&&n.shape.length===1&&(n=de({inputs:{x:n},backend:o,attrs:{shape:[n.shape[0],1,1]}}),C.push(n)),w.push(n)),u&&(!c&&s.shape.length===1&&(s=de({inputs:{x:s},backend:o,attrs:{shape:[s.shape[0],1,1]}}),C.push(s)),w.push(s)),i==="leakyrelu"&&(b.push({type:"float32",data:[a]}),g.uniforms+=" alpha : f32,");let k=o.runWebGPUProgram(g,w,r.dtype,b);for(let _ of C)o.disposeData(_.dataId);return k}function Vre(r){let{inputs:e,attrs:t,backend:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dataFormat:p,dilations:u,dimRoundingMode:c}=t,l=S.convertConv2DDataFormat(p),m=S.computeConv2DInfo(n.shape,s.shape,a,u,i,c,!1,l);return jg({x:n,filter:s,convInfo:m,backend:o})}var QM={kernelName:Go,backendName:"webgpu",kernelFunc:Vre};function zre(r=4){let e=s=>{switch(s){case 1:return"return W[getIndexFromCoords4D(coord, uniforms.wShape)];";case 4:return`
            let coord1 = vec4<i32>(coordX, coordY, col + 1, rowInner);
            let coord2 = vec4<i32>(coordX, coordY, col + 2, rowInner);
            let coord3 = vec4<i32>(coordX, coordY, col + 3, rowInner);
            let v0 = W[getIndexFromCoords4D(coord, uniforms.wShape)];
            let v1 = W[getIndexFromCoords4D(coord1, uniforms.wShape)];
            let v2 = W[getIndexFromCoords4D(coord2, uniforms.wShape)];
            let v3 = W[getIndexFromCoords4D(coord3, uniforms.wShape)];
            return vec4<f32>(v0, v1, v2, v3);
            `;default:throw new Error(`innerElementSize ${s} is not supported.`)}},o=`if (row < uniforms.dimAOuter && col < uniforms.dimInner) {
        ${`
      let outRow = row / uniforms.outShape[2];
      let outCol = row % uniforms.outShape[2];

      let WRow = col / (uniforms.filterDims[1] * uniforms.outBackprop[3]);
      let WCol = col / uniforms.outBackprop[3] % uniforms.filterDims[1];
      let xR = f32(outRow - uniforms.pads[0] + WRow) / f32(uniforms.stride[0]);
      let xC = f32(outCol - uniforms.pads[1] + WCol) / f32(uniforms.stride[1]);
      if (xR < 0.0 || xR >= f32(uniforms.outBackprop[1]) || fract(xR) > 0.0) {
        return ${kt(r)}(0.0);
      }
      if (xC < 0.0 || xC >= f32(uniforms.outBackprop[2]) || fract(xC) > 0.0) {
        return ${kt(r)}(0.0);
      }
      let coord = vec4<i32>(
          batch,
          i32(xR),
          i32(xC),
          col % uniforms.outBackprop[3]);
      return x[getIndexFromCoords4D(coord, uniforms.xShape)/${r}];`}
      }
      return ${kt(r)}(0.0);`;return`
  fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${kt(r)} {
    let col = colIn * ${r};
    ${o}
  }

  fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${kt(r)} {
    let col = colIn * ${r};
    let coordX = uniforms.filterDims.x - 1 -
        row / (uniforms.filterDims[1] * uniforms.outBackprop[3]);
    let coordY = uniforms.filterDims.y - 1 -
        (row / uniforms.outBackprop[3]) % uniforms.filterDims[1];
    if (row < uniforms.dimInner && col < uniforms.dimBOuter &&
        coordX >= 0 && coordY >= 0) {
      let rowInner = row % uniforms.outBackprop[3];
      let coord = vec4<i32>(coordX, coordY, col, rowInner);
      ${e(r)}
    }
    return ${kt(r)}(0.0);
  }

  fn mm_write(batch: i32, row : i32, colIn : i32, valueInput : ${kt(r)}) {
    let col = colIn * ${r};
    if (row < uniforms.dimAOuter && (col + ${r-1}) < uniforms.dimBOuter) {
      var value = valueInput;
      let outCoord = vec4<i32>(
          batch,
          row / uniforms.outShape[2],
          row % uniforms.outShape[2],
          col);
      result[getIndexFromCoords4D(outCoord, uniforms.outShape)/${r}] = value;
    }
  }`}var Xg=class{constructor(e){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, stride : vec2<i32>, outBackprop : vec4<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.inShape,y.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),this.isVec4=e.inChannels%4===0&&e.outChannels%4===0,this.dispatchLayout={x:[3],y:[1,2],z:[0]},this.workgroupSize=Ml(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=Ll(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread),this.isVec4&&(this.variableTypes=["vec4<f32>","f32"]),this.shaderKey=`conv2DDerInputMM_${this.isVec4}_${this.elementsPerThread}`}getUserCode(){let e=this.isVec4?Wu(this.elementsPerThread,this.workgroupSize):Uu(this.elementsPerThread,this.workgroupSize);return`
    ${zre(this.isVec4?4:1)}
    ${e}
    `}};var Yg=class{constructor(e){this.variableNames=["dy","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, stride : vec2<i32>, outBackprop : vec4<i32>,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",this.shaderKey=`conv2DDerInput_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?1:2,t=this.isChannelsLast?2:3,o=this.isChannelsLast?3:1;return`
    ${se("index")} {
      if(index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let batch = coords[0];
        let d1 = coords[${o}];

        let dyCorner = vec2<i32>(coords[${e}], coords[${t}]) - uniforms.pads;
        let dyRCorner = dyCorner.x;
        let 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.
        var dotProd = 0.0;
        for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + 1) {
          let dyR = (f32(dyRCorner) + f32(wR)) / f32(uniforms.stride.x);
          let wRPerm = uniforms.filterDims.x - 1 - wR;
          if (dyR < 0.0 || dyR >= f32(uniforms.outBackprop[1]) || fract(dyR) > 0.0 ||
              wRPerm < 0) {
            continue;
          }
          let idyR = i32(dyR);

          for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + 1) {
            let dyC = (f32(dyCCorner) + f32(wC)) / f32(uniforms.stride.y);
            let wCPerm = uniforms.filterDims.y - 1 - wC;
            if (dyC < 0.0 || dyC >= f32(uniforms.outBackprop[2]) ||
                fract(dyC) > 0.0 || wCPerm < 0) {
              continue;
            }
            let idyC = i32(dyC);

            for (var d2 = 0; d2 < uniforms.outBackprop[3]; d2 = d2 + 1) {
              if (${this.isChannelsLast}) {
                let xValue = getDy(batch, idyR, idyC, d2);
                let wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd = dotProd + xValue * wValue;
              } else {
                let xValue = getDy(batch, d2, idyR, idyC);
                let wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd = dotProd + xValue * wValue;
              }

            }
          }
        }
        setOutputAtIndex(index, dotProd);
      }
    }
  `}};function Wre(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{inputShape:a,strides:i,pad:p,dataFormat:u,dimRoundingMode:c}=o,l=S.convertConv2DDataFormat(u),m=S.computeConv2DInfo(a,s.shape,i,1,p,c,!1,l),d=[{type:"int32",data:[m.filterHeight,m.filterWidth]},{type:"int32",data:[m.filterHeight-1-m.padInfo.top,m.filterWidth-1-m.padInfo.left]},{type:"int32",data:[m.strideHeight,m.strideWidth]},{type:"int32",data:[m.batchSize,m.outHeight,m.outWidth,m.outChannels]}],f;if(O().getBool("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE")||m.filterHeight<=2&&m.filterWidth<=2&&m.outChannels<=16&&m.inChannels===1)f=new Yg(m);else{f=new Xg(m);let h=m.inHeight*m.inWidth,g=m.inChannels,x=m.filterHeight*m.filterWidth*m.outChannels;d.push({type:"uint32",data:[h]},{type:"uint32",data:[g]},{type:"uint32",data:[x]})}return t.runWebGPUProgram(f,[n,s],"float32",d)}var ZM={kernelName:Ho,backendName:"webgpu",kernelFunc:Wre};var Ure=Se({opType:Q.COS}),JM={kernelName:qo,backendName:"webgpu",kernelFunc:Ure};var Gre=Se({opType:Q.COSH}),eL={kernelName:Ko,backendName:"webgpu",kernelFunc:Gre};var Qg=class{constructor(e,t,o,n){this.variableNames=["Image","Boxes","BoxInd"],this.uniforms="extrapolationValue : f32,",this.workgroupSize=[64,1,1],this.size=!0;let[s]=t;this.outputShape=[s,o[0],o[1],e],this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.methodId=n==="bilinear"?1:0,this.cropHeightBiggerThan1=this.outputShape[1]>1,this.cropWidthBiggerThan1=this.outputShape[2]>1,this.shaderKey=`cropAndResize_${this.methodId}_${this.cropHeightBiggerThan1}_${this.cropWidthBiggerThan1}`}getUserCode(){let[e,t]=["f32(uniforms.imageShape[1] - 1)","f32(uniforms.imageShape[2] - 1)"],[o,n,s]=this.cropHeightBiggerThan1?[`(${e} / f32(uniforms.outShape[1] - 1))`,"(y2-y1) * height_ratio",`y1*${e} + f32(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${e}`],[a,i,p]=this.cropWidthBiggerThan1?[`(${t} / f32(uniforms.outShape[2] - 1))`,"(x2-x1) * width_ratio",`x1*${t} + f32(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${t}`];return`
    ${se("index")} {
      if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
        let height_ratio = f32(${o});
        let width_ratio = f32(${a});
        let b = coords[0];
        let y = coords[1];
        let x = coords[2];
        let d = coords[3];
        // get box vals
        let y1 = getBoxes(b, 0);
        let x1 = getBoxes(b, 1);
        let y2 = getBoxes(b, 2);
        let x2 = getBoxes(b, 3);
        // get image in batch index
        let bInd = i32(round(getBoxInd(b)));
        if(bInd < 0 || bInd >= uniforms.outShape[0]) {
          return;
        }
        let height_scale = ${n};
        let width_scale = ${i};
        let in_y = ${s};
        if( in_y < 0.0 || in_y > ${e} ) {
          setOutputAtIndex(index, uniforms.extrapolationValue);
          return;
        }
        let in_x = ${p};
        if( in_x < 0.0 || in_x > ${t} ) {
          setOutputAtIndex(index, uniforms.extrapolationValue);
          return;
        }
        let sourceFracIndexCR = vec2<f32>(in_x,in_y);
        if(${this.methodId} == 1) {
          // Compute the four integer indices.
          let sourceFloorCR = vec2<i32>(sourceFracIndexCR);
          let sourceCeilCR = vec2<i32>(ceil(sourceFracIndexCR));
          let topLeft = getImage(bInd, sourceFloorCR.y, sourceFloorCR.x, d);
          let bottomLeft = getImage(bInd, sourceCeilCR.y, sourceFloorCR.x, d);
          let topRight = getImage(bInd, sourceFloorCR.y, sourceCeilCR.x, d);
          let bottomRight = getImage(bInd, sourceCeilCR.y, sourceCeilCR.x, d);
          let fracCR = sourceFracIndexCR - vec2<f32>(sourceFloorCR);
          let top = topLeft + (topRight - topLeft) * fracCR.x;
          let bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
          let newValue = top + (bottom - top) * fracCR.y;
          setOutputAtIndex(index, newValue);
        } else {
          // Compute the coordinators of nearest neighbor point.
          let sourceNearestCR = vec2<i32>(floor(
            sourceFracIndexCR + vec2<f32>(0.5,0.5)));
          let newValue = getImage(
            bInd, sourceNearestCR.y, sourceNearestCR.x, d);
          setOutputAtIndex(index, newValue);
        }
      }
    }
    `}};var Hre=r=>{let{inputs:e,backend:t,attrs:o}=r,{image:n,boxes:s,boxInd:a}=e,{cropSize:i,method:p,extrapolationValue:u}=o,c=new Qg(n.shape[3],s.shape,i,p),l=[{type:"float32",data:[u]}];return t.runWebGPUProgram(c,[n,s,a],"float32",l)},tL={kernelName:Yo,backendName:"webgpu",kernelFunc:Hre};var Ku;(function(r){r.Prod="*",r.Sum="+"})(Ku||(Ku={}));var Gl=class{constructor(e,t,o,n){this.variableNames=["x"],this.uniforms="index : f32,",this.size=!0,this.workgroupSize=[128,1,1],this.outputShape=t,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.exclusive=o,this.reverse=n,this.op=e,this.shaderKey=`cum_${this.op}_${this.exclusive}_${this.reverse}`}getUserCode(){let e=this.outputShape.length,t=this.op===Ku.Prod?"1.0":"0.0",o=this.exclusive?t:`getX(${rL(e,"coords",this.op)})`,n=this.outputShape[this.outputShape.length-1],s="",a="";return this.exclusive?(s=this.reverse?`end != ${n-1}`:"end != 0",a=this.reverse?"end + 1":"end - 1"):(s=this.reverse?`end + pow2 < ${n}`:"end >= pow2",a=this.reverse?"end + pow2":"end - pow2"),`
      ${se("index")} {
       if (index < uniforms.size) {
         var coords = getCoordsFromIndex(index);

         let end = ${oL(e,"coords",this.op)};
         var val = ${o};
         let pow2 = i32(pow(2.0, uniforms.index));
         if (${s}) {
           let idx = ${a};
           ${oL(e,"coords",this.op)} = idx;
           val ${this.op}= getX(${rL(e,"coords",this.op)});
         }
         setOutputAtIndex(index, val);
       }
      }
    `}};function rL(r,e,t){if(r===1)return`${e}`;if(r===2)return`${e}.x, ${e}.y`;if(r===3)return`${e}.x, ${e}.y, ${e}.z`;if(r===4)return`${e}.x, ${e}.y, ${e}.z, ${e}.w`;throw Error(`Cumulative ${t} for rank ${r} is not yet supported`)}function oL(r,e,t){if(r===1)return`${e}`;if(r===2)return`${e}.y`;if(r===3)return`${e}.z`;if(r===4)return`${e}.w`;throw Error(`Cumulative ${t} for rank ${r} is not yet supported`)}function Zg(r,e,t,o,n,s){let a=e.shape.length,i=S.getAxesPermutation([o],a),p=e;i!=null&&(p=Nr({inputs:{x:e},backend:t,attrs:{perm:i}}));let u=S.getInnerMostAxes(1,a)[0];if(u!==a-1)throw new Error(`WebGPU cumprod shader expects an inner-most axis=${e.shape.length-1} but got axis=${o}`);let c=p.shape[u],l=Ft({inputs:{x:p},backend:t});for(let m=0;m<=Math.ceil(Math.log2(c))-1;m++){let d=new Gl(r,p.shape,!1,s),f=l,h=[{type:"float32",data:[m]}];l=t.runWebGPUProgram(d,[l],l.dtype,h),t.disposeData(f.dataId)}if(n){let m=new Gl(r,p.shape,n,s),d=l,f=[{type:"float32",data:[0]}];l=t.runWebGPUProgram(m,[l],l.dtype,f),t.disposeData(d.dataId)}if(i!=null){let m=S.getUndoAxesPermutation(i),d=Nr({inputs:{x:l},backend:t,attrs:{perm:m}});return t.disposeData(l.dataId),t.disposeData(p.dataId),d}return l}function qre(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,exclusive:a,reverse:i}=o;return Zg(Ku.Prod,n,t,s,a,i)}var nL={kernelName:jo,backendName:"webgpu",kernelFunc:qre};function Kre(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,exclusive:a,reverse:i}=o;return Zg(Ku.Sum,n,t,s,a,i)}var sL={kernelName:Xo,backendName:"webgpu",kernelFunc:Kre};function jre(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a,binaryOutput:i}=o,p=n.shape.length===1,c=y.sizeFromShape(s.shape)>0,l=s.dtype,m=p?[n.shape[0]]:[n.shape[0],n.shape[1]],d=p?[a]:[n.shape[0],a],f=dr({backend:t,attrs:{shape:d,value:0,dtype:l}}),h=new kc(m,c,i),g=[{type:"int32",data:[a]}],x=c?[n,s]:[n];return t.runWebGPUProgram(h,x,l,g,f)}var aL={kernelName:ti,backendName:"webgpu",kernelFunc:jre};var Jg=class{constructor(e,t){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.uniforms="blockSize : i32,",this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`depthToSpace_${t}`,this.dataFormat=t}getUserCode(){return`
      ${se("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let b = coords[0];
          let h = ${this.getHeightCoordString()};
          let w = ${this.getWidthCoordString()};
          let d = ${this.getDepthCoordString()};

          let in_h = h / uniforms.blockSize;
          let offset_h = h % uniforms.blockSize;
          let in_w = w / uniforms.blockSize;
          let offset_w = w % uniforms.blockSize;
          let offset_d = (offset_h * uniforms.blockSize + offset_w) *
            ${this.getOutputDepthSize()};
          let in_d = d + offset_d;

          let rlt = ${this.getInputSamplingString()};
          setOutputAtIndex(index, rlt);
        }
      }`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?"uniforms.outShape[3]":"uniforms.outShape[1]"}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function Xre(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockSize:s,dataFormat:a}=o,i=n.shape[0],p=a==="NHWC"?n.shape[1]:n.shape[2],u=a==="NHWC"?n.shape[2]:n.shape[3],c=a==="NHWC"?n.shape[3]:n.shape[1],l=p*s,m=u*s,d=c/(s*s),f=a==="NHWC"?[i,l,m,d]:[i,d,l,m],h=[{type:"int32",data:[s]}],g=new Jg(f,a);return t.runWebGPUProgram(g,[n],n.dtype,h)}var iL={kernelName:Qo,backendName:"webgpu",kernelFunc:Xre};var ex=class{constructor(e,t,o,n=!1,s=null,a=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, inDims : vec2<i32>,",this.workgroupSize=[16,16,1],this.outputShape=e,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),n&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),this.addBias=n,this.activation=s,this.hasPreluActivation=a,this.filterHeight=t,this.filterWidth=o,this.shaderKey=`depthwiseNCHW_${this.activation}_${this.filterHeight}_${this.filterWidth}`}getUserCode(){let e=this.filterWidth*this.filterHeight,t=this.workgroupSize[0]*this.workgroupSize[1]*this.workgroupSize[2],o=this.workgroupSize[1]+this.filterHeight-1,n=this.workgroupSize[0]+this.filterWidth-1;return`
      ${ur(this.activation,this.hasPreluActivation,!1,4)}

      var<workgroup> mm_Asub : array<array<f32, ${n}>, ${o}>;
      var<workgroup> mm_Bsub : array<array<f32, ${this.filterWidth}>, ${this.filterHeight}>;
      fn readX(batch : i32, channel : i32, row : i32, col : i32) -> f32 {
        var value = 0.0;
        if (row >=0 && row < uniforms.inDims[0] && col >=0 && col < uniforms.inDims[1])
        {
          value = getX(batch, channel, row, col);
        }
        return value;
      }

      ${se()} {
        let coords = getOutputCoords();
        let batch = coords[0];
        let xRCCorner = vec2<i32>(coords.zw) - uniforms.pad;
        let channelMul = uniforms.wShape[3];
        let d1 = coords[1] / channelMul;
        let q = coords[1] % channelMul;

        let inputRowStart = xRCCorner.x;
        let inputColStart = xRCCorner.y;

        let localRow = i32(localId.y);
        let localCol = i32(localId.x);

        // Load one tile of X into local memory.
        for (var inputRow = localRow; inputRow < ${o}; inputRow = inputRow + ${this.workgroupSize[1]}) {
          for (var inputCol = localCol; inputCol < ${n}; inputCol = inputCol + ${this.workgroupSize[0]}) {
            let rowOffset = inputRow - localRow;
            let colOffset = inputCol - localCol;
            mm_Asub[inputRow][inputCol] = readX(batch, d1, inputRowStart + rowOffset, inputColStart + colOffset);
          }
        }

        // Load one tile of W into local memory.
        var wIndex = i32(localIndex);
        ${e<t?`if (wIndex < ${e})`:`for(; wIndex < ${e}; wIndex = wIndex + ${t})`}

        {
          let wRow = wIndex / ${this.filterWidth};
          let wCol = wIndex % ${this.filterWidth};
          mm_Bsub[wRow][wCol] = getW(wRow, wCol, d1, q);
        }

        workgroupBarrier();

        var value = 0.0;
        for (var wR = 0; wR < ${this.filterHeight}; wR = wR + 1) {
          for (var wC = 0; wC < ${this.filterWidth}; wC = wC + 1) {
            let xVal = mm_Asub[localRow + wR][localCol + wC];
            let wVal = mm_Bsub[wR][wC];
            value = fma(xVal, wVal, value);
          }
        }
        ${Hr(this.addBias,this.activation)}
        if (coordsInBounds4D(coords, uniforms.outShape)) {
          setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
        }
      }
    `}};var Tc=class{constructor(e,t=!1,o=null,n=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, inDims : vec2<i32>,",this.workgroupSize=[4,4,4],this.workPerThread=4,this.isVec4=!0,this.outputShape=e.outShape,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize,[4,this.workPerThread,1]),y.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=o,this.hasPreluActivation=n,this.shaderKey=`depthwiseVec4_${o}_${this.convInfo.filterHeight}_${this.convInfo.filterWidth}_${this.convInfo.strideHeight}_${this.convInfo.strideWidth}_${this.workPerThread}`}getUserCode(){let e=(this.workPerThread-1)*this.convInfo.strideWidth+this.convInfo.filterWidth;return`
      ${ur(this.activation,this.hasPreluActivation,!0,4)}
      fn readX(batch : i32, row : i32, col : i32, channel : i32) -> vec4<f32> {
        var value = vec4<f32>(0.0);
        if (col >=0 && col < uniforms.inDims[1]) {
          value = getX(batch, row, col, channel);
        }
        return value;
      }

      const strideHeight = ${this.convInfo.strideHeight};
      const strideWidth = ${this.convInfo.strideWidth};
      ${se()} {
        let batch = i32(globalId.z) / uniforms.outShape[1];
        let r = i32(globalId.z) % uniforms.outShape[1];
        let c = i32(globalId.y) * ${this.workPerThread};
        let d1 = i32(globalId.x) * 4;
        let xRCCorner = vec2<i32>(r, c) * vec2<i32>(strideHeight, strideWidth) - uniforms.pad;

        let xRCorner = xRCCorner.x;
        let xCCorner = xRCCorner.y;
        var xVals : array<vec4<f32>, ${e}>;
        var dotProd : array<vec4<f32>, ${this.workPerThread}>;
        for (var i = 0; i < ${this.workPerThread}; i++) {
          dotProd[i] = vec4<f32>(0.0);
        }

        // Use constant instead of uniform can give better performance.
        for (var wR = 0; wR < ${this.convInfo.filterHeight}; wR = wR + 1) {
          let xR = xRCorner + wR;
          if (xR >=0 && xR < uniforms.inDims[0]) {
            for (var i = 0; i < ${e}; i++) {
              xVals[i] = readX(batch, xR, xCCorner + i, d1);
            }
            for (var wC = 0; wC < ${this.convInfo.filterWidth}; wC = wC + 1) {
              let wValue = getW(wR, wC, d1, 0);
              for (var i = 0; i < ${this.workPerThread}; i++) {
                dotProd[i] = fma(xVals[i * strideWidth + wC], wValue, dotProd[i]);
              }
            }
          }
        }

        for (var i = 0; i < ${this.workPerThread}; i = i + 1) {
          let coords = vec4<i32>(batch, r, c + i, d1);
          if (coordsInBounds4D(coords, uniforms.outShape)) {
            var value = dotProd[i];
            ${Hr(this.addBias,this.activation)}
            setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
          }
        }
      }
    `}};var _c=class{constructor(e,t=!1,o=null,n=!1){this.variableNames=["x","W"],this.uniforms=`pad : vec2<i32>, inDims : vec2<i32>, filterHeight : i32,
      filterWidth : i32, stride : vec2<i32>, dilation : vec2<i32>,`,this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=o,this.hasPreluActivation=n,this.shaderKey=`depthwise_${this.activation}_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?"getX(batch, xR, xC, d1);":"getX(batch, d1, xR, xC);";return`
      ${ur(this.activation,this.hasPreluActivation,!1,4)}

      ${se("index")} {
        if (index < uniforms.size) {
          let coords = getOutputCoords();
          let batch = coords[0];
          let xRCCorner = vec2<i32>(coords.${this.isChannelsLast?"yz":"zw"}) * uniforms.stride - uniforms.pad;
          let d2 = coords[${this.isChannelsLast?3:1}];
          let channelMul = uniforms.wShape[3];
          let d1 = d2 / channelMul;
          let q = d2 % channelMul;

          let inputRowStart = xRCCorner.x;
          let inputColStart = xRCCorner.y;
          let inputRowEnd = inputRowStart + uniforms.filterHeight *
              uniforms.dilation[0];
          let inputColEnd = inputColStart + uniforms.filterWidth *
              uniforms.dilation[1];

          // Convolve x(?, ?, d1)|x(d1, ?, ?) with w(:, :, d1, q) to get
          // y(yR, yC, d2)|y(d2, yR, yC). ? = to be determined. : = across all
          // values in that axis. x(?, ?, d1) and y(yR, yC, d2) is for NHWC.
          // x(d1, ?, ?) and y(d2, yR, yC) is for NCHW.
          var value = 0.0;

          // Extract if checking out of for loop for performance.
          if (inputRowStart >= 0 && inputColStart >= 0 &&
            inputRowEnd < uniforms.inDims[0] &&
                inputColEnd < uniforms.inDims[1]) {
              for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) {
                let xR = inputRowStart + wR * uniforms.dilation[0];

                for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {
                  let xC = inputColStart + wC * uniforms.dilation[1];

                  let xVal = ${e};
                  let wVal = getW(wR, wC, d1, q);
                  value = value + xVal * wVal;
                }
              }
            } else {
              for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) {
                let xR = inputRowStart + wR * uniforms.dilation[0];

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

                for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {
                  let xC = inputColStart + wC * uniforms.dilation[1];

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

                  let xVal = ${e};
                  let wVal = getW(wR, wC, d1, q);
                  value = value + xVal * wVal;
                }
              }
            }
            ${Hr(this.addBias,this.activation)}
          setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
        }
      }
    `}};function Yre(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dataFormat:p,dilations:u,dimRoundingMode:c}=o,l=S.convertConv2DDataFormat(p),m=u;m==null&&(m=[1,1]);let d=S.computeConv2DInfo(n.shape,s.shape,a,m,i,c,!0,l),f=[{type:"int32",data:[d.padInfo.top,d.padInfo.left]},{type:"int32",data:[d.inHeight,d.inWidth]}],h=d.dataFormat==="channelsLast",g;return!h&&d.inHeight>16&&d.inWidth>16&&d.strideHeight===1&&d.strideWidth===1&&d.dilationWidth===1&&d.dilationHeight===1&&d.inChannels===d.outChannels?g=new ex(d.outShape,d.filterHeight,d.filterWidth):h&&d.outHeight>4&&d.outWidth>4&&d.strideWidth<=2&&d.inChannels===d.outChannels&&d.dilationHeight===1&&d.dilationWidth===1&&d.inChannels%4===0?g=new Tc(d):(g=new _c(d),f.push({type:"int32",data:[d.filterHeight]},{type:"int32",data:[d.filterWidth]},{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.dilationHeight,d.dilationWidth]})),t.runWebGPUProgram(g,[n,s],n.dtype,f)}var uL={kernelName:Zo,backendName:"webgpu",kernelFunc:Yre};var dI=ot({opType:ye.MUL,cpuKernelImpl:aM,supportsComplex:!0}),pL={kernelName:kn,backendName:"webgpu",kernelFunc:dI};function Hl(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o;return qr(n,s,a,"sum",t)}var cL={kernelName:Hn,backendName:"webgpu",kernelFunc:Hl};function Qre(r){let{inputs:e,backend:t,attrs:o}=r,{equation:n}=o,s=e,{allDims:a,summedDims:i,idDims:p}=S.decodeEinsumEquation(n,s.length);S.checkEinsumDimSizes(a.length,p,s);let{path:u,steps:c}=S.getEinsumComputePath(i,p),l=c.length,m=null,d=a.length,f=[];for(let h=0;h<l;++h){for(let g of c[h]){let{permutationIndices:x,expandDims:b}=S.getEinsumPermutation(d,p[g]),C;S.isIdentityPermutation(x)?C=s[g]:(C=Nr({inputs:{x:s[g]},backend:t,attrs:{perm:x}}),f.push(C));let w=C.shape.slice();for(let k=0;k<b.length;++k)w.splice(b[k],0,1);y.arraysEqual(C.shape,w)||(C=de({inputs:{x:C},backend:t,attrs:{shape:w}}),f.push(C)),m===null?m=C:(m=dI({inputs:{a:C,b:m},backend:t}),f.push(m))}h<l-1&&(u[h]>=0&&(m=Hl({inputs:{x:m},backend:t,attrs:{axis:u[h]-(a.length-d),keepDims:!1}}),f.push(m)),d--)}for(let h of f)h!==m&&t.disposeData(h.dataId);return m}var lL={kernelName:ri,backendName:"webgpu",kernelFunc:Qre};var Zre=Se({opType:Q.ELU}),mL={kernelName:en,backendName:"webgpu",kernelFunc:Zre};var Jre=ot({opType:ye.EQUAL,dtype:"bool",cpuKernelImpl:q3}),dL={kernelName:tn,backendName:"webgpu",kernelFunc:Jre};var eoe=Se({opType:Q.ERF}),fL={kernelName:ma,backendName:"webgpu",kernelFunc:eoe};var fI=Se({opType:Q.EXP,cpuKernelImpl:K3,dtype:"float32"}),hL={kernelName:rn,backendName:"webgpu",kernelFunc:fI};function tx(r){let{inputs:e,attrs:t,backend:o}=r,{dim:n}=t,{input:s}=e,a=s.shape.length,i=s.shape.slice(),p=n;return n<0&&(y.assert(-(a+1)<=n,()=>`Axis must be in the interval [${-(a+1)}, ${a}]`),p=a+n+1),i.splice(p,0,1),de({inputs:{x:s},backend:o,attrs:{shape:i}})}var gL={kernelName:bs,backendName:"webgpu",kernelFunc:tx};var toe=Se({opType:Q.EXPM1,cpuKernelImpl:j3}),xL={kernelName:da,backendName:"webgpu",kernelFunc:toe};var ql=class{constructor(e,t){this.variableNames=["real","imag"],this.outputShape=[],this.uniforms="exponentMultiplier : f32, denominator: f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.component=e,this.shaderKey=`fft_${e}`}getUserCode(){return`
    fn unaryOpComplex(real: f32, expR: f32, imag: f32, expI: f32) -> f32 {
      ${this.component==="real"?"return real * expR - imag * expI;":"return real * expI + imag * expR;"}
    }

    fn mulMatDFT(batch: i32, index: i32) -> f32 {
      let indexRatio = f32(index) / f32(uniforms.realShape[1]);
      let exponentMultiplierTimesIndexRatio =
          uniforms.exponentMultiplier * indexRatio;

      var result = 0.0;

      for (var i = 0; i < uniforms.realShape[1]; i = i + 1) {
        // x = (-2|2 * PI / N) * index * i;
        let x = exponentMultiplierTimesIndexRatio * f32(i);
        let expR = cos(x);
        let expI = sin(x);
        let real = getReal(batch, i);
        let imag = getImag(batch, i);

        result = result +
            unaryOpComplex(real, expR, imag, expI) / uniforms.denominator;
      }

      return result;
    }

    ${se("index")} {
      if (index < uniforms.size) {
        let coords = getOutputCoords();
        setOutputAtIndex(index, mulMatDFT(coords[0], coords[1]));
      }
    }
  `}};function rx(r,e,t){let o=t.tensorMap.get(r.dataId),n=y.sizeFromShape(r.shape),s=r.shape[r.shape.length-1],a=n/s,i=[],p=de({inputs:{x:r},backend:t,attrs:{shape:[a,s]}});i.push(p);let u=p.shape,c=new ql("real",u),l=new ql("imag",u),m=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:u},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:u}],d=e?2*Math.PI:-2*Math.PI,f=e?u[1]:1,h=[{type:"float32",data:[d]},{type:"float32",data:[f]}],g=t.runWebGPUProgram(c,m,"float32",h);i.push(g);let x=t.runWebGPUProgram(l,m,"float32",h);i.push(x);let b=po({inputs:{real:g,imag:x},backend:t});i.push(b);let C=de({inputs:{x:b},backend:t,attrs:{shape:r.shape}});return i.forEach(w=>t.disposeData(w.dataId)),C}function roe(r){let{inputs:e,backend:t}=r,{input:o}=e;return rx(o,!1,t)}var yL={kernelName:oi,backendName:"webgpu",kernelFunc:roe};var ox=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="flipLeftRight"}getUserCode(){return`
      ${se("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let coordX = uniforms.xShape[2] - coords[2] - 1;
          let outputValue = getX(coords[0], coords[1], coordX, coords[3]);
          setOutputAtIndex(index, outputValue);
        }
      }
    `}};var bL={kernelName:on,backendName:"webgpu",kernelFunc:({inputs:r,backend:e})=>{let{image:t}=r,o=e,n=new ox(t.shape);return o.runWebGPUProgram(n,[t],t.dtype)}};var ooe=Se({opType:Q.FLOOR,cpuKernelImpl:X3}),CL={kernelName:nn,backendName:"webgpu",kernelFunc:ooe};var noe=ot({opType:ye.INT_DIV,dtype:"int32"}),SL={kernelName:sn,backendName:"webgpu",kernelFunc:noe};var nx=class{constructor(e,t,o=!1){this.isFromPixels=!0,this.outputShape=[0],this.variableNames=[],this.workgroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize,[t,1,1]),this.importVideo=o,this.shaderKey=`fromPixels_${this.importVideo}`}getUserCode(){let e=this.importVideo?"textureLoad(src, vec2<i32>(coords.yx));":"textureLoad(src, vec2<i32>(coords.yx), 0)";return`
      @binding(1) @group(0) var src: ${this.importVideo?"texture_external":"texture_2d<f32>"};
      ${se("index")} {
        let flatIndex = index * uniforms.numChannels;
        if (flatIndex < uniforms.size) {
          let coords = getCoordsFromIndex(flatIndex);
          let values = ${e};
          for (var i = 0; i < uniforms.numChannels; i = i + 1) {
            result[flatIndex + i] = i32(floor(255.0 * values[i]));
          }
        }
      }
  `}};var wL={kernelName:Zi,backendName:"webgpu",kernelFunc:soe},Ec,hI=O().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU"),sx=new Map;function soe(r){let{inputs:e,backend:t,attrs:o}=r,{pixels:n}=e,{numChannels:s}=o;if(n==null)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");let a=typeof HTMLVideoElement!="undefined"&&n instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&n instanceof HTMLImageElement,p=typeof HTMLCanvasElement!="undefined"&&n instanceof HTMLCanvasElement||typeof OffscreenCanvas!="undefined"&&n instanceof OffscreenCanvas,u=typeof ImageBitmap!="undefined"&&n instanceof ImageBitmap,[c,l]=a?[n.videoWidth,n.videoHeight]:[n.width,n.height],m=[l,c,s],d=!1,f=a||i;if(u||p||f){let b;if(d){let D=n;if(!sx.has(D)||sx.get(D).expired){let P={source:D};sx.set(D,t.device.importExternalTexture(P))}b={width:c,height:l,format:null,usage:null,texture:sx.get(D)}}else{if(f){let L=O().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(Ec==null||L!==hI)&&(hI=L,Ec=document.createElement("canvas").getContext("2d",{willReadFrequently:hI})),Ec.canvas.width=c,Ec.canvas.height=l,Ec.drawImage(n,0,0,c,l),n=Ec.canvas}let D=GPUTextureUsage.COPY_DST|GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING,P="rgba8unorm",M=t.textureManager.acquireTexture(m[1],m[0],P,D);t.queue.copyExternalImageToTexture({source:n},{texture:M},[m[1],m[0]]),b={width:c,height:l,format:P,usage:D,texture:M}}let C=y.sizeFromShape(m),w=y.computeStrides(m),k=new nx(m,s,d),_=[{type:"uint32",data:[C]},{type:"uint32",data:[s]},{type:"uint32",data:[...w]}],$=t.makeTensorInfo([l,c],"int32"),A=t.tensorMap.get($.dataId);A.resourceInfo=b;let R=t.runWebGPUProgram(k,[$],"int32",_);return t.disposeData($.dataId),R}let h=n.data,g=h;if(s!=null&&s!==4){g=new Uint8Array(n.width*n.height*s);let b=h.length,C=0;for(let w=0;w<b;w++)w%4<s&&(g[C++]=h[w])}let x=t.makeTensorInfo(m,"int32",new Int32Array(g));return t.uploadToGPU(x.dataId),x}var ax=class{constructor(e,t,o,n,s){this.uniforms="varianceEpsilon : f32,",this.workgroupSize=[128,1,1],this.size=!0,this.variableNames=["x","mean","variance"],S.assertAndGetBroadcastShape(e,t),S.assertAndGetBroadcastShape(e,o),this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),n!=null&&(S.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset")),s!=null&&(S.assertAndGetBroadcastShape(e,s),this.variableNames.push("scale")),this.offsetShape=n,this.scaleShape=s,this.shaderKey="batchNorm"}getUserCode(){let e="0.0";this.offsetShape!=null&&(e="getOffsetByOutputIndex(index)");let t="1.0";return this.scaleShape!=null&&(t="getScaleByOutputIndex(index)"),`
      ${se("index")} {
        if (index < uniforms.size)
        {
          let xValue = getXByOutputIndex(index);
          let meanValue = getMeanByOutputIndex(index);
          let varianValue = getVarianceByOutputIndex(index);
          let offsetValue = ${e};
          let scaleValue = ${t};
          let inv = scaleValue * inverseSqrt(varianValue + f32(uniforms.varianceEpsilon));
          setOutputAtIndex(index,dot(vec3<f32>(xValue, -meanValue, offsetValue), vec3<f32>(inv, inv, 1.0)));
        }
      }
  `}};var IL={kernelName:an,backendName:"webgpu",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{x:o,scale:n,offset:s,mean:a,variance:i}=r,{varianceEpsilon:p}=e,u=t,c=[o,a,i],l=null;s!=null&&(l=s.shape,c.push(s));let m=null;n!=null&&(m=n.shape,c.push(n));let d=new ax(o.shape,a.shape,i.shape,l,m),f=[{type:"float32",data:[p]}];return u.runWebGPUProgram(d,c,o.dtype,f)}};function aoe(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s,bias:a,preluActivationWeights:i}=e,{strides:p,pad:u,dataFormat:c,dilations:l,dimRoundingMode:m,activation:d,leakyreluAlpha:f}=o,h=S.convertConv2DDataFormat(c),g=S.computeConv2DInfo(n.shape,s.shape,p,l,u,m,!1,h);return jg({x:n,filter:s,convInfo:g,backend:t,bias:a,preluActivationWeights:i,leakyreluAlpha:f,activation:d})}var vL={kernelName:ho,backendName:"webgpu",kernelFunc:aoe};function ioe(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s,bias:a,preluActivationWeights:i}=e,{strides:p,pad:u,dilations:c,dimRoundingMode:l,activation:m,leakyreluAlpha:d}=o,f=c;f==null&&(f=[1,1]),y.assert(S.eitherStridesOrDilationsAreOne(p,f),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${p} and dilations '${f}'`);let h=S.computeConv2DInfo(n.shape,s.shape,p,f,u,l,!0),g=[n,s],x=a!=null,b=i!=null;x&&g.push(a),b&&g.push(i);let C=[{type:"int32",data:[h.padInfo.top,h.padInfo.left]},{type:"int32",data:[h.inHeight,h.inWidth]}],w;return h.outHeight>4&&h.outWidth>4&&h.strideWidth<=2&&h.inChannels===h.outChannels&&h.dilationHeight===1&&h.dilationWidth===1&&h.inChannels%4===0?w=new Tc(h,x,m,b):(w=new _c(h,x,m,b),C.push({type:"int32",data:[h.filterHeight]},{type:"int32",data:[h.filterWidth]},{type:"int32",data:[h.strideHeight,h.strideWidth]},{type:"int32",data:[h.dilationHeight,h.dilationWidth]})),m==="leakyrelu"&&(C.push({type:"float32",data:[d]}),w.uniforms+=" alpha : f32,"),t.runWebGPUProgram(w,g,"float32",C)}var kL={kernelName:go,backendName:"webgpu",kernelFunc:ioe};var ix=class{constructor(e,t){this.variableNames=["A","indices"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`gathernd_${e}`,this.sliceDim=e,this.uniforms=`sliceDim : i32, strides : ${Rt(e)},`}getUserCode(){let e;return this.sliceDim>1?e="uniforms.strides[j]":e="uniforms.strides",`
      ${se("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          var flattenIndex = 0;
          for (var j = 0; j < uniforms.sliceDim; j = j + 1) {
            let indexTemp = i32(round(getIndices(coords[0], j)));
            let strideNum = ${e};
            flattenIndex = flattenIndex + indexTemp * strideNum;
          }

          setOutputAtIndex(index, getA(flattenIndex, coords[1]));
        }
      }
      `}};function uoe(r){let{inputs:e,backend:t}=r,{params:o,indices:n}=e,s=n.shape,a=s[s.length-1],i=y.sizeFromShape(o.shape),[p,u,c,l]=S.prepareAndValidate(o,n),m=de({inputs:{x:n},backend:t,attrs:{shape:[u,a]}}),d=de({inputs:{x:o},backend:t,attrs:{shape:[y.sizeFromShape(o.shape)/c,c]}});if(t.shouldExecuteOnCPU([o,n])||o.dtype==="string"){let b=t.readSync(n.dataId),C=t.bufferSync(o),w=Y3(b,C,o.dtype,u,a,c,l,o.shape,i);return t.makeTensorInfo(p,o.dtype,w.values)}let f=new ix(a,[u,c]),h=[{type:"int32",data:[a]},{type:"int32",data:l}],g=t.runWebGPUProgram(f,[d,m],d.dtype,h),x=de({inputs:{x:g},backend:t,attrs:{shape:p}});return t.disposeData(m.dataId),t.disposeData(d.dataId),t.disposeData(g.dataId),x}var NL={kernelName:un,backendName:"webgpu",kernelFunc:uoe};var ux=class{constructor(e,t){this.variableNames=["A","indices"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.slice(),this.aShape=e,this.outputShape=t,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="gather"}getUserCode(){let e=poe(this.aShape);return`
      ${se("index")} {
        if (index < uniforms.size) {
          let resRC = getCoordsFromIndex(index);
          let indexZ = i32(getIndices(resRC.x, resRC.z));
          let inBounds = select(0.0, 1.0, indexZ >= 0 && indexZ < uniforms.aShape[2]);
          setOutputAtIndex(index, inBounds * getA(${e}));
        }
      }
    `}};function poe(r){let e=["resRC.x","resRC.y","resRC.z","resRC.w"],t=[];for(let o=0;o<r.length;o++)o===2?t.push("indexZ"):t.push(`${e[o]}`);return t.join()}function gI(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,indices:s}=e,{axis:a,batchDims:i}=o,p=y.parseAxisParam(a,n.shape)[0],u=S.segment_util.collectGatherOpShapeInfo(n,s,p,i),c=y.sizeFromShape(s.shape),l=[],m=de({inputs:{x:n},backend:t,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),d=de({inputs:{x:s},backend:t,attrs:{shape:[u.batchSize,c/u.batchSize]}});l.push(m),l.push(d);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(t.shouldExecuteOnCPU([n,s])){let C=t.tensorMap.get(d.dataId).values,w=le(d.shape,d.dtype,C),_=t.tensorMap.get(m.dataId).values,$=le(m.shape,m.dtype,_),A=Q3($,w,f);return l.forEach(R=>t.disposeData(R.dataId)),t.makeTensorInfo(u.outputShape,A.dtype,A.values)}let h=new ux(m.shape,f),g=t.runWebGPUProgram(h,[m,d],m.dtype);l.push(g);let x=de({inputs:{x:g},backend:t,attrs:{shape:u.outputShape}});return l.forEach(b=>t.disposeData(b.dataId)),x}var TL={kernelName:Ss,backendName:"webgpu",kernelFunc:gI};var coe=ot({opType:ye.GREATER,cpuKernelImpl:J3,dtype:"bool"}),_L={kernelName:pn,backendName:"webgpu",kernelFunc:coe};var loe=ot({opType:ye.GREATER_EQUAL,dtype:"bool",cpuKernelImpl:Z3}),EL={kernelName:cn,backendName:"webgpu",kernelFunc:loe};function moe(r){let{inputs:e,backend:t}=r,{input:o}=e;return rx(o,!0,t)}var $L={kernelName:ni,backendName:"webgpu",kernelFunc:moe};var doe=Se({opType:Q.IS_FINITE,dtype:"bool"}),AL={kernelName:fa,backendName:"webgpu",kernelFunc:doe};var foe=Se({opType:Q.IS_INF,dtype:"bool"}),RL={kernelName:ha,backendName:"webgpu",kernelFunc:foe};var hoe=Se({opType:Q.IS_NAN,dtype:"bool"}),FL={kernelName:ln,backendName:"webgpu",kernelFunc:hoe};function goe(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{alpha:s}=o,a=[{type:"float32",data:[s]}],i=new Ro(n.shape,Q.LEAKYRELU);return i.uniforms="alpha : f32,",t.runWebGPUProgram(i,[n],"float32",a)}var DL={kernelName:mn,backendName:"webgpu",kernelFunc:goe};var xoe=ot({opType:ye.LESS,dtype:"bool",cpuKernelImpl:tM}),OL={kernelName:dn,backendName:"webgpu",kernelFunc:xoe};var yoe=ot({opType:ye.LESS_EQUAL,dtype:"bool",cpuKernelImpl:eM}),PL={kernelName:fn,backendName:"webgpu",kernelFunc:yoe};var boe=Se({opType:Q.LOG,cpuKernelImpl:rM}),ML={kernelName:hn,backendName:"webgpu",kernelFunc:boe};var Coe=Se({opType:Q.LOG1P}),LL={kernelName:ga,backendName:"webgpu",kernelFunc:Coe};var Soe=ot({opType:ye.LOGICAL_AND,dtype:"bool"}),BL={kernelName:gn,backendName:"webgpu",kernelFunc:Soe};var woe=Se({opType:Q.LOGICAL_NOT}),VL={kernelName:xn,backendName:"webgpu",kernelFunc:woe};var Ioe=ot({opType:ye.MAX,cpuKernelImpl:nM}),zL={kernelName:bn,backendName:"webgpu",kernelFunc:Ioe};function voe(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{filterSize:s,strides:a,pad:i,dimRoundingMode:p}=o,u=1,c=S.computePool2DInfo(n.shape,s,a,u,i,p);return Bg(n,c,"max",t)}var WL={kernelName:Cn,backendName:"webgpu",kernelFunc:voe};function koe(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o;return qr(n,s,a,"min",t)}var UL={kernelName:wn,backendName:"webgpu",kernelFunc:koe};var Noe=ot({opType:ye.MIN,cpuKernelImpl:sM}),GL={kernelName:In,backendName:"webgpu",kernelFunc:Noe};var px=class{constructor(e,t,o){this.uniforms="",this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((n,s)=>n[0]+e[s]+n[1]),this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.xShape=e,t.map((n,s)=>{this.uniforms+=` pad${s} : vec2<i32>,`}),this.offset=o==="reflect"?0:1,this.shaderKey=`mirrorPad_${o}`}getUserCode(){let e=this.xShape.length,t=this.xShape.map((u,c)=>`uniforms.pad${c}[0]`).join(","),o=this.xShape.map((u,c)=>`uniforms.pad${c}[0] + uniforms.xShape${e>1?`[${c}]`:""}`).join(","),n=e===1?"start":"start[i]",s=e===1?"end":"end[i]",a=e===1?"outC":"outC[i]",i=Rt(e),p=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
      ${se("index")} {
        if (index < uniforms.size) {
          let start = ${i}(${t});
          let end = ${i}(${o});
          var outC = getCoordsFromIndex(index);
          for (var i = 0; i < ${e}; i = i + 1) {
            if (${a} < ${n}) {
              ${a} = ${n} * 2 - ${a} - ${this.offset};
            } else if(${a} >= ${s}) {
              ${a} = (${s} - 1) * 2 - ${a} + ${this.offset};
            }
          }
          let coords = outC - start;
          setOutputAtIndex(index, getX(${p}));
        }
      }
    `}};var HL={kernelName:vn,backendName:"webgpu",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{x:o}=r,{paddings:n,mode:s}=e,a=t,i=n.map(c=>({type:"int32",data:[c[0],c[1]]})),p=new px(o.shape,n,s);return a.runWebGPUProgram(p,[o],o.dtype,i)}};var Toe=ot({opType:ye.MOD}),qL={kernelName:ya,backendName:"webgpu",kernelFunc:Toe};function _oe(r){let{inputs:e,backend:t}=r,{x:o}=e;if(t.shouldExecuteOnCPU([o])){let s=t.tensorMap.get(o.dataId),[a,i]=iM(s.values,o.shape,o.dtype);return t.makeTensorInfo(i,o.dtype,a)}let n=new Ro(o.shape,Q.NEG);return t.runWebGPUProgram(n,[o],o.dtype)}var KL={kernelName:ws,backendName:"webgpu",kernelFunc:_oe};function Eoe(r){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:p}=o,u=t.readSync(n.dataId),c=t.readSync(s.dataId),{selectedIndices:l}=Lt.nonMaxSuppressionV3Impl(u,c,a,i,p);return t.makeTensorInfo([l.length],"int32",new Int32Array(l))}var jL={kernelName:Tn,backendName:"webgpu",kernelFunc:Eoe};function $oe(r){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:p,softNmsSigma:u}=o,c=t.readSync(n.dataId),l=t.readSync(s.dataId),m=a,d=i,f=p,h=u,{selectedIndices:g,selectedScores:x}=Lt.nonMaxSuppressionV5Impl(c,l,m,d,f,h);return[t.makeTensorInfo([g.length],"int32",new Int32Array(g)),t.makeTensorInfo([x.length],"float32",new Float32Array(x))]}var XL={kernelName:_n,backendName:"webgpu",kernelFunc:$oe};var cx=class{constructor(e,t){this.variableNames=["x"],this.uniforms="onValue : f32, offValue : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e,t],this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="onehot"}getUserCode(){return`
      ${se("index")} {
        if(index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          setOutputAtIndex(index, mix(uniforms.offValue, uniforms.onValue,
                                      f32(i32(round(getX(coords.x))) == coords.y)));
        }
      }
    `}};function Aoe(r){let{inputs:e,backend:t,attrs:o}=r,{indices:n}=e,{dtype:s,depth:a,onValue:i,offValue:p}=o,u=y.sizeFromShape(n.shape),c=new cx(u,a),l=de({inputs:{x:n},backend:t,attrs:{shape:[u]}}),m=[{type:"float32",data:[i]},{type:"float32",data:[p]}],d=t.runWebGPUProgram(c,[l],s,m);t.disposeData(l.dataId);let f=[...n.shape,a],h=de({inputs:{x:d},backend:t,attrs:{shape:f}});return t.disposeData(d.dataId),h}var YL={kernelName:En,backendName:"webgpu",kernelFunc:Aoe};function Kl(r){let{inputs:e,backend:t}=r,{x:o}=e;if(o.dtype==="complex64"){let n=qa({inputs:{input:o},backend:t}),s=Kl({inputs:{x:n},backend:t}),a=qu({inputs:{input:o},backend:t}),i=Kl({inputs:{x:a},backend:t}),p=po({inputs:{real:s,imag:i},backend:t});return t.disposeData(n.dataId),t.disposeData(s.dataId),t.disposeData(a.dataId),t.disposeData(i.dataId),p}else return dr({attrs:{shape:o.shape,dtype:o.dtype,value:o.dtype==="string"?"":0},backend:t})}var QL={kernelName:Fs,backendName:"webgpu",kernelFunc:Kl};function ZL(r){let{inputs:e,backend:t}=r,{x:o}=e;if(o.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(o.dtype==="complex64"){let n=qa({inputs:{input:o},backend:t}),s=ZL({inputs:{x:n},backend:t}),a=qu({inputs:{input:o},backend:t}),i=Kl({inputs:{x:a},backend:t}),p=po({inputs:{real:s,imag:i},backend:t});return t.disposeData(n.dataId),t.disposeData(s.dataId),t.disposeData(a.dataId),t.disposeData(i.dataId),p}else return dr({attrs:{shape:o.shape,dtype:o.dtype,value:1},backend:t})}var JL={kernelName:Is,backendName:"webgpu",kernelFunc:ZL};function Roe(r){let{inputs:e,backend:t,attrs:o}=r,{axis:n}=o;if(e.length===1)return tx({inputs:{input:e[0]},backend:t,attrs:{dim:n}});let s=e[0].shape,a=e[0].dtype;e.forEach(c=>{y.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),y.assert(a===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],p=e.map(c=>{let l=tx({inputs:{input:c},backend:t,attrs:{dim:n}});return i.push(l),l}),u=mI({inputs:p,backend:t,attrs:{axis:n}});return i.forEach(c=>t.disposeData(c.dataId)),u}var eB={kernelName:vs,backendName:"webgpu",kernelFunc:Roe};var lx=class{constructor(e,t){this.variableNames=["x"],this.uniforms="constantValue : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((o,n)=>o[0]+e[n]+o[1]),this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),t.map((o,n)=>{this.uniforms+=` pad${n} : vec2<i32>,`}),this.xShape=e,this.shaderKey="pad"}getUserCode(){let e=this.xShape.length,t=Rt(e),o=this.xShape.map((l,m)=>`uniforms.pad${m}[0]`).join(","),n=this.xShape.map((l,m)=>`uniforms.pad${m}[0] + uniforms.xShape${e>1?`[${m}]`:""}`).join(","),s=e>1?`${t}(${o})`:`${o}`,a=e>1?`${t}(${n})`:`${n}`,i=e>1?"any(outC < start)":"outC < start",p=e>1?"any(outC >= end)":"outC >= end",u=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
      ${se("index")} {
        if (index < uniforms.size) {
          let start = ${s};
          let end = ${a};
          let outC = getCoordsFromIndex(index);

          if (${i} || ${p}) {
            setOutputAtIndex(index, uniforms.constantValue);
          } else {
            let coords = outC - start;
            setOutputAtIndex(index, getX(${u}));
          }
        }
      }
    `}};var xI=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{paddings:s,constantValue:a}=o;if(s.every(u=>y.arraysEqual(u,[0,0])))return Ft({inputs:{x:n},backend:t});if(y.sizeFromShape(n.shape)===0){let u=s.map((c,l)=>c[0]+n.shape[l]+c[1]);return dr({backend:t,attrs:{shape:u,value:a,dtype:n.dtype}})}let i=[{type:"float32",data:[a]}];s.map(u=>i.push({type:"int32",data:[u[0],u[1]]}));let p=new lx(n.shape,s);return t.runWebGPUProgram(p,[n],n.dtype,i)},tB={kernelName:$n,backendName:"webgpu",kernelFunc:xI};var Foe=ot({opType:ye.POW}),rB={kernelName:An,backendName:"webgpu",kernelFunc:Foe};function Doe(r){let{inputs:e,backend:t}=r,{x:o,alpha:n}=e,s=new Hu(ye.PRELU,o.shape,n.shape);return t.runWebGPUProgram(s,[o,n],"float32")}var oB={kernelName:Rn,backendName:"webgpu",kernelFunc:Doe};function Ooe(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o;return qr(n,s,a,"prod",t)}var nB={kernelName:Fn,backendName:"webgpu",kernelFunc:Ooe};var Poe=r=>{let{backend:e,attrs:t}=r,{start:o,stop:n,step:s,dtype:a}=t,i=cM(o,n,s,a);return e.makeTensorInfo([i.length],a,i)},sB={kernelName:ks,backendName:"webgpu",kernelFunc:Poe};var yI=ot({opType:ye.DIV}),aB={kernelName:Jo,backendName:"webgpu",kernelFunc:yI};var Moe=Se({opType:Q.RECIPROCAL}),iB={kernelName:Dn,backendName:"webgpu",kernelFunc:Moe};var Loe=Se({opType:Q.RELU}),uB={kernelName:On,backendName:"webgpu",kernelFunc:Loe};var Boe=Se({opType:Q.RELU6}),pB={kernelName:Ln,backendName:"webgpu",kernelFunc:Boe};var mx=class{constructor(e,t,o){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, halfPixelCenters : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,o,e[3]],this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="resizeBilinear"}getUserCode(){return`
      ${se("index")} {
        if (index < uniforms.size) {
        let coords = getCoordsFromIndex(index);
          let b = coords[0];
          let d = coords[3];
          let rc = coords.yz;

          let effectiveInSize = vec2<f32>(
            f32(uniforms.xShape.y) - uniforms.adjustHeightWidth[0],
            f32(uniforms.xShape.z) - uniforms.adjustHeightWidth[1]);

          let effectiveOutSize = vec2<f32>(
            f32(uniforms.outShape.y) - uniforms.adjustHeightWidth[0],
            f32(uniforms.outShape.z) - uniforms.adjustHeightWidth[1]);

          let effectiveInputOverOutputRatioRC =
              effectiveInSize / effectiveOutSize;

          // Fractional source index
          let sourceFracIndexRC =
            (vec2<f32>(rc) + vec2<f32>(uniforms.halfPixelCenters)) *
            effectiveInputOverOutputRatioRC - vec2<f32>(uniforms.halfPixelCenters);

          // Compute the four integer indices.
          let sourceFloorRC = vec2<i32>(sourceFracIndexRC);
          let sourceCeilRC = vec2<i32>(
            min(vec2<f32>(uniforms.xShape.yz) - vec2<f32>(1.0), ceil(sourceFracIndexRC)));

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

          let fracRC = sourceFracIndexRC - vec2<f32>(sourceFloorRC);

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

          setOutputAtIndex(index, newValue);
        }
      }
    `}};function Voe(r){let{inputs:e,backend:t,attrs:o}=r,{images:n}=e,{alignCorners:s,size:a,halfPixelCenters:i}=o,[p,u]=a,c=s&&p>1?1:0,l=s&&u>1?1:0,d=[{type:"float32",data:[c,l]},{type:"float32",data:[i?.5:0]}],f=new mx(n.shape,p,u);return t.runWebGPUProgram(f,[n],"float32",d)}var cB={kernelName:Mn,backendName:"webgpu",kernelFunc:Voe};var dx=class{constructor(e,t,o,n){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, roundBase : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,o,e[3]],this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.halfPixelCenters=n,this.shaderKey=`resizeNearest_${n}`}getUserCode(){let e;return this.halfPixelCenters?e="max((vec2<f32>(rc) + vec2<f32>(0.5)) * effectiveInputOverOutputRatioRC, vec2<f32>(0.0))":e="vec2<f32>(rc) * effectiveInputOverOutputRatioRC",`
      ${se("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let b = coords[0];
          let d = coords[3];
          let rc = coords.yz;

          let effectiveInSize = vec2<f32>(
            f32(uniforms.xShape.y) - uniforms.adjustHeightWidth[0],
            f32(uniforms.xShape.z) - uniforms.adjustHeightWidth[1]);

          let effectiveOutSize = vec2<f32>(
            f32(uniforms.outShape.y) - uniforms.adjustHeightWidth[0],
            f32(uniforms.outShape.z) - uniforms.adjustHeightWidth[1]);

          let effectiveInputOverOutputRatioRC =
              effectiveInSize / effectiveOutSize;

          // Fractional source index
          let sourceFracIndexRC = ${e};

          // Compute the coordinators of nearest neighbor point.
          let inputShapeRC = vec2<f32>(f32(uniforms.xShape.y), f32(uniforms.xShape.z));
          let sourceNearestRC = vec2<i32>(
            min(inputShapeRC - 1.0, floor(sourceFracIndexRC + uniforms.roundBase)));
          let newValue = getX(b, sourceNearestRC.x, sourceNearestRC.y, d);

          setOutputAtIndex(index, newValue);
        }
      }
    `}};function zoe(r){let{inputs:e,backend:t,attrs:o}=r,{images:n}=e,{alignCorners:s,halfPixelCenters:a,size:i}=o,[p,u]=i,c=s&&p>1?1:0,l=s&&u>1?1:0,d=[{type:"float32",data:[c,l]},{type:"float32",data:[s?.5:0]}],f=new dx(n.shape,p,u,a);return t.runWebGPUProgram(f,[n],n.dtype,d)}var lB={kernelName:Pn,backendName:"webgpu",kernelFunc:zoe};var fx=class{constructor(e){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms=" axis : vec4<i32>,",this.shaderKey="reverse"}getUserCode(){return`
      
      // Using uniform variables as judging conditions, so the function has
      // coherent execution within all threads.
      fn getReverseCoords(coords : vec4<i32>) -> vec4<i32> {
        var reverseCoords = coords;
        if (uniforms.axis[0] == 1) {
          reverseCoords[0] = uniforms.xShape[0] - coords[0] - 1;
        }
        if (uniforms.axis[1] == 1) {
          reverseCoords[1] = uniforms.xShape[1] - coords[1] - 1;
        }
        if (uniforms.axis[2] == 1) {
          reverseCoords[2] = uniforms.xShape[2] - coords[2] - 1;
        }
        if (uniforms.axis[3] == 1) {
          reverseCoords[3] = uniforms.xShape[3] - coords[3] - 1;
        }

        return reverseCoords;
      }
    
      ${se("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let reverseCoords = getReverseCoords(coords);
          setOutputAtIndex(index, getX(reverseCoords[0],
              reverseCoords[1], reverseCoords[2], reverseCoords[3]));
        }
      }
    `}};function Woe(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{dims:s}=o,a=n.shape.length;if(a===0)return Ft({inputs:{x:n},backend:t});let i=n.shape,p=[1,1,1,1];i.forEach((g,x)=>{let b=x+4-a;p[b]=g});let u=y.parseAxisParam(s,n.shape),c=[0,0,0,0];u.forEach(g=>{let x=g+4-a;c[x]=1});let l=[{type:"int32",data:c}],m=de({inputs:{x:n},backend:t,attrs:{shape:p}}),d=new fx(p),f=t.runWebGPUProgram(d,[m],m.dtype,l);t.disposeData(m.dataId);let h=de({inputs:{x:f},backend:t,attrs:{shape:i}});return t.disposeData(f.dataId),h}var mB={kernelName:Bn,backendName:"webgpu",kernelFunc:Woe};var hx=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms=`centerX : f32, centerY : f32, sinRadians : f32,
          cosRadians : f32,`,this.shaderKey="rotate",this.outputShape=e,typeof t=="number"?(this.uniforms+=" fillValue : f32,",this.fillSnippet="var outputValue = uniforms.fillValue;",this.shaderKey+="_float"):(this.uniforms+=" fillValue : vec3<f32>,",this.fillSnippet="var outputValue = uniforms.fillValue[coords[3]];",this.shaderKey+="_vec3")}getUserCode(){return`
        ${se("index")} {
          if (index < uniforms.size) {
            let coords = getCoordsFromIndex(index);
            let coordXFloat = (f32(coords[2]) - uniforms.centerX) *
                uniforms.cosRadians - (f32(coords[1]) - uniforms.centerY) *
                uniforms.sinRadians;
            let coordYFloat = (f32(coords[2]) - uniforms.centerX) *
                uniforms.sinRadians + (f32(coords[1]) - uniforms.centerY) *
                uniforms.cosRadians;
            let coordX = i32(round(coordXFloat + uniforms.centerX));
            let coordY = i32(round(coordYFloat + uniforms.centerY));
            ${this.fillSnippet}
            if(coordX >= 0 && coordX < uniforms.xShape[2] && coordY >= 0 &&
                coordY < uniforms.xShape[1]) {
              outputValue = getX(coords[0], coordY, coordX, coords[3]);
            }
            setOutputAtIndex(index, outputValue);
          }
        }
      `}};var dB={kernelName:es,backendName:"webgpu",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{image:o}=r,{radians:n,fillValue:s,center:a}=e,i=t,p=new hx(o.shape,s),[u,c]=S.getImageCenter(a,o.shape[1],o.shape[2]),l=[{type:"float32",data:[u]},{type:"float32",data:[c]},{type:"float32",data:[Math.sin(n)]},{type:"float32",data:[Math.cos(n)]}];return typeof s=="number"?l.push({type:"float32",data:[Number.parseFloat(s.toFixed(2))]}):l.push({type:"float32",data:s}),i.runWebGPUProgram(p,[o],o.dtype,l)}};var Uoe=Se({opType:Q.RSQRT,cpuKernelImpl:lM}),fB={kernelName:Vn,backendName:"webgpu",kernelFunc:Uoe};var Gi=class{constructor(e,t,o,n,s,a,i,p=!0){this.variableNames=["updates","indices"],this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=a,this.type=i,this.sumDupeIndices=p,this.dispatchLayout=ue(e),this.dispatch=re(this.dispatchLayout,e,this.workgroupSize),this.sliceDimGreaterThanOne=t>1,this.shaderKey=`scatter_${o}_${n}_${this.sliceDimGreaterThanOne}_${i}_${p}`;let u=Rt(s.length);this.uniforms=`sliceDim : i32, strides: ${u}, updatesSize: i32,`,this.updatesRank=n,this.indicesRank=o}getUserCode(){let e="";this.indicesRank===1?e="coords[0]":this.indicesRank===2&&(e="coords[0], j");let t=`getIndices(${e})`,o=this.sliceDimGreaterThanOne?"uniforms.strides[j]":"uniforms.strides",n="",s="";this.dispatchLayout.x.length===1?(n="flattenedIndex",s=`
      fn getUpdatesCoordsFromFlatIndex(index : i32) -> i32 {
        return index;
      }
      `):this.dispatchLayout.x.length===2&&(n="vec2<i32>(flattenedIndex, coords[1])",s=`
      fn getUpdatesCoordsFromFlatIndex(index : i32) -> vec2<i32> {
        // N.B. |updates| could be a scalar tensor, conceptually representing a
        // 2D tensor with all values equal to that. By design, its size must be
        // the same as |outShape[1]| in one dimension, and |indicesShape[0]|
        // gives the other.
        let sliceSize = uniforms.outShape[1];
        let d0 = index / sliceSize;
        let d1 = index - d0 * sliceSize;
        return vec2<i32>(d0, d1);
      }
      `);let i=`getUpdates(${Array.from({length:this.updatesRank},(c,l)=>`coords[${l}]`).join(", ")})`,p=(c,l)=>{let m=`atomicAdd(${c}, bitcast<i32>(${l}))`;this.type==="float32"&&(m=`
          {
            var oldBits = 0;
            var newBits = bitcast<i32>(${l});
            loop {
              let info = atomicCompareExchangeWeak(${c}, oldBits, newBits);
              if (info.exchanged) {
                break;
              }
              oldBits = info.old_value;
              let oldValue = bitcast<f32>(oldBits);
              let newValue = oldValue + (${l});
              newBits = bitcast<i32>(newValue);
            }
          }
        `);let d=`atomicStore(${c}, bitcast<i32>(${l}));`;return this.sumDupeIndices?m:d};return`
    ${s}

      ${se("index")} {
        if (index < uniforms.updatesSize) {
          let coords = getUpdatesCoordsFromFlatIndex(index);
          var flattenedIndex = 0;
          for (var j = 0; j < uniforms.sliceDim; j = j + 1) {
            let indexInside = i32(round(${t}));
            flattenedIndex = flattenedIndex + indexInside * ${o};
          }
          let updateValue =
              ${wc(this.type,!1)}(${i});
          let flatIndex = getOutputIndexFromCoords(${n});

          ${p("&result[flatIndex]","updateValue")};
        }
      }`}};function Goe(r){let{inputs:e,backend:t,attrs:o}=r,{indices:n,updates:s}=e,{shape:a}=o,{sliceRank:i,numUpdates:p,sliceSize:u,strides:c,outputSize:l}=S.calculateShapes(s,n,a),m=[l/u,u];if(l===0)return t.makeTensorInfo(a,n.dtype);let d=de({inputs:{x:n},backend:t,attrs:{shape:[p,i]}}),f=de({inputs:{x:s},backend:t,attrs:{shape:[p,u]}}),h=f.dtype,g=dr({backend:t,attrs:{shape:m,value:0,dtype:h}}),x=y.sizeFromShape(f.shape),b=[{type:"int32",data:[i]},{type:"int32",data:c},{type:"int32",data:[x]}],C=new Gi(f.shape,i,d.shape.length,f.shape.length,c,m,h),w=t.runWebGPUProgram(C,[f,d],h,b,g),k=de({inputs:{x:w},backend:t,attrs:{shape:a}});return t.disposeData(d.dataId),t.disposeData(f.dataId),t.disposeData(w.dataId),k}var hB={kernelName:zn,backendName:"webgpu",kernelFunc:Goe};var gx=class{constructor(e,t){this.outputShape=[],this.variableNames=["sortedSequence","values"],this.uniforms="numInputs : i32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.side=t,this.shaderKey=`search_sorted_${t}`}getUserCode(){return`
      fn findBound(batch: i32, value: f32) -> i32 {
        var left = i32(0);
        var right = uniforms.numInputs;
        while (left < right) {
          var mid = (left + right) / 2;
          if (getSortedSequence(batch, mid) ${this.side==="left"?"<":"<="} value) {
            left = mid + 1;
          } else {
            right = mid;
          }
        }
        return right;
      }

      ${se("index")} {
        if (index < uniforms.size) {
          let coords = getCoordsFromIndex(index);
          let value = getValuesByOutputIndex(index);
          setOutputAtIndexI32(index, findBound(coords[0], value));
        }
      }
    `}};function Hoe(r){let{inputs:e,backend:t,attrs:o}=r,{sortedSequence:n,values:s}=e,{side:a}=o,i=new gx([s.shape[0],s.shape[1]],a),p=[{type:"int32",data:[n.shape[1]]}];return t.runWebGPUProgram(i,[n,s],"int32",p)}var gB={kernelName:ii,backendName:"webgpu",kernelFunc:Hoe};var xx=class{constructor(e,t,o){this.variableNames=["c","a","b"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.cRank=e,this.rank=o,this.shaderKey="select"}getUserCode(){let e,t;if(this.rank>4)throw Error(`Where for rank ${this.rank} is not yet supported`);if(this.rank===1)t="resRC",e="resRC";else{let n=["resRC.x","resRC.y","resRC.z","resRC.w"],s=[],a=[];for(let i=0;i<this.outputShape.length;i++)a.push(`${n[i]}`),i<this.cRank&&s.push(`${n[i]}`);e=s.join(),t=a.join()}return`
      ${se("index")} {
        if (index < uniforms.size) {
          let resRC = getCoordsFromIndex(index);
          let cVal = getC(${e});
          if (cVal >= 1.0) {
            setOutputAtIndex(index, getA(${t}));
          } else {
            setOutputAtIndex(index, getB(${t}));
          }
        }
      }
    `}};function qoe(r){let{inputs:e,backend:t}=r,{condition:o,t:n,e:s}=e,a=new xx(o.shape.length,n.shape,n.shape.length);return t.runWebGPUProgram(a,[o,n,s],dt(n.dtype,s.dtype))}var xB={kernelName:Ts,backendName:"webgpu",kernelFunc:qoe};var Koe=Se({opType:Q.SIGMOID}),yB={kernelName:Un,backendName:"webgpu",kernelFunc:Koe};var joe=Se({opType:Q.SIN}),bB={kernelName:Wn,backendName:"webgpu",kernelFunc:joe};var Xoe=Se({opType:Q.SINH}),CB={kernelName:Sa,backendName:"webgpu",kernelFunc:Xoe};var bI=ot({opType:ye.SUB,cpuKernelImpl:xM,supportsComplex:!0}),SB={kernelName:Xn,backendName:"webgpu",kernelFunc:bI};function Yoe(r){let{inputs:e,backend:t,attrs:o}=r,{logits:n}=e,{dim:s}=o,a=y.parseAxisParam([s],n.shape),i=Ul({inputs:{x:n},backend:t,attrs:{reductionIndices:a,keepDims:!1}}),p=S.expandShapeToKeepDim(i.shape,a),u=de({inputs:{x:i},backend:t,attrs:{shape:p}}),c=bI({inputs:{a:n,b:u},backend:t}),l=fI({inputs:{x:c},backend:t}),m=Hl({inputs:{x:l},backend:t,attrs:{axis:a,keepDims:!1}}),d=de({inputs:{x:m},backend:t,attrs:{shape:p}}),f=yI({inputs:{a:l,b:d},backend:t});return t.disposeData(i.dataId),t.disposeData(u.dataId),t.disposeData(c.dataId),t.disposeData(l.dataId),t.disposeData(m.dataId),t.disposeData(d.dataId),f}var wB={kernelName:qn,backendName:"webgpu",kernelFunc:Yoe};var Qoe=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockShape:s,paddings:a}=o;y.assert(n.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGPU backend not implemented yet");let i=s.reduce((x,b)=>x*b),p=[[0,0]];p.push(...a);for(let x=1+s.length;x<n.shape.length;++x)p.push([0,0]);let u=[],c=xI({inputs:{x:n},backend:t,attrs:{paddings:p,constantValue:0}}),l=S.getReshaped(c.shape,s,i,!1),m=S.getPermuted(l.length,s.length,!1),d=S.getReshapedPermuted(c.shape,s,i,!1),f=de({inputs:{x:c},backend:t,attrs:{shape:l}}),h=Nr({inputs:{x:f},backend:t,attrs:{perm:m}}),g=de({inputs:{x:h},backend:t,attrs:{shape:d}});return u.push(c),u.push(f),u.push(h),u.forEach(x=>t.disposeData(x.dataId)),g},IB={kernelName:Es,backendName:"webgpu",kernelFunc:Qoe};var yx=class{constructor(e,t){this.variableNames=["A"],this.workgroupSize=[64,1,1],this.size=!0;let o=new Array(e.length);for(let n=0;n<o.length;n++)o[n]=e[n]*t[n];this.outputShape=o,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.rank=this.outputShape.length,this.shaderKey="tile"}getUserCode(){let e=Zoe(this.rank,"uniforms.");return`
      ${se("index")} {
        if (index < uniforms.size) {
          let resRC = getCoordsFromIndex(index);
          setOutputAtIndex(index, getA(${e}));
        }
      }
    `}};function Zoe(r,e=""){if(r>=5)throw Error(`Tile for rank ${r} is not yet supported`);if(r===1)return`(resRC % ${e}aShape)`;let t=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[];for(let n=0;n<r;n++)o.push(`(${t[n]} % ${e}aShape[${n}])`);return o.join()}function CI(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{reps:s}=o;if(t.shouldExecuteOnCPU([n])||n.dtype==="string"||n.shape.length>=5){let p=t.readSync(n.dataId),u=n.dtype==="string"?p.map(m=>y.decodeString(m)):p,c=le(n.shape,n.dtype,u),l=yM(c,s);return t.makeTensorInfo(l.shape,l.dtype,l.values)}let a=new yx(n.shape,s);return t.runWebGPUProgram(a,[n],n.dtype)}var vB={kernelName:to,backendName:"webgpu",kernelFunc:CI};function Joe(r){let{inputs:e,backend:t,attrs:o}=r,{sparseIndices:n,sparseValues:s,defaultValue:a}=e,{outputShape:i}=o,{sliceRank:p,numUpdates:u,sliceSize:c,strides:l,outputSize:m}=S.calculateShapes(s,n,i),d=!1;if(s.dtype==="string"){let A=t.bufferSync(n),R=t.bufferSync(s),D=y.decodeString(t.readSync(a.dataId)[0]),P=mM(A,R,i,m,c,u,p,l,D,d);return t.makeTensorInfo(i,P.dtype,P.values)}let f=[m/c,c],h=de({inputs:{x:n},backend:t,attrs:{shape:[u,p]}}),g=s.shape.length?de({inputs:{x:s},backend:t,attrs:{shape:[u,c]}}):Ft({inputs:{x:s},backend:t}),x=g.dtype,b=t.makeTensorInfo([],x,y.makeZerosTypedArray(1,x)),C=de({inputs:{x:a},backend:t,attrs:{shape:Array(f.length).fill(1)}}),w=CI({inputs:{x:C},backend:t,attrs:{reps:f}}),k=y.sizeFromShape([u,c]),_=[{type:"int32",data:[p]},{type:"int32",data:l},{type:"int32",data:[k]}];switch(u){case 0:break;case 1:{let A=new Gi([u,c],p,h.shape.length,g.shape.length,l,f,x,d);t.runWebGPUProgram(A,[g,h],x,_,w)}break;default:{let A=new Gi([u,c],p,h.shape.length,b.shape.length,l,f,x,d);t.runWebGPUProgram(A,[b,h],x,_,w)}{let A=new Gi([u,c],p,h.shape.length,g.shape.length,l,f,x);t.runWebGPUProgram(A,[g,h],x,_,w)}}let $=de({inputs:{x:w},backend:t,attrs:{shape:i}});return t.disposeData(h.dataId),t.disposeData(g.dataId),t.disposeData(C.dataId),t.disposeData(b.dataId),t.disposeData(w.dataId),$}var kB={kernelName:li,backendName:"webgpu",kernelFunc:Joe};function ene(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{numOrSizeSplits:s,axis:a}=o,i=y.parseAxisParam(a,n.shape)[0],p=S.prepareSplitSize(n,s,i),u=n.shape.length,c=new Array(u).fill(0),l=n.shape.slice();return p.map(m=>{let d=[...l];d[i]=m;let f=ds({inputs:{x:n},backend:t,attrs:{begin:c,size:d}});return c[i]+=m,f})}var NB={kernelName:$s,backendName:"webgpu",kernelFunc:ene};var tne=Se({opType:Q.SQRT}),TB={kernelName:Gn,backendName:"webgpu",kernelFunc:tne};var _B={kernelName:mi,backendName:"webgpu",kernelFunc:({inputs:r,backend:e})=>{let{x:t}=r,o=e,n=new Ro(t.shape,Q.SQUARE);return o.runWebGPUProgram(n,[t],t.dtype)}};var rne=ot({opType:ye.SQUARED_DIFFERENCE}),EB={kernelName:Kn,backendName:"webgpu",kernelFunc:rne};var bx=class{constructor(e){this.variableNames=["x"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]);let t=Rt(this.outputShape.length);this.uniforms=`begin : ${t},  strides : ${t}, `,this.shaderKey="stridedSlice"}getUserCode(){let e=this.outputShape.length,t="";if(e===1)t="coords * uniforms.strides + uniforms.begin";else{let n=0;t=this.outputShape.map((s,a)=>(n++,this.outputShape.length===1?`coords * uniforms.strides[${a}] + uniforms.begin[${a}]`:`coords[${n-1}] * uniforms.strides[${a}] + uniforms.begin[${a}]`)).join(",")}return`
       ${se("index")} {
         if (index < uniforms.size) {
           let coords = getCoordsFromIndex(index);
           setOutputAtIndex(index, getX(${t}));
         }
       }
     `}};function one(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{begin:s,end:a,strides:i,beginMask:p,endMask:u,ellipsisMask:c,newAxisMask:l,shrinkAxisMask:m}=o,{finalShapeSparse:d,finalShape:f,isIdentity:h,sliceDim0:g,isSimpleSlice:x,begin:b,end:C,strides:w}=ut.sliceInfo(n.shape,s,a,i,p,u,c,l,m),k;if(h)k=de({inputs:{x:n},backend:t,attrs:{shape:f}});else if(g||x){y.assert(n.shape.length>=1,()=>`Input must have rank at least 1, got: ${n.shape.length}`);let _=ut.computeOutShape(b,C,w),$=ds({inputs:{x:n},backend:t,attrs:{begin:b,size:_}});k=de({inputs:{x:$},backend:t,attrs:{shape:f}}),t.disposeData($.dataId)}else if(t.shouldExecuteOnCPU([n])){let $=t.readSync(n.dataId),A=le(n.shape,n.dtype,$),R=hM(d,A,w,b);k=t.makeTensorInfo(f,n.dtype,R.values)}else{let $=new bx(d),A=[{type:"int32",data:b},{type:"int32",data:w}],R=t.runWebGPUProgram($,[n],n.dtype,A);k=de({inputs:{x:R},backend:t,attrs:{shape:f}}),t.disposeData(R.dataId)}return k}var $B={kernelName:jn,backendName:"webgpu",kernelFunc:one};function nne(r){let{inputs:e,backend:t,attrs:o}=r,{separator:n,nGramWidths:s,leftPad:a,rightPad:i,padWidth:p,preserveShortSequences:u}=o,{data:c,dataSplits:l}=e,m=t.readSync(c.dataId),d=t.readSync(l.dataId),[f,h]=gM(m,d,n,s,a,i,p,u);return[t.makeTensorInfo([f.length],"string",f),t.makeTensorInfo(l.shape,"int32",h)]}var AB={kernelName:As,backendName:"webgpu",kernelFunc:nne};var sne=Se({opType:Q.TAN}),RB={kernelName:Yn,backendName:"webgpu",kernelFunc:sne};var ane=Se({opType:Q.TANH}),FB={kernelName:Qn,backendName:"webgpu",kernelFunc:ane};var Cx=class{constructor(e){this.variableNames=["x","indices"],this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms=`inputSize : i32, firstPass : i32, negativeInf : f32,
        dir : i32, inc : i32,`,this.shaderKey="swap"}getUserCode(){return`
        ${se("index")} {
          if (index < uniforms.size) {
            let outC = getCoordsFromIndex(index);
            let batch = outC[0];
            let elemIdx = outC[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.
            let isFirstInPair = elemIdx % (2 * uniforms.inc) < uniforms.inc;
            var i = 0;
            if (isFirstInPair) {
              i = elemIdx;
            } else {
              i = elemIdx - uniforms.inc;
            }

            var i0 = 0;
            if (uniforms.firstPass == 1) {
              i0 = i;
            } else {
              i0 = i32(getIndices(batch, i));
            }

            var i1 = 0;
            if (uniforms.firstPass == 1) {
              i1 = i + uniforms.inc;
            } else {
              i1 = i32(getIndices(batch, i + uniforms.inc));
            }

            var x0 = f32(0.0);
            var x1 = f32(0.0);
            if (i0 < uniforms.inputSize) {
              x0 = getX(batch, i0);
            } else {
              x0 = uniforms.negativeInf;
            }
            if (i1 < uniforms.inputSize) {
              x1 = getX(batch, i1);
            } else {
              x1 = uniforms.negativeInf;
            }

            let reverse = elemIdx % (2 * uniforms.dir) >= uniforms.dir;
            let isGreater = x0 > x1 || (x0 == x1 && i1 > i0);
            if (reverse == isGreater) {
              // Elements in opposite order of direction
              let iTemp = i0;
              i0 = i1;
              i1 = iTemp;
            }
            if (isFirstInPair) {
              setOutputAtIndex(index, f32(i0));
            } else {
              setOutputAtIndex(index, f32(i1));
            }
          }
        }
      `}},Sx=class{constructor(e){this.variableNames=["x","indices"],this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms="inputSize : i32, firstPass : i32, k : i32,",this.shaderKey="merge"}getUserCode(){return`
        ${se("index")} {
          if (index < uniforms.size) {
            let outC = getCoordsFromIndex(index);
            let batch = outC[0];
            let elemIdx = outC[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.

            var i = 0;
            if (elemIdx < uniforms.k) {
              i = elemIdx;
            } else {
              i = elemIdx * 2 - elemIdx % uniforms.k;
            }
            var i0 = 0;
            if (uniforms.firstPass == 1) {
              i0 = i;
            } else {
              i0 = i32(getIndices(batch, i));
            }
            var i1 = 0;
            if (uniforms.firstPass == 1) {
              i1 = i + uniforms.k;
            } else {
              i1 = i32(getIndices(batch, i + uniforms.k));
            }

            let x0 = getX(batch, i0);
            var x1 = f32(0.0);
            if (i1 < uniforms.inputSize) {
              x1 = getX(batch, i1);
            } else {
              x1 = x0;
            }

            if (x0 >= x1) {
              setOutputAtIndex(index, f32(i0));
            } else {
              setOutputAtIndex(index, f32(i1));
            }
          }
        }
      `}};function $c(r,e){e!==null&&r.disposeData(e.dataId)}function DB(r){let e=1;for(;e<r;)e*=2;return e}function ine(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{k:s,sorted:a}=o,i=n.shape,p=i[i.length-1];if(t.shouldExecuteOnCPU([n])){let k=t.readSync(n.dataId),[_,$]=bM(k,i,n.dtype,s,a);return[t.makeTensorInfo(_.shape,_.dtype,_.values),t.makeTensorInfo($.shape,$.dtype,$.values)]}if(s===0)return i[i.length-1]=0,[t.makeTensorInfo(i,n.dtype,[]),t.makeTensorInfo(i,"int32",[])];if(p===1)return[n,dr({attrs:{shape:i,dtype:"int32",value:0},backend:t})];let c=y.sizeFromShape(i)/p,l=de({inputs:{x:n},attrs:{shape:[c,p]},backend:t}),m=DB(s),d=DB(p),f=null,h=()=>f===null?[l,l]:[l,f],g=(k,_,$)=>{let A=h(),R=new Cx($),P=[{type:"int32",data:[p]},{type:"int32",data:[f===null?1:0]},{type:"float32",data:[Number.NEGATIVE_INFINITY]},{type:"int32",data:[k]},{type:"int32",data:[_]}],M=f;f=t.runWebGPUProgram(R,A,"int32",P),$c(t,M)};for(let k=1;k<m;k*=2){let _=k*2;for(let $=k;$>=1;$/=2)g(_,$,[c,d])}for(let k=d;k>m;k/=2){let _=h(),$=new Sx([c,k/2]),R=[{type:"int32",data:[p]},{type:"int32",data:[f===null?1:0]},{type:"int32",data:[m]}],D=f;f=t.runWebGPUProgram($,_,"int32",R),$c(t,D);let P=m/2,M=P*2;for(let L=P;L>=1;L/=2)g(M,L,f.shape)}let x=f;f=ds({inputs:{x:f},backend:t,attrs:{begin:0,size:[c,s]}}),$c(t,x);let b=gI({inputs:{x:l,indices:f},backend:t,attrs:{axis:1,batchDims:1}});$c(t,l);let C=i.slice(0,-1);C.push(s),x=f,f=de({inputs:{x:f},attrs:{shape:C},backend:t}),$c(t,x);let w=b;return b=de({inputs:{x:b},attrs:{shape:C},backend:t}),$c(t,w),[b,f]}var OB={kernelName:Zn,backendName:"webgpu",kernelFunc:ine};var wx=class{constructor(e){this.variableNames=["Image","Transforms"],this.uniforms="interpolationModeId : i32, fillModeId : i32, fillValue : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=ue(this.outputShape),this.dispatch=re(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="transform"}getUserCode(){return`
          fn mapCoord(outCoord : f32, len : f32) -> f32{
            var inCoord = outCoord;
            if(uniforms.fillModeId == 2) {
              if (inCoord < 0.0) {
                if (len <= 1.0) {
                  inCoord = 0.0;
                } else {
                  let sz2 = 2.0 * len;
                  if (inCoord < sz2) {
                    inCoord = sz2 * f32(i32(f32(-inCoord / sz2))) +
                    inCoord;
                  }
                  if (inCoord < -len) {
                    inCoord = inCoord + sz2;
                  } else {
                    inCoord = -inCoord - 1.0;
                  }
                }
              } else if (inCoord > len - 1.0) {
                if (len <= 1.0) {
                  inCoord = 0.0;
                } else {
                  let sz2 = 2.0 * len;
                  inCoord = inCoord - sz2 * f32(i32(f32(inCoord / sz2)));
                  if (inCoord >= len) {
                    inCoord = sz2 - inCoord - 1.0;
                  }
                }
              }
              return clamp(inCoord, 0.0, len - 1.0);
            } else if (uniforms.fillModeId == 3) {
              if (inCoord < 0.0) {
                if (len <= 1.0) {
                  inCoord = 0.0;
                } else {
                  let sz = len - 1.0;
                  inCoord = inCoord + len * (f32(i32(f32(-inCoord / sz))) + 1.0);
                }
              } else if (inCoord > len - 1.0) {
                if (len <= 1.0) {
                  inCoord = 0.0;
                } else {
                  let sz = len - 1.0;
                  inCoord = inCoord - len * f32(i32(f32(inCoord / sz)));
                }
              }
              return clamp(inCoord, 0.0, len - 1.0);
            } else if (uniforms.fillModeId == 4) {
              return clamp(outCoord, 0.0, len - 1.0);
            }
            return outCoord;
          }
          fn readWithFillValue(batch : i32, coordY : i32, coordX : i32,
            channel : i32) -> f32 {
            var outputValue : f32;
            if (0 <= coordY && coordY < uniforms.imageShape[1] && 0 <= coordX && coordX < uniforms.imageShape[2]) {
                outputValue = getImage(batch, coordY, coordX, channel);
            } else {
              outputValue = uniforms.fillValue;
            }
            return outputValue;
          }

          ${se("index")} {
            if (index < uniforms.size) {
              let coords = getCoordsFromIndex(index);
              var outputValue : f32;
              let batch = coords[0];
              let x = coords[2];
              let y = coords[1];
              let channel = coords[3];
              let xf = f32(x);
              let yf = f32(y);
              let a1 = getTransforms(batch, 0);
              let a2 = getTransforms(batch, 1);
              let a3 = getTransforms(batch, 2);
              let b1 = getTransforms(batch, 3);
              let b2 = getTransforms(batch, 4);
              let b3 = getTransforms(batch, 5);
              let c1 = getTransforms(batch, 6);
              let c2 = getTransforms(batch, 7);
              let projection = c1 * xf + c2 * yf + 1.0;
              if (projection == 0.0) {
                outputValue = uniforms.fillValue;
              } else {
                let inX = (a1 * xf + a2 * yf + a3) / projection;
                let inY = (b1 * xf + b2 * yf + b3) / projection;
                let mapX = mapCoord(inX, f32(uniforms.imageShape[2]));
                let mapY = mapCoord(inY, f32(uniforms.imageShape[1]));

                if (uniforms.interpolationModeId == 1) {
                  let coordY = i32(round(mapY));
                  let coordX = i32(round(mapX));
                  outputValue = readWithFillValue(batch, coordY, coordX,
                    channel);
                } else {
                  let yFloor = floor(mapY);
                  let xFloor = floor(mapX);
                  let yCeil = yFloor + 1.0;
                  let xCeil = xFloor + 1.0;
                  let valueYFloor = (xCeil - mapX) *
                  readWithFillValue(batch, i32(yFloor), i32(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, i32(yFloor), i32(xCeil), channel);
                  let valueYCeil = (xCeil - mapX) *
                  readWithFillValue(batch, i32(yCeil), i32(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, i32(yCeil), i32(xCeil), channel);
                  outputValue = (yCeil - mapY) * valueYFloor +
                  (mapY - yFloor) * valueYCeil;
                }
              }
              setOutputAtIndex(index, outputValue);
            }
          }
        `}};function une(r){let{inputs:e,backend:t,attrs:o}=r,{image:n,transforms:s}=e,{interpolation:a,fillMode:i,fillValue:p,outputShape:u}=o,[c,l,m,d]=n.shape,[f,h]=u!=null?u:[l,m],g=[c,f,h,d],x=new wx(g),b=a==="nearest"?1:2,C;switch(i){case"constant":C=1;break;case"reflect":C=2;break;case"wrap":C=3;break;case"nearest":C=4;break;default:C=1;break}let w=[{type:"int32",data:[b]},{type:"int32",data:[C]},{type:"float32",data:[p]}];return t.runWebGPUProgram(x,[n,s],"float32",w)}var PB={kernelName:Jn,backendName:"webgpu",kernelFunc:une};function pne(r){let{inputs:e,backend:t,attrs:o}=r,{value:n}=e,{axis:s}=o;s<0&&(s+=n.shape.length);let a=n,i=a.shape.length,p=n.shape[s],u=new Array(i-1),c=0;for(let h=0;h<i;h++)h!==s&&(u[c++]=a.shape[h]);let l=[],m=new Array(i).fill(0),d=a.shape.slice();d[s]=1;let f=new Array(p);for(let h=0;h<f.length;h++){m[s]=h;let g=ds({inputs:{x:a},backend:t,attrs:{begin:m,size:d}}),x=de({inputs:{x:g},backend:t,attrs:{shape:u}});f[h]=x,l.push(g)}return l.forEach(h=>t.disposeData(h.dataId)),f}var MB={kernelName:Rs,backendName:"webgpu",kernelFunc:pne};var cne=[B3,SM,wM,IM,vM,kM,TM,_M,EM,$M,AM,RM,FM,DM,OM,LM,BM,zM,WM,qM,KM,jM,z3,YM,QM,ZM,JM,eL,tL,nL,sL,aL,iL,uL,lL,mL,dL,fL,hL,gL,xL,yL,M3,bL,wL,CL,SL,IL,vL,kL,NL,TL,_L,EL,V3,$L,XM,AL,RL,FL,DL,OL,PL,LL,ML,BL,VL,PM,zL,WL,MM,UL,GL,HL,qL,pL,KL,jL,XL,UM,YL,JL,eB,tB,rB,oB,nB,sB,GM,aB,iB,uB,pB,L3,cB,lB,mB,dB,fB,hB,gB,xB,yB,bB,CB,VM,$B,AB,wB,IB,kB,NB,TB,_B,EB,SB,cL,RB,FB,vB,OB,PB,NM,MB,QL];for(let r of cne)Ia(r);var LB="4.1.0",lne="4.1.0",mne="4.1.0",dne="4.1.0",fne="4.1.0",hne="0.0.1-alpha.16",gne={tfjs:LB,"tfjs-core":LB,"tfjs-converter":lne,"tfjs-backend-cpu":mne,"tfjs-backend-webgl":dne,"tfjs-backend-wasm":fne,"tfjs-backend-webgpu":hne};export{gs as Abs,sa as Acos,aa as Acosh,Ei as AdadeltaOptimizer,$i as AdagradOptimizer,Ai as AdamOptimizer,Ri as AdamaxOptimizer,eo as Add,Mo as AddN,Lo as All,Bo as Any,Vo as ArgMax,Za as ArgMin,ia as Asin,ua as Asinh,pa as Atan,la as Atan2,ca as Atanh,zo as AvgPool,ip as AvgPool3D,Im as AvgPool3DGrad,wm as AvgPoolGrad,Pl as BackendWasm,Wo as BatchMatMul,xs as BatchToSpaceND,Ja as Bincount,up as BroadcastArgs,wne as BroadcastTo,co as Cast,Uo as Ceil,lo as ClipByValue,ei as Complex,pp as ComplexAbs,ys as Concat,Go as Conv2D,cp as Conv2DBackpropFilter,Ho as Conv2DBackpropInput,lp as Conv3D,vm as Conv3DBackpropFilterV2,mp as Conv3DBackpropInputV2,qo as Cos,Ko as Cosh,Yo as CropAndResize,jo as Cumprod,Xo as Cumsum,Do as DataStorage,ti as DenseBincount,Qo as DepthToSpace,Zo as DepthwiseConv2dNative,dp as DepthwiseConv2dNativeBackpropFilter,fp as DepthwiseConv2dNativeBackpropInput,hp as Diag,gp as Dilation2D,bb as Dilation2DBackpropFilter,yb as Dilation2DBackpropInput,hb as ENV,ri as Einsum,en as Elu,km as EluGrad,Uc as Environment,tn as Equal,ma as Erf,rn as Exp,bs as ExpandDims,da as Expm1,oi as FFT,Cs as Fill,on as FlipLeftRight,nn as Floor,sn as FloorDiv,Zi as FromPixels,an as FusedBatchNorm,ho as FusedConv2D,go as FusedDepthwiseConv2D,Fu as GPGPUContext,un as GatherNd,Ss as GatherV2,ll as GraphModel,pn as Greater,cn as GreaterEqual,ni as IFFT,mo as Identity,si as Imag,fa as IsFinite,ha as IsInf,ln as IsNan,Zr as KernelBackend,yp as LRN,Nm as LRNGrad,mn as LeakyRelu,dn as Less,fn as LessEqual,xp as LinSpace,hn as Log,ga as Log1p,Ine as LogSoftmax,gn as LogicalAnd,xn as LogicalNot,xa as LogicalOr,GI as LogicalXor,vne as LowerBound,Oi as MathBackendCPU,Bi as MathBackendWebGL,yn as Max,Cn as MaxPool,bp as MaxPool3D,_m as MaxPool3DGrad,Tm as MaxPoolGrad,Cp as MaxPoolWithArgmax,bn as Maximum,Sn as Mean,wn as Min,In as Minimum,vn as MirrorPad,ya as Mod,Fi as MomentumOptimizer,Sp as Multinomial,kn as Multiply,ws as Neg,Tn as NonMaxSuppressionV3,ba as NonMaxSuppressionV4,_n as NonMaxSuppressionV5,Nn as NotEqual,Lb as OP_SCOPE_SUFFIX,En as OneHot,Is as OnesLike,wr as Optimizer,ns as OptimizerConstructors,vs as Pack,$n as PadV2,kne as Pool,An as Pow,Rn as Prelu,Fn as Prod,Di as RMSPropOptimizer,wp as RaggedGather,Ip as RaggedRange,vp as RaggedTensorToTensor,ks as Range,_b as Rank,ai as Real,Jo as RealDiv,Dn as Reciprocal,Et as Reduction,On as Relu,Ln as Relu6,Ns as Reshape,Mn as ResizeBilinear,$m as ResizeBilinearGrad,Pn as ResizeNearestNeighbor,Em as ResizeNearestNeighborGrad,Bn as Reverse,es as RotateWithOffset,Ca as Round,Vn as Rsqrt,qs as SGDOptimizer,zn as ScatterNd,ii as SearchSorted,Ts as Select,Xi as Selu,Un as Sigmoid,Yi as Sign,Wn as Sin,Sa as Sinh,_s as Slice,qn as Softmax,Qi as Softplus,Es as SpaceToBatchND,ui as SparseFillEmptyRows,wa as SparseReshape,pi as SparseSegmentMean,ci as SparseSegmentSum,li as SparseToDense,$s as SplitV,Gn as Sqrt,mi as Square,Kn as SquaredDifference,Ds as Step,jn as StridedSlice,As as StringNGrams,di as StringSplit,fi as StringToHashBucketFast,Xn as Sub,Hn as Sum,Yn as Tan,Qn as Tanh,it as Tensor,st as TensorBuffer,to as Tile,Zn as TopK,Jn as Transform,ro as Transpose,kp as Unique,Rs as Unpack,Np as UnsortedSegmentSum,Nne as UpperBound,va as Variable,Ui as WebGPUBackend,Fs as ZerosLike,fo as _FusedMatMul,Yt as abs,f0 as acos,h0 as acosh,xe as add,g0 as addN,x0 as all,y0 as any,b0 as argMax,C0 as argMin,S0 as asin,w0 as asinh,I0 as atan,v0 as atan2,k0 as atanh,td as avgPool,_0 as avgPool3d,Oie as backend,S as backend_util,E0 as basicLSTMCell,wi as batchNorm,A0 as batchNorm2d,R0 as batchNorm3d,F0 as batchNorm4d,rd as batchToSpaceND,od as bincount,XG as booleanMaskAsync,D0 as broadcastArgs,Ii as broadcastTo,br as broadcast_util,Qv as browser,le as buffer,Ke as cast,O0 as ceil,P0 as clipByValue,Br as clone,Tr as complex,gt as concat,M0 as concat1d,L0 as concat2d,B0 as concat3d,V0 as concat4d,z0 as conv1d,vi as conv2d,W0 as conv2dTranspose,U0 as conv3d,H0 as conv3dTranspose,Dne as copyRegisteredKernels,q0 as cos,K0 as cosh,il as cosineWindow,j0 as cumprod,X0 as cumsum,Cr as customGrad,Y0 as denseBincount,eC as deprecationWarn,Q0 as depthToSpace,Bp as depthwiseConv2d,xK as deregisterOp,yi as device_util,Z0 as diag,J0 as dilation2d,vie as disableDeprecationWarnings,Dt as dispose,kie as disposeVariables,Ge as div,ek as divNoNan,tk as dot,aH as dropout,rk as einsum,ad as elu,Iie as enableDebugMode,wie as enableProdMode,xC as enclosingPowerOfTwo,cr as engine,O as env,sd as equal,ok as erf,ak as euclideanNorm,Co as exp,Fa as expandDims,ik as expm1,id as eye,zp as fft,Ws as fill,Fie as findBackend,Die as findBackendFactory,ud as floor,Jm as floorDiv,L$ as forceHalfFloat,yC as fused,pd as gather,nH as gatherND,Ym as gather_util,Aie as getBackend,Cb as getGradient,qc as getKernel,Am as getKernelsForBackend,Nee as getThreadsCount,yw as gpgpu_util,l4 as grad,m4 as grads,cu as greater,cd as greaterEqual,hu as ifft,Si as imag,uq as image,uH as inTopKAsync,Ea as io,Fd as irfft,uk as isFinite,pk as isInf,ck as isNaN,_r as keep,Lt as kernel_impls,ld as leakyRelu,lk as less,Vp as lessEqual,pq as linalg,mk as linspace,l6 as loadGraphModel,m6 as loadGraphModelSync,dk as localResponseNormalization,Da as log,md as log1p,fk as logSigmoid,hk as logSoftmax,hd as logSumExp,lu as logicalAnd,gd as logicalNot,xd as logicalOr,gk as logicalXor,cq as losses,xk as lowerBound,Xe as matMul,jv as math,Us as max,bd as maxPool,yk as maxPool3d,bk as maxPoolWithArgmax,Cd as maximum,mu as mean,Nie as memory,Ck as meshgrid,sl as min,Sd as minimum,Sk as mirrorPad,wk as mod,Ik as moments,QG as movingAverage,ae as mul,vk as multiRNNCell,kk as multinomial,yr as neg,CC as nextFrame,pu as norm,wd as notEqual,tl as oneHot,Gs as ones,Nk as onesLike,N as op,Tk as outerProduct,Hs as pad,_k as pad1d,Ek as pad2d,$k as pad3d,Ak as pad4d,Rk as pool,Ra as pow,vd as prelu,Gm as print,Fk as prod,Tie as profile,Dk as raggedGather,Ok as raggedRange,Pk as raggedTensorToTensor,Mk as rand,e1 as randomGamma,Ed as randomNormal,t1 as randomStandardNormal,$d as randomUniform,Ni as range,$ie as ready,$a as real,r1 as reciprocal,Ci as registerBackend,Ane as registerGradient,Ia as registerKernel,gK as registerOp,Ti as relu,Ad as relu6,Rie as removeBackend,z as reshape,no as reverse,o1 as reverse1d,n1 as reverse2d,s1 as reverse3d,a1 as reverse4d,Wp as rfft,Rd as round,i1 as rsqrt,be as scalar,JG as scatterND,rl as scatter_util,al as searchSorted,u1 as selu,p1 as separableConv2d,p0 as serialization,Eie as setBackend,Pie as setPlatform,kee as setThreadsCount,Iee as setWasmPath,vee as setWasmPaths,RS as setWebGLContext,c1 as setdiff1dAsync,Qp as shared,zs as sigmoid,l1 as sign,iq as signal,m1 as sin,d1 as sinh,He as slice,f1 as slice1d,h1 as slice2d,g1 as slice3d,x1 as slice4d,ut as slice_util,y1 as softmax,fd as softplus,Id as spaceToBatchND,lq as sparse,rH as sparseToDense,aq as spectral,Oa as split,$r as sqrt,Qt as square,Dd as squaredDifference,Up as squeeze,Sr as stack,Od as step,b1 as stridedSlice,mq as string,Ne as sub,et as sum,ka as sumOutType,C1 as tan,nl as tanh,nr as tensor,mr as tensor1d,_i as tensor2d,Xm as tensor3d,S1 as tensor4d,w1 as tensor5d,I1 as tensor6d,hv as tensor_util,d0 as test_util,Ee as tidy,ki as tile,_ie as time,v1 as topk,hMe as train,Mp as transpose,k1 as truncatedNormal,N1 as unique,Fne as unregisterGradient,Rne as unregisterKernel,T1 as unsortedSegmentSum,so as unstack,dt as upcastType,_1 as upperBound,y as util,d4 as valueAndGrad,f4 as valueAndGrads,E1 as variable,pC as variableGrads,gne as version,f6 as version_converter,xW as version_core,U6 as version_cpu,Tee as version_wasm,L8 as version_webgl,L9e as webgl,oc as webgl_util,nI as webgpu_util,os as where,Md as whereAsync,Vr as zeros,Ut as zerosLike};