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human
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/*
Human
homepage: <https://github.com/vladmandic/human>
author: <https://github.com/vladmandic>'
*/
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Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((e,t)=>this.registryFactory[t].priority-this.registryFactory[e].priority)}initializeBackendsAndReturnBest(){let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let a=e[t],{success:n,asyncInit:r}=this.initializeBackend(a);if(r||n)return{name:a,asyncInit:r}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let a=this.state.tensorInfo.get(t),n=a.backend,r=this.readSync(t),s=n.refCount(t);n.disposeData(t,!0),a.backend=e,e.move(t,r,a.shape,a.dtype,s),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let a=null;if(t==null){if(typeof e!="function")throw new Error("Please provide a function to tidy()");t=e}else{if(typeof e!="string"&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof t!="function")throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");a=e}let n;return this.scopedRun(()=>this.startScope(a),()=>this.endScope(n),()=>(n=t(),n instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),n))}scopedRun(e,t,a){e();try{let n=a();return t(),n}catch(n){throw t(),n}}nextTensorId(){return ld.nextTensorId++}nextVariableId(){return ld.nextVariableId++}clone(e){let t=z.runKernel(ki,{x:e}),a={x:e},n=s=>({x:()=>{let i="float32",o={x:s},l={dtype:i};return z.runKernel(ti,o,l)}}),r=[];return this.addTapeNode(this.state.activeScope.name,a,[t],n,r,{}),t}runKernel(e,t,a){if(this.backendName==null&&this.backend,Sc(e,this.backendName)==null)throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:a})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,a){let n=this.backend.numDataIds(),r=0;a.forEach(o=>{r+=o.dtype==="complex64"?3:1});let s=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=n-t-r-s;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,a=[],n=this.isTapeOn(),r=this.state.numBytes,s=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let o,l=_m(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(_m(e)){let{kernelName:h,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let g=Sc(h,this.backendName);P(g!=null,()=>`Cannot find registered kernel '${h}' for backend '${this.backendName}'`),i=()=>{let x=this.backend.numDataIds();o=g.kernelFunc({inputs:f,attrs:m,backend:this.backend});let A=Array.isArray(o)?o:[o];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(h,x,A);let y=A.map(b=>b.rank!=null?b:this.makeTensorFromTensorInfo(b));if(n){let b=this.getTensorsForGradient(h,f,y);a=this.saveTensorsForBackwardMode(b)}return y}}else{let{forwardFunc:h}=e,f=m=>{!n||(a=m.map(g=>this.keep(this.clone(g))))};i=()=>{let m=this.backend.numDataIds();o=this.tidy(()=>h(this.backend,f));let g=Array.isArray(o)?o:[o];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,m,g),g}}let{inputs:u,attrs:p}=e,c=_m(e)?null:e.backwardsFunc,d;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(d=this.profiler.profileKernel(l,u,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),n&&this.addTapeNode(l,u,t,c,a,p),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-r,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-s,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(h=>u[h]!=null?u[h].shape:null),outputShapes:t.map(h=>h.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(t=>this.keep(this.clone(t)))}getTensorsForGradient(e,t,a){let n=Hm(e);if(n!=null){let r=n.inputsToSave||[],s=n.outputsToSave||[],i;n.saveAllInputs?(P(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(l=>t[l])):i=r.map(l=>t[l]);let o=a.filter((l,u)=>s[u]);return i.concat(o)}return[]}makeTensor(e,t,a,n){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");a=a||"float32",n=n||this.backend;let r=e;a==="string"&&Lr(e[0])&&(r=e.map(o=>Gd(o)));let s=n.write(r,t,a),i=new pt(t,a,s,this.nextTensorId());if(this.trackTensor(i,n),a==="string"){let o=this.state.tensorInfo.get(s),l=pA(r);this.state.numBytes+=l-o.bytes,o.bytes=l}return i}makeTensorFromDataId(e,t,a,n){a=a||"float32";let r={dataId:e,shape:t,dtype:a};return this.makeTensorFromTensorInfo(r,n)}makeTensorFromTensorInfo(e,t){let{dataId:a,shape:n,dtype:r}=e,s=new pt(n,r,a,this.nextTensorId());return this.trackTensor(s,t),s}makeVariable(e,t=!0,a,n){a=a||this.nextVariableId().toString(),n!=null&&n!==e.dtype&&(e=e.cast(n));let r=new od(e,t,a,this.nextTensorId());if(this.state.registeredVariables[r.name]!=null)throw new Error(`Variable with name ${r.name} was already registered`);return this.state.registeredVariables[r.name]=r,this.incRef(r,this.backend),r}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let a=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(a=e.size*Vm(e.dtype)),this.state.numBytes+=a,this.state.tensorInfo.has(e.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(e.dataId,{backend:t||this.backend,dtype:e.dtype,shape:e.shape,bytes:a})),e instanceof od||this.track(e)}incRef(e,t){this.trackTensor(e,t),this.backend.incRef(e.dataId)}removeDataId(e,t){this.state.tensorInfo.has(e)&&this.state.tensorInfo.get(e).backend===t&&(this.state.tensorInfo.delete(e),this.state.numDataBuffers--)}disposeTensor(e){if(!this.state.tensorInfo.has(e.dataId))return;let t=this.state.tensorInfo.get(e.dataId);if(this.state.numTensors--,e.dtype==="string"&&(this.state.numStringTensors--,this.state.numBytes-=t.bytes),e.dtype!=="complex64"&&e.dtype!=="string"){let a=e.size*Vm(e.dtype);this.state.numBytes-=a}t.backend.disposeData(e.dataId)&&this.removeDataId(e.dataId,t.backend)}disposeVariables(){for(let e in this.state.registeredVariables){let t=this.state.registeredVariables[e];this.disposeVariable(t)}}disposeVariable(e){this.disposeTensor(e),this.state.registeredVariables[e.name]!=null&&delete this.state.registeredVariables[e.name]}memory(){let e=this.backend.memory();return e.numTensors=this.state.numTensors,e.numDataBuffers=this.state.numDataBuffers,e.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(e.unreliable=!0,e.reasons==null&&(e.reasons=[]),e.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),e}async profile(e){this.state.profiling=!0;let t=this.state.numBytes,a=this.state.numTensors;this.state.activeProfile.kernels=[],this.state.activeProfile.result=await e(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max(...this.state.activeProfile.kernels.map(n=>n.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-a;for(let n of this.state.activeProfile.kernels)n.kernelTimeMs=await n.kernelTimeMs,n.extraInfo=await n.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(e,t,a,n,r,s){let i={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:a,saved:r},o=Hm(e);o!=null&&(n=o.gradFunc),n!=null&&(i.gradient=l=>(l=l.map((u,p)=>{if(u==null){let c=a[p],d=Gc(c.size,c.dtype);return this.makeTensor(d,c.shape,c.dtype)}return u}),n(l.length>1?l:l[0],r,s))),this.state.activeTape.push(i)}keep(e){return e.kept=!0,e}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){let t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){let t=Q1(e),a=new Set(t.map(r=>r.id));for(let r=0;r<this.state.activeScope.track.length;r++){let s=this.state.activeScope.track[r];!s.kept&&!a.has(s.id)&&s.dispose()}let n=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(r=>{!r.kept&&r.scopeId===n.id&&this.track(r)})}gradients(e,t,a,n=!1){if(P(t.length>0,()=>"gradients() received an empty list of xs."),a!=null&&a.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${a.dtype}'`);let r=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));P(r instanceof pt,()=>"The result y returned by f() must be a tensor.");let s=qS(this.state.activeTape,t,r);if(!n&&s.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",()=>{let i={};i[r.id]=a==null?sT(r.shape):a,XS(i,s,l=>this.tidy(l),iT);let o=t.map(l=>i[l.id]);return this.state.gradientDepth===0&&(this.state.activeTape.forEach(l=>{for(let u of l.saved)u.dispose()}),this.state.activeTape=null),{value:r,grads:o}})}customGrad(e){return P(Hr(e),()=>"The f passed in customGrad(f) must be a function."),(...t)=>{P(t.every(i=>i instanceof pt),()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors");let a,n={};t.forEach((i,o)=>{n[o]=i});let r=(i,o)=>(a=e(...t,o),P(a.value instanceof pt,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),P(Hr(a.gradFunc),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."),a.value),s=(i,o)=>{let l=a.gradFunc(i,o),u=Array.isArray(l)?l:[l];P(u.length===t.length,()=>"The function f passed in customGrad(f) must 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i=R(e,"x","batchNorm"),o=R(t,"mean","batchNorm"),l=R(a,"variance","batchNorm"),u;r!=null&&(u=R(r,"scale","batchNorm"));let p;return n!=null&&(p=R(n,"offset","batchNorm")),P(i.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${i.rank}.`),P(o.rank===4||o.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${o.rank}.`),P(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),u!=null&&P(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),p!=null&&P(p.rank===4||p.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${p.rank}.`),Qd(i,o,l,p,u,s)}var Iy=D({batchNorm4d_:MN});function $N(e,t,a){let n=R(e,"x","bincount"),r=R(t,"weights","bincount");P(n.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${n.dtype}`),P(a>=0,()=>`size must be non-negative, but got 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Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}};Eh.className="Adamax";ss(Eh);var ip=class extends is{constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,a)=>{let n=Array.isArray(e)?e[a].tensor:e[t];if(n==null)return;let r=z.registeredVariables[t];$e(()=>{let s=be(ae(this.c,n),r);r.assign(s)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=On(Fe(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer does 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n=k("tensorArrayId",e,t,a),r=k("tensor",e,t,a),s=k("lengths",e,t,a),i=a.getTensorArray(n.id);return i.split(s,r),[i.idTensor]}case"TensorArraySizeV3":{let n=k("tensorArrayId",e,t,a),r=a.getTensorArray(n.id);return[Fe(r.size(),"int32")]}case"TensorArrayCloseV3":{let n=k("tensorArrayId",e,t,a),r=a.getTensorArray(n.id);return r.clearAndClose(),[r.idTensor]}case"TensorListSetItem":{let n=k("tensorListId",e,t,a),r=k("index",e,t,a),s=k("tensor",e,t,a),i=a.getTensorList(n.id);return i.setItem(r,s),[i.idTensor]}case"TensorListGetItem":{let n=k("tensorListId",e,t,a),r=k("index",e,t,a),s=k("elementShape",e,t,a),i=k("elementDType",e,t,a);return[a.getTensorList(n.id).getItem(r,s,i)]}case"TensorListScatterV2":case"TensorListScatter":{let n=k("indices",e,t,a),r=k("tensor",e,t,a),s=k("elementShape",e,t,a),i=k("numElements",e,t,a),o=qP(r,n,s,i);return a.addTensorList(o),[o.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let n=k("elementShape",e,t,a),r=k("elementDType",e,t,a),s;e.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=k(s,e,t,a),o=e.op==="TensorListReserve"?-1:i,l=jP(n,r,i,o);return a.addTensorList(l),[l.idTensor]}case"TensorListGather":{let n=k("tensorListId",e,t,a),r=k("indices",e,t,a),s=k("elementShape",e,t,a),i=k("elementDType",e,t,a);return[a.getTensorList(n.id).gather(r,i,s)]}case"TensorListStack":{let n=k("tensorListId",e,t,a),r=k("elementShape",e,t,a),s=k("elementDType",e,t,a),i=k("numElements",e,t,a);return[a.getTensorList(n.id).stack(r,s,i)]}case"TensorListFromTensor":{let n=k("tensor",e,t,a),r=k("elementShape",e,t,a),s=k("elementDType",e,t,a),i=HP(n,r,s);return a.addTensorList(i),[i.idTensor]}case"TensorListConcat":case"TensorListConcatV2":{let n=k("tensorListId",e,t,a),r=a.getTensorList(n.id),s=k("dtype",e,t,a),i=k("elementShape",e,t,a);return[r.concat(s,i)]}case"TensorListPushBack":{let n=k("tensorListId",e,t,a),r=k("tensor",e,t,a),s=a.getTensorList(n.id);return 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r=k("strides",e,t,a),s=mc(e,t,a),i=k("dataFormat",e,t,a).toUpperCase(),o=k("dilations",e,t,a);return[n.conv2d(k("x",e,t,a),k("filter",e,t,a),[r[1],r[2]],s,i,[o[1],o[2]])]}case"_FusedConv2D":{let{stride:r,pad:s,dataFormat:i,dilations:o,biasArg:l,preluArg:u,activationFunc:p,leakyreluAlpha:c}=ax(e,t,a);return[n.fused.conv2d({x:k("x",e,t,a),filter:k("filter",e,t,a),strides:[r[1],r[2]],pad:s,dataFormat:i,dilations:[o[1],o[2]],bias:l,activation:p,preluActivationWeights:u,leakyreluAlpha:c})]}case"FusedDepthwiseConv2dNative":{let{stride:r,pad:s,dataFormat:i,dilations:o,biasArg:l,preluArg:u,activationFunc:p,leakyreluAlpha:c}=ax(e,t,a);return[n.fused.depthwiseConv2d({x:k("x",e,t,a),filter:k("filter",e,t,a),strides:[r[1],r[2]],pad:s,dataFormat:i,dilations:[o[1],o[2]],bias:l,activation:p,preluActivationWeights:u,leakyreluAlpha:c})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{let r=k("outputShape",e,t,a),s=k("strides",e,t,a),i=mc(e,t,a);return[n.conv2dTranspose(k("x",e,t,a),k("filter",e,t,a),r,[s[1],s[2]],i)]}case"DepthwiseConv2dNative":case"DepthwiseConv2d":{let r=k("strides",e,t,a),s=mc(e,t,a),i=k("dilations",e,t,a),o=k("dataFormat",e,t,a).toUpperCase();return[n.depthwiseConv2d(k("input",e,t,a),k("filter",e,t,a),[r[1],r[2]],s,o,[i[1],i[2]])]}case"Conv3D":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("dataFormat",e,t,a).toUpperCase(),o=k("dilations",e,t,a);return[n.conv3d(k("x",e,t,a),k("filter",e,t,a),[r[1],r[2],r[3]],s,i,[o[1],o[2],o[3]])]}case"AvgPool":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("kernelSize",e,t,a);return[n.avgPool(k("x",e,t,a),[i[1],i[2]],[r[1],r[2]],s)]}case"MaxPool":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("kernelSize",e,t,a);return[n.maxPool(k("x",e,t,a),[i[1],i[2]],[r[1],r[2]],s)]}case"MaxPoolWithArgmax":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("kernelSize",e,t,a),o=k("includeBatchInIndex",e,t,a),{result:l,indexes:u}=n.maxPoolWithArgmax(k("x",e,t,a),[i[1],i[2]],[r[1],r[2]],s,o);return[l,u]}case"AvgPool3D":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("kernelSize",e,t,a);return[n.avgPool3d(k("x",e,t,a),[i[1],i[2],i[3]],[r[1],r[2],r[3]],s)]}case"MaxPool3D":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("kernelSize",e,t,a);return[n.maxPool3d(k("x",e,t,a),[i[1],i[2],i[3]],[r[1],r[2],r[3]],s)]}case"Dilation2D":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("dilations",e,t,a),o=r[1],l=r[2],u=i[1],p=i[2];return[n.dilation2d(k("x",e,t,a),k("filter",e,t,a),[o,l],s,[u,p],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},YP=(e,t,a,n=Zt)=>{switch(e.op){case"Fill":{let r=k("shape",e,t,a),s=k("dtype",e,t,a),i=k("value",e,t,a);return[n.fill(r,i,s)]}case"LinSpace":{let r=k("start",e,t,a),s=k("stop",e,t,a),i=k("num",e,t,a);return[n.linspace(r,s,i)]}case"Multinomial":{let r=k("logits",e,t,a),s=k("numSamples",e,t,a),i=k("seed",e,t,a);return[n.multinomial(r,s,i)]}case"OneHot":{let r=k("indices",e,t,a),s=k("depth",e,t,a),i=k("onValue",e,t,a),o=k("offValue",e,t,a),l=k("dtype",e,t,a);return[n.oneHot(r,s,i,o,l)]}case"Ones":return[n.ones(k("shape",e,t,a),k("dtype",e,t,a))];case"OnesLike":return[n.onesLike(k("x",e,t,a))];case"RandomStandardNormal":return[n.randomStandardNormal(k("shape",e,t,a),k("dtype",e,t,a),k("seed",e,t,a))];case"RandomUniform":return[n.randomUniform(k("shape",e,t,a),k("minval",e,t,a),k("maxval",e,t,a),k("dtype",e,t,a))];case"Range":{let r=k("start",e,t,a),s=k("stop",e,t,a),i=k("step",e,t,a);return[n.range(r,s,i,k("dtype",e,t,a))]}case"TruncatedNormal":{let r=k("shape",e,t,a),s=k("mean",e,t,a),i=k("stdDev",e,t,a),o=k("seed",e,t,a);return[n.truncatedNormal(r,s,i,k("dtype",e,t,a),o)]}case"Zeros":return[n.zeros(k("shape",e,t,a),k("dtype",e,t,a))];case"ZerosLike":return[n.zerosLike(k("x",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function Dm(e,t,a){let n=k("boxes",e,t,a),r=k("scores",e,t,a),s=k("maxOutputSize",e,t,a),i=k("iouThreshold",e,t,a),o=k("scoreThreshold",e,t,a),l=k("softNmsSigma",e,t,a);return{boxes:n,scores:r,maxOutputSize:s,iouThreshold:i,scoreThreshold:o,softNmsSigma:l}}var JP=async(e,t,a,n,r=Zt)=>{switch(e.op){case"NonMaxSuppressionV5":{let{boxes:s,scores:i,maxOutputSize:o,iouThreshold:l,scoreThreshold:u,softNmsSigma:p}=Dm(e,t,a),c=await r.image.nonMaxSuppressionWithScoreAsync(s,i,o,l,u,p);return[c.selectedIndices,c.selectedScores]}case"NonMaxSuppressionV4":{let{boxes:s,scores:i,maxOutputSize:o,iouThreshold:l,scoreThreshold:u}=Dm(e,t,a),p=k("padToMaxOutputSize",e,t,a),c=await r.image.nonMaxSuppressionPaddedAsync(s,i,o,l,u,p);return[c.selectedIndices,c.validOutputs]}case"NonMaxSuppressionV3":case"NonMaxSuppressionV2":{let{boxes:s,scores:i,maxOutputSize:o,iouThreshold:l,scoreThreshold:u}=Dm(e,t,a);return[await r.image.nonMaxSuppressionAsync(s,i,o,l,u)]}case"Where":{let 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type ${e.op} is not implemented`)}},rF=(e,t,a,n=Zt)=>{switch(e.op){case"Equal":return[n.equal(k("a",e,t,a),k("b",e,t,a))];case"NotEqual":return[n.notEqual(k("a",e,t,a),k("b",e,t,a))];case"Greater":return[n.greater(k("a",e,t,a),k("b",e,t,a))];case"GreaterEqual":return[n.greaterEqual(k("a",e,t,a),k("b",e,t,a))];case"Less":return[n.less(k("a",e,t,a),k("b",e,t,a))];case"LessEqual":return[n.lessEqual(k("a",e,t,a),k("b",e,t,a))];case"LogicalAnd":return[n.logicalAnd(k("a",e,t,a),k("b",e,t,a))];case"LogicalNot":return[n.logicalNot(k("a",e,t,a))];case"LogicalOr":return[n.logicalOr(k("a",e,t,a),k("b",e,t,a))];case"Select":case"SelectV2":return[n.where(k("condition",e,t,a),k("a",e,t,a),k("b",e,t,a))];default:throw TypeError(`Node type ${e.op} is not 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r(()=>UP(i,o,l));case"control":return KP(i,o,l);case"convolution":return r(()=>ZP(i,o,l));case"creation":return r(()=>YP(i,o,l));case"dynamic":return JP(i,o,l);case"evaluation":return r(()=>QP(i,o,l));case"image":return r(()=>nF(i,o,l));case"graph":return r(()=>eF(i,o,l));case"logical":return r(()=>rF(i,o,l));case"matrices":return r(()=>sF(i,o,l));case"normalization":return r(()=>iF(i,o,l));case"ragged":return r(()=>oF(i,o,l));case"reduction":return r(()=>lF(i,o,l));case"slice_join":return r(()=>uF(i,o,l));case"sparse":return r(()=>dF(i,o,l));case"spectral":return r(()=>pF(i,o,l));case"string":return r(()=>cF(i,o,l));case"transformation":return r(()=>hF(i,o,l));case"hash_table":return aF(i,o,l,n);case"custom":let u=w4(i.op);if(u&&u.customExecutor)return u.customExecutor(new WP(i,o,l));throw TypeError(`Custom op ${i.op} is not registered.`);default:throw TypeError(`Unknown op '${i.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`)}})(e,t,a);return v.isPromise(s)?s.then(i=>[].concat(i)):[].concat(s)}var rx=class{constructor(e={},t={},a={},n={}){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=a,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 a=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(a))}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 sx(e,t,a,n){let r=new Set,s=[],i=null,o=null,l=new Set,u=Object.keys(e).map(d=>ja(d)[0]),p=[];n!=null&&(p=n.map(d=>ja(d.name)[0]));let c=[...t];for(;c.length>0;){let d=c.pop();if((G4(d)||AF(d)||yF(d))&&i==null&&(i=d,o=i.children.map(h=>h.name).filter(h=>r.has(h))),r.add(d.name),a[d.name]==null&&u.indexOf(d.name)===-1&&p.indexOf(d.name)===-1){if(d.inputs.length===0){s.push(d.name);continue}d.inputs.forEach(h=>{l.has(h.name)||(l.add(h.name),c.push(h))})}}return{inputs:e,outputs:t,usedNodes:r,missingInputs:s,dynamicNode:i,syncInputs:o}}function fF(e,t,a){let{usedNodes:n,inputs:r}=a,s=[],i=Object.keys(r).map(p=>ja(p)[0]).map(p=>e.nodes[p]),o=e.initNodes;i.forEach(p=>{n.has(p.name)&&s.push(p)}),e.weights.forEach(p=>{n.has(p.name)&&s.push(p)}),o!=null&&o.forEach(p=>{n.has(p.name)&&s.push(p)});let l=new Set,u=[];for(;s.length>0;){let p=s.pop();l.add(p.name),t[p.name]||u.push(p),p.children.forEach(c=>{!l.has(c.name)&&n.has(c.name)&&c.inputs.every(d=>l.has(d.name))&&s.push(c)})}return u}var mF=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],gF=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],xF=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function G4(e){return mF.indexOf(e.op)>=0}function AF(e){return gF.indexOf(e.op)>=0}function yF(e){return xF.indexOf(e.op)>=0}var A1=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(a=>{this._functionExecutorMap[a]=new A1(e.functions[a],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(a=>e[a].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 a=e.map(r=>r.name).sort(),n=t.map(r=>r.name).sort();return a.join(this.SEPERATOR)+"--"+n.join(this.SEPERATOR)}compile(e,t){let a=sx(e,t,this.weightMap,this._initNodes),{missingInputs:n,dynamicNode:r,syncInputs:s}=a;if(r!=null)throw new Error(`This execution contains the node '${r.name}', which has the dynamic op '${r.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${s}]`);if(n.length>0){let i=t.map(l=>l.name),o=Object.keys(e);throw new Error(`Cannot compute the outputs [${i}] from the provided inputs [${o}]. Missing the following inputs: [${n}]`)}return fF(this.graph,this.weightMap,a)}cloneAndKeepTensor(e){if(e==null)return null;let t=e.clone();return On(t),t}cloneTensorList(e){return e?e.map(t=>this.cloneAndKeepTensor(t)):null}cloneTensorMap(e){return Object.fromEntries(Object.entries(e).map(([t,a])=>[t,this.cloneTensorList(a)]))}execute(e,t){this.disposeIntermediateTensors(),e=this.mapInputs(e);let a=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let n=a.map(p=>this.graph.nodes[ja(p)[0]]),r=t.map(p=>ja(p)[0]),s=r.map(p=>this.graph.nodes[p]);s.length===0&&(s=this._outputs);let i=this.getCompilationKey(n,s),o=this.compiledMap.get(i);o==null&&(o=this.compile(e,s),this.compiledMap.set(i,o));try{this.keepIntermediateTensors=W().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(p){this.keepIntermediateTensors=!1,console.warn(p.message)}let l={},u={};return $e(()=>{let p=new rx(this.weightMap,l,u,this.functionExecutorMap),c=Object.assign({},this.weightMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap)),Object.keys(e).forEach(f=>{let[m,g]=ja(f),x=[];x[g]=e[f],c[m]=x,this.keepIntermediateTensors&&(this.clonedTensorsMap[m]=this.cloneTensorList(x))});let d=this.getFrozenTensorIds(c),h={};for(let f=0;f<o.length;f++){let m=o[f];if(!c[m.name]){let g=nx(m,c,p,this._resourceManager);if(v.isPromise(g))throw new Error(`The execution of the op '${m.op}' returned a promise. Please use model.executeAsync() instead.`);c[m.name]=g,this.keepIntermediateTensors&&(this.clonedTensorsMap[m.name]=this.cloneTensorList(g)),this.checkTensorForDisposal(m.name,m,c,p,d,r,h)}}return this.parent==null&&p.dispose(d),t.map(f=>ba(f,c,p))})}getFrozenTensorIds(e){let t=[].concat.apply([],Object.keys(e).map(a=>e[a]).map(a=>a.map(n=>n.id)));return new Set(t)}checkTensorForDisposal(e,t,a,n,r,s,i){t.category==="control"||s.indexOf(e)!==-1||(a[e].forEach(o=>{o!=null&&(i[o.id]=(i[o.id]||0)+t.children.length)}),t.inputs.forEach(o=>{if(o.category!=="control"){let l=bP(o.name,a,n);l!=null&&l.forEach(u=>{if(u&&!u.kept&&!r.has(u.id)){let p=i[u.id];p===1?(u.dispose(),delete i[u.id]):p!=null&&i[u.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,a=!1,n={},r={}){this.disposeIntermediateTensors(),a||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));try{this.keepIntermediateTensors=W().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(c){this.keepIntermediateTensors=!1,console.warn(c.message)}let s=new rx(this.weightMap,n,r,this.functionExecutorMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap));let i=await this.executeWithControlFlow(e,s,t,a),o=t.map(c=>ba(c,i,s)),l=o.map(c=>c.id),u=Object.keys(e).map(c=>e[c].id),p=new Set([...l,...u,...this.weightIds]);return Object.values(i).forEach(c=>{c.forEach(d=>{d&&!d.isDisposed&&!p.has(d.id)&&d.dispose()})}),this.parent==null&&s.dispose(p),o}async executeFunctionAsync(e,t,a){let n=e.reduce((r,s,i)=>(r[this.inputs[i].name]=s,r),{});return this._executeAsync(n,this.outputNodes,!0,t,a)}async executeWithControlFlow(e,t,a,n){let r=Object.keys(e),s=r.map(A=>this.graph.nodes[ja(A)[0]]),i=a.map(A=>ja(A)[0]),o=i.map(A=>this.graph.nodes[A]);o.length===0&&(o=this._outputs);let{usedNodes:l,missingInputs:u,dynamicNode:p,syncInputs:c}=sx(e,o,this.weightMap,this._initNodes),d=[...s,...this.graph.weights,...this._initNodes||[]].map(A=>({node:A,contexts:t.currentContext})),h=Object.assign({},this.weightMap);Object.keys(e).forEach(A=>{let[y,b]=ja(A),w=[];w[b]=e[A],h[y]=w});let f={},m=this.getFrozenTensorIds(h),g={};for(;d.length>0;){let A=this.processStack(s,d,t,h,g,m,i,f,l);await Promise.all(A)}p==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 x=o.filter(A=>!G4(A)&&!ba(A.name,h,t)).map(A=>A.name);if(x.length>0){let A="";throw p!=null&&(A=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${c}]`),new Error(`Cannot compute the outputs [${x}] from the provided inputs [${r}]. Consider providing the following inputs: [${u}]. ${A}`)}return h}processStack(e,t,a,n,r,s,i,o,l){let u=[];for(;t.length>0;){let p=t.pop();a.currentContext=p.contexts;let c="";if(p.node.op==="Enter"&&k("isConstant",p.node,n,a)&&([c]=mr(p.node.name,a)),n[p.node.name]==null){let d=nx(p.node,n,a,this._resourceManager);c||([c]=mr(p.node.name,a));let h=a.currentContext;v.isPromise(d)?u.push(d.then(f=>(n[c]=f,this.keepIntermediateTensors&&(this.clonedTensorsMap[c]=this.cloneTensorList(f)),a.currentContext=h,this.checkTensorForDisposal(c,p.node,n,a,s,i,o),this.processChildNodes(p.node,t,a,n,r,l),f))):(n[c]=d,this.keepIntermediateTensors&&(this.clonedTensorsMap[c]=this.cloneTensorList(d)),this.checkTensorForDisposal(c,p.node,n,a,s,i,o),this.processChildNodes(p.node,t,a,n,r,l))}else this.processChildNodes(p.node,t,a,n,r,l)}return u}processChildNodes(e,t,a,n,r,s){e.children.forEach(i=>{let[o]=mr(i.name,a);r[o]||!s.has(i.name)||(i.op==="Merge"?i.inputNames.some(l=>!!ba(l,n,a))&&(r[o]=!0,t.push({contexts:a.currentContext,node:i})):i.inputNames.every(l=>!!ba(l,n,a))&&(r[o]=!0,t.push({contexts:a.currentContext,node:i})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let a=e[t],[n]=ja(t),r=this.graph.nodes[n];if(r.attrParams.shape&&r.attrParams.shape.value){let s=r.attrParams.shape.value,i=s.length===a.shape.length&&a.shape.every((o,l)=>s[l]===-1||s[l]===o);v.assert(i,()=>`The shape of dict['${r.name}'] provided in model.execute(dict) must be [${s}], but was [${a.shape}]`)}r.attrParams.dtype&&r.attrParams.dtype.value&&v.assert(a.dtype===r.attrParams.dtype.value,()=>`The dtype of dict['${r.name}'] provided in model.execute(dict) must be ${r.attrParams.dtype.value}, but was ${a.dtype}`)})}mapInputs(e){var t,a;let n={};for(let r in e){let s=(a=(t=this._signature)===null||t===void 0?void 0:t.inputs)===null||a===void 0?void 0:a[r];s!=null?n[s.name]=e[r]:n[r]=e[r]}return n}checkInputs(e){let t=Object.keys(e).filter(a=>{let[n]=ja(a);return this.graph.nodes[n]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map(t=>{var a,n;let r=(n=(a=this._signature)===null||a===void 0?void 0:a.outputs)===null||n===void 0?void 0:n[t];return r!=null?r.name:t},{})}checkOutputs(e){e.forEach(t=>{let[a]=ja(t);if(!this.graph.nodes[a])throw new Error(`The output '${t}' is not found in the graph`)})}},bF=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},vF="?tfjs-format=file",wF="model.json",op=class{constructor(e,t={},a=jn){this.modelUrl=e,this.loadOptions=t,this.version="n/a",this.io=a,t==null&&(this.loadOptions={}),this.resourceManager=new bF}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=this.io.browserHTTPRequest(e,this.loadOptions);else{let t=this.io.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(this.io.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=this.handler.load();return v.isPromise(e)?e.then(t=>this.loadSync(t)):this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,a=this.artifacts.signature;if(this.artifacts.userDefinedMetadata!=null){let r=this.artifacts.userDefinedMetadata;r.signature!=null&&(a=r.signature),r.structuredOutputKeys!=null&&(this.structuredOutputKeys=r.structuredOutputKeys)}this.signature=a,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let n=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new A1(Q5.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(n),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let r=Q5.Instance.transformGraph(e.modelInitializer);this.initializer=new A1(r),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializerSignature=e.initializerSignature}return!0}async save(e,t){if(typeof e=="string"){let a=this.io.getSaveHandlers(e);if(a.length===0)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(a.length>1)throw new Error(`Found more than one (${a.length}) save handlers for URL '${e}'`);e=a[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 pt?[e]:e,a={};return t.forEach((n,r)=>a[this.structuredOutputKeys[r]]=n),a}return e}predict(e,t){let a=this.execute(e,this.outputNodes);return this.addStructuredOutputNames(a)}async predictAsync(e,t){let a=await this.executeAsync(e,this.outputNodes);return this.addStructuredOutputNames(a)}normalizeInputs(e){var t;if(!(e instanceof pt)&&!Array.isArray(e)){let r=(t=this.signature)===null||t===void 0?void 0:t.inputs;if(r!=null)for(let s in r){let i=r[s];i.resourceId!=null&&(e[s]=this.resourceIdToCapturedInput[i.resourceId])}return e}e=Array.isArray(e)?e:[e];let a=Object.keys(this.resourceIdToCapturedInput).length;if(e.length+a!==this.inputNodes.length)throw new Error(`Input tensor count mismatch, the graph model has ${this.inputNodes.length-a} non-resource placeholders, while there are ${e.length} input tensors provided.`);let n=0;return this.inputNodes.reduce((r,s)=>{var i,o,l;let u=(l=(o=(i=this.signature)===null||i===void 0?void 0:i.inputs)===null||o===void 0?void 0:o[s])===null||l===void 0?void 0:l.resourceId;return u!=null?r[s]=this.resourceIdToCapturedInput[u]:r[s]=e[n++],r},{})}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,a=Object.keys(t);for(let n=0;n<a.length;n++){let r=a[n],s=t[r];this.resourceIdToCapturedInput[s.resourceId]=e[n]}}}execute(e,t){this.resourceIdToCapturedInput==null&&this.setResourceIdToCapturedInput(this.executeInitializerGraph()),e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let a=this.executor.execute(e,t);return a.length>1?a:a[0]}async executeAsync(e,t){this.resourceIdToCapturedInput==null&&this.setResourceIdToCapturedInput(await this.executeInitializerGraphAsync()),e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let a=await this.executor.executeAsync(e,t);return a.length>1?a:a[0]}getIntermediateTensors(){return this.executor.getIntermediateTensors()}disposeIntermediateTensors(){this.executor.disposeIntermediateTensors()}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,a)=>(t[a]=[e[a]],t),{})}dispose(){this.executor.dispose(),this.initializer&&(this.initializer.dispose(),this.resourceIdToCapturedInput&&Y(this.resourceIdToCapturedInput)),this.resourceManager.dispose()}};async function r3(e,t={},a=jn){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&typeof e=="string"&&(e=IF(e));let n=new op(e,t,a);return await n.load(),n}function kF(e){if(e==null)throw new Error("modelUrl in loadGraphModelSync() cannot be null. Please provide model artifacts or an IOHandler that loads the model");let t;if(e instanceof Array){let[n,r]=e;if(!n)throw new Error("modelJSON must be the first element of the array");if(!r||!(r instanceof ArrayBuffer))throw new Error("An ArrayBuffer of weights must be the second element of the array");if(!("modelTopology"in n))throw new Error("Model JSON is missing 'modelTopology'");if(!("weightsManifest"in n))throw new Error("Model JSON is missing 'weightsManifest'");let s=jn.getWeightSpecs(n.weightsManifest),i=jn.getModelArtifactsForJSONSync(n,s,r);t=jn.fromMemorySync(i)}else if("load"in e)t=e;else if("modelTopology"in e&&"weightSpecs"in e&&"weightData"in e)t=jn.fromMemorySync(e);else throw new Error("Unknown model format");let a=new op(t);return a.load(),a}function IF(e){return e.endsWith("/")||(e=e+"/"),`${e}${wF}${vF}`}var SF="4.1.0";function ye(e,t){Array.isArray(e)||(e=[e]),e.forEach(a=>{a!=null&&v.assert(a.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}var TF=Tn.whereImpl,$h=class extends bl{constructor(){super(),this.blockSize=48,this.firstUse=!0,this.data=new vd(this,kt())}nextDataId(){return $h.nextDataId++}write(e,t,a){this.firstUse&&(this.firstUse=!1,W().get("IS_NODE")&&T.warn(`
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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.
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if(b=Math.ceil(Math.abs((A-x)/y)),b>ox)throw new Error(`Requires ((limit - start) / delta) <= ${ox}`);d[g+1]=d[g]+b}let h=d[c],f=v.getArrayFromDType(a,h),m=0;for(let g=0;g<c;++g){let x=d[g+1]-d[g],A=o?e[0]:e[g],y=u?s[0]:s[g];for(let b=0;b<x;++b)f[m++]=A,A+=y}return[d,f]}var vn=T.RowPartitionType,y1=class{constructor(e,t,a,n,r,s,i,o,l,u){this.shape=e,this.shapeShape=t,this.values=a,this.valuesShape=n,this.valuesDType=r,this.defaultValue=s,this.defaultValueShape=i,this.rowPartitionValues=o,this.rowPartitionValuesShapes=l,this.rowPartitionTypes=T.getRowPartitionTypesHelper(u),this.raggedRank=T.getRaggedRank(this.rowPartitionTypes)}getRowPartitionTypeByDimension(e){return this.rowPartitionTypes[0]===vn.FIRST_DIM_SIZE?this.rowPartitionTypes[e+1]:this.rowPartitionTypes[e]}getRowPartitionTensor(e){return this.rowPartitionTypes[0]===vn.FIRST_DIM_SIZE?this.rowPartitionValues[e+1]:this.rowPartitionValues[e]}getMaxWidth(e){let t=this.getRowPartitionTensor(e-1);switch(this.getRowPartitionTypeByDimension(e-1)){case vn.VALUE_ROWIDS:return y1.getMaxWidthValueRowID(t);case vn.ROW_SPLITS:return y1.getMaxWidthRowSplit(t);default:throw new Error(`Cannot handle partition type ${vn[this.getRowPartitionTypeByDimension(e-1)]}`)}}static getMaxWidthRowSplit(e){let t=e.length;if(t===0||t===1)return 0;let a=0;for(let n=0;n<t-1;++n){let r=e[n+1]-e[n];r>a&&(a=r)}return a}static getMaxWidthValueRowID(e){let t=e.length;if(t===0)return 0;let a=0,n=e[0],r=0;for(let s=1;s<t;++s){let i=e[s];i!==n&&(n=i,r=Math.max(s-a,r),a=s)}return Math.max(t-a,r)}tensorShapeFromTensor(e,t,a=!0){if(t.length===0){if(e[0]===-1)return[];throw new Error("The only valid scalar shape tensor is the fully unknown shape specified as -1.")}return ux(e,a)}calculateOutputSize(e){let t=this.valuesShape,a=this.defaultValueShape;T.validateDefaultValueShape(a,t);let n=this.tensorShapeFromTensor(this.shape,this.shapeShape),r=T.combineRaggedTensorToTensorShapes(this.raggedRank,n,t);r[0]<0&&(r[0]=e);for(let s=1;s<=this.raggedRank;++s)r[s]<0&&(r[s]=this.getMaxWidth(s));return r}calculateFirstParentOutputIndex(e,t,a){let n=Math.min(e,a),r=[],s=0;for(let i=0;i<n;++i,s+=t)r.push(s);for(let i=n;i<e;++i)r.push(-1);return v.assert(r.length===e,()=>"Final length of result must be equal to firstDimension."),r}calculateOutputIndexRowSplit(e,t,a,n){let r=e.length,s=[];for(let i=0;i<r-1;++i){let o=e[i+1]-e[i],l=Math.min(n,o),u=t[i];u===-1&&(l=0);for(let p=0;p<l;++p)s.push(u),u+=a;for(let p=0;p<o-l;++p)s.push(-1)}if(r>0&&s.length!==e[r-1])throw new Error("Invalid row split size.");return s}calculateOutputIndexValueRowID(e,t,a,n){let r=e.length,s=[];if(r===0)return[];let i=0,o=e[0];if(o>=t.length)throw new Error(`Got currentValueRowId=${o}, which is not less than ${t.length}`);let l=t[o];s.push(l);for(let u=1;u<r;++u){let p=e[u];if(p===o)l>=0&&(++i,i<n?l+=a:l=-1);else{if(i=0,o=p,p>=t.length)throw new Error(`Got nextValueRowId=${p} which is not less than ${t.length}`);l=t[p]}s.push(l)}if(s.length!==e.length)throw new Error("Invalid row ids.");return s}calculateOutputIndex(e,t,a,n){let r=this.getRowPartitionTensor(e),s=this.getRowPartitionTypeByDimension(e);switch(s){case vn.VALUE_ROWIDS:return this.calculateOutputIndexValueRowID(r,t,a,n);case vn.ROW_SPLITS:if(r.length-1>t.length)throw new Error(`Row partition size is greater than output size: ${r.length-1} > ${t.length}`);return this.calculateOutputIndexRowSplit(r,t,a,n);default:throw new Error(`Unsupported partition type: ${vn[s]}`)}}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 vn.FIRST_DIM_SIZE:return e[0];case vn.VALUE_ROWIDS:throw new Error("Cannot handle VALUE_ROWIDS in first dimension.");case vn.ROW_SPLITS:return this.rowPartitionValuesShapes[0][0]-1;default:throw new Error(`Cannot handle type ${vn[t]}`)}}compute(){if(this.rowPartitionValues[0].length<=0)throw new Error("Invalid first partition input. Tensor requires at least one element.");let e=this.getFirstDimensionSize(),t=this.calculateOutputSize(e),a=new Array(this.raggedRank+1);a[a.length-1]=1;for(let s=a.length-2;s>=0;--s)a[s]=a[s+1]*t[s+1];let n=ux(t,!1),r=v.getArrayFromDType(this.valuesDType,v.sizeFromShape(n));if(a[0]*t[0]>0){let s=this.calculateFirstParentOutputIndex(e,a[0],t[0]);for(let i=1;i<=this.raggedRank;++i)s=this.calculateOutputIndex(i-1,s,a[i],t[i]);this.setOutput(this.raggedRank,s,r,n)}return[n,r]}setOutput(e,t,a,n){if(a.length===0)return;let r=this.values,s=a,i=n.slice();i=i.slice(e+1);let o=v.sizeFromShape(i),l=t.length,u=this.defaultValue;if(u.length!==o&&u.length!==1){let h=this.defaultValueShape;$e(()=>{let f=J(u,h);u=sl(f,i).dataSync()})}let p=0,c=0,d=0;for(let h=0;h<=l;++h){let f=h<l?t[h]:-1;if(f===d){++d;continue}if(c<d){let m=r.subarray(p*o),g=s.subarray(c*o),x=(d-c)*o;lx(g,m,x)}if(h>=l){let m=a.length;f=Math.floor(m/o)}if(f>d)if(this.defaultValue.length===1)s.subarray(d*o,f*o).fill(this.defaultValue[0]),d=f;else for(;f>d;){let m=s.slice(d*o);lx(m,u,o),++d}f<0?(p=h+1,c=d):(p=h,c=d,d=c+1)}}};function lx(e,t,a){for(let n=0;n<a;n++)e[n]=t[n]}function ux(e,t){let a=[];for(let n of e){if(n<0){if(!t)throw new Error(`Dimension ${n} must be >= 0`);if(n<-1)throw new Error(`Dimension ${n} must be >= -1`);n=-1}a.push(n)}return a}function A7(e,t,a,n,r,s,i,o,l,u){return new y1(e,t,a,n,r,s,i,o,l,u).compute()}function d3(e,t,a,n){let r=e===t,s=e<t&&a<0,i=t<e&&a>1;if(r||s||i)return v.makeZerosTypedArray(0,n);let o=Math.abs(Math.ceil((t-e)/a)),l=v.makeZerosTypedArray(o,n);t<e&&a===1&&(a=-1),l[0]=e;for(let u=1;u<l.length;u++)l[u]=l[u-1]+a;return l}var y7=os(e=>1/Math.sqrt(e)),AO=ou(Qi,y7),yO={kernelName:Qi,backendName:"cpu",kernelFunc:AO};function tl(e,t,a,n,r,s,i,o,l,u){let p=[n/r,r],c=e.values,d=t.values;if(n===0)return Me(a,t.dtype);let h=Me(p,t.dtype);typeof l=="string"||typeof l=="number"?h.values.fill(l):typeof l=="boolean"&&h.values.fill(+l);for(let f=0;f<s;f++){let m=[],g=0;for(let x=0;x<i;x++){let A=c[f*i+x];m.push(A),g+=A*o[x]}if(g<0||g>=n/r)throw new Error(`Invalid indices: ${m} does not index into ${a}`);for(let x=0;x<r;x++)u?h.values[g*r+x]+=d[f*r+x]:h.values[g*r+x]=t.rank===0?d[0]:d[f*r+x]}return h}var bO=os(e=>1/(1+Math.exp(-e))),b7=ot(ao,e=>1/(1+Math.exp(-e))),vO={kernelName:ao,backendName:"cpu",kernelFunc:b7};function _c(e,t,a,n,r){let s=It.isSliceContinous(n,t,a),i=v.sizeFromShape(a),o=v.computeStrides(n);if(s){let c=It.computeFlatOffset(t,o);return r==="string"?e.slice(c,c+i):e.subarray(c,c+i)}let l=r==="string"?T.fromUint8ToStringArray(e):e,u=Me(n,r,l),p=Me(a,r);for(let c=0;c<p.size;++c){let d=p.indexToLoc(c),h=d.map((f,m)=>f+t[m]);p.set(u.get(...h),...d)}return r==="string"?T.fromStringArrayToUint8(p.values):p.values}function Gs(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,size:i}=n;ye(r,"slice");let[o,l]=It.parseSliceParams(r,s,i);It.assertParamsValid(r,o,l);let u=a.data.get(r.dataId).values,p=_c(u,o,l,r.shape,r.dtype);return a.makeTensorInfo(l,r.dtype,p)}var wO={kernelName:Zl,backendName:"cpu",kernelFunc:Gs};function v7(e,t,a,n,r,s,i){let o=t[0],l=s[0],u=new Array(l),p=new Array(o),c=t[1];if(l===0){if(o!==0)throw new Error(T.getSparseFillEmptyRowsIndicesDenseShapeMismatch(o));let g=v.getArrayFromDType(a,0),x=v.getArrayFromDType(r,0);return[g,[0,c],x,u,p]}let d=!0,h=0,f=new Array(l).fill(0);for(let g=0;g<o;++g){let x=e[g*c];if(x<0)throw new Error(T.getSparseFillEmptyRowsNegativeIndexErrorMessage(g,x));if(x>=l)throw new Error(T.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(g,x,l));++f[x],d=d&&x>=h,h=x}let m=!0;for(let g=0;g<l;++g){let x=f[g]===0;u[g]=x,m=m&&!x,f[g]=Math.max(f[g],1),g>0&&(f[g]+=f[g-1])}if(m&&d){let g=e,x=n;for(let A=0;A<o;++A)p[A]=A;return[g,[o,c],x,u,p]}else{let g=f[l-1],x=v.getArrayFromDType(a,g*c),A=v.getArrayFromDType(r,g),y=new Array(l).fill(0);for(let b=0;b<o;++b){let w=e[b*c],S=y[w],C=(w===0?0:f[w-1])+S;y[w]++;for(let E=0;E<c;++E)x[C*c+E]=e[b*c+E];A[C]=n[b],p[b]=C}for(let b=0;b<l;++b)if(y[b]===0){let w=b===0?0:f[b-1];x[w*c+0]=b;for(let S=1;S<c;++S)x[w*c+S]=0;A[w]=i}return[x,[g,c],A,u,p]}}function w7(e,t,a,n,r){let s=v.sizeFromShape(n),i=t[0],o=r.length,l=[],u=1,p=-1;for(let m=0;m<o;++m){let g=r[m];if(g===-1){if(p!==-1)throw new Error(T.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(p,m));p=m,l.push(1)}else{if(g<0)throw new Error(T.getSparseReshapeNegativeOutputDimErrorMessage(m,g));u*=g,l.push(g)}}if(p!==-1){if(u<=0)throw new Error(T.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage());let m=Math.trunc(s/u);if(u*m!==s)throw new Error(T.getSparseReshapeInputOutputMultipleErrorMessage(n,l));l[p]=m}if(v.sizeFromShape(l)!==s)throw new Error(T.getSparseReshapeInputOutputMismatchErrorMessage(n,l));let c=n.length,d=[];if(c>0){d[c-1]=1;for(let m=c-2;m>=0;--m)d[m]=d[m+1]*n[m+1]}let h=[];if(o>0){h[o-1]=1;for(let m=o-2;m>=0;--m)h[m]=h[m+1]*l[m+1]}let f=v.getArrayFromDType(a,i*o);for(let m=0;m<i;++m){let g=0;for(let x=0;x<c;++x)g+=e[m*c+x]*d[x];for(let x=0;x<o;++x)f[m*o+x]=Math.trunc(g/h[x]),g%=h[x]}return[f,[i,o],l]}function p3(e,t,a,n,r,s=!1,i=0){let o=n.length,l=[t[0],e.length/t[0]],u=l[1],p=o>0?r[o-1]+1:0;if(p<0)throw new Error(T.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let c=t.slice();c[0]=p;let d=c.reduce((A,y)=>A*y,1),h=v.getArrayFromDType(a,d);if(o===0)return p>0&&h.fill(i),[h,c];if(p<=0)throw new Error(T.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let f=0,m=1,g=0,x=r[f];for(;;){let A=0;if(m<o){if(A=r[m],x===A){++m;continue}if(x>=A)throw new Error(T.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage())}if(x<0||x>=p)throw new Error(T.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(x,p));x>g&&h.fill(i,g*u,x*u);for(let y=f;y<m;++y){let b=n[y];if(b<0||b>=l[0])throw new Error(T.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(y,n[y],l[0]));for(let w=0;w<u;w++)h[x*u+w]+=e[b*u+w]}if(s)for(let y=0;y<u;y++)h[x*u+y]/=m-f;if(f=m,++m,g=x+1,x=A,m>o)break}return g<p&&h.fill(i,g*u,p*u),[h,c]}var kO=os(e=>Math.sqrt(e)),IO=ot(no,e=>Math.sqrt(e)),SO={kernelName:no,backendName:"cpu",kernelFunc:IO},k7=Lt((e,t)=>{let a=e-t;return a*a}),TO=Yt(io,k7),CO={kernelName:io,backendName:"cpu",kernelFunc:TO};function I7(e,t,a,n){let r=Me(e,t.dtype);for(let s=0;s<r.size;s++){let i=r.indexToLoc(s),o=new Array(i.length);for(let l=0;l<o.length;l++)o[l]=i[l]*a[l]+n[l];r.set(t.get(...o),...i)}return r}var NO=class{constructor(e,t,a,n,r,s){this.separator=v.encodeString(e),this.nGramWidths=t,this.leftPad=v.encodeString(a),this.rightPad=v.encodeString(n),this.padWidth=r,this.preserveShort=s}getPadWidth(e){return Math.min(this.padWidth<0?e-1:this.padWidth,e-1)}getNumNGrams(e,t){let a=this.getPadWidth(t);return Math.max(0,e+2*a-t+1)}createNGrams(e,t,a,n,r,s){for(let i=0;i<r;++i){let o=this.getPadWidth(s),l=Math.max(0,o-i),u=Math.max(0,o-(r-(i+1))),p=s-(l+u),c=t+(l>0?0:i-o),d=0;d+=l*this.leftPad.length;for(let x=0;x<p;++x)d+=e[c+x].length;d+=u*this.rightPad.length;let h=l+u+p-1;d+=h*this.separator.length,a[n+i]=new Uint8Array(d);let f=a[n+i],m=0,g=x=>x.forEach(A=>f[m++]=A);for(let x=0;x<l;++x)g(this.leftPad),g(this.separator);for(let x=0;x<p-1;++x)g(e[c+x]),g(this.separator);if(p>0){g(e[c+p-1]);for(let x=0;x<u;++x)g(this.separator),g(this.rightPad)}else{for(let x=0;x<u-1;++x)g(this.rightPad),g(this.separator);g(this.rightPad)}}}compute(e,t){let a=e.length,n=t.length;if(n>0){let o=t[0];if(o!==0)throw new Error(`First split value must be 0, got ${o}`);for(let l=1;l<n;++l){let u=t[l]>=o;if(u=u&&t[l]<=a,!u)throw new Error(`Invalid split value ${t[l]}, must be in [${o}, ${a}]`);o=t[l]}if(o!==a)throw new Error(`Last split value must be data size. 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s=0;s<e.length+1;s++)if(s===e.length||t.indexOf(e[s])!==-1){let i=e.subarray(r,s);(!a||i.length!==0)&&n.push(i),r=s+1}}function h3(e,t,a){let n=e.length,r=[],s=0,i=0,o=new Array(n);for(let d=0;d<n;++d){let h=r.length;EO(e[d],t,a,r);let f=r.length-h;o[d]=f,s+=f,i=Math.max(i,f)}let l=v.getArrayFromDType("int32",s*2),u=new Array(s),p=[n,i],c=0;for(let d=0;d<n;++d)for(let h=0;h<o[d];++h)l[c*2]=d,l[c*2+1]=h,u[c]=r[c],++c;return[l,u,p]}function f3(e,t){let a=v.getArrayFromDType("int32",e.length);for(let n=0;n<e.length;++n)a[n]=v.fingerPrint64(e[n]).modulo(t).getLowBitsUnsigned();return a}var S7=Lt((e,t)=>e-t),RO=s3((e,t,a,n)=>({real:e-a,imag:t-n})),m3=Yt(lo,S7,RO),MO={kernelName:lo,backendName:"cpu",kernelFunc:m3};function T7(e,t){let a=new Array(e.rank);for(let r=0;r<a.length;r++)a[r]=e.shape[r]*t[r];let n=Me(a,e.dtype);for(let r=0;r<n.values.length;++r){let s=n.indexToLoc(r),i=new Array(e.rank);for(let l=0;l<i.length;l++)i[l]=s[l]%e.shape[l];let 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p=T.computePool3DInfo(s.shape,i,o,1,l,u),c=p.strideDepth,d=p.strideHeight,h=p.strideWidth,f=p.filterDepth,m=p.filterHeight,g=p.filterWidth,x=p.dilationDepth,A=p.dilationHeight,y=p.dilationWidth,b=p.effectiveFilterDepth,w=p.effectiveFilterHeight,S=p.effectiveFilterWidth,C=b-1-p.padInfo.front,E=S-1-p.padInfo.left,_=w-1-p.padInfo.top,$=Me(s.shape,"float32"),M=1/(f*m*g),I=a.bufferSync(r);for(let N=0;N<p.batchSize;++N)for(let O=0;O<p.inChannels;++O)for(let L=0;L<p.inDepth;++L)for(let B=0;B<p.inHeight;++B)for(let G=0;G<p.inWidth;++G){let j=L-C,U=B-_,H=G-E,V=0;for(let Q=0;Q<b;Q+=x){let Z=(j+Q)/c;if(!(Z<0||Z>=p.outDepth||Math.floor(Z)!==Z))for(let re=0;re<w;re+=A){let ee=(U+re)/d;if(!(ee<0||ee>=p.outHeight||Math.floor(ee)!==ee))for(let he=0;he<S;he+=y){let oe=(H+he)/h;if(oe<0||oe>=p.outWidth||Math.floor(oe)!==oe)continue;let Ae=I.get(N,Z,ee,oe,O);V+=Ae}}}$.set(V*M,N,L,B,G,O)}return a.makeTensorInfo($.shape,$.dtype,$.values)}var bD={kernelName:G1,backendName:"cpu",kernelFunc:yD};function 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a.makeTensorInfo(r.shape,r.dtype,m)}var ID={kernelName:yi,backendName:"cpu",kernelFunc:kD};function SD(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,crops:i}=n;ye([r],"batchToSpaceND");let o=s.reduce((x,A)=>x*A),l=T.getReshaped(r.shape,s,o),u=T.getPermuted(l.length,s.length),p=T.getReshapedPermuted(r.shape,s,o),c=T.getSliceBeginCoords(i,s.length),d=T.getSliceSize(p,i,s.length),h=mt({inputs:{x:r},backend:a,attrs:{shape:l}}),f=La({inputs:{x:h},backend:a,attrs:{perm:u}}),m=mt({inputs:{x:f},backend:a,attrs:{shape:p}}),g=Gs({inputs:{x:m},backend:a,attrs:{begin:c,size:d}});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(m),g}var TD={kernelName:Rl,backendName:"cpu",kernelFunc:SD};function CD(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i}=n,o=a.data.get(r.dataId).values,l=a.data.get(s.dataId).values,u=i3(o,l,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,u)}var 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a.makeTensorInfo(A.shape,A.dtype,A.values)}var LD={kernelName:Xc,backendName:"cpu",kernelFunc:zD};function BD(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=n;ye([r,s],"conv2dBackpropInput");let c=v.computeStrides(s.shape),d=v.computeStrides(r.shape),h=T.convertConv2DDataFormat(u),f=T.computeConv2DInfo(i,s.shape,o,1,l,p,!1,h),m=new jt(f.inShape,"float32"),g=m.values,x=a.data.get(r.dataId).values,A=a.data.get(s.dataId).values,[y,b,w]=c,{batchSize:S,filterHeight:C,filterWidth:E,inChannels:_,inHeight:$,inWidth:M,outChannels:I,outHeight:N,outWidth:O,strideHeight:L,strideWidth:B}=f;h=f.dataFormat;let G=C-1-f.padInfo.top,j=E-1-f.padInfo.left,U=h==="channelsLast",H=m.strides[0],V=U?m.strides[1]:m.strides[2],Q=U?m.strides[2]:1,Z=U?1:m.strides[1],re=d[0],ee=U?d[1]:d[2],he=U?d[2]:1,oe=U?1:d[1];for(let Ae=0;Ae<S;++Ae)for(let we=0;we<_;++we)for(let Re=0;Re<$;++Re){let 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u=v.computeStrides(r.shape),p=v.computeStrides(s.shape),c=T.computeConv3DInfo(r.shape,l,i,1,o),d=c.strideDepth,h=c.strideHeight,f=c.strideWidth,m=c.filterDepth,g=c.filterHeight,x=c.filterWidth,A=new jt(c.filterShape,"float32"),y=A.values,[b,w,S,C]=A.strides,E=a.data.get(s.dataId).values,[_,$,M,I]=p,N=a.data.get(r.dataId).values,[O,L,B,G]=u,j=c.padInfo.front,U=c.padInfo.left,H=c.padInfo.top;for(let V=0;V<m;++V){let Q=Math.max(0,Math.ceil((j-V)/d)),Z=Math.min(c.outDepth,(c.inDepth+j-V)/d),re=V*b;for(let ee=0;ee<g;++ee){let he=Math.max(0,Math.ceil((H-ee)/h)),oe=Math.min(c.outHeight,(c.inHeight+H-ee)/h),Ae=ee*w+re;for(let we=0;we<x;++we){let Re=Math.max(0,Math.ceil((U-we)/f)),Ge=Math.min(c.outWidth,(c.inWidth+U-we)/f),Ke=we*S+Ae;for(let nt=0;nt<c.inChannels;++nt){let ut=nt*C+Ke;for(let et=0;et<c.outChannels;++et){let rt=0;for(let je=0;je<c.batchSize;++je){let ht=je*O,Va=je*_;for(let Ft=Q;Ft<Z;++Ft){let sn=(V+Ft*d-j)*L+ht,aa=Ft*$+Va;for(let $a=he;$a<oe;++$a){let 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c=ca(u.dtype,"int32"),d=v.makeZerosTypedArray(v.sizeFromShape(u.shape),c),h=a.data.get(u.dataId).values,f=u.shape[u.shape.length-1],m=o?(x,A)=>x+f-A-1:(x,A)=>x+A;for(let x=0;x<h.length;x+=f)for(let A=0;A<f;A++){let y=m(x,A);if(A===0)d[y]=i?0:h[y];else{let b=m(x,A-1);d[y]=i?h[b]+d[b]:h[y]+d[b]}}let g=a.makeTensorInfo(u.shape,c,d);if(l!=null){let x=T.getUndoAxesPermutation(l),A=La({inputs:{x:g},backend:a,attrs:{perm:x}});return a.disposeIntermediateTensorInfo(g),a.disposeIntermediateTensorInfo(u),A}return g}var nz={kernelName:li,backendName:"cpu",kernelFunc:az};function rz(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n;if(r.shape.length===1){let l=a.data.get(r.dataId).values,u=a.data.get(s.dataId).values,p=i3(l,u,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=a.bufferSync(r),u=a.bufferSync(s),p=X4(l,u,i,o);return a.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be 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dz={kernelName:Yc,backendName:"cpu",kernelFunc:uz};function pz(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:p}=n;ye([r,s],"depthwiseConv2DNativeBackpropInput");let c=v.computeStrides(r.shape),d=v.computeStrides(s.shape),h=T.computeConv2DInfo(p,s.shape,i,o,l,u,!0),f=new jt(h.inShape,"float32"),m=f.values,[g,x,A]=f.strides,y=a.data.get(r.dataId).values,[b,w,S]=c,C=a.data.get(s.dataId).values,[E,_,$]=d,{batchSize:M,filterHeight:I,filterWidth:N,inChannels:O,inHeight:L,inWidth:B,outChannels:G,outHeight:j,outWidth:U,strideHeight:H,strideWidth:V}=h,Q=I-1-h.padInfo.top,Z=N-1-h.padInfo.left,re=G/O;for(let ee=0;ee<M;++ee)for(let he=0;he<O;++he)for(let oe=0;oe<L;++oe){let Ae=oe-Q,we=Math.max(0,Math.ceil(Ae/H)),Re=Math.min(j,(I+Ae)/H);for(let Ge=0;Ge<B;++Ge){let Ke=Ge-Z,nt=Math.max(0,Math.ceil(Ke/V)),ut=Math.min(U,(N+Ke)/V),et=0;for(let rt=we;rt<Re;++rt){let je=rt*H-Ae;for(let ht=nt;ht<ut;++ht){let 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if(!cn(t,"EXT_color_buffer_float"))return!1;return S1(t)}function m6(e){if(e===0)return!1;let t=Dn(e);if(e===1){if(!cn(t,"OES_texture_float")||!cn(t,"WEBGL_color_buffer_float"))return!1}else{if(cn(t,"EXT_color_buffer_float"))return S1(t);let a="EXT_color_buffer_half_float";if(cn(t,a)){let n=t.getExtension(a);return lV(t,n)}return!1}return S1(t)}function S1(e){let t=y3(e),a=e.createTexture();e.bindTexture(e.TEXTURE_2D,a);let n=1,r=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,n,r,0,t.textureFormatFloat,t.textureTypeFloat,null);let s=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,s),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,a,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(a),e.deleteFramebuffer(s),i}function lV(e,t){let a=y3(e,t),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let r=1,s=1;e.texImage2D(e.TEXTURE_2D,0,a.internalFormatHalfFloat,r,s,0,a.textureFormatFloat,a.textureTypeHalfFloat,null);let i=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,i),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(i),o}function g6(e){return e!==2?!1:Dn(e).fenceSync!=null}function uu(e,t){Array.isArray(e)||(e=[e]),e.forEach(a=>{a!=null&&v.assert(a.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var ve=W();ve.registerFlag("HAS_WEBGL",()=>ve.getNumber("WEBGL_VERSION")>0);ve.registerFlag("WEBGL_VERSION",()=>I1(2)?2:I1(1)?1:0);ve.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);ve.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>ve.get("WEBGL_VERSION")===2);ve.registerFlag("WEBGL_CPU_FORWARD",()=>!0);ve.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);ve.registerFlag("WEBGL_PACK",()=>ve.getBool("HAS_WEBGL"));ve.registerFlag("WEBGL_PACK_NORMALIZATION",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_CLIP",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_REDUCE",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_LAZILY_UNPACK",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_CONV_IM2COL",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>p6(ve.getNumber("WEBGL_VERSION")));ve.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>c6(ve.getNumber("WEBGL_VERSION")));ve.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=ve.getNumber("WEBGL_VERSION");return e===0?0:h6(e)});ve.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>ve.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!jd.isMobile());ve.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>f6(ve.getNumber("WEBGL_VERSION")));ve.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>ve.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:ve.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));ve.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>m6(ve.getNumber("WEBGL_VERSION")));ve.registerFlag("WEBGL_FENCE_API_ENABLED",()=>g6(ve.getNumber("WEBGL_VERSION")));ve.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>ve.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);ve.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${e}.`)});ve.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>jd.isMobile()?1:-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});ve.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);ve.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);ve.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);ve.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);ve.registerFlag("WEBGL_EXP_CONV",()=>!1);ve.registerFlag("SOFTWARE_WEBGL_ENABLED",()=>ve.getBool("IS_TEST"));ve.registerFlag("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE",()=>1/0);ve.registerFlag("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE",()=>!1);ve.registerFlag("WEBGL2_ISNAN_CUSTOM",()=>!1);ve.registerFlag("ENGINE_COMPILE_ONLY",()=>!1);function Ca(){let e,t,a,n,r,s,i,o,l,u;return W().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",a="out",n="in",r="texture",s="outputColor",i="out vec4 outputColor;",o=W().getBool("WEBGL2_ISNAN_CUSTOM")?`
bool isnan_custom(float val) {
uint floatToUint = floatBitsToUint(val);
return (floatToUint & 0x7fffffffu) > 0x7f800000u;
}
bvec4 isnan_custom(vec4 val) {
return bvec4(isnan_custom(val.x),
isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));
}
#define isnan(value) isnan_custom(value)
`:"",l="",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)));
}
`):(e="",t="attribute",a="varying",n="varying",r="texture2D",s="gl_FragColor",i="",o=`
#define isnan(value) isnan_custom(value)
bool isnan_custom(float val) {
return (val > 0. || val < 1. || val == 0.) ? false : true;
}
bvec4 isnan_custom(vec4 val) {
return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
}
`,l=`
uniform float INFINITY;
bool isinf(float val) {
return abs(val) == INFINITY;
}
bvec4 isinf(vec4 val) {
return equal(abs(val), vec4(INFINITY));
}
`,u=`
int round(float value) {
return int(floor(value + 0.5));
}
ivec4 round(vec4 value) {
return ivec4(floor(value + vec4(0.5)));
}
`),{version:e,attribute:t,varyingVs:a,varyingFs:n,texture2D:r,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:u}}function Ao(e,t,a="index"){let n=v.computeStrides(t);return n.map((r,s)=>{let i=`int ${e[s]} = ${a} / ${r}`,o=s===n.length-1?`int ${e[s+1]} = ${a} - ${e[s]} * ${r}`:`index -= ${e[s]} * ${r}`;return`${i}; ${o};`}).join("")}function Oh(e,t,a="index"){let n=v.computeStrides(t);return n.map((r,s)=>{let i=`int ${e[s]} = ${a} / outShapeStrides[${s}]`,o=s===n.length-1?`int ${e[s+1]} = ${a} - ${e[s]} * outShapeStrides[${s}]`:`index -= ${e[s]} * outShapeStrides[${s}]`;return`${i}; ${o};`}).join("")}function uV(e,t){let a=e.length,n=e.map(s=>`${t}[${s}]`),r=new Array(a-1);r[a-2]=n[a-1];for(let s=a-3;s>=0;--s)r[s]=`(${r[s+1]} * ${n[s+1]})`;return r}function dV(e,t,a="index"){let n=e.map((s,i)=>i),r=uV(n,t);return r.map((s,i)=>{let o=`int ${e[i]} = ${a} / ${r[i]}`,l=i===r.length-1?`int ${e[i+1]} = ${a} - ${e[i]} * ${r[i]}`:`index -= ${e[i]} * ${r[i]}`;return`${o}; ${l};`}).join("")}function v3(e){let t=v.computeStrides(e).map(a=>a.toString());return`
int getFlatIndex(ivec3 coords) {
return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
}
`}function w3(){return`
int getFlatIndex(ivec3 coords) {
return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
}
`}var x6=`
const float FLOAT_MAX = 1.70141184e38;
const float FLOAT_MIN = 1.17549435e-38;
lowp vec4 encode_float(highp float v) {
if (isnan(v)) {
return vec4(255, 255, 255, 255);
}
highp float av = abs(v);
if(av < FLOAT_MIN) {
return vec4(0.0, 0.0, 0.0, 0.0);
} else if(v > FLOAT_MAX) {
return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;
} else if(v < -FLOAT_MAX) {
return vec4(0.0, 0.0, 128.0, 255.0) / 255.0;
}
highp vec4 c = vec4(0,0,0,0);
highp float e = floor(log2(av));
highp float m = exp2(fract(log2(av))) - 1.0;
c[2] = floor(128.0 * m);
m -= c[2] / 128.0;
c[1] = floor(32768.0 * m);
m -= c[1] / 32768.0;
c[0] = floor(8388608.0 * m);
highp float ebias = e + 127.0;
c[3] = floor(ebias / 2.0);
ebias -= c[3] * 2.0;
c[2] += floor(ebias) * 128.0;
c[3] += 128.0 * step(0.0, -v);
return c / 255.0;
}
`,{getBroadcastDims:A6}=T;function pV(e,t,a){let n=[];if(e.forEach(d=>{let h=v.sizeFromShape(d.shapeInfo.logicalShape);if(d.shapeInfo.isUniform?n.push(`uniform float ${d.name}${h>1?`[${h}]`:""};`):(n.push(`uniform sampler2D ${d.name};`),n.push(`uniform int offset${d.name};`)),a.enableShapeUniforms){let{uniformShape:f}=k3(a.packedInputs,d.shapeInfo.logicalShape,d.shapeInfo.texShape);switch(f.length){case 1:n.push(`uniform int ${d.name}Shape;`);break;case 2:n.push(`uniform ivec2 ${d.name}Shape;`);break;case 3:n.push(`uniform ivec3 ${d.name}Shape;`);break;case 4:n.push(`uniform ivec4 ${d.name}Shape;`);break;default:break}n.push(`uniform ivec2 ${d.name}TexShape;`)}}),a.enableShapeUniforms){switch(t.logicalShape.length){case 1:n.push("uniform int outShape;");break;case 2:n.push("uniform ivec2 outShape;"),n.push("uniform int outShapeStrides;");break;case 3:n.push("uniform ivec3 outShape;"),n.push("uniform ivec2 outShapeStrides;");break;case 4:n.push("uniform ivec4 outShape;"),n.push("uniform ivec3 outShapeStrides;");break;default:break}n.push("uniform ivec2 outTexShape;")}a.customUniforms&&a.customUniforms.forEach(d=>{n.push(`uniform ${d.type} ${d.name}${d.arrayIndex?`[${d.arrayIndex}]`:""};`)});let r=n.join(`
`),s=e.map(d=>cV(d,t,a.packedInputs,a.enableShapeUniforms)).join(`
`),i=t.texShape,o=Ca(),l=mV(o),u,p,c=AV(o);return t.isPacked?(u=hV(t.logicalShape,i,a.enableShapeUniforms),p=xV(o)):(u=fV(t.logicalShape,i,a.enableShapeUniforms),p=gV(o)),a.packedInputs&&(c+=wV),[c,l,p,r,u,s,a.userCode].join(`
`)}function du(e,t=!1){let a=e.shapeInfo.logicalShape;switch(a.length){case 0:return PV(e,t);case 1:return OV(e,t);case 2:return zV(e,t);case 3:return BV(e,t);case 4:return VV(e,t);case 5:return UV(e);case 6:return GV(e);default:throw new Error(`${a.length}-D input sampling is not yet supported`)}}function y6(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return _V(e);case 1:return FV(e,t);case 2:return DV(e,t);case 3:return LV(e,t);default:return WV(e,t)}}function cV(e,t,a=!1,n){let r="";a?r+=y6(e,n):r+=du(e,n);let s=e.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(a?r+=HV(e,t):r+=jV(e,t)),r}function hV(e,t,a){switch(e.length){case 0:return b6();case 1:return kV(e,t,a);case 2:return MV(e,t,a);case 3:return SV(e,t,a);default:return CV(e,t,a)}}function fV(e,t,a){switch(e.length){case 0:return b6();case 1:return IV(e,t,a);case 2:return $V(e,t,a);case 3:return TV(e,t,a);case 4:return NV(e,t,a);case 5:return EV(e,t);case 6:return RV(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function mV(e){return`
float sampleTexture(sampler2D textureSampler, vec2 uv) {
return ${e.texture2D}(textureSampler, uv).r;
}
`}function gV(e){return`
void setOutput(float val) {
${e.output} = vec4(val, 0, 0, 0);
}
`}function xV(e){return`
void setOutput(vec4 val) {
${e.output} = val;
}
`}function AV(e){return`${e.version}
precision highp float;
precision highp int;
precision highp sampler2D;
${e.varyingFs} vec2 resultUV;
${e.defineOutput}
const vec2 halfCR = vec2(0.5, 0.5);
struct ivec5
{
int x;
int y;
int z;
int w;
int u;
};
struct ivec6
{
int x;
int y;
int z;
int w;
int u;
int v;
};
uniform float NAN;
${e.defineSpecialNaN}
${e.defineSpecialInf}
${e.defineRound}
int imod(int x, int y) {
return x - y * (x / y);
}
int idiv(int a, int b, float sign) {
int res = a / b;
int mod = imod(a, b);
if (sign < 0. && mod != 0) {
res -= 1;
}
return res;
}
//Based on the work of Dave Hoskins
//https://www.shadertoy.com/view/4djSRW
#define HASHSCALE1 443.8975
float random(float seed){
vec2 p = resultUV * seed;
vec3 p3 = fract(vec3(p.xyx) * HASHSCALE1);
p3 += dot(p3, p3.yzx + 19.19);
return fract((p3.x + p3.y) * p3.z);
}
${yV}
${bV}
${vV}
`}var yV=`
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);
}
`,bV=`
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);
}
`,vV=`
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);
}
`,wV=`
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 b6(){return`
int getOutputCoords() {
return 0;
}
`}function kV(e,t,a){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?a?`
int getOutputCoords() {
return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
}
`:`
int getOutputCoords() {
return 2 * int(resultUV.x * ${n[1]}.0);
}
`:n[1]===1?a?`
int getOutputCoords() {
return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
}
`:`
int getOutputCoords() {
return 2 * int(resultUV.y * ${n[0]}.0);
}
`:a?`
int getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
}
`}function IV(e,t,a){return t[0]===1?a?`
int getOutputCoords() {
return int(resultUV.x * float(outTexShape[1]));
}
`:`
int getOutputCoords() {
return int(resultUV.x * ${t[1]}.0);
}
`:t[1]===1?a?`
int getOutputCoords() {
return int(resultUV.y * float(outTexShape[0]));
}
`:`
int getOutputCoords() {
return int(resultUV.y * ${t[0]}.0);
}
`:a?`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
return resTexRC.x * outTexShape[1] + resTexRC.y;
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
return resTexRC.x * ${t[1]} + resTexRC.y;
}
`}function SV(e,t,a){if(a)return`
ivec3 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec3(b, r, c);
}
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),s=r*Math.ceil(e[1]/2);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
int b = index / ${s};
index -= b * ${s};
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec3(b, r, c);
}
`}function TV(e,t,a){if(a)return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
${Oh(["r","c","d"],e)}
return ivec3(r, c, d);
}
`;let n=Ao(["r","c","d"],e);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec3(r, c, d);
}
`}function CV(e,t,a){if(a)return`
ivec4 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
int texelsInBatchN = texelsInBatch * outShape[1];
int b2 = index / texelsInBatchN;
index -= b2 * texelsInBatchN;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec4(b2, b, r, c);
}
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),s=r*Math.ceil(e[e.length-2]/2),i=s,o="",l="b, r, c";for(let u=2;u<e.length-1;u++)i*=e[e.length-u-1],o=`
int b${u} = index / ${i};
index -= b${u} * ${i};
`+o,l=`b${u}, `+l;return`
ivec${e.length} getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
${o}
int b = index / ${s};
index -= b * ${s};
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec${e.length}(${l});
}
`}function NV(e,t,a){if(a)return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
${Oh(["r","c","d","d2"],e)}
return ivec4(r, c, d, d2);
}
`;let n=Ao(["r","c","d","d2"],e);return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec4(r, c, d, d2);
}
`}function EV(e,t){let a=Ao(["r","c","d","d2","d3"],e);return`
ivec5 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${a}
ivec5 outShape = ivec5(r, c, d, d2, d3);
return outShape;
}
`}function RV(e,t){let a=Ao(["r","c","d","d2","d3","d4"],e);return`
ivec6 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${a}
ivec6 result = ivec6(r, c, d, d2, d3, d4);
return result;
}
`}function MV(e,t,a){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return a?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
}
`;let r=Math.ceil(e[1]/2);return a?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec2(r, c);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec2(r, c);
}
`}function $V(e,t,a){return v.arraysEqual(e,t)?a?`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
}
`:e[1]===1?a?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
return ivec2(index, 0);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
return ivec2(index, 0);
}
`:e[0]===1?a?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
return ivec2(0, index);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
return ivec2(0, index);
}
`:a?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
int r = index / outShape[1];
int c = index - r * outShape[1];
return ivec2(r, c);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
int r = index / ${e[1]};
int c = index - r * ${e[1]};
return ivec2(r, c);
}
`}function yo(e){return`offset${e}`}function _V(e){let t=e.name,a="get"+t.charAt(0).toUpperCase()+t.slice(1),n=Ca();return`
vec4 ${a}() {
return ${n.texture2D}(${t}, halfCR);
}
`}function PV(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${a};}`;let[r,s]=e.shapeInfo.texShape;if(r===1&&s===1)return`
float ${n}() {
return sampleTexture(${a}, halfCR);
}
`;let i=yo(a);if(t)return`
float ${n}() {
vec2 uv = uvFromFlat(${a}TexShape[0], ${a}TexShape[1], ${i});
return sampleTexture(${a}, uv);
}
`;let[o,l]=e.shapeInfo.texShape;return`
float ${n}() {
vec2 uv = uvFromFlat(${o}, ${l}, ${i});
return sampleTexture(${a}, uv);
}
`}function FV(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1),r=e.shapeInfo.texShape,s=Ca();if(t)return`
vec4 ${n}(int index) {
ivec2 packedTexShape = ivec2(ceil(float(${a}TexShape[0]) / 2.0), ceil(float(${a}TexShape[1]) / 2.0));
vec2 uv = packedUVfrom1D(
packedTexShape[0], packedTexShape[1], index);
return ${s.texture2D}(${a}, uv);
}
`;let i=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)];return`
vec4 ${n}(int index) {
vec2 uv = packedUVfrom1D(
${i[0]}, ${i[1]}, index);
return ${s.texture2D}(${a}, uv);
}
`}function OV(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1);if(e.shapeInfo.isUniform)return`
float ${n}(int index) {
${pu(e)}
}
`;let r=e.shapeInfo.texShape,s=r[0],i=r[1];if(i===1&&s===1)return`
float ${n}(int index) {
return sampleTexture(${a}, halfCR);
}
`;let o=yo(a);return i===1?t?`
float ${n}(int index) {
vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / float(${a}TexShape[0]));
return sampleTexture(${a}, uv);
}
`:`
float ${n}(int index) {
vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / ${s}.0);
return sampleTexture(${a}, uv);
}
`:s===1?t?`
float ${n}(int index) {
vec2 uv = vec2((float(index + ${o}) + 0.5) / float(${a}TexShape[1]), 0.5);
return sampleTexture(${a}, uv);
}
`:`
float ${n}(int index) {
vec2 uv = vec2((float(index + ${o}) + 0.5) / ${i}.0, 0.5);
return sampleTexture(${a}, uv);
}
`:t?`
float ${n}(int index) {
vec2 uv = uvFromFlat(${a}TexShape[0], ${a}TexShape[1], index + ${o});
return sampleTexture(${a}, uv);
}
`:`
float ${n}(int index) {
vec2 uv = uvFromFlat(${s}, ${i}, index + ${o});
return sampleTexture(${a}, uv);
}
`}function DV(e,t){let a=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape,i=s[0],o=s[1],l=Ca();if(s!=null&&v.arraysEqual(a,s))return t?`
vec4 ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
return ${l.texture2D}(${n}, uv);
}
`:`
vec4 ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${o}.0, ${i}.0);
return ${l.texture2D}(${n}, uv);
}
`;if(t)return`
vec4 ${r}(int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
int valuesPerRow = int(ceil(float(${n}Shape[1]) / 2.0));
vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);
return ${l.texture2D}(${n}, uv);
}
`;let u=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],p=Math.ceil(a[1]/2);return`
vec4 ${r}(int row, int col) {
vec2 uv = packedUVfrom2D(${p}, ${u[0]}, ${u[1]}, row, col);
return ${l.texture2D}(${n}, uv);
}
`}function zV(e,t){let a=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape;if(s!=null&&v.arraysEqual(a,s)){if(t)return`
float ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`;let d=s[0],h=s[1];return`
float ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${h}.0, ${d}.0);
return sampleTexture(${n}, uv);
}
`}let{newShape:i,keptDims:o}=v.squeezeShape(a),l=i;if(l.length<a.length){let d=cu(e,l),h=["row","col"];return`
${du(d,t)}
float ${r}(int row, int col) {
return ${r}(${hu(h,o)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col) {
int index = round(dot(vec2(row, col), vec2(${a[1]}, 1)));
${pu(e)}
}
`;let u=s[0],p=s[1],c=yo(n);return p===1?t?`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${c}), vec3(${n}Shape[1], 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / float(${n}TexShape[0]));
return sampleTexture(${n}, uv);
}
`:`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${c}), vec3(${a[1]}, 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / ${u}.0);
return sampleTexture(${n}, uv);
}
`:u===1?t?`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${c}), vec3(${n}Shape[1], 1, 1));
vec2 uv = vec2((index + 0.5) / float(${n}TexShape[1]), 0.5);
return sampleTexture(${n}, uv);
}
`:`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${c}), vec3(${a[1]}, 1, 1));
vec2 uv = vec2((index + 0.5) / ${p}.0, 0.5);
return sampleTexture(${n}, uv);
}
`:t?`
float ${r}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${n}Shape[1] + col + ${c};
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
return sampleTexture(${n}, uv);
}
`:`
float ${r}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${a[1]} + col + ${c};
vec2 uv = uvFromFlat(${u}, ${p}, index);
return sampleTexture(${n}, uv);
}
`}function LV(e,t){let a=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];if(a[0]===1){let d=a.slice(1),h=[1,2],f=cu(e,d),m=["b","row","col"];return`
${y6(f,t)}
vec4 ${r}(int b, int row, int col) {
return ${r}(${hu(m,h)});
}
`}let o=Ca();if(t)return`
vec4 ${r}(int b, int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
int valuesPerRow = int(ceil(float(${n}Shape[2]) / 2.0));
int texelsInBatch = valuesPerRow * int(ceil(float(${n}Shape[1]) / 2.0));
vec2 uv = packedUVfrom3D(
packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);
return ${o.texture2D}(${n}, uv);
}
`;let l=i[0],u=i[1],p=Math.ceil(a[2]/2),c=p*Math.ceil(a[1]/2);return`
vec4 ${r}(int b, int row, int col) {
vec2 uv = packedUVfrom3D(
${l}, ${u}, ${c}, ${p}, b, row, col);
return ${o.texture2D}(${n}, uv);
}
`}function BV(e,t){let a=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=a[1]*a[2],i=a[2],{newShape:o,keptDims:l}=v.squeezeShape(a),u=o;if(u.length<a.length){let m=cu(e,u),g=["row","col","depth"];return`
${du(m,t)}
float ${r}(int row, int col, int depth) {
return ${r}(${hu(g,l)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col, int depth) {
int index = round(dot(vec3(row, col, depth),
vec3(${s}, ${i}, 1)));
${pu(e)}
}
`;let p=e.shapeInfo.texShape,c=p[0],d=p[1],h=e.shapeInfo.flatOffset;if(d===s&&h==null)return t?`
float ${r}(int row, int col, int depth) {
int stride1 = ${n}Shape[2];
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(stride1, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`:`
float ${r}(int row, int col, int depth) {
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(${i}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${d}.0, ${c}.0);
return sampleTexture(${n}, uv);
}
`;if(d===i&&h==null)return t?`
float ${r}(int row, int col, int depth) {
float texR = dot(vec2(row, col), vec2(${n}Shape[1], 1));
float texC = float(depth);
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`:`
float ${r}(int row, int col, int depth) {
float texR = dot(vec2(row, col), vec2(${a[1]}, 1));
float texC = float(depth);
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${d}.0, ${c}.0);
return sampleTexture(${n}, uv);
}
`;let f=yo(n);return t?`
float ${r}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int stride0 = ${n}Shape[1] * ${n}Shape[2];
int stride1 = ${n}Shape[2];
int index = row * stride0 + col * stride1 + depth + ${f};
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
return sampleTexture(${n}, uv);
}
`:`
float ${r}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${s} + col * ${i} + depth + ${f};
vec2 uv = uvFromFlat(${c}, ${d}, index);
return sampleTexture(${n}, uv);
}
`}function WV(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1),r=Ca();if(t)return`
vec4 ${n}(int b2, int b, int row, int col) {
int valuesPerRow = int(ceil(float(${a}Shape[3]) / 2.0));
int texelsInBatch = valuesPerRow * int(ceil(float(${a}Shape[2]) / 2.0));
int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);
texelsInBatch *= ${a}Shape[1];
index = b2 * texelsInBatch + index;
ivec2 packedTexShape = ivec2(ceil(float(${a}TexShape[0]) / 2.0), ceil(float(${a}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 ${r.texture2D}(${a}, uv);
}
`;let s=e.shapeInfo.logicalShape,i=s.length,o=e.shapeInfo.texShape,l=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],u=l[0],p=l[1],c=Math.ceil(s[i-1]/2),d=c*Math.ceil(s[i-2]/2),h="int b, int row, int col",f=`b * ${d} + (row / 2) * ${c} + (col / 2)`;for(let m=2;m<i-1;m++)h=`int b${m}, `+h,d*=s[i-m-1],f=`b${m} * ${d} + `+f;return`
vec4 ${n}(${h}) {
int index = ${f};
int texR = index / ${p};
int texC = index - texR * ${p};
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${p}, ${u});
return ${r.texture2D}(${a}, uv);
}
`}function VV(e,t){let a=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),s=a[3],i=a[2]*s,o=a[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(a);if(l.length<a.length){let A=cu(e,l),y=["row","col","depth","depth2"];return`
${du(A,t)}
float ${r}(int row, int col, int depth, int depth2) {
return ${r}(${hu(y,u)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col, int depth, int depth2) {
int index = round(dot(vec4(row, col, depth, depth2),
vec4(${o}, ${i}, ${s}, 1)));
${pu(e)}
}
`;let p=e.shapeInfo.flatOffset,c=e.shapeInfo.texShape,d=c[0],h=c[1],f=`int stride2 = ${n}Shape[3];`,m=`int stride1 = ${n}Shape[2] * stride2;`,g=`int stride0 = ${n}Shape[1] * stride1;`;if(h===o&&p==null)return t?`
float ${r}(int row, int col, int depth, int depth2) {
${f}
${m}
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(stride1, stride2, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`:`
float ${r}(int row, int col, int depth, int depth2) {
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(${i}, ${s}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${h}.0, ${d}.0);
return sampleTexture(${n}, uv);
}
`;if(h===s&&p==null)return t?`
float ${r}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${n}Shape[1] * ${n}Shape[2], ${n}Shape[2], 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`:`
float ${r}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${a[1]*a[2]}, ${a[2]}, 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${h}.0, ${d}.0);
return sampleTexture(${n}, uv);
}
`;let x=yo(n);return t?`
float ${r}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
${f}
${m}
${g}
int index = row * stride0 + col * stride1 +
depth * stride2 + depth2;
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index + ${x});
return sampleTexture(${n}, uv);
}
`:`
float ${r}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${o} + col * ${i} +
depth * ${s} + depth2;
vec2 uv = uvFromFlat(${d}, ${h}, index + ${x});
return sampleTexture(${n}, uv);
}
`}function UV(e){let t=e.shapeInfo.logicalShape,a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1),r=t[4],s=t[3]*r,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(t);if(l.length<t.length){let m=cu(e,l),g=["row","col","depth","depth2","depth3"];return`
${du(m)}
float ${n}(int row, int col, int depth, int depth2, int depth3) {
return ${n}(${hu(g,u)});
}
`}if(e.shapeInfo.isUniform)return`
float ${n}(int row, int col, int depth, int depth2, int depth3) {
float index = dot(
vec4(row, col, depth, depth2),
vec4(${o}, ${i}, ${s}, ${r})) +
depth3;
${pu(e)}
}
`;let p=e.shapeInfo.flatOffset,c=e.shapeInfo.texShape,d=c[0],h=c[1];if(h===o&&p==null)return`
float ${n}(int row, int col, int depth, int depth2, int depth3) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${i}, ${s}, ${r}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${h}.0, ${d}.0);
return sampleTexture(${a}, uv);
}
`;if(h===r&&p==null)return`
float ${n}(int row, int col, int depth, int depth2, int depth3) {
float texR = dot(
vec4(row, col, depth, depth2),
vec4(${t[1]*t[2]*t[3]},
${t[2]*t[3]}, ${t[3]}, 1));
int texC = depth3;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${h}.0, ${d}.0);
return sampleTexture(${a}, uv);
}
`;let f=yo(a);return`
float ${n}(int row, int col, int depth, int depth2, int depth3) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${o} + col * ${i} + depth * ${s} +
depth2 * ${r} + depth3 + ${f};
vec2 uv = uvFromFlat(${d}, ${h}, index);
return sampleTexture(${a}, uv);
}
`}function GV(e){let t=e.shapeInfo.logicalShape,a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1),{newShape:r,keptDims:s}=v.squeezeShape(t);if(r.length<t.length){let g=cu(e,r),x=["row","col","depth","depth2","depth3","depth4"];return`
${du(g)}
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
return ${n}(${hu(x,s)});
}
`}let i=t[5],o=t[4]*i,l=t[3]*o,u=t[2]*l,p=t[1]*u;if(e.shapeInfo.isUniform)return`
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int index = round(dot(
vec4(row, col, depth, depth2),
vec4(${p}, ${u}, ${l}, ${o})) +
dot(
vec2(depth3, depth4),
vec2(${i}, 1)));
${pu(e)}
}
`;let c=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,h=d[0],f=d[1];if(f===p&&c==null)return`
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${u}, ${l}, ${o}, ${i})) +
float(depth4);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${f}.0, ${h}.0);
return sampleTexture(${a}, uv);
}
`;if(f===i&&c==null)return`
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
float texR = dot(vec4(row, col, depth, depth2),
vec4(${t[1]*t[2]*t[3]*t[4]},
${t[2]*t[3]*t[4]},
${t[3]*t[4]},
${t[4]})) + float(depth3);
int texC = depth4;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${f}.0, ${h}.0);
return sampleTexture(${a}, uv);
}
`;let m=yo(a);return`
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${p} + col * ${u} + depth * ${l} +
depth2 * ${o} + depth3 * ${i} + depth4 + ${m};
vec2 uv = uvFromFlat(${h}, ${f}, index);
return sampleTexture(${a}, uv);
}
`}function pu(e){let t=e.name,a=v.sizeFromShape(e.shapeInfo.logicalShape);return a<2?`return ${t};`:`
for (int i = 0; i < ${a}; i++) {
if (i == index) {
return ${t}[i];
}
}
`}function HV(e,t){let a=e.name,n=a.charAt(0).toUpperCase()+a.slice(1),r="get"+n+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=A6(e.shapeInfo.logicalShape,t.logicalShape),l=gt(i),u=i-s,p,c=["x","y","z","w","u","v"];s===0?p="":i<2&&o.length>=1?p="coords = 0;":p=o.map(g=>`coords.${c[g+u]} = 0;`).join(`
`);let d="";i<2&&s>0?d="coords":d=e.shapeInfo.logicalShape.map((g,x)=>`coords.${c[x+u]}`).join(", ");let h="return outputValue;",f=v.sizeFromShape(e.shapeInfo.logicalShape)===1,m=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!f&&!m)h=`
return vec4(outputValue.xy, outputValue.xy);
`;else if(f&&!m)i===1?h=`
return vec4(outputValue.x, outputValue.x, 0., 0.);
`:h=`
return vec4(outputValue.x);
`;else if(o.length){let g=s-2,x=s-1;o.indexOf(g)>-1&&o.indexOf(x)>-1?h="return vec4(outputValue.x);":o.indexOf(g)>-1?h="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":o.indexOf(x)>-1&&(h="return vec4(outputValue.xx, outputValue.zz);")}return`
vec4 ${r}() {
${l} coords = getOutputCoords();
${p}
vec4 outputValue = get${n}(${d});
${h}
}
`}function jV(e,t){let a=e.name,n=a.charAt(0).toUpperCase()+a.slice(1),r="get"+n+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
float ${r}() {
return sampleTexture(${a}, resultUV);
}
`;let u=gt(l),p=A6(e.shapeInfo.logicalShape,t.logicalShape),c=l-o,d,h=["x","y","z","w","u","v"];o===0?d="":l<2&&p.length>=1?d="coords = 0;":d=p.map(m=>`coords.${h[m+c]} = 0;`).join(`
`);let f="";return l<2&&o>0?f="coords":f=e.shapeInfo.logicalShape.map((m,g)=>`coords.${h[g+c]}`).join(", "),`
float ${r}() {
${u} coords = getOutputCoords();
${d}
return get${n}(${f});
}
`}function gt(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function k3(e,t,a){let{newShape:n,keptDims:r}=v.squeezeShape(t),s=t.length,i=e&&s===3&&t[0]===1,o=i?t.slice(1):n,l=!e&&s>1&&!v.arraysEqual(t,a)&&n.length<s||i;return{useSqueezeShape:l,uniformShape:l?o:t,keptDims:r}}function cu(e,t){let a=JSON.parse(JSON.stringify(e));return a.shapeInfo.logicalShape=t,a}function hu(e,t){return t.map(a=>e[a]).join(", ")}function qV(e,t,a,n){let r=a.map((p,c)=>{let d={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(d.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[c],shapeInfo:d}}),s=r.map(p=>p.shapeInfo),i={logicalShape:n.shape,texShape:n.texData.texShape,isUniform:!1,isPacked:n.texData.isPacked,flatOffset:null},o=pV(r,i,t),l=Z7(e.gl,o),u=e.createProgram(l);return W().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i,uniformLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,inShapesLocations:null,inTexShapesLocations:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:Object.assign({program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i},v6(e,t,u))}function v6(e,t,a){let n={},r={},s={},i=[],o,l,u,p=null,c=null;c=e.getUniformLocation(a,"NAN",!1),W().getNumber("WEBGL_VERSION")===1&&(p=e.getUniformLocation(a,"INFINITY",!1));let d=!1;for(let h=0;h<t.variableNames.length;h++){let f=t.variableNames[h];n[f]=e.getUniformLocation(a,f,d),n[`offset${f}`]=e.getUniformLocation(a,`offset${f}`,d),t.enableShapeUniforms&&(r[`${f}Shape`]=e.getUniformLocation(a,`${f}Shape`,d),s[`${f}TexShape`]=e.getUniformLocation(a,`${f}TexShape`,d))}return t.enableShapeUniforms&&(o=e.getUniformLocation(a,"outShape",d),u=e.getUniformLocation(a,"outShapeStrides",d),l=e.getUniformLocation(a,"outTexShape",d)),t.customUniforms&&t.customUniforms.forEach((h,f)=>{i[f]=e.getUniformLocation(a,h.name,d)}),{uniformLocations:n,customUniformLocations:i,infLoc:p,nanLoc:c,inShapesLocations:r,inTexShapesLocations:s,outShapeLocation:o,outShapeStridesLocation:u,outTexShapeLocation:l}}function cx(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((a,n)=>{let r=a.logicalShape,s=t[n],i=s.shape;if(!v.arraysEqual(r,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${r} and ${i} must match`);if(a.isUniform&&s.isUniform)return;let o=a.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function XV(e,t,a,n,r){t.program.enableShapeUniforms||(cx(t.inShapeInfos,a),cx([t.outShapeInfo],[n]));let s=n.texData.texture,i=n.texData.texShape;n.texData.isPacked?e.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):e.setOutputMatrixTexture(s.texture,i[0],i[1]),e.setProgram(t.webGLProgram),W().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),a.forEach((l,u)=>{let p=t.program.variableNames[u],c=t.uniformLocations[p],d=t.uniformLocations[`offset${p}`],h=t.inShapesLocations[`${p}Shape`],f=t.inTexShapesLocations[`${p}TexShape`];if(h){let{uniformShape:m}=k3(t.program.packedInputs,l.shape,l.texData.texShape);switch(m.length){case 1:e.gl.uniform1iv(h,new Int32Array(m));break;case 2:e.gl.uniform2iv(h,new Int32Array(m));break;case 3:e.gl.uniform3iv(h,new Int32Array(m));break;case 4:e.gl.uniform4iv(h,new Int32Array(m));break;default:break}}if(f&&e.gl.uniform2i(f,l.texData.texShape[0],l.texData.texShape[1]),c!=null){if(l.isUniform){if(v.sizeFromShape(l.shape)<2)e.gl.uniform1f(c,l.uniformValues[0]);else{let m=l.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),e.gl.uniform1fv(c,m)}return}l.texData.slice!=null&&d!=null&&e.gl.uniform1i(d,l.texData.slice.flatOffset),e.setInputMatrixTexture(l.texData.texture.texture,c,u)}});let o=t.outShapeLocation;if(o)switch(n.shape.length){case 1:e.gl.uniform1iv(o,new Int32Array(n.shape));break;case 2:e.gl.uniform2iv(o,new Int32Array(n.shape));break;case 3:e.gl.uniform3iv(o,new Int32Array(n.shape));break;case 4:e.gl.uniform4iv(o,new Int32Array(n.shape));break;default:break}if(t.outShapeStridesLocation){let l=v.computeStrides(n.shape);switch(n.shape.length){case 2:e.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(l));break;case 3:e.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(l));break;case 4:e.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(l));break;default:break}}t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,n.texData.texShape[0],n.texData.texShape[1]),t.program.customUniforms&&r&&t.program.customUniforms.forEach((l,u)=>{let p=t.customUniformLocations[u],c=r[u];if(l.type==="float")e.gl.uniform1fv(p,c);else if(l.type==="vec2")e.gl.uniform2fv(p,c);else if(l.type==="vec3")e.gl.uniform3fv(p,c);else if(l.type==="vec4")e.gl.uniform4fv(p,c);else if(l.type==="int")e.gl.uniform1iv(p,c);else if(l.type==="ivec2")e.gl.uniform2iv(p,c);else if(l.type==="ivec3")e.gl.uniform3iv(p,c);else if(l.type==="ivec4")e.gl.uniform4iv(p,c);else throw Error(`uniform type ${l.type} is not supported yet.`)}),e.executeProgram()}function KV(e,t,a){let n="";t.concat(a).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!i.isUniform){let l=i.texData.texShape,{useSqueezeShape:u,uniformShape:p,keptDims:c}=k3(e.packedInputs,i.shape,l),d="",h="",f="";if(p.length===1&&e.packedInputs){let w=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];d=`${w[0]>1}_${w[1]>1}`}else if(p.length===2&&!e.packedInputs)h=`${p[0]>1}_${p[1]>1}`;else if(p.length>2&&!e.packedInputs){let w=v.computeStrides(p);f=`${w[0]===l[1]}_${w[w.length-1]===l[1]}`}let m=i.shape.length,g=p.length===2&&v.arraysEqual(i.shape,l),x=v.sizeFromShape(i.shape)===1,A=T.getBroadcastDims(i.shape,a.shape),y=!e.packedInputs&&m===a.shape.length&&v.arraysEqual(l,a.texData.texShape),b=e.packedInputs||p.length>2?"":`${l[0]>1}_${l[1]>1}`;n+=`${m}_${y}_${u?c:""}_${p.length}_${x}_${A}_${g}_${d}_${h}_${f}_${b}_${o}`}else{let l=i.isUniform?"uniform":i.texData.texShape;n+=`${i.shape}_${l}_${o}`}});let r=e.userCode,s=e.constructor.name;return s+="_"+n+"_"+r+`${W().getNumber("WEBGL_VERSION")}`,s}function Na(e){return W().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var ZV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=fd.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=Ca();this.outputShape=e,this.enableShapeUniforms=Na(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?Oh(["r","c","d"],e):Ao(["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;
}
`}},YV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=fd.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=Ca();this.outputShape=e,this.enableShapeUniforms=Na(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?Oh(["r","c","d"],e):Ao(["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;
}
`}},JV=class{constructor(e){this.variableNames=["A"],this.outTexUsage=pn.DOWNLOAD;let t=Ca();this.outputShape=e,this.userCode=`
${x6}
void main() {
float x = getAAtOutCoords();
${t.output} = encode_float(x);
}
`}},QV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=pn.DOWNLOAD;let t=Ca();this.outputShape=e,this.userCode=`
${x6}
void main() {
ivec3 coords = getOutputCoords();
float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
${t.output} = encode_float(x);
}
`}},eU={R:0,G:1,B:2,A:3},hx=class{constructor(e,t=!1,a="RGBA"){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=Ca();this.outputShape=e,this.enableShapeUniforms=Na(this.outputShape.length);let r="result";t&&(r="floor(result * 255. + 0.5)");let s="";for(let i=0;i<a.length;i++){let o=a[i];s+=`
if(offset == ${i}) {
result = values[${eU[o]}];
}`}this.userCode=`
${this.enableShapeUniforms?w3():v3(e)}
void main() {
ivec3 coords = getOutputCoords();
int flatIndex = getFlatIndex(coords);
float result = 0.;
int offset = imod(flatIndex, ${a.length});
flatIndex = idiv(flatIndex, ${a.length}, 1.);
int r = flatIndex / texShape[1];
if (r < texShape[0]) {
int c = imod(flatIndex, texShape[1]);
vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
vec4 values = ${n.texture2D}(A, uv);
${s}
}
${n.output} = vec4(${r}, 0., 0., 0.);
}
`}},tU=class{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let a=Ca();this.outputShape=e,this.enableShapeUniforms=Na(this.outputShape.length);let n="",r="result";t&&(r="floor(result * 255. + 0.5)");for(let s=0;s<=1;s++)for(let i=0;i<=1;i++){let o=s*2+i;n+=`
localCoords = coords;
if(localCoords[2] + ${i} < ${this.enableShapeUniforms?"outShape[2]":`${e[2]}`}) {
localCoords[2] += ${i};
if (localCoords[1] + ${s} < ${this.enableShapeUniforms?"outShape[1]":`${e[1]}`}) {
localCoords[1] += ${s};
flatIndex = getFlatIndex(localCoords);
offset = imod(flatIndex, 4);
flatIndex = idiv(flatIndex, 4, 1.);
int r = flatIndex / texShape[1];
int c = imod(flatIndex, texShape[1]);
vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
values = ${a.texture2D}(A, uv);
if (offset == 0) {
result[${o}] = values[0];
} else if (offset == 1) {
result[${o}] = values[1];
} else if (offset == 2) {
result[${o}] = values[2];
} else {
result[${o}] = values[3];
}
}
}
`}this.userCode=`
${this.enableShapeUniforms?w3():v3(e)}
void main() {
ivec3 coords = getOutputCoords();
vec4 result = vec4(0.);
int flatIndex, r, c, offset;
ivec3 localCoords;
vec2 uv;
vec4 values;
${n}
${a.output} = ${r};
}
`}},w6={};Xe(w6,{bindVertexProgramAttributeStreams:()=>M6,createBufferFromOutputTexture:()=>P6,createFloat16MatrixTexture:()=>C6,createFloat16PackedMatrixTexture:()=>R6,createFloat32MatrixTexture:()=>T6,createIndexBuffer:()=>S6,createPackedMatrixTexture:()=>E6,createUnsignedBytesMatrixTexture:()=>N6,createVertexBuffer:()=>I6,createVertexShader:()=>k6,downloadByteEncodedFloatMatrixFromOutputTexture:()=>O6,downloadFloat32MatrixFromBuffer:()=>F6,downloadMatrixFromPackedOutputTexture:()=>z6,downloadPackedMatrixFromBuffer:()=>D6,getInternalFormatForFloat16MatrixTexture:()=>S3,getInternalFormatForFloat16PackedMatrixTexture:()=>N3,getInternalFormatForFloat32MatrixTexture:()=>I3,getInternalFormatForPackedMatrixTexture:()=>C3,getInternalFormatForUnsignedBytesMatrixTexture:()=>T3,uploadDenseMatrixToTexture:()=>$6,uploadPixelDataToTexture:()=>_6});function k6(e){let t=Ca(),a=`${t.version}
precision highp float;
${t.attribute} vec3 clipSpacePos;
${t.attribute} vec2 uv;
${t.varyingVs} vec2 resultUV;
void main() {
gl_Position = vec4(clipSpacePos, 1);
resultUV = uv;
}`;return K7(e,a)}function I6(e){let t=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return Q7(e,t)}function S6(e){let t=new Uint16Array([0,1,2,2,1,3]);return e6(e,t)}function dp(e,t,a,n,r,s){a6(t,a);let i=t6(e),o=e.TEXTURE_2D;return le(e,()=>e.bindTexture(o,i)),le(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),le(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),le(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),le(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),W().getNumber("WEBGL_VERSION")===1?le(e,()=>e.texImage2D(o,0,n,t,a,0,r,s,null)):le(e,()=>e.texStorage2D(o,1,n,t,a)),le(e,()=>e.bindTexture(e.TEXTURE_2D,null)),{texture:i,texShape:[a,t]}}function I3(e){return e.internalFormatFloat}function T6(e,t,a,n){let[r,s]=up(t,a);return dp(e,r,s,I3(n),n.textureFormatFloat,e.FLOAT)}function S3(e){return e.internalFormatHalfFloat}function C6(e,t,a,n){let[r,s]=up(t,a);return dp(e,r,s,S3(n),n.textureFormatFloat,n.textureTypeHalfFloat)}function T3(e){return e.downloadTextureFormat}function N6(e,t,a,n){let[r,s]=up(t,a);return dp(e,r,s,T3(n),e.RGBA,e.UNSIGNED_BYTE)}function C3(e){return e.internalFormatPackedFloat}function E6(e,t,a,n){let[r,s]=lu(t,a);return dp(e,r,s,C3(n),e.RGBA,e.FLOAT)}function N3(e){return e.internalFormatPackedHalfFloat}function R6(e,t,a,n){let[r,s]=lu(t,a);return dp(e,r,s,N3(n),e.RGBA,n.textureTypeHalfFloat)}function M6(e,t,a){return le(e,()=>e.bindBuffer(e.ARRAY_BUFFER,a)),w1(e,t,"clipSpacePos",a,3,20,0)&&w1(e,t,"uv",a,2,20,12)}function $6(e,t,a,n,r,s){le(e,()=>e.bindTexture(e.TEXTURE_2D,t));let i,o,l;r instanceof Uint8Array?(i=new Uint8Array(a*n*4),o=e.UNSIGNED_BYTE,l=e.RGBA):(i=new Float32Array(a*n*4),o=e.FLOAT,l=s.internalFormatPackedFloat),i.set(r),W().getNumber("WEBGL_VERSION")===2?le(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,a,n,e.RGBA,o,i)):le(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,a,n,0,e.RGBA,o,i)),le(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function _6(e,t,a){le(e,()=>e.bindTexture(e.TEXTURE_2D,t)),a.data instanceof Uint8Array?W().getNumber("WEBGL_VERSION")===2?le(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,a.width,a.height,e.RGBA,e.UNSIGNED_BYTE,a.data)):le(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,a.width,a.height,0,e.RGBA,e.UNSIGNED_BYTE,a.data)):W().getNumber("WEBGL_VERSION")===2?le(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,a)):le(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,a)),le(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function P6(e,t,a,n){let r=e.createBuffer();le(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,r));let s=4*4*t*a;return le(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),le(e,()=>e.readPixels(0,0,a,t,e.RGBA,e.FLOAT,0)),le(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),r}function F6(e,t,a){let n=e,r=new Float32Array(a);return n.bindBuffer(n.PIXEL_PACK_BUFFER,t),n.getBufferSubData(n.PIXEL_PACK_BUFFER,0,r),n.bindBuffer(n.PIXEL_PACK_BUFFER,null),r}function O6(e,t,a,n){let[r,s]=up(t,a),i=4,o=new Uint8Array(YW(t*a,i));return le(e,()=>e.readPixels(0,0,r,s,n.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function D6(e,t,a,n,r,s,i,o){let l=e,u=new Float32Array(JW(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,u),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),u}function z6(e,t,a){let n=new Float32Array(t*a*4);return le(e,()=>e.readPixels(0,0,a,t,e.RGBA,e.FLOAT,n)),n}var il=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.itemsToPoll=[];let t=W().getNumber("WEBGL_VERSION");if(e!=null?(this.gl=e,Fh(t,e)):this.gl=Dn(t),e=this.gl,W().getNumber("WEBGL_VERSION")===2){let r=e;this.createVertexArray=()=>le(r,()=>r.createVertexArray()),this.bindVertexArray=s=>le(r,()=>r.bindVertexArray(s)),this.deleteVertexArray=s=>le(r,()=>r.deleteVertexArray(s)),this.getVertexArray=()=>le(r,()=>r.getParameter(r.VERTEX_ARRAY_BINDING))}else if(e!=null){let r=e.getExtension("OES_vertex_array_object");if(r==null)throw new Error("All WebGL1 implementations are expected to offer OES_vertex_array_object.");this.createVertexArray=()=>le(e,()=>r.createVertexArrayOES()),this.bindVertexArray=s=>le(e,()=>r.bindVertexArrayOES(s)),this.deleteVertexArray=s=>le(e,()=>r.deleteVertexArrayOES(s)),this.getVertexArray=()=>le(e,()=>e.getParameter(r.VERTEX_ARRAY_BINDING_OES))}let a="WEBGL_color_buffer_float",n="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),W().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=qu(this.gl,r),cn(this.gl,s))this.textureHalfFloatExtension=qu(this.gl,s);else if(W().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(a),cn(this.gl,n))this.colorBufferHalfFloatExtension=qu(this.gl,n);else if(W().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(a="EXT_color_buffer_float",cn(this.gl,a))this.colorBufferFloatExtension=this.gl.getExtension(a);else if(cn(this.gl,n))this.colorBufferHalfFloatExtension=this.gl.getExtension(n);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=I6(this.gl),this.indexBuffer=S6(this.gl),this.framebuffer=n6(this.gl),this.textureConfig=y3(this.gl,this.textureHalfFloatExtension)}get debug(){return W().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),this.outputTexture!=null&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture. This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let e=this.gl;le(e,()=>e.finish()),le(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),le(e,()=>e.deleteFramebuffer(this.framebuffer)),le(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),le(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),le(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),T6(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),C6(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),N6(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),_6(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,a,n){this.throwIfDisposed(),$6(this.gl,e,t,a,n,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),R6(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),E6(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(k1(this.gl,this.framebuffer),this.outputTexture=null),le(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,a){return this.downloadMatrixDriver(e,()=>O6(this.gl,t,a,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,a,n,r,s){return D6(this.gl,e,t,a,n,r,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return F6(this.gl,e,t)}createBufferFromTexture(e,t,a){this.bindTextureToFrameBuffer(e);let n=P6(this.gl,t,a,this.textureConfig);return this.unbindTextureToFrameBuffer(),n}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,a;if(W().getBool("WEBGL_FENCE_API_ENABLED")){let n=e,r=n.fenceSync(n.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),a=()=>{let s=n.clientWaitSync(r,0,0);return s===n.ALREADY_SIGNALED||s===n.CONDITION_SATISFIED},t=r}else W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),a=()=>this.isQueryAvailable(t,W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):a=()=>!0;return{query:t,isFencePassed:a}}downloadMatrixFromPackedTexture(e,t,a){return this.downloadMatrixDriver(e,()=>z6(this.gl,t,a))}createProgram(e){this.throwIfDisposed();let t=this.gl;this.vertexShader==null&&(this.vertexShader=k6(t));let a=Y7(t);le(t,()=>t.attachShader(a,this.vertexShader)),le(t,()=>t.attachShader(a,e)),J7(t,a);let n;return n=Object.assign(a,{vao:this.createVertexArray()}),this.bindVertexArray(n.vao),le(t,()=>t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,this.indexBuffer)),console.assert(M6(t,n,this.vertexBuffer),"gpgpu_util.bindVertexProgramAttributeStreams not fully successful."),this.debug&&gc(t,n),this.setProgram(n),n}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&(le(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&&gc(this.gl,this.program)),le(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,a=!0){return this.throwIfDisposed(),a?s6(this.gl,e,t):i6(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),le(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,a){this.throwIfDisposed(),this.throwIfNoProgram(),o6(this.gl,e,t,a)}setOutputMatrixTexture(e,t,a){this.setOutputMatrixTextureDriver(e,a,t)}setOutputPackedMatrixTexture(e,t,a){this.throwIfDisposed();let[n,r]=lu(t,a);this.setOutputMatrixTextureDriver(e,n,r)}setOutputMatrixWriteRegion(e,t,a,n){this.setOutputMatrixWriteRegionDriver(a,e,n,t)}setOutputPackedMatrixWriteRegion(e,t,a,n){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&gc(this.gl,this.program),Xu(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()}le(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),le(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=qu(this.gl,W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}getQueryTimerExtensionWebGL2(){return this.getQueryTimerExtension()}getQueryTimerExtensionWebGL1(){return this.getQueryTimerExtension()}beginQuery(){if(W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let a=this.gl,n=this.getQueryTimerExtensionWebGL2(),r=a.createQuery();return a.beginQuery(n.TIME_ELAPSED_EXT,r),r}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,a=this.getQueryTimerExtensionWebGL2();t.endQuery(a.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await v.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let a=this.gl;return a.getQueryParameter(e,a.QUERY_RESULT)/1e6}else{let a=this.getQueryTimerExtensionWebGL1();return a.getQueryObjectEXT(e,a.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let a=this.gl,n=this.getQueryTimerExtensionWebGL2(),r=a.getQueryParameter(e,a.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),r&&!this.disjoint}else{let a=this.getQueryTimerExtensionWebGL1(),n=a.getQueryObjectEXT(e,a.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(a.GPU_DISJOINT_EXT)),n&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=aU(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:a}=this.itemsToPoll[t];a()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){if(this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),this.itemsToPoll.length>1)return;let a;"setTimeoutCustom"in W().platform&&(a=W().platform.setTimeoutCustom.bind(W().platform)),v.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0),()=>0,null,a)}bindTextureToFrameBuffer(e){this.throwIfDisposed(),xc(this.gl,e,this.framebuffer),this.debug&&Xu(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(xc(this.gl,this.outputTexture,this.framebuffer),this.debug&&Xu(this.gl)):k1(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let a=t();return this.unbindTextureToFrameBuffer(),a}setOutputMatrixTextureDriver(e,t,a){this.throwIfDisposed();let n=this.gl;xc(n,e,this.framebuffer),this.debug&&Xu(n),this.outputTexture=e,le(n,()=>n.viewport(0,0,t,a)),le(n,()=>n.scissor(0,0,t,a))}setOutputMatrixWriteRegionDriver(e,t,a,n){this.throwIfDisposed(),le(this.gl,()=>this.gl.scissor(e,t,a,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 aU(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:nU,bincountImpl:L6,bincountReduceImpl:rU,castImpl:sU,ceilImpl:iU,concatImpl:oU,equalImpl:lU,expImpl:uU,expm1Impl:dU,floorImpl:pU,gatherNdImpl:cU,gatherV2Impl:hU,greaterImpl:fU,greaterEqualImpl:mU,lessImpl:gU,lessEqualImpl:xU,linSpaceImpl:AU,logImpl:yU,maxImpl:bU,maximumImpl:vU,minimumImpl:wU,multiplyImpl:kU,negImpl:IU,notEqualImpl:SU,prodImpl:TU,raggedGatherImpl:CU,raggedRangeImpl:NU,raggedTensorToTensorImpl:EU,rangeImpl:RU,rsqrtImpl:MU,scatterImpl:$U,sigmoidImpl:_U,simpleAbsImpl:B6,sliceImpl:PU,sparseFillEmptyRowsImpl:FU,sparseReshapeImpl:OU,sparseSegmentReductionImpl:W6,sqrtImpl:DU,stridedSliceImpl:zU,stringNGramsImpl:LU,stringSplitImpl:BU,stringToHashBucketFastImpl:WU,subImpl:VU,tileImpl:UU,topKImpl:GU,transposeImpl:E3,uniqueImpl:HU}=_h;function V6(e,t){return["x","y","z","w","u","v"].slice(0,t).map(a=>`${e}.${a}`)}function va(e,t){return t===1?[e]:V6(e,t)}function jU(e,t){if(e===1)return"rc";let a="";for(let n=0;n<e;n++)a+=t[n],n<e-1&&(a+=",");return a}var qU=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=Na(this.outputShape.length),this.rank===0)this.userCode=`
void main() {
setOutput(vec4(getA(), 0., 0., 0.));
}
`;else{let t=va("rc",this.rank),a=gt(this.rank),n=this.getOutOfBoundsCondition(t),r=this.getSetup(t),s=this.getOutput(t);this.userCode=`
void main() {
${a} rc = getOutputCoords();
if(${n}) {
setOutput(vec4(0));
} else {
${r}
setOutput(vec4(${s}));
}
}
`}}getSourceCoordsArr(e){let t=[];for(let a=0;a<=1;a++)for(let n=0;n<=1;n++){let r=`${a===0?"r":"rp1"}, ${n===0?"c":"cp1"}`;for(let s=2;s<this.rank;s++)r=`${e[e.length-1-s]},`+r;t.push(r)}return t}getOutOfBoundsCondition(e){if(this.rank===1)return`rc > ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let t="";for(let a=this.rank-2;a<this.rank;a++)t+=`${e[a]} >= ${this.enableShapeUniforms?`outShape[${a}]`:this.outputShape[a]}`,a<this.rank-1&&(t+="||");return t}getSetup(e){if(this.rank===1)return"";let t=e.slice(-2),a=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 >= ${a};
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]})`}},U6=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=Na(this.outputShape.length);let a="";for(let n=0;n<4;n++){let r="thisRC = rc;";n%2===1&&(r+="thisRC.z += 1;"),n>1&&(r+="thisRC.y += 1;"),a+=`
${r}
${n>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
int flatIndex = getFlatIndex(thisRC);
ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));
result[${n}] =
getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
${n>0?"}":""}
`}this.userCode=`
${XU(t,this.enableShapeUniforms)}
${this.enableShapeUniforms?w3():v3(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]};
${a}
setOutput(result);
}
`}};function XU(e,t){return`
ivec3 inputCoordsFromReshapedOutCoords(int index) {
${t?dV(["r","c","d"],"inputShape"):Ao(["r","c","d"],e)}
return ivec3(r, c, d);
}
`}var KU=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,a){let n=mx(t,a),r=gx(e,n,a);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let s=fx(e,n,this.gpgpu.gl,this.gpgpu.textureConfig,a);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[r].shift();return this.usedTextures[r].push(o),o}let i;return n===na.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):n===na.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):n===na.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):n===na.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):n===na.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,a,n){if(this.freeTextures==null)return;let r=mx(a,n),s=gx(t,r,n);s in this.freeTextures||(this.freeTextures[s]=[]);let i=fx(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,n),o=W().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function ZU(e,t){let a=e;if(t===a.R32F)return 4;if(t===a.R16F)return 2;if(t===a.RGBA32F||t===e.RGBA)return 16;if(t===a.RGBA16F)return 8;if(t===a.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function fx(e,t,a,n,r){let s=YU(t,n),i;if(r){let[l,u]=lu(e[0],e[1]);i=l*u}else{let[l,u]=up(e[0],e[1]);i=l*u}let o=ZU(a,s);return i*o}function YU(e,t){switch(e){case na.PACKED_2X2_FLOAT32:return C3(t);case na.PACKED_2X2_FLOAT16:return N3(t);case na.UNPACKED_FLOAT32:return I3(t);case na.UNPACKED_FLOAT16:return S3(t);case na.PACKED_4X1_UNSIGNED_BYTE:return T3(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function JU(e){return W().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?na.PACKED_2X2_FLOAT32:na.UNPACKED_FLOAT32:e?na.PACKED_2X2_FLOAT16:na.UNPACKED_FLOAT16}function mx(e,t){if(e===pn.UPLOAD)return na.PACKED_2X2_FLOAT32;if(e===pn.RENDER||e==null)return JU(t);if(e===pn.DOWNLOAD||e===pn.PIXELS)return na.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function gx(e,t,a){return`${e[0]}_${e[1]}_${t}_${a}`}var qn=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=Na(this.outputShape.length),this.userCode=`
float unaryOperation(float x) {
${t}
}
void main() {
float x = getAAtOutCoords();
float y = unaryOperation(x);
setOutput(y);
}
`}},Cn="if (isnan(x)) return x;",QU="return x;",xx="return abs(x);",eG="return (x >= 0.0) ? x : (exp(x) - 1.0);",tG=Cn+`
return (x < 0.0) ? 0.0 : x;
`,aG=Cn+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,Dr="return x;",nG="return 1.0 / (1.0 + exp(-1.0 * x));",rG="return x;",sG=`
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;
`,iG=`
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;
`,oG=`
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;
`,lG="return 1.0 / (1.0 + exp(-1.0 * x));",Vr=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=Na(this.outputShape.length),this.userCode=`
vec4 unaryOperation(vec4 x) {
${t}
}
void main() {
vec4 x = getAAtOutCoords();
vec4 y = unaryOperation(x);
setOutput(y);
}
`}},uG=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=Na(this.outputShape.length);let t=e.length,a=va("rc",t),n=gt(t),r=jU(t,a),s=a.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
void main() {
${n} rc = getOutputCoords();
vec4 packedInput = getA(${r});
setOutput(getChannel(packedInput, ${i}));
}
`}},dG=Tn.whereImpl,pG=1e-7,cG=1e-4,zm={};function hG(e){return e in zm||(zm[e]={}),zm[e]}var fG=W().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),mG=600;function gG(){return W().global.screen==null?1024:W().global.screen.height*W().global.screen.width*window.devicePixelRatio*mG/1024/1024}var fu=class extends bl{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,!W().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let t;if(e!=null){if(e instanceof il)t=e;else{let a=Dn(W().getNumber("WEBGL_VERSION"),e);t=new il(a)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let a=Dn(W().getNumber("WEBGL_VERSION"));t=new il(a),this.binaryCache=hG(W().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=t,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new KU(this.gpgpu),this.numMBBeforeWarning=gG(),this.texData=new vd(this,kt())}nextDataId(){return fu.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}writeTexture(e,t,a,n,r,s){let i=this.makeTensorInfo(t,a),o=this.texData.get(i.dataId);o.isPacked=!1,o.texture={texture:e,texShape:[n,r]},o.texShape=[n,r];let l=Ku(t),u=new hx(l,!1,s),p=this.runWebGLProgram(u,[i],a,[[n,r]]);return p.shape=t,o.texture=null,this.disposeIntermediateTensorInfo(i),p.dataId}write(e,t,a){if((W().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||W().getBool("DEBUG"))&&this.checkNumericalProblems(e),a==="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:a,values:e,usage:pn.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,a,n,r){if(W().getBool("DEBUG")&&this.checkNumericalProblems(t),n==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:a,dtype:n,values:t,usage:pn.UPLOAD,refCount:r})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:a,dtype:n,complexTensorInfos:r,slice:s,shape:i,isPacked:o}=t;if(s!=null){let c;o?c=new Vr(i,Dr):c=new qn(i,Dr);let d=this.runWebGLProgram(c,[{dataId:e,shape:i,dtype:n}],n),h=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),h}if(a!=null)return this.convertAndCacheOnCPU(e);if(n==="string")return a;let l=this.activeTimers!=null,u;l&&(u=v.now());let p;if(n==="complex64"){let c=this.readSync(r.real.dataId),d=this.readSync(r.imag.dataId);p=T.mergeRealAndImagArrays(c,d)}else p=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-u),this.convertAndCacheOnCPU(e,p)}async read(e){if(this.pendingRead.has(e)){let h=this.pendingRead.get(e);return new Promise(f=>h.push(f))}let t=this.texData.get(e),{values:a,shape:n,slice:r,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(r!=null){let h;o?h=new Vr(n,Dr):h=new qn(n,Dr);let f=this.runWebGLProgram(h,[{dataId:e,shape:n,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(a!=null)return this.convertAndCacheOnCPU(e);if(W().getBool("DEBUG")&&!W().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&W().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(s!=="complex64"&&W().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let h=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(h.texture.texture,...uc(n))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let p;if(s==="complex64"){let h=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=h[0],m=h[1];p=T.mergeRealAndImagArrays(f,m)}else if(l==null)p=this.getValuesFromTexture(e);else{let h=v.sizeFromShape(n);p=this.gpgpu.downloadFloat32MatrixFromBuffer(l,h)}if(u!=null&&this.disposeIntermediateTensorInfo(u),l!=null){let h=this.gpgpu.gl;le(h,()=>h.deleteBuffer(l))}let c=this.convertAndCacheOnCPU(e,p),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(h=>h(c)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&kt().removeDataId(e,this),this.pendingDeletes--),c}readToGPU(e,t={}){let a=this.texData.get(e),{values:n,shape:r,slice:s,dtype:i,isPacked:o,texture:l}=a;if(i==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(s!=null){let d;o?d=new Vr(r,Dr):d=new qn(r,Dr);let h=this.runWebGLProgram(d,[{dataId:e,shape:r,dtype:i}],i),f=this.readToGPU(h,t);return this.disposeIntermediateTensorInfo(h),f}if(l==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 u=this.decode(e,t.customTexShape),p=kt().makeTensorFromTensorInfo(u),c=this.texData.get(u.dataId);return Object.assign({tensorRef:p},c.texture)}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let a=t.map(n=>v.decodeString(n));return Me(e.shape,e.dtype,a)}catch(a){throw new Error("Failed to decode encoded string bytes into utf-8")}return Me(e.shape,e.dtype,t)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let a=e[t];if(!q7(a))throw W().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${a} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${a} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:a,isPacked:n}=this.texData.get(e),r=v.sizeFromShape(t);if(W().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let c=this.decode(e),d=this.texData.get(c.dataId),h=this.gpgpu.downloadMatrixFromPackedTexture(d.texture.texture,...uc(t)).subarray(0,r);return this.disposeIntermediateTensorInfo(c),h}let s=W().getBool("WEBGL_PACK")&&n===!0,i=s?Ku(t):t,o=s?new QV(i):new JV(i),l=this.runWebGLProgram(o,[{shape:i,dtype:a,dataId:e}],"float32"),u=this.texData.get(l.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture.texture,u.texShape[0],u.texShape[1]).subarray(0,r);return this.disposeIntermediateTensorInfo(l),p}timerAvailable(){return W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){let t=this.activeTimers,a=[],n=!1;this.programTimersStack==null?(this.programTimersStack=a,n=!0):this.activeTimers.push(a),this.activeTimers=a,e();let r=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,n&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(r);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:a}=this.texData.get(e);return a!=null&&(this.disposeData(a.real.dataId,t),this.disposeData(a.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:a,texShape:n,usage:r,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(n,a),this.textureManager.releaseTexture(t,n,r,s)));let u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=fG){return W().getBool("WEBGL_CPU_FORWARD")&&e.every(a=>this.texData.get(a.dataId).texture==null&&v.sizeFromShape(a.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){T.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return dG(e.shape,t)}packedUnaryOp(e,t,a){let n=new Vr(e.shape,t),r=this.compileAndRun(n,[e],a);return kt().makeTensorFromTensorInfo(r)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let n=B6(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,n)}if(W().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,xx,e.dtype);let t=new qn(e.shape,xx),a=this.compileAndRun(t,[e]);return kt().makeTensorFromTensorInfo(a)}makeTensorInfo(e,t,a){let n;if(t==="string"&&a!=null&&a.length>0&&v.isString(a[0])){let r=a.map(s=>v.encodeString(s));n=this.write(r,e,t)}else n=this.write(a,e,t);return this.texData.get(n).usage=null,{dataId:n,shape:e,dtype:t}}makeOutput(e,t,a){return kt().makeTensorFromTensorInfo(this.makeTensorInfo(e,t,a),this)}unpackTensor(e){let t=new uG(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new qU(e.shape),a=!0;return this.runWebGLProgram(t,[e],e.dtype,null,a)}packedReshape(e,t){let a=[Hs(e.shape),...js(e.shape)],n={dtype:e.dtype,shape:a,dataId:e.dataId},r=[Hs(t),...js(t)],s=new U6(r,a),i=!0,o=[a],l=this.runWebGLProgram(s,[n],e.dtype,o,i);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e,t){let a=this.texData.get(e),{isPacked:n,shape:r,dtype:s}=a;if(t!=null){let c=v.sizeFromShape(r),d=t[0]*t[1]*4;v.assert(c<=d,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let i=Ku(r),o;n?o=new YV(i):o=new ZV(i);let l=!0,u=[t!=null?t:uc(i)],p=this.runWebGLProgram(o,[{shape:i,dtype:s,dataId:e}],s,u,l,t);return{dtype:s,shape:r,dataId:p.dataId}}runWebGLProgram(e,t,a,n,r=!1,s){let i=this.makeTensorInfo(e.outputShape,a),o=this.texData.get(i.dataId);if(e.packedOutput&&(o.isPacked=!0),e.outPackingScheme===fd.DENSE){let g=s!=null?s:uc(e.outputShape);o.texShape=g.map(x=>x*2)}if(e.outTexUsage!=null&&(o.usage=e.outTexUsage),v.sizeFromShape(i.shape)===0)return o.values=v.getTypedArrayFromDType(i.dtype,0),i;let l=[],u=t.map(g=>{if(g.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let x=this.texData.get(g.dataId);if(x.texture==null){if(!e.packedInputs&&v.sizeFromShape(g.shape)<=W().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:g.shape,texData:null,isUniform:!0,uniformValues:x.values};e.packedInputs&&(x.isPacked=!0,x.shape=g.shape)}if(this.uploadToGPU(g.dataId),!!x.isPacked!=!!e.packedInputs)g=x.isPacked?this.unpackTensor(g):this.packTensor(g),l.push(g),x=this.texData.get(g.dataId);else if(x.isPacked&&!md(x.shape,g.shape)){let A=g,y=g.shape;g.shape=x.shape,g=this.packedReshape(g,y),l.push(g),x=this.texData.get(g.dataId),A.shape=y}return{shape:g.shape,texData:x,isUniform:!1}});this.uploadToGPU(i.dataId);let p={shape:i.shape,texData:o,isUniform:!1},c=KV(e,u,p),d=this.getAndSaveBinary(c,()=>qV(this.gpgpu,e,u,p)),h=this.activeTimers!=null,f;h&&(f=this.startTimer()),W().get("ENGINE_COMPILE_ONLY")||XV(this.gpgpu,d,u,p,n),l.forEach(g=>this.disposeIntermediateTensorInfo(g)),h&&(f=this.endTimer(f),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(f)}));let m=W().get("WEBGL_FLUSH_THRESHOLD");if(m>0){let g=v.now();g-this.lastGlFlushTime>m&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!W().getBool("WEBGL_LAZILY_UNPACK")&&o.isPacked&&r===!1){let g=this.unpackTensor(i);return this.disposeIntermediateTensorInfo(i),g}return i}compileAndRun(e,t,a,n,r=!1){return a=a||t[0].dtype,this.runWebGLProgram(e,t,a,n,r)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(W().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=$e(()=>{if(!W().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=W().getBool("DEBUG");W().set("DEBUG",!1);let t=this.abs(Fe(1e-8)).dataSync()[0];if(W().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?pG:cG}uploadToGPU(e){let t=this.texData.get(e),{shape:a,dtype:n,values:r,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,u;l&&(u=v.now());let p=t.texShape;if(p==null&&(p=d6(a,o),t.texShape=p),r!=null){let c=Ku(a),d,h=p[1],f=p[0],m=r instanceof Uint8Array||r instanceof Uint8ClampedArray;(o||!m)&&([h,f]=lu(p[0],p[1])),o?d=new tU(c,m):d=new hx(c,m);let g=m?[f,h]:p,x=this.makeTensorInfo(g,n),A=this.texData.get(x.dataId);m?A.usage=pn.PIXELS:A.usage=pn.UPLOAD,A.texShape=g,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(x.dataId),h,f,r);let y=[[f,h]],b=!0,w=this.runWebGLProgram(d,[x],n,y,b),S=this.texData.get(w.dataId);t.texShape=S.texShape,t.isPacked=S.isPacked,t.usage=S.usage,W().get("ENGINE_COMPILE_ONLY")?this.disposeData(w.dataId):(t.texture=S.texture,t.values=null,this.texData.delete(w.dataId)),this.disposeIntermediateTensorInfo(x),l&&(this.uploadWaitMs+=v.now()-u)}else{let c=this.acquireTexture(p,i,n,o);t.texture=c}}convertAndCacheOnCPU(e,t){let a=this.texData.get(e),{dtype:n}=a;return t!=null&&(a.values=xG(t,n)),a.values}acquireTexture(e,t,a,n){if(this.numBytesInGPU+=this.computeBytes(e,a),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let r=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${r} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,n)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}checkCompileCompletion(){for(let[,e]of Object.entries(this.binaryCache))this.checkCompletion_(e)}async checkCompileCompletionAsync(){let e=[];if(this.gpgpu.parallelCompilationExtension){for(let[,t]of Object.entries(this.binaryCache))e.push(this.checkCompletionAsync_(t));return Promise.all(e)}else{for(let[,t]of Object.entries(this.binaryCache)){let a=new Promise(n=>{try{this.checkCompletion_(t),n(!0)}catch(r){throw r}});e.push(a)}return Promise.all(e)}}async checkCompletionAsync_(e){return this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(e):(await b4(),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?(b3(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:a,infLoc:n,nanLoc:r,inShapesLocations:s,inTexShapesLocations:i,outShapeLocation:o,outShapeStridesLocation:l,outTexShapeLocation:u}=v6(this.gpgpu,e.program,e.webGLProgram);e.uniformLocations=t,e.customUniformLocations=a,e.infLoc=n,e.nanLoc=r,e.inShapesLocations=s,e.inTexShapesLocations=i,e.outShapeLocation=o,e.outShapeStridesLocation=l,e.outTexShapeLocation=u}}createTensorFromTexture(e,t,a){let{texture:n,height:r,width:s,channels:i}=e,o=kt().backend;if(!o.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 l=o.writeTexture(n,t,a,r,s,i);return kt().makeTensorFromDataId(l,t,a,o)}};fu.nextDataId=0;function xG(e,t){if(t==="float32"||t==="complex64")return e;if(t==="int32"||t==="bool"){let a=t==="int32"?new Int32Array(e.length):new Uint8Array(e.length);for(let n=0;n<a.length;++n)a[n]=Math.round(e[n]);return a}else throw new Error(`Unknown dtype ${t}`)}var AG="4.1.0";function G6(){W().set("WEBGL_FORCE_F16_TEXTURES",!0)}jd.isBrowser()&&go("webgl",()=>new fu,2);var yG={forceHalfFloat:G6},R3=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,Al=class{constructor(e,t,a){this.variableNames=["A","B"],this.outputShape=T.assertAndGetBroadcastShape(t,a),this.enableShapeUniforms=Na(this.outputShape.length),this.userCode=`
float binaryOperation(float a, float b) {
${e}
}
void main() {
float a = getAAtOutCoords();
float b = getBAtOutCoords();
setOutput(binaryOperation(a, b));
}
`}},pp=`
result.r = isNaN.r ? NAN : result.r;
result.g = isNaN.g ? NAN : result.g;
result.b = isNaN.b ? NAN : result.b;
result.a = isNaN.a ? NAN : result.a;
`,cp=class{constructor(e,t,a,n=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=T.assertAndGetBroadcastShape(t,a);let r=this.outputShape.length;this.enableShapeUniforms=Na(r);let s="";if(n)if(r===0||v.sizeFromShape(this.outputShape)===1)s=`
result.y = 0.;
result.z = 0.;
result.w = 0.;
`;else if(s=`
${gt(r)} coords = getOutputCoords();
`,r===1)this.enableShapeUniforms?s+=`
result.y = (coords + 1) >= outShape ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`:s+=`
result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`;else{let i=va("coords",r);this.enableShapeUniforms?s+=`
bool nextRowOutOfBounds =
(${i[r-2]} + 1) >= outShape[${r} - 2];
bool nextColOutOfBounds =
(${i[r-1]} + 1) >= outShape[${r} - 1];
result.y = nextColOutOfBounds ? 0. : result.y;
result.z = nextRowOutOfBounds ? 0. : result.z;
result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
`:s+=`
bool nextRowOutOfBounds =
(${i[r-2]} + 1) >= ${this.outputShape[r-2]};
bool nextColOutOfBounds =
(${i[r-1]} + 1) >= ${this.outputShape[r-1]};
result.y = nextColOutOfBounds ? 0. : result.y;
result.z = nextRowOutOfBounds ? 0. : result.z;
result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
`}this.userCode=`
vec4 binaryOperation(vec4 a, vec4 b) {
${e}
}
void main() {
vec4 a = getAAtOutCoords();
vec4 b = getBAtOutCoords();
vec4 result = binaryOperation(a, b);
${s}
setOutput(result);
}
`}};function Za(e){let{inputs:t,backend:a}=e,{x:n}=t;return a.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var bG={kernelName:ki,backendName:"webgl",kernelFunc:Za};function ls(e){let{inputs:t,backend:a}=e,{real:n,imag:r}=t,s=a.makeTensorInfo(n.shape,"complex64"),i=a.texData.get(s.dataId),o=Za({inputs:{x:n},backend:a}),l=Za({inputs:{x:r},backend:a});return i.complexTensorInfos={real:o,imag:l},s}var vG={kernelName:Sd,backendName:"webgl",kernelFunc:ls},H6="return (a < 0.) ? b * a : a;",j6=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function wG(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{alpha:s}=n,i=a.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new cp(j6,r.shape,i.shape):new Al(H6,r.shape,i.shape),l=a.runWebGLProgram(o,[r,i],"float32");return a.disposeIntermediateTensorInfo(i),l}var kG={kernelName:Si,backendName:"webgl",kernelFunc:wG},q6="return (a < 0.) ? b * a : a;",X6=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function IG(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t,s=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new cp(X6,n.shape,r.shape):new Al(q6,n.shape,r.shape);return a.runWebGLProgram(s,[n,r],"float32")}var SG={kernelName:Hi,backendName:"webgl",kernelFunc:IG},mu="if (isnan(x)) return x;";function Qe({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:a,dtype:n}){return({inputs:r,backend:s})=>{let{x:i}=r,o=s,l=n||i.dtype;if(o.shouldExecuteOnCPU([i])&&a!=null){let c=o.texData.get(i.dataId),d=a(c.values,l);return o.makeTensorInfo(i.shape,l,d)}let u=W().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,p;return u?p=new Vr(i.shape,t):p=new qn(i.shape,e),o.runWebGLProgram(p,[i],l)}}function oa({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:a=!1,supportsComplex:n=!1,cpuKernelImpl:r,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:u}=i,p=o;if(n&&l.dtype==="complex64"){let f=p.texData.get(l.dataId),m=p.texData.get(u.dataId),[g,x]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(y=>{let[b,w]=y,S={dataId:b.dataId,dtype:b.dtype,shape:l.shape},C={dataId:w.dataId,dtype:w.dtype,shape:u.shape},E=new Al(e,l.shape,u.shape);return p.runWebGLProgram(E,[S,C],ca(b.dtype,w.dtype))}),A=ls({inputs:{real:g,imag:x},backend:p});return p.disposeIntermediateTensorInfo(g),p.disposeIntermediateTensorInfo(x),A}let c=s||ca(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||p.shouldExecuteOnCPU([l,u]))&&r!=null){let f=p.texData.get(l.dataId).values,m=p.texData.get(u.dataId).values,g=l.dtype==="string"?T.fromUint8ToStringArray(f):f,x=l.dtype==="string"?T.fromUint8ToStringArray(m):m,[A,y]=r(l.shape,u.shape,g,x,c),b=p.makeTensorInfo(y,c),w=p.texData.get(b.dataId);return w.values=A,b}let d=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,h;return d?h=new cp(t,l.shape,u.shape,a):h=new Al(e,l.shape,u.shape),p.runWebGLProgram(h,[l,u],c)}}function gd(e,t=!1){if(e==="linear")return t?rG:QU;if(e==="relu")return t?iG:tG;if(e==="elu")return t?sG:eG;if(e==="relu6")return t?oG:aG;if(e==="prelu")return t?X6:q6;if(e==="leakyrelu")return t?j6:H6;if(e==="sigmoid")return t?lG:nG;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var K6=class{constructor(e,t,a,n=!1,r=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=a,this.enableShapeUniforms=Na(this.outputShape.length);let u=n?e[1]:e[2],p=Math.ceil(u/2),c=n?"i * 2, rc.y":"rc.y, i * 2",d=r?"rc.z, i * 2":"i * 2, rc.z",h=n?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",g="";i&&(o?m=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${i}
}`:l?m=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${i}
}`:m=`vec4 activation(vec4 x) {
${i}
}`,g="result = activation(result);");let x=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let A="rc.x",y="rc.x";e[0]<t[0]?A=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(y=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
${m}
// Don't use uniform for sharedDimensionPacked for performance.
const float sharedDimension = ${p}.0;
vec4 dot2x2ARowBCol(ivec3 rc) {
vec4 result = vec4(0);
for (int i = 0; i < ${p}; i++) {
int batchA = ${A};
int batchB = ${y};
vec4 a = getMatrixA(batchA, ${c});
vec4 b = getMatrixB(batchB, ${d});
// These swizzled products need to be separately added.
// See: https://github.com/tensorflow/tfjs/issues/1735
result += (${h[0]} * ${f[0]});
result += (${h[1]} * ${f[1]});
}
return result;
}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = dot2x2ARowBCol(rc);
${x}
${g}
setOutput(result);
}
`}},Ax={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},yx=class{constructor(e,t,a){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=T.assertAndGetBroadcastShape(t,a),this.userCode=`
float binaryOpComplex(
float areal, float aimag, float breal, float bimag) {
${e}
}
void main() {
float areal = getARealAtOutCoords();
float aimag = getAImagAtOutCoords();
float breal = getBRealAtOutCoords();
float bimag = getBImagAtOutCoords();
setOutput(binaryOpComplex(areal, aimag, breal, bimag));
}
`}},bx="return a * b;";function M3(e){let{inputs:t,backend:a}=e,{a:n,b:r}=t,s=T.upcastType(n.dtype,r.dtype);if(n.dtype==="complex64"){let o=a.texData.get(n.dataId),l=a.texData.get(r.dataId),u=new yx(Ax.REAL,n.shape,r.shape),p=new yx(Ax.IMAG,n.shape,r.shape),c=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:n.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:n.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:r.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:r.shape}],d=a.runWebGLProgram(u,c,"float32"),h=a.runWebGLProgram(p,c,"float32"),f=ls({inputs:{real:d,imag:h},backend:a});return a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),f}if(a.shouldExecuteOnCPU([n,r])){let o=a.texData.get(n.dataId),l=a.texData.get(r.dataId),[u,p]=kU(n.shape,r.shape,o.values,l.values,s),c=a.makeTensorInfo(p,s),d=a.texData.get(c.dataId);return d.values=u,c}let i;return W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new cp(bx,n.shape,r.shape):i=new Al(bx,n.shape,r.shape),a.runWebGLProgram(i,[n,r],s)}var TG={kernelName:zi,backendName:"webgl",kernelFunc:M3};function CG(e,t,a){let n=[Hs(e.shape),...js(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},s=[Hs(t),...js(t)],i=new U6(s,n),o=!0,l=[n],u=a.runWebGLProgram(i,[r],e.dtype,l,o);return{dataId:u.dataId,shape:t,dtype:u.dtype}}function ce(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{shape:s}=n,i=a,o=v.sizeFromShape(r.shape),l=v.inferFromImplicitShape(s,o),u=v.sizeFromShape(l);v.assert(o===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${r.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let p=i.texData.get(r.dataId);return p.isPacked&&!md(r.shape,l)&&!(p.texture!==null&&md(p.shape,l))?CG(r,l,i):(i.incRef(r.dataId),{dataId:r.dataId,shape:l,dtype:r.dtype})}var NG={kernelName:ql,backendName:"webgl",kernelFunc:ce},vx=class{constructor(e,t){this.variableNames=["x"];let{windowSize:a,batchSize:n,inSize:r,outSize:s}=e;this.outputShape=[n,s];let i=Math.floor(a/4)*4,o=a%4,l="sumValue += dot(values, ones);";if(t!=null){let p=1/t;l=`sumValue += dot(values * ${v.isInt(p)?p.toPrecision(2):p}, ones);`}let u="";r%a>0&&(u=`
if (inIdx < 0 || inIdx >= ${r}) {
return 0.0;
}
`),this.userCode=`
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float getValue(int batch, int inIdx) {
${u}
return getX(batch, inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${a};
float sumValue = 0.0;
for (int i = 0; i < ${i}; i += 4) {
int inIdx = inOffset + i;
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
getValue(batch, inIdx + 3)
);
${l}
}
int inIdx = inOffset + ${i};
if (${o===1}) {
vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);
${l}
} else if (${o===2}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1), 0.0, 0.0);
${l}
} else if (${o===3}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2), 0.0);
${l}
}
setOutput(sumValue);
}
`}},EG=class{constructor(e,t){this.variableNames=["x"];let{windowSize:a,batchSize:n,inSize:r,outSize:s}=e;this.outputShape=[n,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let u=Math.floor(a/4)*4,p=a%4,c=`
if (${t==="sum"}) {
sumValue += dot(values, ones);
} else if (${t==="prod"}) {
vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
prodValue *= tmp[0] * tmp[1];
} else {
minMaxValue = ${o}(values, minMaxValue);
if (${t==="min"} || ${t==="max"}) {
minMaxValue = ${o}(values, minMaxValue);
bvec4 isNaN = isnan(values);
if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {
minMaxValue = vec4(NAN);
}
}
}
`,d="vec4";t==="all"?(i="1.0",c=`
bool reducedAllValue = all(values);
float floatedReducedAllValue = float(reducedAllValue);
allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
`,d="bvec4"):t==="any"&&(i="0.0",c=`
bool reducedAnyValue = any(values);
float floatedReducedAnyValue = float(reducedAnyValue);
anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
`,d="bvec4");let h="";r%a>0&&(h=`
if (inIdx < 0 || inIdx >= ${r}) {
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) {
${h}
return getX(batch, inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${a};
vec4 minMaxValue = vec4(${i});
float prodValue = 1.0;
float sumValue = 0.0;
float allValue = 1.0;
float anyValue = 0.0;
for (int i = 0; i < ${u}; i += 4) {
int inIdx = inOffset + i;
${d} values = ${d}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
getValue(batch, inIdx + 3)
);
${c}
}
int inIdx = inOffset + ${u};
if (${p===1}) {
${d} values = ${d}(
getValue(batch, inIdx),
initializationValue,
initializationValue,
initializationValue
);
${c}
} else if (${p===2}) {
${d} values = ${d}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
initializationValue,
initializationValue
);
${c}
} else if (${p===3}) {
${d} values = ${d}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
initializationValue
);
${c}
}
setOutput(${l});
}
`}};function RG(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let a=t.length?t[t.length-1].outSize:e[1],n=T.computeOptimalWindowSize(a);t.push({inSize:a,windowSize:n,outSize:Math.ceil(a/n)})}return t}function bo(e,t,a,n){let r=RG(e.shape),s=e;for(let i=0;i<r.length;i++){let{inSize:o,windowSize:l,outSize:u}=r[i],p,c;a==="mean"?p=i===0?new vx({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},o):new vx({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u}):p=new EG({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},a),c=s,s=n.runWebGLProgram(p,[s],t),c.dataId!==e.dataId&&n.disposeIntermediateTensorInfo(c)}return s}var MG=class{constructor(e,t){this.variableNames=["A"];let a=new Array(e.length);for(let s=0;s<a.length;s++)a[s]=e[t[s]];this.outputShape=a,this.rank=a.length;let n=gt(this.rank),r=$G(t);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
setOutput(getA(${r}));
}
`}};function $G(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let a=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],n=new Array(t);for(let r=0;r<e.length;r++)n[e[r]]=a[r];return n.join()}var _G=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let a=new Array(e.length);for(let u=0;u<a.length;u++)a[u]=e[t[u]];if(this.outputShape=a,this.rank=a.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let n=gt(this.rank),r=V6("rc",this.rank),s=new Array(this.rank);for(let u=0;u<t.length;u++)s[t[u]]=r[u];let i=`vec2(${s.slice(-2).join()})`,o=`++${r[this.rank-1]} < ${a[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
void main() {
${n} rc = getOutputCoords();
vec4 result = vec4(0.);
result[0] = ${l};
if(${o}) {
result[1] = ${l};
}
--${r[this.rank-1]};
if(++${r[this.rank-2]} < ${a[this.rank-2]}) {
result[2] = ${l};
if(${o}) {
result[3] = ${l};
}
}
setOutput(result);
}
`}};function Dh(e,t,a){let n=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new _G(e.shape,t):new MG(e.shape,t);return a.runWebGLProgram(n,[e],e.dtype)}function PG(e,t,a,n){let r=t,s=e.shape.length,i=v.parseAxisParam(r,e.shape),o=i,l=T.getAxesPermutation(o,s),u=l!=null,p=e;u&&(p=Dh(e,l,n),o=T.getInnerMostAxes(o.length,s)),T.assertAxesAreInnerMostDims("sum",o,s);let[c,d]=T.computeOutAndReduceShapes(p.shape,o),h=c;a&&(h=T.expandShapeToKeepDim(c,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,g=ce({inputs:{x:p},attrs:{shape:[m,f]},backend:n}),x=Hd(e.dtype),A=bo(g,x,"sum",n),y=ce({inputs:{x:A},attrs:{shape:h},backend:n});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(A),u&&n.disposeIntermediateTensorInfo(p),y}function zh(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return PG(r,s,i,a)}var FG={kernelName:ro,backendName:"webgl",kernelFunc:zh};function Ia(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{perm:s}=n,i=a,o=r.shape.length,l=new Array(o);for(let p=0;p<l.length;p++)l[p]=r.shape[s[p]];let u;if(i.shouldExecuteOnCPU([r])){let p=i.texData.get(r.dataId).values,c=E3(p,r.shape,r.dtype,s,l);u=i.makeTensorInfo(l,r.dtype);let d=i.texData.get(u.dataId);d.values=c}else u=Dh(r,s,i);return u}var OG={kernelName:Ar,backendName:"webgl",kernelFunc:Ia},Z6=1e3;function Dc({a:e,b:t,transposeA:a,transposeB:n,backend:r,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,p=t.shape.length,c=a?e.shape[u-2]:e.shape[u-1],d=n?t.shape[p-1]:t.shape[p-2],h=a?e.shape[u-1]:e.shape[u-2],f=n?t.shape[p-2]:t.shape[p-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),x=v.sizeFromShape(m),A=v.sizeFromShape(g),y=xo.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,f]);v.assert(c===d,()=>`Error in matMul: inner shapes (${c}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${a} and transposeB=${n} must match.`);let b=a?[x,c,h]:[x,h,c],w=n?[A,f,d]:[A,d,f],S=ce({inputs:{x:e},backend:r,attrs:{shape:b}}),C=ce({inputs:{x:t},backend:r,attrs:{shape:w}}),E=[S,C],_=Math.max(x,A),$=a?S.shape[1]:S.shape[2],M=s!=null,I=i!=null,N=l==="leakyrelu",O=l!=null?gd(l,!0):null,L=M||I||N||O!=null,B;if((h===1||f===1)&&$>Z6&&L===!1){let j=S,U=C;a&&(j=Ia({inputs:{x:S},backend:r,attrs:{perm:[0,2,1]}}),E.push(j)),n&&(U=Ia({inputs:{x:C},backend:r,attrs:{perm:[0,2,1]}}),E.push(U));let H=f!==1,V=f===1,Q=j;H&&(Q=ce({inputs:{x:j},backend:r,attrs:{shape:[_,$,1]}}),E.push(Q));let Z=f===1?2:1,re=U;V&&(re=ce({inputs:{x:U},backend:r,attrs:{shape:[_,1,$]}}),E.push(re));let ee=M3({inputs:{a:Q,b:re},backend:r});B=zh({inputs:{x:ee},backend:r,attrs:{axis:Z,keepDims:!0}}),E.push(ee)}else{let j=ca(e.dtype,t.dtype),U=new K6(b,w,[_,h,f],a,n,M,O,I,N),H=[S,C];if(s!=null&&H.push(s),I&&H.push(i),N){let V=r.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));H.push(V),E.push(V)}B=r.runWebGLProgram(U,H,j)}let G=ce({inputs:{x:B},backend:r,attrs:{shape:y}});E.push(B);for(let j of E)r.disposeIntermediateTensorInfo(j);return G}function DG(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:c}=n;return Dc({a:r,b:s,transposeA:l,transposeB:u,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:c,activation:p})}var zG={kernelName:jr,backendName:"webgl",kernelFunc:DG},wx="return abs(x);";function LG(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])&&n.dtype!=="complex64"){let s=a.texData.get(n.dataId),i=B6(s.values);return a.makeTensorInfo(n.shape,n.dtype,i)}let r;return W().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Vr(n.shape,wx):r=new qn(n.shape,wx),a.runWebGLProgram(r,[n],n.dtype)}var BG={kernelName:wl,backendName:"webgl",kernelFunc:LG},WG=Cn+`
if (abs(x) > 1.) {
return NAN;
}
return acos(x);
`,VG=Qe({opSnippet:WG}),UG={kernelName:kl,backendName:"webgl",kernelFunc:VG},GG=Cn+`
if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,HG=Qe({opSnippet:GG}),jG={kernelName:Il,backendName:"webgl",kernelFunc:HG},kx="return a + b;",qG=oa({opSnippet:kx,packedOpSnippet:kx,supportsComplex:!0,cpuKernelImpl:nU}),XG={kernelName:ts,backendName:"webgl",kernelFunc:qG},KG=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((r,s)=>`T${s}`);let a=[];this.variableNames.forEach(r=>{a.push(`float v${r} = get${r}AtOutCoords();`)});let n=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
void main() {
${a.join(`
`)}
float result = ${n};
setOutput(result);
}
`}},ZG=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((r,s)=>`T${s}`);let a=[];this.variableNames.forEach(r=>{a.push(`vec4 v${r} = get${r}AtOutCoords();`)});let n=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
void main() {
${a.join(`
`)}
vec4 result = ${n};
setOutput(result);
}
`}};function bc(e){let{inputs:t,backend:a}=e,n=t;if(n.length===1)return Za({inputs:{x:n[0]},backend:a});if(n.length>W().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(n.length/2),l=bc({inputs:n.slice(0,o),backend:a}),u=bc({inputs:n.slice(o),backend:a});return bc({inputs:[l,u],backend:a})}let r=n.map(o=>o.dtype).reduce((o,l)=>ca(o,l)),s=n.map(o=>o.shape),i=W().getBool("WEBGL_PACK")?new ZG(n[0].shape,s):new KG(n[0].shape,s);return a.runWebGLProgram(i,n,r)}var YG={kernelName:Ks,backendName:"webgl",kernelFunc:bc};function JG(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=T.getAxesPermutation(u,o),c=r;p!=null&&(c=Ia({inputs:{x:r},backend:a,attrs:{perm:p}}),u=T.getInnerMostAxes(u.length,o)),T.assertAxesAreInnerMostDims("all",u,o);let[d,h]=T.computeOutAndReduceShapes(c.shape,u),f=v.sizeFromShape(h),m=ce({inputs:{x:c},backend:a,attrs:{shape:[-1,f]}}),g=bo(m,m.dtype,"all",a),x;if(i){let A=T.expandShapeToKeepDim(d,l);x=ce({inputs:{x:g},backend:a,attrs:{shape:A}})}else x=ce({inputs:{x:g},backend:a,attrs:{shape:d}});return a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(g),p!=null&&a.disposeIntermediateTensorInfo(c),x}var QG={kernelName:Zs,backendName:"webgl",kernelFunc:JG};function eH(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=T.getAxesPermutation(u,o),c=r;p!=null&&(c=Ia({inputs:{x:r},backend:a,attrs:{perm:p}}),u=T.getInnerMostAxes(u.length,o)),T.assertAxesAreInnerMostDims("any",u,o);let[d,h]=T.computeOutAndReduceShapes(c.shape,u),f=v.sizeFromShape(h),m=ce({inputs:{x:c},backend:a,attrs:{shape:[-1,f]}}),g=bo(m,m.dtype,"any",a),x;if(i){let A=T.expandShapeToKeepDim(d,l);x=ce({inputs:{x:g},backend:a,attrs:{shape:A}})}else x=ce({inputs:{x:g},backend:a,attrs:{shape:d}});return a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(g),p!=null&&a.disposeIntermediateTensorInfo(c),x}var tH={kernelName:Ys,backendName:"webgl",kernelFunc:eH},aH=class{constructor(e,t,a){this.variableNames=["A"];let{windowSize:n,batchSize:r,outSize:s}=e;a||this.variableNames.push("bestIndicesA"),this.outputShape=[r,s];let i=t==="max"?">":"<",o=a?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${n};
int bestIndex = inOffset;
float bestValue = getA(batch, bestIndex);
for (int i = 0; i < ${n}; i++) {
int inIdx = ${o};
float candidate = getA(batch, inIdx);
if (candidate ${i} bestValue) {
bestValue = candidate;
bestIndex = inIdx;
}
}
setOutput(float(bestIndex));
}
`}},nH=class{constructor(e,t,a,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${a.charAt(0).toUpperCase()+a.slice(1)} supports only inputs with rank above 2.`);let r=e[e.length-1],s=Math.ceil(r/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),n||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=gt(o),u=va("coords",o),p,c;if(s===1){c=o+1;let C=gt(c);p=`
${C} sourceLocR = ${C}(${u.join()}, 0);
++${u[o-1]};
${C} sourceLocG = ${C}(${u.join()}, 0);
++${u[o-2]};
${C} sourceLocA = ${C}(${u.join()}, 0);
--${u[o-1]};
${C} sourceLocB = ${C}(${u.join()}, 0);
--${u[o-2]};`}else c=o,p=`
${l} sourceLocR = coords;
++${u[o-1]};
${l} sourceLocG = coords;
++${u[o-2]};
${l} sourceLocA = coords;
--${u[o-1]};
${l} sourceLocB = coords;
--${u[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,c),h="."+d[c-1],f=d.map(C=>"int "+C),m=va("sourceLocR",c-1).concat("inIdx.r"),g=va("sourceLocG",c-1).concat("inIdx.g"),x=va("sourceLocB",c-1).concat("inIdx.b"),A=va("sourceLocA",c-1).concat("inIdx.a"),y=a==="max"?"greaterThan":"lessThan",b=n?"":`
inIdx = round(vec4(getBestIndicesAChannel(${m.join()}),
getBestIndicesAChannel(${g.join()}),
getBestIndicesAChannel(${x.join()}),
getBestIndicesAChannel(${A.join()})));`,w=`vec4(
getAChannel(${m.join()}),
hasNextCol ? getAChannel(${g.join()}) : 0.,
hasNextRow ? getAChannel(${x.join()}) : 0.,
hasNextRow && hasNextCol ? getAChannel(${A.join()}) : 0.)`,S=n?"":`
float getBestIndicesAChannel(${f.join()}) {
return getChannel(getBestIndicesA(${d.join()}),
vec2(${d.slice(-2).join()}));
}`;this.userCode=`
float getAChannel(${f.join()}) {
return getChannel(getA(${d.join()}),
vec2(${d.slice(-2).join()}));
}
${S}
void main() {
${l} coords = getOutputCoords();
bool hasNextCol = ${u[o-1]} < ${i[o-1]-1};
bool hasNextRow = ${u[o-2]} < ${i[o-2]-1};
${p}
ivec4 srcIdx = ivec4(sourceLocR${h}, sourceLocG${h},
sourceLocB${h}, sourceLocA${h}) * ${t};
ivec4 inIdx = srcIdx;
vec4 bestIndex = vec4(inIdx);
vec4 bestValue = ${w};
for (int i = 0; i < ${t}; i++) {
inIdx = srcIdx;
${b}
vec4 candidate = ${w};
bvec4 nan = isnan(candidate);
bvec4 replace = bvec4(
vec4(${y}(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 Y6(e,t,a,n=null){let r=t.shape[0],s=t.shape[1];n!=null&&(r=n.shape[0],s=n.shape[1]);let i=T.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:r,outSize:Math.ceil(s/i)},l=new aH(o,a,n==null),u=[t];n!=null&&u.push(n);let p=e.runWebGLProgram(l,u,"int32");if(p.shape[1]===1)return p;let c=Y6(e,t,a,p);return e.disposeIntermediateTensorInfo(p),c}function J6(e,t,a,n=null){let r=n!=null?n.shape:t.shape,s=r[r.length-1],i=T.computeOptimalWindowSize(s),o=new nH(r,i,a,n==null),l=n==null?[t]:[t,n],u=e.runWebGLProgram(o,l,"int32");if(u.shape.length===t.shape.length){let p=J6(e,t,a,u);return e.disposeIntermediateTensorInfo(u),p}return u}function Q6(e,t,a,n){let r=[a];if(T.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),r,t.shape.length),!W().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],i=e.texData.get(t.dataId),o=i!==null&&i.isPacked,l=t;o&&(l=e.unpackTensor(t),s.push(l));let[u,p]=T.computeOutAndReduceShapes(l.shape,r),c=v.sizeFromShape(p),d=ce({inputs:{x:l},backend:e,attrs:{shape:[-1,c]}});s.push(d);let h=Y6(e,d,n);s.push(h);let f=ce({inputs:{x:h},backend:e,attrs:{shape:u}});return s.forEach(m=>e.disposeIntermediateTensorInfo(m)),f}return J6(e,t,n)}function rH(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=T.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Ia({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=T.getInnerMostAxes(i.length,l.shape.length)),T.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let p=Q6(a,l,i[0],"max");return u.forEach(c=>a.disposeIntermediateTensorInfo(c)),p}var sH={kernelName:Js,backendName:"webgl",kernelFunc:rH};function iH(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=T.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Ia({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=T.getInnerMostAxes(i.length,l.shape.length)),T.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let p=Q6(a,l,i[0],"min");return u.forEach(c=>a.disposeIntermediateTensorInfo(c)),p}var oH={kernelName:kd,backendName:"webgl",kernelFunc:iH},lH=Cn+`
if (abs(x) > 1.) {
return NAN;
}
return asin(x);
`,uH=Qe({opSnippet:lH}),dH={kernelName:Sl,backendName:"webgl",kernelFunc:uH},pH=Cn+"return log(x + sqrt(x * x + 1.0));",cH=Qe({opSnippet:pH}),hH={kernelName:Tl,backendName:"webgl",kernelFunc:cH},fH=Cn+`
return atan(x);
`,mH=Qe({opSnippet:fH}),gH={kernelName:Cl,backendName:"webgl",kernelFunc:mH},xH=R3+`
return atan(a, b);
`,AH=`
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);
`+pp+`
return result;
`,yH=oa({opSnippet:xH,packedOpSnippet:AH}),bH={kernelName:El,backendName:"webgl",kernelFunc:yH},vH=Cn+`
if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wH=Qe({opSnippet:vH}),kH={kernelName:Nl,backendName:"webgl",kernelFunc:wH},xd=class{constructor(e,t,a,n=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&a)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterHeight,c=e.effectiveFilterWidth,d=e.padInfo.top,h=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,x="0.0";if(f||(x="-1.0 / 1e-20"),a){let C=">=";this.userCode=`
const ivec2 strides = ivec2(${i}, ${o});
const ivec2 pads = ivec2(${d}, ${h});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
float minMaxValue = 0.0;
float minMaxValueFound = 0.0;
int minMaxPosition = 0;
float avgValue = 0.0;
for (int wR = 0; wR < ${p};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${c};
wC += ${u}) {
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 ${C} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${n?r?m:g:`wR * ${c} + wC`};
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let A="max",y=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(y="avgValue / count");let b=Math.floor(s/4)*4,w=s%4,S=`
if (${f}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${A}(values, minMaxValue);
}
`;this.userCode=`
const ivec2 strides = ivec2(${i}, ${o});
const ivec2 pads = ivec2(${d}, ${h});
const float initializationValue = ${x};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float count = 0.0;
float getValue(int batch, int xR, int xC, int d) {
if (xC < 0 || xC >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xR, xC, d);
}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
vec4 minMaxValue = vec4(${x});
float avgValue = 0.0;
count = 0.0;
for (int wR = 0; wR < ${p};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${b}; wC += 4) {
int xC = xCCorner + wC * ${u};
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${u}, d),
getValue(batch, xR, xC + 2 * ${u}, d),
getValue(batch, xR, xC + 3 * ${u}, d)
);
${S}
}
int xC = xCCorner + ${b};
if (${w===1}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
initializationValue,
initializationValue,
initializationValue
);
${S}
} else if (${w===2}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${u}, d),
initializationValue,
initializationValue
);
${S}
} else if (${w===3}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${u}, d),
getValue(batch, xR, xC + 2 * ${u}, d),
initializationValue
);
${S}
}
}
setOutput(${y});
}
`}},$3=class{constructor(e,t,a,n=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&a)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,p=e.dilationHeight,c=e.dilationWidth,d=e.effectiveFilterDepth,h=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,g=e.padInfo.top,x=e.padInfo.left;this.outputShape=e.outShape;let A=t==="avg",y="0.0";if(A||(y="-1.0 / 1e-20"),a){let _=">=";this.userCode=`
const ivec3 strides =
ivec3(${i}, ${o}, ${l});
const ivec3 pads = ivec3(${m}, ${g}, ${x});
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 += ${u}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${h};
wR += ${p}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${f};
wC += ${c}) {
int xC = xCCorner + wC;
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float value = getX(batch, xD, xR, xC, ch);
// If a min / max value has already been found, use it. If not,
// use the current value.
float currMinMaxValue = mix(
value, minMaxValue, minMaxValueFound);
if (value ${_} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${n?r?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${h} * ${f} +
wR * ${f} + wC`};
}
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let b="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / count");let S=Math.floor(s/4)*4,C=s%4,E=`
if (${A}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${b}(values, minMaxValue);
}
`;this.userCode=`
const ivec3 strides =
ivec3(${i}, ${o}, ${l});
const ivec3 pads = ivec3(${m}, ${g}, ${x});
const float initializationValue = ${y};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float count = 0.0;
float getValue(int batch, int xD, int xR, int xC, int ch) {
if (xC < 0 || xC >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xD, xR, xC, ch);
}
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xDCorner = xCorner.x;
int xRCorner = xCorner.y;
int xCCorner = xCorner.z;
// max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
// ? = to be determined
vec4 minMaxValue = vec4(${y});
float avgValue = 0.0;
count = 0.0;
for (int wD = 0; wD < ${d};
wD += ${u}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${h};
wR += ${p}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${S}; wC += 4) {
int xC = xCCorner + wC * ${c};
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${c}, ch),
getValue(batch, xD, xR, xC + 2 * ${c}, ch),
getValue(batch, xD, xR, xC + 3 * ${c}, ch)
);
${E}
}
int xC = xCCorner + ${S};
if (${C===1}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
initializationValue,
initializationValue,
initializationValue
);
${E}
} else if (${C===2}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${c}, ch),
initializationValue,
initializationValue
);
${E}
} else if (${C===3}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${c}, ch),
getValue(batch, xD, xR, xC + 2 * ${c}, ch),
initializationValue
);
${E}
}
}
setOutput(${w});
}
}
`}};function IH(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;uu(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(T.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=T.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))return Za({inputs:{x:r},backend:a});let c=new xd(p,"avg",!1);return a.runWebGLProgram(c,[r],"float32")}var SH={kernelName:Qs,backendName:"webgl",kernelFunc:IH};function TH(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n,p=[1,1,1],c=T.computePool3DInfo(r.shape,s,i,p,o,l,u),d=new $3(c,"avg",!1);return a.runWebGLProgram(d,[r],"float32")}var CH={kernelName:Hc,backendName:"webgl",kernelFunc:TH},NH=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,a=e.filterWidth,n=e.strideHeight,r=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=o-1-e.padInfo.top,p=l-1-e.padInfo.left,c=1/(t*a);this.userCode=`
const ivec2 pads = ivec2(${u}, ${p});
const float avgMultiplier = float(${c});
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 dyRCCorner = coords.yz - pads;
int dyRCorner = dyRCCorner.x;
int dyCCorner = dyRCCorner.y;
// Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${o};
wR += ${s}) {
float dyR = float(dyRCorner + wR) / ${n}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${l};
wC+= ${i}) {
float dyC = float(dyCCorner + wC) / ${r}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
dotProd += dyValue * avgMultiplier;
}
}
setOutput(dotProd);
}
`}},EH=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,a=e.filterHeight,n=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterDepth,c=e.effectiveFilterHeight,d=e.effectiveFilterWidth,h=p-1-e.padInfo.front,f=c-1-e.padInfo.top,m=d-1-e.padInfo.left,g=1/(t*a*n);this.userCode=`
const ivec3 pads = ivec3(${h}, ${f}, ${m});
const float avgMultiplier = float(${g});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
int dyDCorner = dyCorner.x;
int dyRCorner = dyCorner.y;
int dyCCorner = dyCorner.z;
// Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get
// dx(xD, xR, xC, ch).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wD = 0; wD < ${p};
wD += ${o}) {
float dyD = float(dyDCorner + wD) / ${r}.0;
if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
continue;
}
int idyD = int(dyD);
for (int wR = 0; wR < ${c};
wR += ${l}) {
float dyR = float(dyRCorner + wR) / ${s}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${d};
wC += ${u}) {
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 RH(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:p}=n,c=[1,1,1],d=T.computePool3DInfo(i.shape,o,l,c,u,p),h=new EH(d);return a.runWebGLProgram(h,[r],i.dtype)}var MH={kernelName:G1,backendName:"webgl",kernelFunc:RH};function $H(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s;uu([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,p=T.computePool2DInfo(i.shape,o,l,1,u),c=new NH(p);return a.runWebGLProgram(c,[r],i.dtype)}var _H={kernelName:U1,backendName:"webgl",kernelFunc:$H};function PH(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;return Dc({a:r,b:s,transposeA:i,transposeB:o,backend:a})}var FH={kernelName:ei,backendName:"webgl",kernelFunc:PH},OH=class{constructor(e,t,a,n,r,s){this.outputShape=[],this.variableNames=["x","mean","variance"],T.assertAndGetBroadcastShape(e,t),T.assertAndGetBroadcastShape(e,a);let i="0.0";n!=null&&(T.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";r!=null&&(T.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
float x = getXAtOutCoords();
float mean = getMeanAtOutCoords();
float variance = getVarianceAtOutCoords();
float offset = ${i};
float scale = ${o};
float inv = scale * inversesqrt(variance + float(${s}));
setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
}
`}},DH=class{constructor(e,t,a,n,r,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],T.assertAndGetBroadcastShape(e,t),T.assertAndGetBroadcastShape(e,a);let i="vec4(0.0)";n!=null&&(T.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";r!=null&&(T.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
vec4 offset = ${i};
vec4 scale = ${o};
vec4 x = getXAtOutCoords();
vec4 mean = getMeanAtOutCoords();
vec4 variance = getVarianceAtOutCoords();
vec4 inv = scale * inversesqrt(variance + vec4(${s}));
setOutput((x - mean) * inv + offset);
}
`}},zH=({inputs:e,backend:t,attrs:a})=>{let{x:n,mean:r,variance:s,offset:i,scale:o}=e;v.assert(r.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||r.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||r.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=a;l==null&&(l=.001);let u=[n,r,s],p=null;i!=null&&(p=i.shape,u.push(i));let c=null;o!=null&&(c=o.shape,u.push(o));let d=W().getBool("WEBGL_PACK_NORMALIZATION")?new DH(n.shape,r.shape,s.shape,p,c,l):new OH(n.shape,r.shape,s.shape,p,c,l);return t.runWebGLProgram(d,u,u[0].dtype)},LH={kernelName:yi,backendName:"webgl",kernelFunc:zH},BH=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=gt(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let a=WH(this.rank),n,r=e.map((s,i)=>`sourceLoc.${T1[i]} = start[${i}] + coords.${T1[i]};`);n=`
${t} sourceLoc;
${t} coords = getOutputCoords();
${r.join(`
`)}
`,this.userCode=`
void main() {
${n}
setOutput(getSource(${a}));
}
`}},T1=["x","y","z","w","u","v"];function WH(e){if(e===1)return"sourceLoc";if(e<=6)return T1.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var VH=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=gt(this.rank),a=va("coords",this.rank),n=va("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${n.slice(-2).join()})`,s=`getChannel(getSource(${n.join()}), ${r})`,i=`
result.x = ${s};
if (++${a[this.rank-1]} < ${e[this.rank-1]}) {
++${n[this.rank-1]};
result.y = ${s};
--${n[this.rank-1]};
}
`,o=this.rank===1?"":`
--${a[this.rank-1]};
if (++${a[this.rank-2]} < ${e[this.rank-2]}) {
++${n[this.rank-2]};
result.z = ${s};
if (++${a[this.rank-1]} < ${e[this.rank-1]}) {
++${n[this.rank-1]};
result.w = ${s};
}
}
`,l=this.rank<=4?`sourceLoc = coords +
${t}(${e.map((u,p)=>`start[${p}]`).join()});`:e.map((u,p)=>`${n[p]} = ${a[p]} + start[${p}];`).join(`
`);this.userCode=`
void main() {
${t} coords = getOutputCoords();
${t} sourceLoc;
${l}
vec4 result = vec4(0.);
${i}
${o}
setOutput(result);
}
`}};function UH(e,t,a,n){let r=n.texData.get(e.dataId),s=n.makeTensorInfo(a,e.dtype),i=n.texData.get(s.dataId);Object.assign(i,r),i.refCount=1,i.shape=a,i.dtype=e.dtype;let o=It.computeFlatOffset(t,v.computeStrides(e.shape));r.slice&&(o+=r.slice.flatOffset),i.slice={flatOffset:o,origDataId:r.slice&&r.slice.origDataId||e.dataId};let l=n.dataRefCount.get(i.slice.origDataId)||1;return n.dataRefCount.set(i.slice.origDataId,l+1),s}function gu(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,size:i}=n,[o,l]=It.parseSliceParams(r,s,i);if(It.assertParamsValid(r,o,l),v.sizeFromShape(l)===0)return a.makeTensorInfo(l,r.dtype,[]);if(a.shouldExecuteOnCPU([r])||r.dtype==="string"){let c=a.texData.get(r.dataId),d=PU(c.values,o,l,r.shape,r.dtype);return a.makeTensorInfo(l,r.dtype,d)}let{isPacked:u}=a.texData.get(r.dataId),p=It.isSliceContinous(r.shape,o,l);if(u||!p){let c=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new VH(l):new BH(l),d=[o];return a.runWebGLProgram(c,[r],r.dtype,d)}return a.uploadToGPU(r.dataId),UH(r,o,l,a)}var GH={kernelName:Zl,backendName:"webgl",kernelFunc:gu},HH=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,crops:i}=n;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((A,y)=>A*y),l=T.getReshaped(r.shape,s,o),u=T.getPermuted(l.length,s.length),p=T.getReshapedPermuted(r.shape,s,o),c=T.getSliceBeginCoords(i,s.length),d=T.getSliceSize(p,i,s.length),h=[],f=ce({inputs:{x:r},backend:a,attrs:{shape:l}}),m=Ia({inputs:{x:f},backend:a,attrs:{perm:u}}),g=ce({inputs:{x:m},backend:a,attrs:{shape:p}}),x=gu({inputs:{x:g},backend:a,attrs:{begin:c,size:d}});return h.push(f),h.push(m),h.push(g),h.forEach(A=>a.disposeIntermediateTensorInfo(A)),x},jH={kernelName:Rl,backendName:"webgl",kernelFunc:HH};function qH(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i}=n,o=a.readSync(r.dataId),l=a.readSync(s.dataId),u=L6(o,l,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,u)}var XH={kernelName:Id,backendName:"webgl",kernelFunc:qH};function KH(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t,s=a.readSync(n.dataId),i=a.readSync(r.dataId),o=T.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return a.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var ZH={kernelName:jc,backendName:"webgl",kernelFunc:KH},YH="return float(a != b);",ev=oa({opSnippet:YH,cpuKernelImpl:SU,dtype:"bool"}),JH={kernelName:Li,backendName:"webgl",kernelFunc:ev};function hp(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.texData.get(n.dataId);return Za({inputs:{x:r.complexTensorInfos.real},backend:a})}var QH={kernelName:Md,backendName:"webgl",kernelFunc:hp},ej="return float(int(x));";function tj(e,t){let a=new qn(e.shape,ej),n=t.runWebGLProgram(a,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function C1(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dtype:s}=n;if(s==="complex64"){if(r.dtype==="complex64")return Za({inputs:{x:r},backend:a});let i=fn(r.shape),o=C1({inputs:{x:r},backend:a,attrs:{dtype:"float32"}}),l=ls({inputs:{real:o,imag:i},backend:a});return i.dispose(),a.disposeIntermediateTensorInfo(o),l}if(r.dtype==="complex64"){let i=hp({inputs:{input:r},backend:a}),o=C1({inputs:{x:i},backend:a,attrs:{dtype:s}});return a.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(r.dtype,s)){let i=Za({inputs:{x:r},backend:a});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(a.shouldExecuteOnCPU([r])){let i=a.texData.get(r.dataId).values,[o,l,u]=sU(i,r.shape,r.dtype,s);return a.makeTensorInfo(o,l,u)}if(s==="int32")return tj(r,a);if(s==="bool"){let i=a.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=ev({inputs:{a:r,b:i},backend:a});return a.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${s}`)}var aj={kernelName:ti,backendName:"webgl",kernelFunc:C1},Ix="return ceil(x);",nj=Qe({opSnippet:Ix,packedOpSnippet:Ix,cpuKernelImpl:iU}),rj={kernelName:ai,backendName:"webgl",kernelFunc:nj},sj=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));
}
`}},ij=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 oj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=n,o;W().getBool("WEBGL_PACK_CLIP")?o=new ij(r.shape):o=new sj(r.shape);let l=[[s],[i]];return a.runWebGLProgram(o,[r],r.dtype,l)}var lj={kernelName:as,backendName:"webgl",kernelFunc:oj},uj=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 Sx(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function dj(e){let{inputs:t,backend:a}=e,{x:n}=t,r=a.texData.get(n.dataId),s=new uj(n.shape),i=[Sx(n,r.complexTensorInfos.real),Sx(n,r.complexTensorInfos.imag)];return a.runWebGLProgram(s,i,i[0].dtype)}var pj={kernelName:qc,backendName:"webgl",kernelFunc:dj},cj=class{constructor(e){this.outputShape=[],this.outputShape=T.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let a=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];a.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let n=t.length,r=t[t.length-1];a.push(`else setOutput(getT${n}(yR, yC-${r}));`),this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int yR = coords.x;
int yC = coords.y;
${a.join(`
`)}
}
`}},hj=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=T.computeOutShape(e,t);let a=this.outputShape,n=a.length,r=gt(n),s=va("coords",n),i=["x","y","z","w","u","v"].slice(0,n);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],u=i.slice(-2),p=i.join(),c=`if (${l} < ${o[0]}) {
return getChannel(
getT0(${p}), vec2(${u.join()}));
}`;for(let f=1;f<o.length;f++){let m=o[f-1];c+=`
if (${l} < ${o[f]} && ${l} >= ${o[f-1]}) {
return getChannel(
getT${f}(${pc(i,l,m)}),
vec2(${pc(u,l,m)}));
}`}let d=o.length,h=o[o.length-1];c+=`
return getChannel(
getT${d}(${pc(i,l,h)}),
vec2(${pc(u,l,h)}));`,this.userCode=`
float getValue(${i.map(f=>"int "+f)}) {
${c}
}
void main() {
${r} coords = getOutputCoords();
vec4 result = vec4(getValue(${s}), 0., 0., 0.);
${s[n-1]} = ${s[n-1]} + 1;
if (${s[n-1]} < ${a[n-1]}) {
result.g = getValue(${s});
}
${s[n-2]} = ${s[n-2]} + 1;
if (${s[n-2]} < ${a[n-2]}) {
result.a = getValue(${s});
}
${s[n-1]} = ${s[n-1]} - 1;
if (${s[n-2]} < ${a[n-2]} &&
${s[n-1]} < ${a[n-1]}) {
result.b = getValue(${s});
}
setOutput(result);
}
`}};function pc(e,t,a){let n=e.indexOf(t);return e.map((r,s)=>s===n?`${r} - ${a}`:r).join()}function Lh(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.texData.get(n.dataId);return Za({inputs:{x:r.complexTensorInfos.imag},backend:a})}var fj={kernelName:Rd,backendName:"webgl",kernelFunc:Lh};function Zu(e,t,a){let n=e[0].dtype;if(n==="complex64"){let h=e.map(A=>hp({inputs:{input:A},backend:a})),f=e.map(A=>Lh({inputs:{input:A},backend:a})),m=Zu(h,t,a),g=Zu(f,t,a),x=ls({inputs:{real:m,imag:g},backend:a});return h.forEach(A=>a.disposeIntermediateTensorInfo(A)),f.forEach(A=>a.disposeIntermediateTensorInfo(A)),a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(g),x}let r=a.shouldExecuteOnCPU(e);if(n==="string"&&(r=!0),r){let h=e.map(b=>{let w=[-1,v.sizeFromShape(b.shape.slice(t))];return ce({inputs:{x:b},backend:a,attrs:{shape:w}})}),f=h.map(b=>({vals:a.readSync(b.dataId),shape:b.shape})),m=T.computeOutShape(h.map(b=>b.shape),1),g=h[0].shape[0]===1,x=oU(f,m,n,g),A=T.computeOutShape(e.map(b=>b.shape),t),y=a.makeTensorInfo(A,n,x);return h.forEach(b=>a.disposeIntermediateTensorInfo(b)),y}let s=e.filter(h=>v.sizeFromShape(h.shape)>0),i=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&s[0].shape.length>1;if(s.length===1){let h=i?new qn(e[0].shape,Dr):new Vr(e[0].shape,Dr);return a.runWebGLProgram(h,e,n)}let o=W().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(s.length>o){let h=[];for(let m=0;m<s.length;m+=o){let g=s.slice(m,m+o);h.push(Zu(g,t,a))}let f=Zu(h,t,a);for(let m of h)a.disposeIntermediateTensorInfo(m);return f}if(i){let h=new hj(s.map(f=>f.shape),t);return a.runWebGLProgram(h,s,n)}let{tensors2D:l,outShape:u}=mj(s,t,a),p=new cj(l.map(h=>h.shape)),c=a.runWebGLProgram(p,l,n);l.forEach(h=>a.disposeIntermediateTensorInfo(h));let d=ce({inputs:{x:c},attrs:{shape:u},backend:a});return a.disposeIntermediateTensorInfo(c),d}function mj(e,t,a){let n=T.computeOutShape(e.map(r=>r.shape),t);return{tensors2D:e.map(r=>ce({inputs:{x:r},attrs:{shape:[-1,v.sizeFromShape(r.shape.slice(t))]},backend:a})),outShape:n}}function tv(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(u=>u.shape);T.assertParamsConsistent(i,s);let o=T.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(o)===0)return a.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(u=>v.sizeFromShape(u.shape)>0);return l.length===1?Za({inputs:{x:l[0]},backend:a}):Zu(l,s,a)}var gj={kernelName:Ml,backendName:"webgl",kernelFunc:tv},av=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,p=e.dilationWidth,c=e.filterHeight,d=e.filterWidth,h=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",g=m?1:2,x=m?2:3,A=m?3:1,y="",b="";a&&(n?y=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${a}
}`:r?y=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${a}
}`:y=`
float activation(float x) {
${a}
}
`,b="result = activation(result);");let w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${y}
const ivec2 strides = ivec2(${o}, ${l});
const ivec2 pads = ivec2(${s}, ${i});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d2 = coords[${A}];
ivec2 xRCCorner =
ivec2(coords[${g}], coords[${x}]) * 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 < ${c}; wR++) {
int xR = xRCorner + wR * ${u};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${d}; wC++) {
int xC = xCCorner + wC * ${p};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${h}; d1 += 4) {
vec4 wValues = vec4(
getW(wR, wC, d1, d2),
getW(wR, wC, d1 + 1, d2),
getW(wR, wC, d1 + 2, d2),
getW(wR, wC, d1 + 3, d2)
);
if (${m}) {
vec4 xValues = vec4(
getX(batch, xR, xC, d1),
getX(batch, xR, xC, d1 + 1),
getX(batch, xR, xC, d1 + 2),
getX(batch, xR, xC, d1 + 3)
);
dotProd += dot(xValues, wValues);
} else {
vec4 xValues = vec4(
getX(batch, d1, xR, xC),
getX(batch, d1 + 1, xR, xC),
getX(batch, d1 + 2, xR, xC),
getX(batch, d1 + 3, xR, xC)
);
dotProd += dot(xValues, wValues);
}
}
if (${f===1}) {
if (${m}) {
dotProd +=
getX(batch, xR, xC, ${h}) *
getW(wR, wC, ${h}, d2);
} else {
dotProd +=
getX(batch, ${h}, xR, xC) *
getW(wR, wC, ${h}, d2);
}
} else if (${f===2}) {
vec2 wValues = vec2(
getW(wR, wC, ${h}, d2),
getW(wR, wC, ${h} + 1, d2)
);
if (${m}) {
vec2 xValues = vec2(
getX(batch, xR, xC, ${h}),
getX(batch, xR, xC, ${h} + 1)
);
dotProd += dot(xValues, wValues);
} else {
vec2 xValues = vec2(
getX(batch, ${h}, xR, xC),
getX(batch, ${h} + 1, xR, xC)
);
dotProd += dot(xValues, wValues);
}
} else if (${f===3}) {
vec3 wValues = vec3(
getW(wR, wC, ${h}, d2),
getW(wR, wC, ${h} + 1, d2),
getW(wR, wC, ${h} + 2, d2)
);
if (${m}) {
vec3 xValues = vec3(
getX(batch, xR, xC, ${h}),
getX(batch, xR, xC, ${h} + 1),
getX(batch, xR, xC, ${h} + 2)
);
dotProd += dot(xValues, wValues);
} else {
vec3 xValues = vec3(
getX(batch, ${h}, xR, xC),
getX(batch, ${h} + 1, xR, xC),
getX(batch, ${h} + 2, xR, xC)
);
dotProd += dot(xValues, wValues);
}
}
}
}
float result = dotProd;
${w}
${b}
setOutput(result);
}
`}},xj=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,a=e.padInfo.top,n=e.padInfo.left,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,p=e.filterDepth,c=e.filterHeight,d=e.filterWidth,h=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
const ivec3 strides = ivec3(${r}, ${s}, ${i});
const ivec3 pads = ivec3(${t}, ${a}, ${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 < ${p}; wF++) {
int xF = xFCorner + wF * ${o};
if (xF < 0 || xF >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${c}; wR++) {
int xR = xRCorner + wR * ${l};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${d}; wC++) {
int xC = xCCorner + wC * ${u};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${h}; d1 += 4) {
vec4 xValues = vec4(
getX(batch, xF, xR, xC, d1),
getX(batch, xF, xR, xC, d1 + 1),
getX(batch, xF, xR, xC, d1 + 2),
getX(batch, xF, xR, xC, d1 + 3)
);
vec4 wValues = vec4(
getW(wF, wR, wC, d1, d2),
getW(wF, wR, wC, d1 + 1, d2),
getW(wF, wR, wC, d1 + 2, d2),
getW(wF, wR, wC, d1 + 3, d2)
);
dotProd += dot(xValues, wValues);
}
if (${f===1}) {
dotProd +=
getX(batch, xF, xR, xC, ${h}) *
getW(wF, wR, wC, ${h}, d2);
} else if (${f===2}) {
vec2 xValues = vec2(
getX(batch, xF, xR, xC, ${h}),
getX(batch, xF, xR, xC, ${h} + 1)
);
vec2 wValues = vec2(
getW(wF, wR, wC, ${h}, d2),
getW(wF, wR, wC, ${h} + 1, d2)
);
dotProd += dot(xValues, wValues);
} else if (${f===3}) {
vec3 xValues = vec3(
getX(batch, xF, xR, xC, ${h}),
getX(batch, xF, xR, xC, ${h} + 1),
getX(batch, xF, xR, xC, ${h} + 2)
);
vec3 wValues = vec3(
getW(wF, wR, wC, ${h}, d2),
getW(wF, wR, wC, ${h} + 1, d2),
getW(wF, wR, wC, ${h} + 2, d2)
);
dotProd += dot(xValues, wValues);
}
}
}
}
setOutput(dotProd);
}
`}},nv=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=Na(this.outputShape.length);let s=e.padInfo.left,i=e.strideWidth,o=e.dilationWidth,l=e.filterHeight,u=e.filterWidth,p=u,c=`
int xR; int xC; int xCOffset;
vec4 wTexel; vec4 previous; vec4 final;`;for(let m=0;m<u;m++)c+=`
vec4 xTexelC${m*2};
int xTexelC${m*2}Ready;
vec4 xTexelC${m*2+1};
int xTexelC${m*2+1}Ready;
vec4 xC${m};`;c+=`
for (int r = 0; r < ${l}; r++) {
for (int d1 = 0; d1 < ${e.inChannels}; d1 += 2) {
`;for(let m=0;m<u;m++)c+=`
xTexelC${m*2} = vec4(0.0);
xTexelC${m*2}Ready = 0;
xTexelC${m*2+1} = vec4(0.0);
xTexelC${m*2+1}Ready = 0;
xC${m} = vec4(0.0);`;c+=`
xR = xRCorner + r * dilations[0];
if (xR >=0 && xR < inDims[0]) {
`;for(let m=0;m<(p+1)/2;m++){let g=m*2;if(c+=`
xC = xCCorner + ${g*o};
`,i===1){if(g<u&&(s%2===1?(c+=`
xCOffset = xC + 1;
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
xTexelC${g} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g}.zw = vec2(0.0);
}
xTexelC${g}Ready = 1;
}
`,o===1&&g>0?c+=`
xC${g} = vec4(xTexelC${g-2}.zw, xTexelC${g}.xy);
`:c+=`
xCOffset = xC + 1 - 2;
if (xCOffset >= 0 && xCOffset < inDims[1]) {
previous = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
previous.zw = vec2(0.0);
}
xC${g} = vec4(previous.zw, xTexelC${g}.xy);
} else {
xC${g} = vec4(0.0, 0.0, xTexelC${g}.xy);
}
`):c+=`
if (xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) {
xTexelC${g} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${g}.zw = vec2(0.0);
}
xTexelC${g}Ready = 1;
}
xC${g} = xTexelC${g};
`,g+1<u)){let x=s%2===0?v.nearestLargerEven(o):o;o%2===0&&s%2===1||o%2!==0&&s%2!==1?(c+=`
xCOffset = xC + imod(pads[1], 2) + ${x};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.0);
}
xTexelC${g+1}Ready = 1;
}
`,o>1?c+=`
xCOffset -= 2;
if (xCOffset >= 0 && xCOffset < inDims[1]) {
previous = getX(batch, xR, xCOffset, d1);
xC${g+1} = vec4(previous.zw, xTexelC${g+1}.xy);
} else {
xC${g+1} = vec4(0.0, 0.0, xTexelC${g+1}.xy);
}
`:c+=`
xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.xy);
`):x===1?c+=`
xC${g+1} = xTexelC${g};
`:c+=`
xCOffset = xC + ${x};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.0);
}
xTexelC${g+1}Ready = 1;
}
xC${g+1} = xTexelC${g+1};
`}}else g<u&&(s%2===1?(c+=`
xCOffset = xC + 1 - strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
xTexelC${g} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g}.zw = vec2(0.0);
}
xTexelC${g}Ready = 1;
}
if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xC + 1, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xC + 2 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.0);
}
xTexelC${g+1}Ready = 1;
}
xC${g} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw);
`,g+1<u&&(c+=`
final = vec4(0.0);
xCOffset = xC + 1 + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1]) {
final = getX(batch, xR, xCOffset, d1);
}
xC${g+1} = vec4(xTexelC${g+1}.xy, final.xy);
`)):(c+=`
if(xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) {
xTexelC${g} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${g}.zw = vec2(0.0);
}
xTexelC${g}Ready = 1;
}
xCOffset = xC + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.);
}
xTexelC${g+1}Ready = 1;
}
xC${g} = vec4(
xTexelC${g}.xy, xTexelC${g+1}.xy);
`,g+1<u&&(c+=`
xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw);
`)));g<u&&(c+=`
wTexel = getW(r, ${g}, d1, d2);
dotProd += xC${g}.xxzz * vec4(wTexel.xy, wTexel.xy);
if(d1 + 1 < ${e.inChannels}) {
dotProd += xC${g}.yyww * vec4(wTexel.zw, wTexel.zw);
}
`,g+1<u&&(c+=`
wTexel = getW(r, ${g+1}, d1, d2);
dotProd += xC${g+1}.xxzz * vec4(wTexel.xy, wTexel.xy);
if(d1 + 1 < ${e.inChannels}) {
dotProd += xC${g+1}.yyww * vec4(wTexel.zw, wTexel.zw);
}
`))}c+=`
}
`,c+=`
}
`,c+=`
}
`;let d="",h="";a&&(n?d=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${a}
}`:r?d=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${a}
}`:d=`vec4 activation(vec4 x) {
${a}
}`,h="result = activation(result);");let f=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),r&&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);
${c}
vec4 result = dotProd - vec4(0.000000000000001);
${f}
${h}
setOutput(result);
}
`}},Aj=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=Na(this.outputShape.length);let{dataFormat:a}=t,n=Ca(),r=a==="channelsLast",s=r?1:2,i=r?2:3,o=this.enableShapeUniforms?"if(blockIndex < outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${e[2]} && pos < ${e[1]}) {`,l="";for(let u=0;u<=1;u++)for(let p=0;p<=1;p++)l+=`
blockIndex = rc.z + ${p};
pos = rc.y + ${u};
${o}
offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];
d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);
if(d0 < inputShape[${s}] && d0 >= 0) {
// Use custom imod instead mod. On Intel GPU, mod may generate
// unexpected value.
// https://github.com/tensorflow/tfjs/issues/5447
offsetX = imod(blockIndex, outWidth) * stride[1] - pad[1];
d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) /
inChannels);
if(d1 < inputShape[${i}] && d1 >= 0) {
ch = imod(pos, inChannels);
if (${r}) {
innerDims = vec2(d1, ch);
result[${u*2+p}] = getChannel(
getA(rc.x, d0, int(innerDims.x),
int(innerDims.y)), innerDims);
} else {
innerDims = vec2(d0, d1);
result[${u*2+p}] = getChannel(
getA(rc.x, ch, int(innerDims.x),
int(innerDims.y)), innerDims);
}
}
}
}
`;this.userCode=`
void main() {
ivec3 rc = getOutputCoords();
vec4 result = vec4(0);
int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
vec2 innerDims;
${l}
${n.output} = result;
}
`}};function zc(e,t){let a=e.length;return a>=3?t?[...e.slice(0,-3),e[a-3]*e[a-2],e[a-1]]:[...e.slice(0,-3),e[a-3],e[a-2]*e[a-1]]:!t&&a===1&&e[0]>1?[e[0],1]:null}function rv({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,u=n.texData.get(e.dataId),p=a.inChannels,c=l[0]*l[1]*l[2],d=a.outChannels,h=a.dataFormat==="channelsLast",f=!1,m=!1,g,x=[];if(s!=null){let A=zc(s.shape,h);A!=null&&(s=ce({inputs:{x:s},backend:n,attrs:{shape:A}}),x.push(s))}if(r!=null){let A=zc(r.shape,h);A!=null&&(r=ce({inputs:{x:r},backend:n,attrs:{shape:A}}),x.push(r))}if(!((c===1||d===1)&&p>Z6)&&u.isPacked&&h&&u.texture!=null&&l[2]%2!==0&&v.arraysEqual(u.shape.slice(-3),l.slice(-3))){let A=l[0]*l[1]*(l[2]+1),y={dataId:e.dataId,shape:[1,A,a.inChannels],dtype:e.dtype},b=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(md(u.shape,y.shape),()=>`packed reshape ${u.shape} to ${y.shape} isn't free`);let w=ce({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}});x.push(w);let S=Dc({a:y,b:w,backend:n,transposeA:f,transposeB:m,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),C=n.texData.get(S.dataId);v.assert(C.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=b,C.shape=a.outShape,g=Za({inputs:{x:S},backend:n}),g.shape=a.outShape,x.push(S)}else{let A=a.outHeight*a.outWidth,y=ce({inputs:{x:e},backend:n,attrs:{shape:h?[a.batchSize,A,a.inChannels]:[a.batchSize,a.inChannels,A]}}),b=ce({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}}),w=Dc({a:h?y:b,b:h?b:y,transposeA:!h,transposeB:m,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i});g=ce({inputs:{x:w},backend:n,attrs:{shape:a.outShape}}),x.push(y),x.push(b),x.push(w)}for(let A of x)n.disposeIntermediateTensorInfo(A);return g}function sv({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:p,outWidth:c,outHeight:d,dataFormat:h}=a,f=h==="channelsLast",m=l*u*p,g=d*c,x=[a.batchSize,m,g],A=!0,y=!1,b=[];if(s!=null){let j=zc(s.shape,f);j!=null&&(s=ce({inputs:{x:s},backend:n,attrs:{shape:j}}),b.push(s))}if(r!=null){let j=zc(r.shape,f);j!=null&&(r=ce({inputs:{x:r},backend:n,attrs:{shape:j}}),b.push(r))}let w=ce({inputs:{x:t},backend:n,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(w);let S=new Aj(x,a),C=[e.shape,[a.padInfo.top,a.padInfo.left],[a.strideHeight,a.strideWidth],[a.dilationHeight,a.dilationWidth],[a.inChannels],[a.filterWidth*a.inChannels],[a.outWidth]],E=n.runWebGLProgram(S,[e],"float32",C),_=ce({inputs:{x:E},backend:n,attrs:{shape:x}});b.push(E),b.push(_);let $=r!=null,M=s!=null,I=o==="leakyrelu",N=o?gd(o,!0):null,O=new K6(f?_.shape:w.shape,f?w.shape:_.shape,f?[a.batchSize,g,a.outChannels]:[a.batchSize,a.outChannels,g],A,y,$,N,M,I),L=f?[_,w]:[w,_];if(r&&L.push(r),M&&L.push(s),I){let j=n.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));L.push(j),b.push(j)}let B=n.runWebGLProgram(O,L,"float32"),G=ce({inputs:{x:B},backend:n,attrs:{shape:a.outShape}});b.push(B);for(let j of b)n.disposeIntermediateTensorInfo(j);return G}function yj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:p}=n,c=T.convertConv2DDataFormat(l),d=T.computeConv2DInfo(r.shape,s.shape,i,u,o,p,!1,c),h;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))h=rv({x:r,filter:s,convInfo:d,backend:a});else if(d.strideWidth<=2&&c==="channelsLast"&&W().getBool("WEBGL_EXP_CONV")){let m=new nv(d),g=[[d.padInfo.top,d.padInfo.left],[d.strideHeight,d.strideWidth],[d.dilationHeight,d.dilationWidth],[d.inHeight,d.inWidth]];h=a.runWebGLProgram(m,[r,s],"float32",g)}else if(W().getBool("WEBGL_CONV_IM2COL"))h=sv({x:r,filter:s,convInfo:d,backend:a});else{let m=new av(d);h=a.runWebGLProgram(m,[r,s],"float32")}let f=ce({inputs:{x:h},backend:a,attrs:{shape:d.outShape}});return a.disposeIntermediateTensorInfo(h),f}var bj={kernelName:ni,backendName:"webgl",kernelFunc:yj},vj=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,a=e.strideWidth,n=e.padInfo.top,r=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int wR = coords.x;
int wC = coords.y;
int d1 = coords.z;
int d2 = coords.w;
// Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int b = 0; b < ${e.batchSize}; b++) {
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${t} - ${n};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${a} - ${r};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
if (${s}) {
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);
}
`}},wj=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,a=e.filterWidth,n=e.strideHeight,r=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=a-1-e.padInfo.left,l=s?1:2,u=s?2:3,p=s?3:1;this.userCode=`
const ivec2 pads = ivec2(${i}, ${o});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[${p}];
ivec2 dyCorner = ivec2(coords[${l}], coords[${u}]) - 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 < ${a}; wC++) {
float dyC = float(dyCCorner + wC) / ${r}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${a} - 1 - wC;
for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
if (${s}) {
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
} else {
float xValue = getDy(batch, d2, idyR, idyC);
float wValue = getW(wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
}
}
}
}
setOutput(dotProd);
}
`}},kj=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,a=e.strideHeight,n=e.strideWidth,r=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
void main() {
ivec5 coords = getOutputCoords();
int wF = coords.x;
int wR = coords.y;
int wC = coords.z;
int d1 = coords.w;
int d2 = coords.u;
float dotProd = 0.0;
for (int b = 0; b < ${e.batchSize}; b++) {
for (int yF = 0; yF < ${e.outDepth}; yF++) {
int xF = wF + yF * ${t} - ${r};
if (xF < 0 || xF >= ${e.inDepth}) {
continue;
}
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${a} - ${s};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${n} - ${i};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yF, yR, yC, d2);
float xValue = getX(b, xF, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},Ij=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,a=e.filterHeight,n=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=a-1-e.padInfo.top,u=n-1-e.padInfo.left;this.userCode=`
const ivec3 pads = ivec3(${o}, ${l}, ${u});
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) / ${r}.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 < ${a}; wR++) {
float dyR = float(dyRCorner + wR) / ${s}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${a} - 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 Sj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:p}=n,c=T.convertConv2DDataFormat(l),d=T.computeConv2DInfo(r.shape,p,i,1,o,u,!1,c),h=new vj(d);return a.runWebGLProgram(h,[r,s],"float32")}var Tj={kernelName:Xc,backendName:"webgl",kernelFunc:Sj};function Cj(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=n,c=T.convertConv2DDataFormat(u),d=T.computeConv2DInfo(i,s.shape,o,1,l,p,!1,c),h=new wj(d);return a.runWebGLProgram(h,[r,s],"float32")}var Nj={kernelName:ri,backendName:"webgl",kernelFunc:Cj};function Ej(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=T.computeConv3DInfo(r.shape,s.shape,i,l,o),p=new xj(u);return a.runWebGLProgram(p,[r,s],"float32")}var Rj={kernelName:Kc,backendName:"webgl",kernelFunc:Ej};function Mj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=n,u=T.computeConv3DInfo(r.shape,l,i,1,o),p=new kj(u);return a.runWebGLProgram(p,[r,s],"float32")}var $j={kernelName:H1,backendName:"webgl",kernelFunc:Mj};function _j(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=n,u=T.computeConv3DInfo(l,s.shape,o,1,i),p=new Ij(u);return a.runWebGLProgram(p,[r,s],"float32")}var Pj={kernelName:Zc,backendName:"webgl",kernelFunc:_j},Fj=mu+`
return cos(x);
`,Oj=Qe({opSnippet:Fj}),Dj={kernelName:si,backendName:"webgl",kernelFunc:Oj},zj=`
float e2x = exp(-x);
return (e2x + 1.0 / e2x) / 2.0;
`,Lj=Qe({opSnippet:zj}),Bj={kernelName:ii,backendName:"webgl",kernelFunc:Lj},Wj=class{constructor(e,t,a,n,r){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[p,c]=a;this.outputShape=[u,p,c,l];let d=n==="bilinear"?1:0,[h,f]=[`${i-1}.0`,`${o-1}.0`],[m,g,x]=p>1?[`${(i-1)/(p-1)}`,"(y2-y1) * height_ratio",`y1*${h} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${h}`],[A,y,b]=c>1?[`${(o-1)/(c-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
const float height_ratio = float(${m});
const float width_ratio = float(${A});
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int y = coords[1];
int x = coords[2];
int d = coords[3];
// get box vals
float y1 = getBoxes(b,0);
float x1 = getBoxes(b,1);
float y2 = getBoxes(b,2);
float x2 = getBoxes(b,3);
// get image in batch index
int bInd = round(getBoxInd(b));
if(bInd < 0 || bInd >= ${s}) {
return;
}
float height_scale = ${g};
float width_scale = ${y};
float in_y = ${x};
if( in_y < 0.0 || in_y > ${h} ) {
setOutput(float(${r}));
return;
}
float in_x = ${b};
if( in_x < 0.0 || in_x > ${f} ) {
setOutput(float(${r}));
return;
}
vec2 sourceFracIndexCR = vec2(in_x,in_y);
if(${d} == 1) {
// Compute the four integer indices.
ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
float top = topLeft + (topRight - topLeft) * fracCR.x;
float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
float newValue = top + (bottom - top) * fracCR.y;
setOutput(newValue);
} else {
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestCR = ivec2(floor(
sourceFracIndexCR + vec2(0.5,0.5)));
float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
setOutput(newValue);
}
}
`}},Vj=e=>{let{inputs:t,backend:a,attrs:n}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,p=new Wj(r.shape,s.shape,o,l,u);return a.runWebGLProgram(p,[r,s,i],"float32")},Uj={kernelName:ui,backendName:"webgl",kernelFunc:Vj},Ad;(function(e){e.Prod="*",e.Sum="+"})(Ad||(Ad={}));var Tx=class{constructor(e,t,a,n){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let r=this.outputShape.length,s=this.op===Ad.Prod?"1.0":"0.0",i=a?s:`getX(${Cx(r,"coords",this.op)})`,o=this.outputShape[this.outputShape.length-1],l="",u="";a?(l=n?`end != ${o-1}`:"end != 0",u=n?"end + 1":"end - 1"):(l=n?`end + pow2 < ${o}`:"end >= pow2",u=n?"end + pow2":"end - pow2"),this.userCode=`
void main() {
${gt(r)} coords = getOutputCoords();
int end = ${Nx(r,"coords",this.op)};
float val = ${i};
int pow2 = int(pow(2.0, index));
if (${l}) {
int idx = ${u};
${Nx(r,"coords",this.op)} = idx;
val ${this.op}= getX(${Cx(r,"coords",this.op)});
}
setOutput(val);
}
`}};function Cx(e,t,a){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw new Error(`Cumulative ${a} for rank ${e} is not yet supported`)}function Nx(e,t,a){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw new Error(`Cumulative ${a} for rank ${e} is not yet supported`)}function iv(e,t,a,n,r,s){let i=t.shape.length,o=T.getAxesPermutation([n],i),l=t;o!=null&&(l=Ia({inputs:{x:t},backend:a,attrs:{perm:o}}));let u=T.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let p=l.shape[u],c=Za({inputs:{x:l},backend:a});for(let d=0;d<=Math.ceil(Math.log2(p))-1;d++){let h=new Tx(e,l.shape,!1,s),f=[[d]],m=c;c=a.runWebGLProgram(h,[c],c.dtype,f),a.disposeIntermediateTensorInfo(m)}if(r){let d=new Tx(e,l.shape,r,s),h=c;c=a.runWebGLProgram(d,[c],c.dtype),a.disposeIntermediateTensorInfo(h)}if(o!=null){let d=T.getUndoAxesPermutation(o),h=Ia({inputs:{x:c},backend:a,attrs:{perm:d}});return a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(l),h}return c}function Gj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return iv(Ad.Prod,r,a,s,i,o)}var Hj={kernelName:oi,backendName:"webgl",kernelFunc:Gj};function jj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return iv(Ad.Sum,r,a,s,i,o)}var qj={kernelName:li,backendName:"webgl",kernelFunc:jj};function Xj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n;if(r.shape.length===1){let l=a.readSync(r.dataId),u=a.readSync(s.dataId),p=L6(l,u,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=a.bufferSync(r),u=a.bufferSync(s),p=rU(l,u,i,o);return a.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var Kj={kernelName:Td,backendName:"webgl",kernelFunc:Xj},Zj=class{constructor(e,t,a){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=a,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 Yj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockSize:s,dataFormat:i}=n,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],c=l*s,d=u*s,h=p/(s*s),f=i==="NHWC"?[o,c,d,h]:[o,h,c,d],m=new Zj(f,s,i);return a.runWebGLProgram(m,[r],r.dtype)}var Jj={kernelName:di,backendName:"webgl",kernelFunc:Yj},ov=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=Na(this.outputShape.length);let s=e.filterHeight,i=e.filterWidth,o=e.outChannels/e.inChannels,l="",u="";a&&(n?l=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${a}
}`:r?l=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${a}
}`:l=`
float activation(float x) {
${a}
}
`,u="result = activation(result);");let p=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${l}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
ivec2 xRCCorner = coords.yz * strides - pads;
int d2 = coords.w;
int d1 = d2 / ${o};
int q = d2 - d1 * ${o};
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
// TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.
for (int wR = 0; wR < ${s}; wR++) {
int xR = xRCorner + wR * dilations[0];
if (xR < 0 || xR >= inDims[0]) {
continue;
}
for (int wC = 0; wC < ${i}; wC++) {
int xC = xCCorner + wC * dilations[1];
if (xC < 0 || xC >= inDims[1]) {
continue;
}
float xVal = getX(batch, xR, xC, d1);
float wVal = getW(wR, wC, d1, q);
dotProd += xVal * wVal;
}
}
float result = dotProd;
${p}
${u}
setOutput(result);
}
`}},lv=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=Na(this.outputShape.length);let s=e.outChannels/e.inChannels,i=e.padInfo.left,o=e.strideWidth,l=e.dilationWidth,u=e.filterHeight,p=e.filterWidth,c=p,d=`
int xR; int xC; int xCOffset;
vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g<p;g++)d+=`
vec4 xTexelC${g*2};
int xTexelC${g*2}Ready;
vec4 xTexelC${g*2+1};
int xTexelC${g*2+1}Ready;
vec4 xC${g};`;d+=`
for (int r = 0; r < ${u}; r++) {
`;for(let g=0;g<p;g++)d+=`
xTexelC${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);`;d+=`
xR = xRCorner + r * dilations[0];
if (xR >=0 && xR < inDims[0]) {
`;for(let g=0;g<(c+1)/2;g++){let x=g*2;if(d+=`
xC = xCCorner + ${x*l};
`,o===1){if(x<p&&(i%2===1?(d+=`
xCOffset = xC + 1;
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${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${x}Ready = 1;
}
`,l===1&&x>0?d+=`
xC${x} = vec4(xTexelC${x-2}.zw, xTexelC${x}.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${x} = vec4(previous.zw, xTexelC${x}.xy);
} else {
xC${x} = vec4(0.0, 0.0, xTexelC${x}.xy);
}
`):d+=`
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<p)){let A=i%2===0?v.nearestLargerEven(l):l;l%2===0&&i%2===1||l%2!==0&&i%2!==1?(d+=`
xCOffset = xC + imod(pads[1], 2) + ${A};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${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${x+1}Ready = 1;
}
`,l>1?d+=`
xCOffset -= 2;
if (xCOffset >= 0 && xCOffset < inDims[1]) {
previous = getX(batch, xR, xCOffset, d1);
xC${x+1} = vec4(previous.zw, xTexelC${x+1}.xy);
} else {
xC${x+1} = vec4(0.0, 0.0, xTexelC${x+1}.xy);
}
`:d+=`
xC${x+1} = vec4(xTexelC${x}.zw, xTexelC${x+1}.xy);
`):A===1?d+=`
xC${x+1} = xTexelC${x};
`:d+=`
xCOffset = xC + ${A};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${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${x+1};
`}}else x<p&&(i%2===1?(d+=`
xCOffset = xC + 1 - strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${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<p&&(d+=`
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);
`)):(d+=`
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${x+1}.xy);
`,x+1<p&&(d+=`
xC${x+1} = vec4(xTexelC${x}.zw, xTexelC${x+1}.zw);
`)));x<p&&(d+=`
wTexel = getW(r, ${x}, d1, q);
dotProd += xC${x} * vec4(wTexel.xz, wTexel.xz);
`,x+1<p&&(d+=`
wTexel = getW(r, ${x+1}, d1, q);
dotProd += xC${x+1} * vec4(wTexel.xz, wTexel.xz);
`))}d+=`
}
`,d+=`
}
`;let h="",f="";a&&(n?h=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${a}
}`:r?h=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${a}
}`:h=`vec4 activation(vec4 x) {
${a}
}`,f="result = activation(result);");let m=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${h}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
ivec2 xRCCorner = coords.yz * strides - pads;
int d2 = coords.w;
int d1 = d2 / ${s};
int q = d2 - d1 * ${s};
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
//intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
vec4 dotProd = vec4(0.000000000000001);
${d}
vec4 result = dotProd - vec4(0.000000000000001);
${m}
${f}
setOutput(result);
}
`}};function Qj(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=n,p=l;p==null&&(p=[1,1]),v.assert(T.eitherStridesOrDilationsAreOne(i,p),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${p}'`);let c=T.computeConv2DInfo(r.shape,s.shape,i,p,o,u,!0),d;W().getBool("WEBGL_PACK_DEPTHWISECONV")&&c.strideWidth<=2&&c.outChannels/c.inChannels===1?d=new lv(c):d=new ov(c);let h=[[c.padInfo.top,c.padInfo.left],[c.strideHeight,c.strideWidth],[c.dilationHeight,c.dilationWidth],[c.inHeight,c.inWidth]];return a.runWebGLProgram(d,[r,s],"float32",h)}var eq={kernelName:pi,backendName:"webgl",kernelFunc:Qj},tq=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,a=e.strideWidth,n=e.padInfo.top,r=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int wR = coords.x;
int wC = coords.y;
int d1 = coords.z;
int dm = coords.w;
int d2 = d1 * ${s} + dm;
float dotProd = 0.0;
// TO DO: Vec4 over the batch size
for (int b = 0; b < ${e.batchSize}; b++) {
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${t} - ${n};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${a} - ${r};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
setOutput(dotProd);
}
`}},aq=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,a=e.filterWidth,n=e.strideHeight,r=e.strideWidth,s=t-1-e.padInfo.top,i=a-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
const ivec2 pads = ivec2(${s}, ${i});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[3];
ivec2 dyCorner = coords.yz - pads;
int dyRCorner = dyCorner.x;
int dyCCorner = dyCorner.y;
float dotProd = 0.0;
for (int wR = 0; wR < ${t}; wR++) {
float dyR = float(dyRCorner + wR) / ${n}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${t} - 1 - wR;
for (int wC = 0; wC < ${a}; wC++) {
float dyC = float(dyCCorner + wC) / ${r}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${a} - 1 - wC;
// TO DO: Vec4 over the channelMul
for (int dm = 0; dm < ${o}; dm++) {
int d2 = d1 * ${o} + dm;
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, dm);
dotProd += xValue * wValue;
}
}
}
setOutput(dotProd);
}
`}};function nq(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:p}=n,c=T.computeConv2DInfo(r.shape,p,i,o,l,u,!0),d=new tq(c);return a.runWebGLProgram(d,[r,s],"float32")}var rq={kernelName:Yc,backendName:"webgl",kernelFunc:nq};function sq(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:p}=n,c=T.computeConv2DInfo(p,s.shape,i,o,l,u,!0),d=new aq(c);return a.runWebGLProgram(d,[r,s],"float32")}var iq={kernelName:Jc,backendName:"webgl",kernelFunc:sq},oq=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
setOutput(val);
}
`}};function lq(e){let{inputs:t,backend:a}=e,{x:n}=t,r=[...n.shape,...n.shape],s=v.sizeFromShape(n.shape),i=ce({inputs:{x:n},backend:a,attrs:{shape:[s]}}),o=new oq(s),l=a.runWebGLProgram(o,[i],i.dtype),u=ce({inputs:{x:l},backend:a,attrs:{shape:r}});return a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(l),u}var uq={kernelName:Qc,backendName:"webgl",kernelFunc:lq},dq=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:a,padInfo:n,strideHeight:r,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:p,left:c}=n;this.userCode=`
const ivec2 strides = ivec2(${r}, ${s});
const ivec2 pads = ivec2(${p}, ${c});
const float neg_infinity = -3.4e38;
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
int d1 = coords.w;
ivec2 outTopLeftCorner =
coords.yz * strides - pads;
int hBeg = outTopLeftCorner.x;
int wBeg = outTopLeftCorner.y;
float curVal = neg_infinity;
for (int h = 0; h < ${i}; h++) {
int hIn = hBeg + h * ${l};
if (hIn >= 0 && hIn < ${t}) {
for (int w = 0; w < ${o}; w++) {
int wIn = wBeg + w * ${u};
if (wIn >= 0 && wIn < ${a}) {
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 pq(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=T.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),p,c=new dq(u);p=a.runWebGLProgram(c,[r,s],"float32");let d=ce({inputs:{x:p},backend:a,attrs:{shape:u.outShape}});return a.disposeIntermediateTensorInfo(p),d}var cq={kernelName:eh,backendName:"webgl",kernelFunc:pq};function hq(e){let{inputs:t,backend:a,attrs:n}=e,{equation:r}=n,s=t,{allDims:i,summedDims:o,idDims:l}=T.decodeEinsumEquation(r,s.length);T.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:p}=T.getEinsumComputePath(o,l),c=p.length,d=null,h=i.length,f=[];for(let m=0;m<c;++m){for(let g of p[m]){let{permutationIndices:x,expandDims:A}=T.getEinsumPermutation(h,l[g]),y;T.isIdentityPermutation(x)?y=s[g]:(y=Ia({inputs:{x:s[g]},backend:a,attrs:{perm:x}}),f.push(y));let b=y.shape.slice();for(let w=0;w<A.length;++w)b.splice(A[w],0,1);v.arraysEqual(y.shape,b)||(y=ce({inputs:{x:y},backend:a,attrs:{shape:b}}),f.push(y)),d===null?d=y:(d=M3({inputs:{a:y,b:d},backend:a}),f.push(d))}m<c-1&&(u[m]>=0&&(d=zh({inputs:{x:d},backend:a,attrs:{axis:u[m]-(i.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&a.disposeIntermediateTensorInfo(m);return d}var fq={kernelName:Cd,backendName:"webgl",kernelFunc:hq},mq="return (x >= 0.0) ? x : (exp(x) - 1.0);",gq=`
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;
`,xq=Qe({opSnippet:mq,packedOpSnippet:gq}),Aq={kernelName:hi,backendName:"webgl",kernelFunc:xq},yq="return (b >= 1.0) ? a : a * (b + 1.0);",bq=`
vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,vq=e=>{let{inputs:t,backend:a}=e,{dy:n,y:r}=t,s=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new cp(bq,n.shape,r.shape):new Al(yq,n.shape,r.shape);return a.runWebGLProgram(s,[n,r],n.dtype)},wq={kernelName:j1,backendName:"webgl",kernelFunc:vq},kq=`
return vec4(equal(a, b));
`,Iq="return float(a == b);",Sq=oa({opSnippet:Iq,packedOpSnippet:kq,dtype:"bool",cpuKernelImpl:lU}),Tq={kernelName:fi,backendName:"webgl",kernelFunc:Sq},Cq=`
// Error function is calculated approximately with elementary function.
// See "Handbook of Mathematical Functions with Formulas,
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
float p = ${T.ERF_P};
float a1 = ${T.ERF_A1};
float a2 = ${T.ERF_A2};
float a3 = ${T.ERF_A3};
float a4 = ${T.ERF_A4};
float a5 = ${T.ERF_A5};
float sign = sign(x);
x = abs(x);
float t = 1.0 / (1.0 + p * x);
return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,Nq=Qe({opSnippet:Cq}),Eq={kernelName:$l,backendName:"webgl",kernelFunc:Nq},Rq=mu+`
return exp(x);
`,Mq=`
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;
`,uv=Qe({opSnippet:Rq,packedOpSnippet:Mq,cpuKernelImpl:uU,dtype:"float32"}),$q={kernelName:mi,backendName:"webgl",kernelFunc:uv};function N1(e){let{inputs:t,attrs:a,backend:n}=e,{dim:r}=a,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=r;return r<0&&(v.assert(-(i+1)<=r,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+r+1),o.splice(l,0,1),ce({inputs:{x:s},backend:n,attrs:{shape:o}})}var _q={kernelName:_l,backendName:"webgl",kernelFunc:N1},Ex="return exp(x) - 1.0;",Pq=Qe({opSnippet:Ex,packedOpSnippet:Ex,cpuKernelImpl:dU}),Fq={kernelName:Pl,backendName:"webgl",kernelFunc:Pq},Rx=class{constructor(e,t,a){this.variableNames=["real","imag"];let n=t[1];this.outputShape=t;let r=a?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=a?`${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 = ${r};
float unaryOpComplex(float real, float expR, float imag, float expI) {
${i}
}
float mulMatDFT(int batch, int index) {
float indexRatio = float(index) / float(${n});
float exponentMultiplierTimesIndexRatio =
exponentMultiplier * indexRatio;
float result = 0.0;
for (int i = 0; i < ${n}; i++) {
// x = (-2|2 * PI / N) * index * i;
float x = exponentMultiplierTimesIndexRatio * float(i);
float expR = cos(x);
float expI = sin(x);
float real = getReal(batch, i);
float imag = getImag(batch, i);
result +=
unaryOpComplex(real, expR, imag, expI) / ${s};
}
return result;
}
void main() {
ivec2 coords = getOutputCoords();
setOutput(mulMatDFT(coords[0], coords[1]));
}
`}};function dv(e,t,a){let n=a.texData.get(e.dataId),r=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=r/s,o=ce({inputs:{x:e},backend:a,attrs:{shape:[i,s]}}),l=o.shape,u=new Rx("real",l,t),p=new Rx("imag",l,t),c=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:l},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:l}],d=a.runWebGLProgram(u,c,"float32"),h=a.runWebGLProgram(p,c,"float32"),f=ls({inputs:{real:d,imag:h},backend:a});a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h);let m=ce({inputs:{x:f},backend:a,attrs:{shape:e.shape}});return a.disposeIntermediateTensorInfo(o),a.disposeIntermediateTensorInfo(f),m}function Oq(e){let{inputs:t,backend:a}=e,{input:n}=t;return dv(n,!1,a)}var Dq={kernelName:Nd,backendName:"webgl",kernelFunc:Oq},zq=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 fp(e){let{backend:t,attrs:a}=e,{shape:n,value:r}=a,{dtype:s}=a;if(s=s||v.inferDtype(r),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(n));return i.fill(r),t.makeTensorInfo(n,s,i)}else{let i=new zq(n,r),o=[[r]];return t.runWebGLProgram(i,[],s,o)}}var Lq={kernelName:Fl,backendName:"webgl",kernelFunc:fp},Bq=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 < ${t}) {
outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
} else {
outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
}
setOutput(outputValue);
}
`}},Wq={kernelName:gi,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:a}=e,n=t,r=new Bq(a.shape);return n.runWebGLProgram(r,[a],a.dtype)}},Mx="return floor(x);",Vq=Qe({opSnippet:Mx,packedOpSnippet:Mx,cpuKernelImpl:pU}),Uq={kernelName:xi,backendName:"webgl",kernelFunc:Vq},Gq=`
float s = sign(a) * sign(b);
int ia = round(a);
int ib = round(b);
if (ib != 0) {
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
return float(idiv(ia, ib, s));
} else {
return NAN;
}
`,Hq=`
ivec4 ia = round(a);
ivec4 ib = round(b);
bvec4 cond = notEqual(ib, ivec4(0));
ivec4 result = ivec4(0);
vec4 s = sign(a) * sign(b);
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
if (cond[0]) {
result[0] = idiv(ia[0], ib[0], s[0]);
}
if (cond[1]) {
result[1] = idiv(ia[1], ib[1], s[1]);
}
if (cond[2]) {
result[2] = idiv(ia[2], ib[2], s[2]);
}
if (cond[3]) {
result[3] = idiv(ia[3], ib[3], s[3]);
}
return vec4(result);
`,jq=oa({opSnippet:Gq,packedOpSnippet:Hq,dtype:"int32"}),qq={kernelName:Ai,backendName:"webgl",kernelFunc:jq},Xq=class{constructor(e){this.variableNames=["A"];let t=Ca(),[a,n]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${n}.0, ${a}.0);
vec4 values = ${t.texture2D}(A, uv);
float value;
if (depth == 0) {
value = values.r;
} else if (depth == 1) {
value = values.g;
} else if (depth == 2) {
value = values.b;
} else if (depth == 3) {
value = values.a;
}
setOutput(floor(value * 255.0 + 0.5));
}
`}},Kq=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=Ca(),[a,n]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec4 result = vec4(0.);
for(int row=0; row<=1; row++) {
for(int col=0; col<=1; col++) {
texC = coords[1] + row;
depth = coords[2] + col;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${n}.0, ${a}.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);
}
}
${t.output} = result;
}
`}},Zq={kernelName:rd,backendName:"webgl",kernelFunc:Yq},Zo,Lm=W().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function Yq(e){let{inputs:t,backend:a,attrs:n}=e,{pixels:r}=t,{numChannels:s}=n,i=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,[l,u]=i?[r.videoWidth,r.videoHeight]:[r.width,r.height],p=[u,l],c=[u,l,s];if(o||i){let m=W().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(Zo==null||m!==Lm)&&(Lm=m,Zo=document.createElement("canvas").getContext("2d",{willReadFrequently:Lm})),Zo.canvas.width=l,Zo.canvas.height=u,Zo.drawImage(r,0,0,l,u),r=Zo.canvas}let d=a.makeTensorInfo(p,"int32");a.texData.get(d.dataId).usage=pn.PIXELS,a.gpgpu.uploadPixelDataToTexture(a.getTexture(d.dataId),r);let h=W().getBool("WEBGL_PACK")?new Kq(c):new Xq(c),f=a.runWebGLProgram(h,[d],"int32");return a.disposeData(d.dataId),f}function Jq(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:p,dilations:c,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=n,m=T.convertConv2DDataFormat(p),g=T.computeConv2DInfo(r.shape,s.shape,l,c,u,d,!1,m),x,A=[],y=i!=null,b=o!=null,w=h==="leakyrelu",S=()=>{let E=[r,s],_=($,M)=>{if(M==="NCHW"&&$.shape.length===1&&$.shape[0]!==1){let I=ce({inputs:{x:$},backend:a,attrs:{shape:[$.shape[0],1,1]}});return A.push(I),I}return $};if(y&&E.push(_(i,p)),b&&E.push(_(o,p)),w){let $=a.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));E.push($),A.push($)}return E};if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))x=rv({x:r,filter:s,convInfo:g,backend:a,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:f});else if(g.strideWidth<=2&&m==="channelsLast"&&W().getBool("WEBGL_EXP_CONV")){let E=h?gd(h,!0):null,_=new nv(g,y,E,b,w),$=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],M=S();x=a.runWebGLProgram(_,M,"float32",$)}else if(W().getBool("WEBGL_CONV_IM2COL"))x=sv({x:r,filter:s,convInfo:g,backend:a,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:f});else{let E=h?gd(h,!1):null,_=new av(g,y,E,b,w),$=S();x=a.runWebGLProgram(_,$,"float32")}let C=ce({inputs:{x},backend:a,attrs:{shape:g.outShape}});return A.push(x),A.forEach(E=>a.disposeIntermediateTensorInfo(E)),C}var Qq={kernelName:qr,backendName:"webgl",kernelFunc:Jq};function eX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dimRoundingMode:c,activation:d,leakyreluAlpha:h}=n,f=[],m=p;m==null&&(m=[1,1]),v.assert(T.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let g=T.computeConv2DInfo(r.shape,s.shape,l,m,u,c,!0),x=W().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,A=d?gd(d,x):null,y=[r,s],b=i!=null,w=o!=null,S=d==="leakyrelu";if(b&&y.push(i),w&&y.push(o),S){let $=a.makeTensorInfo([],"float32",v.createScalarValue(h,"float32"));y.push($),f.push($)}let C;x?C=new lv(g,b,A,w,S):C=new ov(g,b,A,w,S);let E=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],_=a.runWebGLProgram(C,y,"float32",E);return f.forEach($=>a.disposeIntermediateTensorInfo($)),_}var tX={kernelName:Xr,backendName:"webgl",kernelFunc:eX},aX=class{constructor(e,t,a,n){this.sliceDim=e,this.strides=t,this.paramsShape=n,this.variableNames=["x","indices"],this.outputShape=a;let r=gt(a.length),s=`
int index;`;for(let i=0;i<this.sliceDim;i++)s+=`
index = round(getIndices(coords[0], ${i}));
out_of_bounds = out_of_bounds || index < 0;
out_of_bounds = out_of_bounds || index >= ${this.paramsShape[i]};
flattenIndex += index * ${this.strides[i]};`;this.userCode=`
void main() {
${r} coords = getOutputCoords();
int flattenIndex = 0;
bool out_of_bounds = false;
${s}
setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));
}
`}};function nX(e){let{inputs:t,backend:a}=e,{params:n,indices:r}=t,s=r.shape,i=s[s.length-1],o=v.sizeFromShape(n.shape),[l,u,p,c]=T.prepareAndValidate(n,r),d=ce({inputs:{x:r},backend:a,attrs:{shape:[u,i]}}),h=ce({inputs:{x:n},backend:a,attrs:{shape:[v.sizeFromShape(n.shape)/p,p]}});if(a.shouldExecuteOnCPU([n,r])||n.dtype==="string"){let x=a.readSync(r.dataId),A=a.bufferSync(n),y=cU(x,A,n.dtype,u,i,p,c,n.shape,o);return a.makeTensorInfo(l,n.dtype,y.values)}let f=new aX(i,c,[u,p],n.shape),m=a.runWebGLProgram(f,[h,d],h.dtype),g=ce({inputs:{x:m},backend:a,attrs:{shape:l}});return a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),g}var rX={kernelName:bi,backendName:"webgl",kernelFunc:nX},sX=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let a=gt(this.rank),n=iX(e,2);this.userCode=`
void main() {
${a} 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 iX(e,t){let a=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let r=0;r<e.length;r++)r===2?n.push("index"):n.push(`${a[r]}`);return n.join()}function pv(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,indices:s}=t,{axis:i,batchDims:o}=n,l=v.parseAxisParam(i,r.shape)[0];if(W().get("DEBUG")){let A=a.readSync(s.dataId),y=r.shape[l];for(let b=0;b<A.length;++b){let w=A[b];v.assert(w<=y-1&&w>=0,()=>`GatherV2: the index value ${w} is not in [0, ${y-1}]`)}}let u=T.segment_util.collectGatherOpShapeInfo(r,s,l,o),p=v.sizeFromShape(s.shape),c=[],d=ce({inputs:{x:r},backend:a,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=ce({inputs:{x:s},backend:a,attrs:{shape:[u.batchSize,p/u.batchSize]}});c.push(d),c.push(h);let f=[u.batchSize,u.outerSize,p/u.batchSize,u.sliceSize];if(a.shouldExecuteOnCPU([r,s])||r.dtype==="string"){let A=a.bufferSync(h),y=a.bufferSync(d),b=hU(y,A,f);return c.forEach(w=>a.disposeIntermediateTensorInfo(w)),a.makeTensorInfo(u.outputShape,b.dtype,b.values)}let m=new sX(d.shape,f),g=a.runWebGLProgram(m,[d,h],d.dtype);c.push(g);let x=ce({inputs:{x:g},backend:a,attrs:{shape:u.outputShape}});return c.forEach(A=>a.disposeIntermediateTensorInfo(A)),x}var oX={kernelName:Ol,backendName:"webgl",kernelFunc:pv},lX="return float(a > b);",uX=`
return vec4(greaterThan(a, b));
`,dX=oa({opSnippet:lX,packedOpSnippet:uX,cpuKernelImpl:fU,dtype:"bool"}),pX={kernelName:vi,backendName:"webgl",kernelFunc:dX},cX="return float(a >= b);",hX=`
return vec4(greaterThanEqual(a, b));
`,fX=oa({opSnippet:cX,packedOpSnippet:hX,dtype:"bool",cpuKernelImpl:mU}),mX={kernelName:wi,backendName:"webgl",kernelFunc:fX};function gX(e){let{inputs:t,backend:a}=e,{input:n}=t;return dv(n,!0,a)}var xX={kernelName:Ed,backendName:"webgl",kernelFunc:gX},AX="return float(!isnan(x) && !isinf(x));",yX=Qe({opSnippet:AX,dtype:"bool"}),bX={kernelName:Dl,backendName:"webgl",kernelFunc:yX},vX="return float(isinf(x));",wX=Qe({opSnippet:vX,dtype:"bool"}),kX={kernelName:zl,backendName:"webgl",kernelFunc:wX},IX="return float(isnan(x));",SX=Qe({opSnippet:IX,dtype:"bool"}),TX={kernelName:Ii,backendName:"webgl",kernelFunc:SX},CX="return float(a < b);",NX=`
return vec4(lessThan(a, b));
`,EX=oa({opSnippet:CX,packedOpSnippet:NX,cpuKernelImpl:gU,dtype:"bool"}),RX={kernelName:Ti,backendName:"webgl",kernelFunc:EX},MX="return float(a <= b);",$X=`
return vec4(lessThanEqual(a, b));
`,_X=oa({opSnippet:MX,packedOpSnippet:$X,cpuKernelImpl:xU,dtype:"bool"}),PX={kernelName:Ci,backendName:"webgl",kernelFunc:_X};function FX(e){let{backend:t,attrs:a}=e,{start:n,stop:r,num:s}=a,i=AU(n,r,s);return t.makeTensorInfo([i.length],"float32",i)}var OX={kernelName:th,backendName:"webgl",kernelFunc:FX},DX=mu+`
return x < 0.0 ? 0./0. : log(x);
`,zX=`
vec4 result = log(x);
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : (x.r < 0.0 ? 0./0. : result.r);
result.g = isNaN.g ? x.g : (x.g < 0.0 ? 0./0. : result.g);
result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);
result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);
return result;
`,LX=Qe({opSnippet:DX,packedOpSnippet:zX,cpuKernelImpl:yU}),BX={kernelName:Ni,backendName:"webgl",kernelFunc:LX},WX=mu+`
return log(1.0 + x);
`,VX=Qe({opSnippet:WX}),UX={kernelName:Ll,backendName:"webgl",kernelFunc:VX},GX="return float(a >= 1.0 && b >= 1.0);",HX=`
return vec4(
vec4(greaterThanEqual(a, vec4(1.0))) *
vec4(greaterThanEqual(b, vec4(1.0))));
`,jX=oa({opSnippet:GX,packedOpSnippet:HX,dtype:"bool"}),qX={kernelName:Ei,backendName:"webgl",kernelFunc:jX},XX="return float(!(x >= 1.0));",KX=Qe({opSnippet:XX}),ZX={kernelName:Ri,backendName:"webgl",kernelFunc:KX},YX="return float(a >= 1.0 || b >= 1.0);",JX=`
return min(
vec4(greaterThanEqual(a, vec4(1.0))) +
vec4(greaterThanEqual(b, vec4(1.0))),
vec4(1.0));
`,QX=oa({opSnippet:YX,packedOpSnippet:JX,dtype:"bool"}),eK={kernelName:Bl,backendName:"webgl",kernelFunc:QX},tK=class{constructor(e,t,a,n,r){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${a}) + float(${n}) * sum`;r===.5?o=`inversesqrt(${l})`:r===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${r}));`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int r = coords[1];
int c = coords[2];
int d = coords[3];
float x = getX(b, r, c, d);
float sum = 0.0;
for (int j = -${s}; j <= ${s}; j++) {
int idx = d + j;
if (idx >= 0 && idx <= ${i}) {
float z = getX(b, r, c, idx);
sum += z * z;
}
}
float val = x * ${o};
setOutput(val);
}
`}},aK=class{constructor(e,t,a,n,r){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${a}) + float(${n}) * sum`;r===.5?o=`inversesqrt(${l})`:r===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${r}));`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords.x;
int r = coords.y;
int c = coords.z;
int d = coords.w;
bool hasNextCol = d < ${this.outputShape[3]};
bool hasNextRow = c < ${this.outputShape[2]};
vec4 sum = vec4(0.);
vec4 xFragAtOutputCoords = getX(b, r, c, d);
vec4 xAtOutputCoords = vec4(
getChannel(xFragAtOutputCoords, vec2(c, d)),
hasNextCol ?
getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,
hasNextRow ?
getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,
(hasNextRow && hasNextCol) ?
getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0
);
int firstChannel = d - ${s};
vec2 cache = vec2(0.);
if(firstChannel >= 0){
vec4 firstChannelFrag = getX(b, r, c, firstChannel);
cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));
if(hasNextRow){
cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));
}
}
ivec2 depth = ivec2(d, d + 1);
for (int j = - ${s}; j <= ${s}; j++) {
ivec2 idx = depth + j;
bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${i}));
bool depthInRange = aboveLowerBound.x && belowUpperBound.x;
bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;
if(depthInRange || depthPlusOneInRange){
vec4 z = vec4(0.);
vec4 xFragAtCurrentDepth;
z.xz = cache.xy;
if(depthPlusOneInRange && hasNextCol){
xFragAtCurrentDepth = idx.y != d ?
getX(b, r, c, idx.y) : xFragAtOutputCoords;
z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));
if(hasNextRow){
z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));
}
}
cache.xy = z.yw;
sum += z * z;
}
}
vec4 result = xAtOutputCoords * ${o};
setOutput(result);
}
`}},nK=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n,u=W().getBool("WEBGL_PACK_NORMALIZATION")?new aK(r.shape,s,i,o,l):new tK(r.shape,s,i,o,l);return a.runWebGLProgram(u,[r],r.dtype)},rK={kernelName:ah,backendName:"webgl",kernelFunc:nK},sK=class{constructor(e,t,a,n,r){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=a,this.alpha=n,this.beta=r,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(${a});
for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd){
float dyi = -2.0 * float(${n})
* float(${r})
* getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
/ norm;
if (k == d) {
dyi += pow(norm, -1.0 * ${r});
}
if (k == coords[3]) {
dyi *= getDy(b, r, c, d);
result += dyi;
}
}
else {
break;
}
}
}
setOutput(result);
}
`}},iK=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:p}=n,c=new sK(r.shape,o,l,u,p);return a.runWebGLProgram(c,[r,s,i],r.dtype)},oK={kernelName:q1,backendName:"webgl",kernelFunc:iK};function lK(e,t,a,n){let r=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/r,i=ce({inputs:{x:e},attrs:{shape:[s,r]},backend:n}),o=bo(i,e.dtype,"max",n),l=ce({inputs:{x:o},attrs:{shape:a},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}function cv(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reductionIndices:s,keepDims:i}=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=T.getAxesPermutation(u,o),c=p!=null,d=a.shouldExecuteOnCPU([r]),h=r;if(c){if(d){let A=a.texData.get(h.dataId).values,y=new Array(o);for(let S=0;S<y.length;S++)y[S]=r.shape[p[S]];let b=E3(A,r.shape,r.dtype,p,y);h=a.makeTensorInfo(y,r.dtype);let w=a.texData.get(h.dataId);w.values=b}else h=Dh(r,p,a);u=T.getInnerMostAxes(u.length,o)}T.assertAxesAreInnerMostDims("max",u,o);let[f,m]=T.computeOutAndReduceShapes(h.shape,u),g=f;i&&(g=T.expandShapeToKeepDim(f,l));let x;if(d){let A=a.texData.get(h.dataId).values,y=bU(A,v.sizeFromShape(m),g,r.dtype);x=a.makeTensorInfo(g,r.dtype);let b=a.texData.get(x.dataId);b.values=y}else x=lK(h,m,g,a);return c&&a.disposeIntermediateTensorInfo(h),x}var uK={kernelName:Mi,backendName:"webgl",kernelFunc:cv},dK=R3+`
return max(a, b);
`,pK=`
vec4 result = vec4(max(a, b));
bvec4 isNaNA = isnan(a);
bvec4 isNaNB = isnan(b);
bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
`+pp+`
return result;
`,cK=oa({opSnippet:dK,packedOpSnippet:pK,cpuKernelImpl:vU}),hK={kernelName:$i,backendName:"webgl",kernelFunc:cK};function fK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;uu(r,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(T.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=T.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))return Za({inputs:{x:r},backend:a});let c=new xd(p,"max",!1);return a.runWebGLProgram(c,[r],r.dtype)}var mK={kernelName:_i,backendName:"webgl",kernelFunc:fK};function gK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=n,p=[1,1,1],c=T.computePool3DInfo(r.shape,s,i,p,o,u,l),d=new $3(c,"max",!1);return a.runWebGLProgram(d,[r],r.dtype)}var xK={kernelName:nh,backendName:"webgl",kernelFunc:gK},AK=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,a=e.strideWidth,n=e.dilationHeight,r=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=r-1-e.padInfo.top,o=s-1-e.padInfo.left,l=r*s-1;this.userCode=`
const ivec2 pads = ivec2(${i}, ${o});
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 dyRCCorner = coords.yz - pads;
int dyRCorner = dyRCCorner.x;
int dyCCorner = dyRCCorner.y;
// Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${r};
wR += ${n}) {
float dyR = float(dyRCorner + wR) / ${t}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${s}; wC++) {
float dyC = float(dyCCorner + wC) / ${a}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
int maxPosValue = ${l} - int(getMaxPos(b, idyR, idyC, d));
// Get the current value, check it against the value from the
// position matrix.
int curPosValue = wR * ${s} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
setOutput(dotProd);
}
`}},yK=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,a=e.strideHeight,n=e.strideWidth,r=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,p=o-1-e.padInfo.front,c=l-1-e.padInfo.top,d=u-1-e.padInfo.left,h=o*l*u-1;this.userCode=`
const ivec3 pads = ivec3(${p}, ${c}, ${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 < ${o};
wD += ${r}) {
float dyD = float(dyDCorner + wD) / ${t}.0;
if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
continue;
}
int idyD = int(dyD);
for (int wR = 0; wR < ${l};
wR += ${s}) {
float dyR = float(dyRCorner + wR) / ${a}.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) / ${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 = ${h} -
int(getMaxPos(batch, idyD, idyR, idyC, ch));
// Get the current value, check it against the value from the
// position matrix.
int curPosValue =
wD * ${l} * ${u} +
wR * ${u} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
}
setOutput(dotProd);
}
`}};function bK(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:p}=n,c=[1,1,1],d=T.computePool3DInfo(i.shape,o,l,c,u,p),h=new $3(d,"max",!0),f=a.runWebGLProgram(h,[i],i.dtype),m=new yK(d),g=a.runWebGLProgram(m,[r,f],i.dtype);return a.disposeIntermediateTensorInfo(f),g}var vK={kernelName:K1,backendName:"webgl",kernelFunc:bK};function wK(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s,output:i}=t,o=s;uu([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:p,dimRoundingMode:c}=n,d=T.computePool2DInfo(o.shape,l,u,1,p,c),h=!0,f=new xd(d,"max",h),m=a.runWebGLProgram(f,[o],o.dtype),g=new AK(d),x=a.runWebGLProgram(g,[r,m],o.dtype);return a.disposeIntermediateTensorInfo(m),x}var kK={kernelName:X1,backendName:"webgl",kernelFunc:wK};function IK(e,t,a,n){let r=new xd(a,"max",!1),s=n.runWebGLProgram(r,[e],"float32");r=new xd(a,"max",!0,!0,t);let i=n.runWebGLProgram(r,[e],"float32");return[s,i]}var SK={kernelName:rh,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n}=e,{filterSize:r,strides:s,pad:i,includeBatchInIndex:o}=t,l=a;v.assert(n.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${n.shape.length}.`);let u=[1,1];v.assert(T.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let p=T.computePool2DInfo(n.shape,r,s,u,i),[c,d]=IK(n,o,p,l);return[c,d]}};function TK(e,t,a,n){let r=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/r,i=ce({inputs:{x:e},attrs:{shape:[s,r]},backend:n}),o=bo(i,"float32","mean",n),l=ce({inputs:{x:o},attrs:{shape:a},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}var CK={kernelName:Pi,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n}=e,{keepDims:r,axis:s}=t,i=a,o=n.shape.length,l=v.parseAxisParam(s,n.shape),u=l,p=T.getAxesPermutation(u,o),c=p!=null,d=i.shouldExecuteOnCPU([n]),h=[],f=n;if(c){if(d){let y=i.texData.get(f.dataId).values,b=new Array(o);for(let C=0;C<b.length;C++)b[C]=n.shape[p[C]];let w=E3(y,n.shape,n.dtype,p,b);f=i.makeTensorInfo(b,n.dtype);let S=i.texData.get(f.dataId);S.values=w}else f=Dh(n,p,i);h.push(f),u=T.getInnerMostAxes(u.length,o)}T.assertAxesAreInnerMostDims("sum",u,o);let[m,g]=T.computeOutAndReduceShapes(f.shape,u),x=m;r&&(x=T.expandShapeToKeepDim(m,l));let A=TK(f,g,x,i);for(let y of h)i.disposeIntermediateTensorInfo(y);return A}};function NK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=T.getAxesPermutation(u,o),c=r;p!=null&&(c=Ia({inputs:{x:r},backend:a,attrs:{perm:p}}),u=T.getInnerMostAxes(u.length,r.shape.length)),T.assertAxesAreInnerMostDims("min",u,o);let[d,h]=T.computeOutAndReduceShapes(c.shape,u),f=v.sizeFromShape(h),m=ce({inputs:{x:c},backend:a,attrs:{shape:[-1,f]}}),g=bo(m,m.dtype,"min",a),x;if(i){let A=T.expandShapeToKeepDim(d,l);x=ce({inputs:{x:g},backend:a,attrs:{shape:A}})}else x=ce({inputs:{x:g},backend:a,attrs:{shape:d}});return a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(g),p!=null&&a.disposeIntermediateTensorInfo(c),x}var EK={kernelName:Fi,backendName:"webgl",kernelFunc:NK},RK=R3+`
return min(a, b);
`,MK=`
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);
`+pp+`
return result;
`,$K=oa({opSnippet:RK,packedOpSnippet:MK,cpuKernelImpl:wU}),_K={kernelName:Oi,backendName:"webgl",kernelFunc:$K},PK=class{constructor(e,t,a){this.variableNames=["x"],this.outputShape=t.map((u,p)=>u[0]+e[p]+u[1]);let n=e.length,r=gt(n),s=t.map(u=>u[0]).join(","),i=t.map((u,p)=>u[0]+e[p]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n),l=a==="reflect"?0:1;if(n===1){this.userCode=`
int start = ${s};
int end = ${i};
void main() {
int outC = getOutputCoords();
if (outC < start) {
outC = start * 2 - outC - ${l};
} else if(outC >= end) {
outC = (end - 1) * 2 - outC + ${l};
}
setOutput(getX(outC - start));
}
`;return}this.userCode=`
${r} start = ${r}(${s});
${r} end = ${r}(${i});
void main() {
${r} outC = getOutputCoords();
for (int i = 0; i < ${n}; i++) {
if (outC[i] < start[i]) {
outC[i] = start[i] * 2 - outC[i] - ${l};
} else if(outC[i] >= end[i]) {
outC[i] = (end[i] - 1) * 2 - outC[i] + ${l};
}
}
${r} coords = outC - start;
setOutput(getX(${o}));
}
`}},FK=class{constructor(e,t,a){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((h,f)=>h[0]+e[f]+h[1]);let n=e.length,r=gt(n),s=t.map(h=>h[0]).join(","),i=t.map((h,f)=>h[0]+e[f]).join(","),o=va("rc",n),l=va("source",n),u=`${o[n-1]} < ${this.outputShape[n-1]}`,p=n===1?"source":`vec2(${l.slice(-2).join()})`,c=a==="reflect"?0:1,d="";if(n===1){let h=`
${r} source = rc;
if (source < start) {
source = start * 2 - source - ${c};
} else if (source >= end) {
source = (end - 1) * 2 - source + ${c};
}
source -= start;
`;d=`
${r} rc = outputLoc;
${h}
result[0] = getChannel(getX(${l.join()}), ${p});
${o[n-1]} += 1;
if(${u}) {
${h}
result[1] = getChannel(getX(${l.join()}), ${p});
}
`}else{let h=`
${r} source = rc;
${r} lt = ${r}(lessThan(source, start));
${r} gte = ${r}(greaterThanEqual(source, end));
${r} orig = 1 - (lt + gte);
source = orig * source +
lt * (start * 2 - source - ${c}) +
gte * ((end - 1) * 2 - source + ${c});
source -= start;
`;d=`
${r} rc = outputLoc;
${h}
result[0] = getChannel(getX(${l.join()}), ${p});
${o[n-1]} += 1;
if(${u}) {
${h}
result[1] = getChannel(getX(${l.join()}), ${p});
}
rc = outputLoc;
${o[n-2]} += 1;
if(${o[n-2]} < ${this.outputShape[n-2]}) {
${h}
result[2] = getChannel(getX(${l.join()}), ${p});
${o[n-1]} += 1;
if(${u}) {
${h}
result[3] = getChannel(getX(${l.join()}), ${p});
}
}
`}this.userCode=`
const ${r} start = ${r}(${s});
const ${r} end = ${r}(${i});
void main() {
${r} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${d}
setOutput(result);
}
`}},OK=({inputs:e,backend:t,attrs:a})=>{let{x:n}=e,{paddings:r,mode:s}=a,i=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new FK(n.shape,r,s):new PK(n.shape,r,s);return t.runWebGLProgram(i,[n],n.dtype)},DK={kernelName:Di,backendName:"webgl",kernelFunc:OK},zK=`if (b == 0.0) return NAN;
return mod(a, b);`,LK=`
vec4 result = mod(a, b);
bvec4 isNaN = equal(b, vec4(0.0));
`+pp+`
return result;
`,BK=oa({opSnippet:zK,packedOpSnippet:LK}),WK={kernelName:Wl,backendName:"webgl",kernelFunc:BK},VK=class{constructor(e,t,a){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,a],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}));
}
`}},UK=`
if (a == b) {
return 1.0;
};
return a / b;`,GK=`
// 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;
`,hv=oa({opSnippet:UK,packedOpSnippet:GK,checkOutOfBounds:!0}),HK={kernelName:ci,backendName:"webgl",kernelFunc:hv},$x="return a - b;",fv=oa({opSnippet:$x,packedOpSnippet:$x,supportsComplex:!0,cpuKernelImpl:VU}),jK={kernelName:lo,backendName:"webgl",kernelFunc:fv};function mv(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{dim:s}=n,i=v.parseAxisParam([s],r.shape),o=cv({inputs:{x:r},backend:a,attrs:{reductionIndices:i,keepDims:!1}}),l=T.expandShapeToKeepDim(o.shape,i),u=ce({inputs:{x:o},backend:a,attrs:{shape:l}}),p=fv({inputs:{a:r,b:u},backend:a}),c=uv({inputs:{x:p},backend:a}),d=zh({inputs:{x:c},backend:a,attrs:{axis:i,keepDims:!1}}),h=ce({inputs:{x:d},backend:a,attrs:{shape:l}}),f=hv({inputs:{a:c,b:h},backend:a});return a.disposeIntermediateTensorInfo(o),a.disposeIntermediateTensorInfo(u),a.disposeIntermediateTensorInfo(p),a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),f}var qK={kernelName:so,backendName:"webgl",kernelFunc:mv};function XK(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n,l=o?r:mv({inputs:{logits:r},backend:a,attrs:{dim:r.shape.length-1}}),u=l.shape[0],p=l.shape[1],c=new VK(u,p,s),d=[[i]],h=a.runWebGLProgram(c,[l],"int32",d);return o||a.disposeIntermediateTensorInfo(l),h}var KK={kernelName:sh,backendName:"webgl",kernelFunc:XK},ZK=Cn+`
return -x;
`,YK=`
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 JK(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])){let s=a.texData.get(n.dataId),[i,o]=IU(s.values,n.shape,n.dtype);return a.makeTensorInfo(o,n.dtype,i)}let r;return W().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Vr(n.shape,YK):r=new qn(n.shape,ZK),a.runWebGLProgram(r,[n],n.dtype)}var QK={kernelName:Vl,backendName:"webgl",kernelFunc:JK},eZ=Tn.nonMaxSuppressionV3Impl;function tZ(e){T.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=n,u=a.readSync(r.dataId),p=a.readSync(s.dataId),{selectedIndices:c}=eZ(u,p,i,o,l);return a.makeTensorInfo([c.length],"int32",new Int32Array(c))}var aZ={kernelName:Bi,backendName:"webgl",kernelFunc:tZ},nZ=Tn.nonMaxSuppressionV4Impl;function rZ(e){T.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=n,p=a.readSync(r.dataId),c=a.readSync(s.dataId),{selectedIndices:d,validOutputs:h}=nZ(p,c,i,o,l,u);return[a.makeTensorInfo([d.length],"int32",new Int32Array(d)),a.makeTensorInfo([],"int32",new Int32Array([h]))]}var sZ={kernelName:Ul,backendName:"webgl",kernelFunc:rZ},iZ=Tn.nonMaxSuppressionV5Impl;function oZ(e){T.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=n,p=a.readSync(r.dataId),c=a.readSync(s.dataId),d=i,h=o,f=l,m=u,{selectedIndices:g,selectedScores:x}=iZ(p,c,d,h,f,m);return[a.makeTensorInfo([g.length],"int32",new Int32Array(g)),a.makeTensorInfo([x.length],"float32",new Float32Array(x))]}var lZ={kernelName:Wi,backendName:"webgl",kernelFunc:oZ},uZ=class{constructor(e,t,a,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(${a}),
float(index == coords.y)));
}
`}},dZ=e=>{let{inputs:t,backend:a,attrs:n}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=n,u=v.sizeFromShape(r.shape),p=new uZ(u,i,o,l),c=ce({inputs:{x:r},backend:a,attrs:{shape:[u]}}),d=a.runWebGLProgram(p,[c],s);a.disposeIntermediateTensorInfo(c);let h=[...r.shape,i],f=ce({inputs:{x:d},backend:a,attrs:{shape:h}});return a.disposeIntermediateTensorInfo(d),f},pZ={kernelName:Vi,backendName:"webgl",kernelFunc:dZ};function Lc(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="complex64"){let r=hp({inputs:{input:n},backend:a}),s=Lc({inputs:{x:r},backend:a}),i=Lh({inputs:{input:n},backend:a}),o=Lc({inputs:{x:i},backend:a}),l=ls({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return fp({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:a})}var cZ={kernelName:nu,backendName:"webgl",kernelFunc:Lc};function gv(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(n.dtype==="complex64"){let r=hp({inputs:{input:n},backend:a}),s=gv({inputs:{x:r},backend:a}),i=Lh({inputs:{input:n},backend:a}),o=Lc({inputs:{x:i},backend:a}),l=ls({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return fp({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:a})}var hZ={kernelName:Gl,backendName:"webgl",kernelFunc:gv};function fZ(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return N1({inputs:{input:t[0]},backend:a,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{v.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===p.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(p=>{let c=N1({inputs:{input:p},backend:a,attrs:{dim:r}});return o.push(c),c}),u=tv({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(p=>a.disposeIntermediateTensorInfo(p)),u}var mZ={kernelName:Hl,backendName:"webgl",kernelFunc:fZ},gZ=class{constructor(e,t,a){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let n=e.length,r=gt(n),s=t.map(l=>l[0]).join(","),i=t.map((l,u)=>l[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n);if(n===1){this.userCode=`
int start = ${s};
int end = ${i};
void main() {
int outC = getOutputCoords();
if (outC < start || outC >= end) {
setOutput(value);
} else {
setOutput(getX(outC - start));
}
}
`;return}this.userCode=`
${r} start = ${r}(${s});
${r} end = ${r}(${i});
void main() {
${r} outC = getOutputCoords();
if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
setOutput(value);
} else {
${r} coords = outC - start;
setOutput(getX(${o}));
}
}
`}},xZ=class{constructor(e,t,a){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let n=e.length,r=gt(n),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=va("rc",n),l=va("source",n),u=`${o[n-1]} < ${this.outputShape[n-1]}`,p=n===1?"source":`vec2(${l.slice(-2).join()})`,c=[`${r} rc = outputLoc;`,`${o[n-1]} += 1;
if(${u}) {
`,n===1?"":`}
rc = outputLoc;
${o[n-2]} += 1;
if(${o[n-2]} < ${this.outputShape[n-2]}) {`,n===1?"":` ${o[n-1]} += 1;
if(${u}) {`],d=n===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",h="";for(let f=0,m=n===1?2:4;f<m;f++)h+=`
${c[f]}
if (${d}) {
result[${f}] = float(value);
} else {
${r} source = rc - start;
result[${f}] = getChannel(getX(${l.join()}), ${p});
}
`;h+=n===1?"} ":"}}",this.userCode=`
const ${r} start = ${r}(${s});
const ${r} end = ${r}(${i});
void main() {
${r} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${h}
setOutput(result);
}
`}},xv=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{paddings:s,constantValue:i}=n;if(v.sizeFromShape(r.shape)===0){let u=s.map((p,c)=>p[0]+r.shape[c]+p[1]);return fp({backend:a,attrs:{shape:u,value:i,dtype:r.dtype}})}let o=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new xZ(r.shape,s,i):new gZ(r.shape,s,i),l=[[i]];return a.runWebGLProgram(o,[r],r.dtype,l)},AZ={kernelName:Ui,backendName:"webgl",kernelFunc:xv},yZ=`
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);
`,bZ=`
// 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);
`+pp+`
return result;
`,vZ=oa({opSnippet:yZ,packedOpSnippet:bZ}),wZ={kernelName:Gi,backendName:"webgl",kernelFunc:vZ};function kZ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=r.shape.length,l=[],u=v.parseAxisParam(s,r.shape),p=u,c=T.getAxesPermutation(p,o),d=r;c!=null&&(d=Ia({inputs:{x:r},backend:a,attrs:{perm:c}}),p=T.getInnerMostAxes(p.length,o),l.push(d)),T.assertAxesAreInnerMostDims("prod",p,o);let h;if(a.shouldExecuteOnCPU([d])){let f=a.texData.get(d.dataId).values,{outVals:m,outShape:g,outDtype:x}=TU(d.shape,d.dtype,f,p);h=a.makeTensorInfo(g,x,m)}else{let[f,m]=T.computeOutAndReduceShapes(d.shape,p),g=v.sizeFromShape(m),x=ce({inputs:{x:d},backend:a,attrs:{shape:[-1,g]}}),A=Hd(r.dtype),y=bo(x,A,"prod",a);h=ce({inputs:{x:y},backend:a,attrs:{shape:f}}),l.push(x),l.push(y)}if(i){l.push(h);let f=T.expandShapeToKeepDim(h.shape,u);h=ce({inputs:{x:h},backend:a,attrs:{shape:f}})}return l.forEach(f=>a.disposeIntermediateTensorInfo(f)),h}var IZ={kernelName:ji,backendName:"webgl",kernelFunc:kZ};function SZ(e){let{inputs:t,backend:a,attrs:n}=e,{paramsNestedSplits:r,paramsDenseValues:s,indices:i}=t,{outputRaggedRank:o}=n,l=r.map(x=>a.readSync(x.dataId)),u=r.map(x=>x.shape),p=a.readSync(s.dataId),c=a.readSync(i.dataId),[d,h,f]=CU(l,u,p,s.shape,s.dtype,c,i.shape,o),m=d.map(x=>a.makeTensorInfo([x.length],"int32",x)),g=a.makeTensorInfo(f,s.dtype,h);return m.concat([g])}var TZ={kernelName:ih,backendName:"webgl",kernelFunc:SZ};function CZ(e){let{inputs:t,backend:a}=e,{starts:n,limits:r,deltas:s}=t,i=a.readSync(n.dataId),o=a.readSync(r.dataId),l=a.readSync(s.dataId),[u,p]=NU(i,n.shape,n.dtype,o,r.shape,l,s.shape),c=a.makeTensorInfo([u.length],"int32",u),d=a.makeTensorInfo([p.length],n.dtype,p);return[c,d]}var NZ={kernelName:oh,backendName:"webgl",kernelFunc:CZ};function EZ(e){let{inputs:t,backend:a,attrs:n}=e,{shape:r,values:s,defaultValue:i,rowPartitionTensors:o}=t,{rowPartitionTypes:l}=n,u=a.readSync(r.dataId),p=a.readSync(s.dataId),c=a.readSync(i.dataId),d=o.map(g=>a.readSync(g.dataId)),h=o.map(g=>g.shape),[f,m]=EU(u,r.shape,p,s.shape,s.dtype,c,i.shape,d,h,l);return a.makeTensorInfo(f,s.dtype,m)}var RZ={kernelName:lh,backendName:"webgl",kernelFunc:EZ},Av=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=RU(n,r,s,i);return t.makeTensorInfo([o.length],i,o)},MZ={kernelName:jl,backendName:"webgl",kernelFunc:Av},$Z="return 1.0 / x;",_Z=Qe({opSnippet:$Z}),PZ={kernelName:qi,backendName:"webgl",kernelFunc:_Z},FZ=Cn+`
return (x < 0.0) ? 0.0 : x;
`,OZ=`
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;
`,DZ=Qe({opSnippet:FZ,packedOpSnippet:OZ}),zZ={kernelName:Xi,backendName:"webgl",kernelFunc:DZ},LZ=Cn+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,BZ=`
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;
`,WZ=Qe({opSnippet:LZ,packedOpSnippet:BZ}),VZ={kernelName:Yi,backendName:"webgl",kernelFunc:WZ},UZ=class{constructor(e,t,a,n,r){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,a,l];let u=[n&&t>1?i-1:i,n&&a>1?o-1:o],p=[n&&t>1?t-1:t,n&&a>1?a-1:a],c;r?c="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":c="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${u[0]/p[0]},
${u[1]/p[1]});
const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 yRC = coords.yz;
// Fractional source index.
vec2 sourceFracIndexRC = ${c};
// 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);
}
`}},GZ=class{constructor(e,t,a,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,a,l];let u=[n&&t>1?i-1:i,n&&a>1?o-1:o],p=[n&&t>1?t-1:t,n&&a>1?a-1:a],c;r?c="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":c="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${u[0]/p[0]},
${u[1]/p[1]},
${u[1]/p[1]});
const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
${o}.0);
float getAValue(int b, int r, int c, int d) {
return getChannel(getA(b, r, c, d), vec2(c, d));
}
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
// Calculate values for next column in yRC.z.
ivec3 yRC = coords.yzz + ivec3(0, 0, 1);
// Fractional source index.
vec3 sourceFracIndexRC = ${c};
// Compute the four integer indices.
ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0)));
ivec3 sourceCeilRC = ivec3(
min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));
// Should we calculate next column and row elements in 2x2 packed cell.
bool hasNextCol = d < ${l-1};
bool hasNextRow = coords.z < ${a-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 HZ(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,p=W().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new GZ(r.shape,l,u,s,i):new UZ(r.shape,l,u,s,i);return a.runWebGLProgram(p,[r],"float32")}var jZ={kernelName:Zi,backendName:"webgl",kernelFunc:HZ},qZ=class{constructor(e,t,a){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,r]=t,[,s,i]=e,o=[a&&s>1?n-1:n,a&&i>1?r-1:r],l=[a&&s>1?s-1:s,a&&i>1?i-1:i],u=o[0]/l[0],p=o[1]/l[1],c=1/u,d=1/p,h=Math.ceil(c)*2+2,f=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(${u});
const float widthScale = float(${p});
const float invHeightScale = float(${c});
const float invWidthScale = float(${d});
const int winHeight = int(${h});
const int winWidth = int(${f});
// Compute bounds for where in dy we will look
float startRLerp = floor(float(r) * invHeightScale);
int startDyR = int(startRLerp - float(winHeight / 2));
float startCLerp = floor(float(c) * invWidthScale);
int startDyC = int(startCLerp - float(winWidth / 2));
// Loop over dy
for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
int dyR = dyROffset + startDyR;
// Guard against the window exceeding the bounds of dy
if (dyR < 0 || dyR >= ${s}) {
continue;
}
for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
int dyC = dyCOffset + startDyC;
// Guard against the window exceeding the bounds of dy
if (dyC < 0 || dyC >= ${i}) {
continue;
}
float dxR = float(dyR) * heightScale;
int topDxRIndex = int(floor(dxR));
int bottomDxRIndex = int(min(ceil(dxR), ${n-1}.0));
float dxRLerp = dxR - float(topDxRIndex);
float inverseDxRLerp = 1.0 - dxRLerp;
float dxC = float(dyC) * widthScale;
int leftDxCIndex = int(floor(dxC));
int rightDxCIndex = int(min(ceil(dxC), ${r-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 XZ(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=new qZ(s.shape,r.shape,i);return a.runWebGLProgram(o,[s],s.dtype)}var KZ={kernelName:Y1,backendName:"webgl",kernelFunc:XZ},ZZ=class{constructor(e,t,a,n,r){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,a,l];let u=[n&&t>1?i-1:i,n&&a>1?o-1:o],p=[n&&t>1?t-1:t,n&&a>1?a-1:a],c=n?"0.5":"0.0",d;r?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${u[0]/p[0]},
${u[1]/p[1]});
const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 yRC = coords.yz;
// Fractional source index.
vec2 sourceFracIndexRC = ${d};
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestRC = ivec2(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${c})));
float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);
setOutput(newValue);
}
`}},YZ=class{constructor(e,t,a,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,a,l];let u=[n&&t>1?i-1:i,n&&a>1?o-1:o],p=[n&&t>1?t-1:t,n&&a>1?a-1:a],c=n?"0.5":"0.0",d;r?d="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":d="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${u[0]/p[0]},
${u[1]/p[1]},
${u[1]/p[1]});
const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
${o}.0);
float getAValue(int b, int r, int c, int d) {
return getChannel(getA(b, r, c, d), vec2(c, d));
}
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
// Calculate values for next column in yRC.z.
ivec3 yRC = coords.yzz + ivec3(0, 0, 1);
// Fractional source index.
vec3 sourceFracIndexRC = ${d};
// Compute the coordinators of nearest neighbor point.
ivec3 sourceNearestRC = ivec3(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${c})));
// Should we calculate next column and row elements in 2x2 packed cell.
bool hasNextCol = d < ${l-1};
bool hasNextRow = coords.z < ${a-1};
vec4 newValue = vec4(
getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);
setOutput(newValue);
}
`}};function JZ(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,p=W().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new YZ(r.shape,l,u,s,i):new ZZ(r.shape,l,u,s,i);return a.runWebGLProgram(p,[r],r.dtype)}var QZ={kernelName:Ki,backendName:"webgl",kernelFunc:JZ},eY=class{constructor(e,t,a){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,r]=t,[,s,i]=e,o=[a&&s>1?n-1:n,a&&i>1?r-1:r],l=[a&&s>1?s-1:s,a&&i>1?i-1:i],u=o[0]/l[0],p=o[1]/l[1],c=1/u,d=1/p,h=Math.ceil(c)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
int r = coords[1];
int c = coords[2];
float accumulator = 0.0;
const float heightScale = float(${u});
const float widthScale = float(${p});
const float invHeightScale = float(${c});
const float invWidthScale = float(${d});
const int winHeight = int(${h});
const int winWidth = int(${f});
// Compute bounds for where in dy we will look
float startRLerp = floor(float(r) * invHeightScale);
int startDyR = int(floor(startRLerp - float(winHeight / 2)));
float startCLerp = floor(float(c) * invWidthScale);
int startDyC = int(floor(startCLerp - float(winWidth / 2)));
// Loop over dy
for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
int dyR = dyROffset + startDyR;
// Guard against the window exceeding the bounds of dy
if (dyR < 0 || dyR >= ${s}) {
continue;
}
for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
int dyC = dyCOffset + startDyC;
// Guard against the window exceeding the bounds of dy
if (dyC < 0 || dyC >= ${i}) {
continue;
}
float sourceFracRow =
float(${o[0]}) *
(float(dyR) / float(${l[0]}));
float sourceFracCol =
float(${o[1]}) *
(float(dyC) / float(${l[1]}));
int sourceNearestRow = int(min(
float(int(${n}) - 1),
${a} ? float(round(sourceFracRow)) :
float(floor(sourceFracRow))));
int sourceNearestCol = int(min(
float(int(${r}) - 1),
${a} ? float(round(sourceFracCol)) :
float(floor(sourceFracCol))));
if (r == sourceNearestRow && c == sourceNearestCol) {
accumulator += getDy(b, dyR, dyC, d);
}
}
}
// End loop over dy
setOutput(accumulator);
}
`}};function tY(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=new eY(s.shape,r.shape,i);return a.runWebGLProgram(o,[s],s.dtype)}var aY={kernelName:Z1,backendName:"webgl",kernelFunc:tY},nY=class{constructor(e,t){this.variableNames=["x"];let a=e.length;if(a>4)throw new Error(`WebGL backend: Reverse of rank-${a} tensor is not yet supported`);if(this.outputShape=e,a===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}]`,r=e.map((i,o)=>n(o)).join(","),s=gt(a);this.userCode=`
void main() {
${s} coords = getOutputCoords();
setOutput(getX(${r}));
}
`}},rY=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let a=e.length;if(a>4)throw new Error(`WebGL backend: Reverse of rank-${a} tensor is not yet supported`);this.outputShape=e;let n=va("rc",a),r=`${n[a-1]} + 1 < ${this.outputShape[a-1]}`,s=`${n[a-2]} + 1 < ${this.outputShape[a-2]}`,i=gt(a);a===1?this.userCode=`
void main(){
int rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = getChannel(getX(${e[0]} - rc - 1),
${e[0]} - rc - 1);
if(${r}){
result.g = getChannel(getX(${e[0]} - (rc + 1) - 1),
${e[0]} - (rc + 1) - 1);
}
setOutput(result);
}
`:this.userCode=`
void main() {
${i} rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = ${o(n.slice())};
if(${r}){
result.g = ${l(n.slice())};
}
if(${s}) {
result.b = ${u(n.slice())};
if(${r}) {
result.a = ${p(n.slice())};
}
}
setOutput(result);
}
`;function o(h){return c(h)}function l(h){return h[a-1]="("+h[a-1]+" + 1)",c(h)}function u(h){return h[a-2]="("+h[a-2]+" + 1)",c(h)}function p(h){return h[a-1]="("+h[a-1]+" + 1)",h[a-2]="("+h[a-2]+" + 1)",c(h)}function c(h){let f=e.map((x,A)=>d(A,h)),m=f.join(","),g=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${g}))`}function d(h,f){return t.indexOf(h)!==-1&&e[h]!==1?`${e[h]} - ${f[h]} - 1`:`${f[h]}`}}};function sY(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dims:s}=n,i=r.shape.length,o=v.parseAxisParam(s,r.shape);if(i===0)return Za({inputs:{x:r},backend:a});let l=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new rY(r.shape,o):new nY(r.shape,o);return a.runWebGLProgram(l,[r],r.dtype)}var iY={kernelName:Ji,backendName:"webgl",kernelFunc:sY},oY=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let a=e[1],n=e[2];this.outputShape=e;let r="";typeof t=="number"?r=`float outputValue = ${t.toFixed(2)};`:r=`
vec3 fill = vec3(${t.join(",")});
float outputValue = fill[coords[3]];`,this.userCode=`
void main() {
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]));
${r}
if(coordX >= 0 && coordX < ${n} && coordY >= 0 && coordY < ${a}) {
outputValue = getImage(coords[0], coordY, coordX, coords[3]);
}
setOutput(outputValue);
}
`}},lY={kernelName:mo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{image:n}=e,{radians:r,fillValue:s,center:i}=t,o=a,l=new oY(n.shape,s),[u,p]=T.getImageCenter(i,n.shape[1],n.shape[2]),c=[[u,p,Math.sin(r),Math.cos(r)]];return o.runWebGLProgram(l,[n],n.dtype,c)}},uY=`
// OpenGL ES does not support round function.
// The algorithm is based on banker's rounding.
float base = floor(x);
if ((x - base) < 0.5) {
return floor(x);
} else if ((x - base) > 0.5) {
return ceil(x);
} else {
if (mod(base, 2.0) == 0.0) {
return base;
} else {
return base + 1.0;
}
}
`,dY=Qe({opSnippet:uY}),pY={kernelName:Xl,backendName:"webgl",kernelFunc:dY},cY="return inversesqrt(x);",hY=Qe({opSnippet:cY,cpuKernelImpl:MU}),fY={kernelName:Qi,backendName:"webgl",kernelFunc:hY},yv=class{constructor(e,t,a,n,r,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=gt(r.length),l=gt(s.length),u="";a===1?u="i":a===2&&(u="i, j");let p=`getIndices(${u})`,c="";n===1?c="i":n===2&&(c="i, coords[1]");let d=`getUpdates(${c})`,h=t>1?"strides[j]":"strides";this.userCode=`
${o} strides = ${o}(${r});
void main() {
${l} coords = getOutputCoords();
float sum = 0.0;
bool found = false;
for (int i = 0; i < ${e}; i++) {
int flattenedIndex = 0;
for (int j = 0; j < ${t}; j++) {
int index = round(${p});
flattenedIndex += index * ${h};
}
if (flattenedIndex == coords[0]) {
sum += ${d};
found = true;
}
}
setOutput(mix(getDefaultValue(), sum, float(found)));
}
`}};function mY(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r,updates:s}=t,{shape:i}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:c}=T.calculateShapes(s,r,i),d=[c/u,u];if(c===0)return a.makeTensorInfo(i,r.dtype);let h=ce({inputs:{x:r},backend:a,attrs:{shape:[l,o]}}),f=ce({inputs:{x:s},backend:a,attrs:{shape:[l,u]}}),m=a.makeTensorInfo([],"float32",new Float32Array([0])),g=new yv(l,o,h.shape.length,f.shape.length,p,d),x=a.runWebGLProgram(g,[f,h,m],f.dtype),A=ce({inputs:{x},backend:a,attrs:{shape:i}});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(x),a.disposeIntermediateTensorInfo(m),A}var gY={kernelName:eo,backendName:"webgl",kernelFunc:mY},xY=class{constructor(e,t,a,n){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[e,a];let r="while (left < right) {",s=`for (int i = 0; i < ${Math.ceil(Math.log2(t+1))}; ++i) { if (left >= right) break;`,i=W().getNumber("WEBGL_VERSION")===2?r:s,o=n==="left"?"<":"<=";this.userCode=`
int findBound(int batch, float value) {
int left = 0;
int right = numInputs;
int mid;
${i}
mid = (left + right) / 2;
if (getSortedSequence(batch, mid) ${o} value) {
left = mid + 1;
} else {
right = mid;
}
}
return right;
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int valueIndex = coords[1];
float value = getValues(batch, valueIndex);
setOutput(float(findBound(batch, value)));
}
`}};function AY(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n,o=new xY(r.shape[0],r.shape[1],s.shape[1],i),l=[[r.shape[1]]];return a.runWebGLProgram(o,[r,s],"int32",l)}var yY={kernelName:$d,backendName:"webgl",kernelFunc:AY},bY=class{constructor(e,t,a){this.variableNames=["c","a","b"],this.outputShape=t;let n,r;if(a>4)throw Error(`Where for rank ${a} is not yet supported`);if(a===1)r="resRC",n="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let u=0;u<t.length;u++)l.push(`${i[u]}`),u<e&&o.push(`${i[u]}`);n=o.join(),r=l.join()}let s=gt(a);this.userCode=`
void main() {
${s} resRC = getOutputCoords();
float cVal = getC(${n});
if (cVal >= 1.0) {
setOutput(getA(${r}));
} else {
setOutput(getB(${r}));
}
}
`}};function vY(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t,i=new bY(n.shape.length,r.shape,r.shape.length);return a.runWebGLProgram(i,[n,r,s],ca(r.dtype,s.dtype))}var wY={kernelName:Kl,backendName:"webgl",kernelFunc:vY},kY=`
// Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
// see: https://arxiv.org/abs/1706.02515
float scaleAlpha = ${T.SELU_SCALEALPHA};
float scale = ${T.SELU_SCALE};
return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,IY=Qe({opSnippet:kY}),SY={kernelName:_d,backendName:"webgl",kernelFunc:IY},TY=mu+`
return 1.0 / (1.0 + exp(-1.0 * x));
`,CY=`
vec4 result = 1.0 / (1.0 + exp(-1.0 * x));
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : result.r;
result.g = isNaN.g ? x.g : result.g;
result.b = isNaN.b ? x.b : result.b;
result.a = isNaN.a ? x.a : result.a;
return result;
`,NY=Qe({opSnippet:TY,packedOpSnippet:CY,cpuKernelImpl:_U}),EY={kernelName:ao,backendName:"webgl",kernelFunc:NY},RY=`
if (isnan(x)) { return 0.0; }
return sign(x);
`,MY=Qe({opSnippet:RY}),$Y={kernelName:Pd,backendName:"webgl",kernelFunc:MY},_Y=mu+`
return sin(x);
`,PY=Qe({opSnippet:_Y}),FY={kernelName:to,backendName:"webgl",kernelFunc:PY},OY=`
float e2x = exp(x);
return (e2x - 1.0 / e2x) / 2.0;
`,DY=Qe({opSnippet:OY}),zY={kernelName:Yl,backendName:"webgl",kernelFunc:DY},LY=`
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;
`,BY=Qe({opSnippet:LY}),WY={kernelName:Fd,backendName:"webgl",kernelFunc:BY},VY=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,paddings:i}=n;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((x,A)=>x*A),l=[[0,0]];l.push(...i);for(let x=1+s.length;x<r.shape.length;++x)l.push([0,0]);let u=[],p=xv({inputs:{x:r},backend:a,attrs:{paddings:l,constantValue:0}}),c=T.getReshaped(p.shape,s,o,!1),d=T.getPermuted(c.length,s.length,!1),h=T.getReshapedPermuted(p.shape,s,o,!1),f=ce({inputs:{x:p},backend:a,attrs:{shape:c}}),m=Ia({inputs:{x:f},backend:a,attrs:{perm:d}}),g=ce({inputs:{x:m},backend:a,attrs:{shape:h}});return u.push(p),u.push(f),u.push(m),u.forEach(x=>a.disposeIntermediateTensorInfo(x)),g},UY={kernelName:Jl,backendName:"webgl",kernelFunc:VY};function GY(e){let{inputs:t,backend:a}=e,{indices:n,values:r,denseShape:s,defaultValue:i}=t;if(s.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
${s.shape}`);if(n.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
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${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
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${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${s.shape}`);let i=a.readSync(n.dataId),o=a.readSync(r.dataId),l=a.readSync(s.dataId),[u,p]=W6(i,n.shape,n.dtype,o,l);return a.makeTensorInfo(p,n.dtype,u)}var YY={kernelName:zd,backendName:"webgl",kernelFunc:ZY};function JY(e){let{inputs:t,backend:a,attrs:n}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=t,{outputShape:o}=n,{sliceRank:l,numUpdates:u,sliceSize:p,strides:c,outputSize:d}=T.calculateShapes(s,r,o),h=!1;if(s.dtype==="string"){let x=a.bufferSync(r),A=a.bufferSync(s),y=v.decodeString(a.readSync(i.dataId)[0]),b=$U(x,A,o,d,p,u,l,c,y,h);return a.makeTensorInfo(o,b.dtype,b.values)}let f=new yv(u,l,r.shape.length,s.shape.length,c,[d,1],h),m=a.runWebGLProgram(f,[s,r,i],s.dtype),g=ce({inputs:{x:m},backend:a,attrs:{shape:o}});return a.disposeIntermediateTensorInfo(m),g}var QY={kernelName:Ld,backendName:"webgl",kernelFunc:JY};function eJ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=n,o=v.parseAxisParam(i,r.shape)[0],l=T.prepareSplitSize(r,s,o),u=r.shape.length,p=new Array(u).fill(0),c=r.shape.slice();return l.map(d=>{let h=[...c];h[o]=d;let f=gu({inputs:{x:r},backend:a,attrs:{begin:p,size:h}});return p[o]+=d,f})}var tJ={kernelName:Ql,backendName:"webgl",kernelFunc:eJ},_x="return sqrt(x);",aJ=Qe({opSnippet:_x,packedOpSnippet:_x,cpuKernelImpl:DU}),nJ={kernelName:no,backendName:"webgl",kernelFunc:aJ},rJ="return x * x;",sJ=Qe({opSnippet:rJ}),iJ={kernelName:Bd,backendName:"webgl",kernelFunc:sJ},Px="return (a - b) * (a - b);",oJ=oa({opSnippet:Px,packedOpSnippet:Px}),lJ={kernelName:io,backendName:"webgl",kernelFunc:oJ};function uJ({inputs:e,attrs:t,backend:a}){let{x:n}=e,r=Cn+`
return x > 0.0 ? 1.0 : float(${t.alpha});
`,s=new qn(n.shape,r);return a.runWebGLProgram(s,[n],n.dtype)}var dJ={kernelName:fo,backendName:"webgl",kernelFunc:uJ},pJ=class{constructor(e,t,a){this.variableNames=["x"],this.outputShape=a;let n=a.length,r=gt(a.length),s=gt(a.length),i="";if(n===1)i="coords * strides + begin";else{let o=0;i=a.map((l,u)=>(o++,a.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${o-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
${r} begin = ${r}(${e});
${r} strides = ${r}(${t});
void main() {
${s} coords = getOutputCoords();
setOutput(getX(${i}));
}
`}};function cJ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:p,newAxisMask:c,shrinkAxisMask:d}=n,{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:x,begin:A,end:y,strides:b}=It.sliceInfo(r.shape,s,i,o,l,u,p,c,d),w;if(m)w=ce({inputs:{x:r},backend:a,attrs:{shape:f}});else if(g||x){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let C=It.computeOutShape(A,y,b),E=gu({inputs:{x:r},backend:a,attrs:{begin:A,size:C}});w=ce({inputs:{x:E},backend:a,attrs:{shape:f}}),a.disposeIntermediateTensorInfo(E)}else if(a.shouldExecuteOnCPU([r])){let C=a.readSync(r.dataId),E=Me(r.shape,r.dtype,C),_=zU(h,E,b,A);w=a.makeTensorInfo(f,r.dtype,_.values)}else{let C=new pJ(A,b,h);w=a.runWebGLProgram(C,[r],r.dtype)}let S=ce({inputs:{x:w},backend:a,attrs:{shape:f}});return a.disposeIntermediateTensorInfo(w),S}var hJ={kernelName:oo,backendName:"webgl",kernelFunc:cJ};function fJ(e){let{inputs:t,backend:a,attrs:n}=e,{separator:r,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:u}=n,{data:p,dataSplits:c}=t,d=a.readSync(p.dataId),h=a.readSync(c.dataId),[f,m]=LU(d,h,r,s,i,o,l,u);return[a.makeTensorInfo([f.length],"string",f),a.makeTensorInfo(c.shape,"int32",m)]}var mJ={kernelName:tu,backendName:"webgl",kernelFunc:fJ};function gJ(e){let{inputs:t,backend:a,attrs:n}=e,{skipEmpty:r}=n,{input:s,delimiter:i}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(s.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${s.shape}`);if(i.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${i.shape}`);let o=a.readSync(s.dataId),l=a.readSync(i.dataId)[0],[u,p,c]=BU(o,l,r),d=p.length;return[a.makeTensorInfo([d,2],"int32",u),a.makeTensorInfo([d],"string",p),a.makeTensorInfo([2],"int32",new Int32Array(c))]}var xJ={kernelName:Wd,backendName:"webgl",kernelFunc:gJ};function AJ(e){let{inputs:t,backend:a,attrs:n}=e,{numBuckets:r}=n,{input:s}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");let i=a.readSync(s.dataId),o=WU(i,r);return a.makeTensorInfo(s.shape,"int32",o)}var yJ={kernelName:Vd,backendName:"webgl",kernelFunc:AJ},bJ="return tan(x);",vJ=Qe({opSnippet:bJ}),wJ={kernelName:uo,backendName:"webgl",kernelFunc:vJ},kJ=`
float e2x = exp(-2.0 * abs(x));
return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,IJ=Qe({opSnippet:kJ}),SJ={kernelName:po,backendName:"webgl",kernelFunc:IJ},TJ=class{constructor(e,t){this.variableNames=["A"];let a=new Array(e.length);for(let s=0;s<a.length;s++)a[s]=e[s]*t[s];this.outputShape=a,this.rank=a.length;let n=gt(this.rank),r=CJ(e);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
setOutput(getA(${r}));
}
`}};function CJ(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let a=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],n=[];for(let r=0;r<e.length;r++)n.push(`imod(${a[r]}, ${e[r]})`);return n.join()}function bv(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reps:s}=n;if(r.dtype==="string"||r.shape.length>5){let o=a.readSync(r.dataId),l=r.dtype==="string"?o.map(c=>v.decodeString(c)):o,u=Me(r.shape,r.dtype,l),p=UU(u,s);return a.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new TJ(r.shape,s);return a.runWebGLProgram(i,[r],r.dtype)}var NJ={kernelName:ns,backendName:"webgl",kernelFunc:bv},EJ=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));
}
}
`}},RJ=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 Es(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function Fx(e){let t=1;for(;t<e;)t*=2;return t}function MJ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{k:s,sorted:i}=n,o=W().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=W().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=r.shape,p=u[u.length-1];if(a.shouldExecuteOnCPU([r])||p<o||s>l){let _=a.readSync(r.dataId),[$,M]=GU(_,u,r.dtype,s,i);return[a.makeTensorInfo($.shape,$.dtype,$.values),a.makeTensorInfo(M.shape,M.dtype,M.values)]}if(s===0)return u[u.length-1]=0,[a.makeTensorInfo(u,r.dtype,[]),a.makeTensorInfo(u,"int32",[])];if(p===1)return[r,fp({attrs:{shape:u,dtype:"int32",value:0},backend:a})];let c=a.texData.get(r.dataId),d=c!==null&&c.isPacked,h=d?a.unpackTensor(r):r,f=v.sizeFromShape(u)/p,m=ce({inputs:{x:h},attrs:{shape:[f,p]},backend:a});d&&Es(a,h);let g=Fx(s),x=Fx(p),A=null,y=()=>A===null?[m,m]:[m,A],b=(_,$,M)=>{let I=y(),N=new EJ(M),O=[[p],[A===null?1:0],[Number.NEGATIVE_INFINITY],[_],[$]],L=A;A=a.runWebGLProgram(N,I,"int32",O),Es(a,L)};for(let _=1;_<g;_*=2){let $=_*2;for(let M=_;M>=1;M/=2)b($,M,[f,x])}for(let _=x;_>g;_/=2){let $=y(),M=new RJ([f,_/2]),I=[[p],[A===null?1:0],[g]],N=A;A=a.runWebGLProgram(M,$,"int32",I),Es(a,N);let O=g/2,L=O*2;for(let B=O;B>=1;B/=2)b(L,B,A.shape)}let w=A;A=gu({inputs:{x:A},backend:a,attrs:{begin:0,size:[f,s]}}),Es(a,w);let S=pv({inputs:{x:m,indices:A},backend:a,attrs:{axis:1,batchDims:1}});Es(a,m);let C=u.slice(0,-1);C.push(s),w=A,A=ce({inputs:{x:A},attrs:{shape:C},backend:a}),Es(a,w);let E=S;return S=ce({inputs:{x:S},attrs:{shape:C},backend:a}),Es(a,E),[S,A]}var $J={kernelName:co,backendName:"webgl",kernelFunc:MJ},_J=class{constructor(e,t,a,n,r,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=a==="nearest"?1:2,o;switch(n){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
float mapCoord(float outCoord, float len) {
float inCoord = outCoord;
if(${o} == 2) {
if (inCoord < 0.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz2 = 2.0 * len;
if (inCoord < sz2) {
inCoord = sz2 * float(int(float(-inCoord / sz2))) +
inCoord;
}
inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;
}
} else if (inCoord > len - 1.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz2 = 2.0 * len;
inCoord -= sz2 * float(int(float(inCoord / sz2)));
if (inCoord >= len) {
inCoord = sz2 - inCoord - 1.0;
}
}
}
return clamp(inCoord, 0.0, len - 1.0);
} else if (${o} == 3) {
if (inCoord < 0.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz = len - 1.0;
inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
}
} else if (inCoord > len - 1.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz = len - 1.0;
inCoord -= len * float(int(float(inCoord / sz)));
}
}
return clamp(inCoord, 0.0, len - 1.0);
} else if (${o} == 4) {
return clamp(outCoord, 0.0, len - 1.0);
} else {
return outCoord;
}
}
float readWithFillValue(int batch, int coordY, int coordX,
int channel) {
float outputValue;
if (0 <= coordY && coordY < ${e} && 0 <= coordX && coordX < ${t}) {
outputValue = getImage(batch, coordY, coordX, channel);
} else {
outputValue = float(${r});
}
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(${r});
} else {
float inX = (a1 * xf + a2 * yf + a3) / projection;
float inY = (b1 * xf + b2 * yf + b3) / projection;
float mapX = mapCoord(inX, float(${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 PJ(e){let{inputs:t,backend:a,attrs:n}=e,{image:r,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=n,[p,c,d,h]=r.shape,[f,m]=u!=null?u:[c,d],g=[p,f,m,h],x=new _J(c,d,i,o,l,g);return a.runWebGLProgram(x,[r,s],"float32")}var FJ={kernelName:ho,backendName:"webgl",kernelFunc:PJ};function OJ(e){let{inputs:t,attrs:a,backend:n}=e,{axis:r}=a,{x:s}=t;uu(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=n.readSync(s.dataId),{outputValues:o,outputShape:l,indices:u}=HU(i,r,s.shape,s.dtype);return[n.makeTensorInfo(l,s.dtype,o),n.makeTensorInfo([u.length],"int32",u)]}var DJ={kernelName:uh,backendName:"webgl",kernelFunc:OJ};function zJ(e){let{inputs:t,backend:a,attrs:n}=e,{value:r}=t,{axis:s}=n;s<0&&(s+=r.shape.length);let i=r,o=i.shape.length,l=r.shape[s],u=new Array(o-1),p=0;for(let m=0;m<o;m++)m!==s&&(u[p++]=i.shape[m]);let c=[],d=new Array(o).fill(0),h=i.shape.slice();h[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let g=gu({inputs:{x:i},backend:a,attrs:{begin:d,size:h}}),x=ce({inputs:{x:g},backend:a,attrs:{shape:u}});f[m]=x,c.push(g)}return c.forEach(m=>a.disposeIntermediateTensorInfo(m)),f}var LJ={kernelName:au,backendName:"webgl",kernelFunc:zJ},BJ=class{constructor(e,t){this.variableNames=["x","segmentIds"];let a=e.windowSize,n=e.batchSize,r=e.inSize,s=e.numSegments,i=s*Math.ceil(r/a);this.outputShape=[n,i];let o="0.0",l="sumValue",u=Math.floor(a/4)*4,p=a%4,c=`
sumValue += dot(values, segFilter);
`,d="";r%a>0&&(d=`
if (inIdx < 0 || inIdx >= ${r}) {
return initializationValue;
}
`);let h="";r%a>0&&(h=`
if (inIdx < 0 || inIdx >= ${r}) {
return -1.0;
}
`),this.userCode=`
const float initializationValue = ${o};
float getValue(int batch, int inIdx) {
${d}
return getX(batch, inIdx);
}
float getSegmentIdAtIndex(int inIdx) {
${h}
return getSegmentIds(inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = int(floor(float(outIdx) / float(
${s})) * float(${a}));
int currentSeg = int(mod(float(outIdx), float(${s})));
float sumValue = 0.0;
for (int i = 0; i < ${u}; 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
);
${c}
}
int inIdx = inOffset + ${u};
if (${p===1}) {
vec4 values = vec4(
getValue(batch, inIdx),
initializationValue,
initializationValue,
initializationValue
);
int inIdxSeg = int(getSegmentIdAtIndex(inIdx));
vec4 segFilter = vec4(
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
0,
0,
0
);
${c}
} else if (${p===2}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
initializationValue,
initializationValue
);
vec4 segFilter = vec4(
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
0,
0
);
${c}
} else if (${p===3}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
initializationValue
);
vec4 segFilter = vec4(
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
0
);
${c}
}
setOutput(${l});
}
`}};function WJ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,segmentIds:s}=t,{numSegments:i}=n,o=r.shape.length,l=[],u=0,p=T.getAxesPermutation([u],o),c=r;p!=null&&(c=Ia({inputs:{x:r},backend:a,attrs:{perm:p}}),l.push(c),u=T.getInnerMostAxes(1,o)[0]);let d=T.segment_util.computeOutShape(c.shape,u,i),h=v.sizeFromShape([c.shape[u]]),f=ce({inputs:{x:c},backend:a,attrs:{shape:[-1,h]}});l.push(f);let m=Hd(r.dtype),g=(b,w,S,C,E)=>{let _=b.shape[0],$=b.shape[1],M=T.segment_util.segOpComputeOptimalWindowSize($,E),I={windowSize:M,inSize:$,batchSize:_,numSegments:E},N=new BJ(I,w),O=a.compileAndRun(N,[b,S],C);if(l.push(O),O.shape[1]===E)return O;let L=Av({backend:a,attrs:{start:0,stop:E,step:1,dtype:"float32"}}),B=bv({inputs:{x:L},backend:a,attrs:{reps:[$/M]}});return l.push(L),l.push(B),g(O,w,B,C,E)},x=g(f,"unsortedSegmentSum",s,m,i),A=ce({inputs:{x},backend:a,attrs:{shape:d}}),y=A;if(p!=null){l.push(A);let b=T.getUndoAxesPermutation(p);y=Ia({inputs:{x:y},backend:a,attrs:{perm:b}})}return l.forEach(b=>a.disposeIntermediateTensorInfo(b)),y}var VJ={kernelName:dh,backendName:"webgl",kernelFunc:WJ},UJ=[zG,BG,UG,jG,XG,YG,QG,tH,sH,oH,dH,hH,gH,bH,kH,SH,CH,MH,_H,FH,LH,jH,XH,ZH,aj,rj,lj,vG,pj,gj,bj,Tj,Nj,Rj,$j,Pj,Dj,Bj,Uj,Hj,qj,Kj,Jj,eq,rq,iq,uq,cq,fq,Aq,wq,Tq,Eq,$q,_q,Fq,Dq,Lq,Wq,Uq,qq,Zq,Qq,tX,rX,oX,pX,mX,bG,xX,fj,bX,kX,TX,kG,RX,PX,OX,BX,UX,qX,ZX,eK,rK,oK,uK,hK,mK,xK,vK,kK,SK,CK,EK,_K,DK,WK,KK,TG,QK,aZ,sZ,lZ,JH,pZ,hZ,mZ,AZ,wZ,SG,IZ,TZ,NZ,RZ,MZ,QH,HK,PZ,zZ,VZ,NG,jZ,KZ,QZ,aY,iY,lY,pY,fY,gY,yY,wY,SY,EY,$Y,FY,zY,GH,qK,WY,UY,HY,qY,KY,YY,QY,tJ,nJ,iJ,lJ,dJ,hJ,mJ,xJ,yJ,jK,FG,wJ,SJ,NJ,$J,FJ,OG,DJ,LJ,VJ,cZ];for(let e of UJ)mn(e);var Tt;(function(e){e[e.float32=0]="float32",e[e.int32=1]="int32",e[e.bool=2]="bool",e[e.string=3]="string",e[e.complex64=4]="complex64"})(Tt||(Tt={}));var yd;(function(e){e[e.linear=0]="linear",e[e.relu=1]="relu",e[e.relu6=2]="relu6",e[e.prelu=3]="prelu",e[e.leakyrelu=4]="leakyrelu",e[e.sigmoid=5]="sigmoid",e[e.elu=6]="elu"})(yd||(yd={}));var vv;function GJ(e){vv=e.wasm.cwrap(jr,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function HJ(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:c}=n,d=a.dataIdMap.get(r.dataId).id,h=a.dataIdMap.get(s.dataId).id,f=0;if(i!=null){let E=a.dataIdMap.get(i.dataId);if(E.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${E.shape.length}.`);f=E.id}let m=o==null?0:a.dataIdMap.get(o.dataId).id,g=yd[p];if(g==null)throw new Error(`${p} activation not yet supported for FusedConv2D in the wasm backend.`);let x=l?r.shape[2]:r.shape[1],A=u?s.shape[1]:s.shape[2],y=xo.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)),b=a.makeOutput([...y,x,A],r.dtype),w=a.dataIdMap.get(b.dataId).id,S=new Uint8Array(new Int32Array(r.shape).buffer),C=new Uint8Array(new Int32Array(s.shape).buffer);return vv(d,S,r.shape.length,h,C,s.shape.length,l,u,g,f,m,c||0,w),b}var jJ={kernelName:jr,backendName:"wasm",setupFunc:GJ,kernelFunc:HJ};function Bt(e,t){let a;function n(s){a=s.wasm.cwrap(e,null,["number","number","number"])}function r(s){let{backend:i,inputs:{x:o}}=s,l=i.dataIdMap.get(o.dataId).id,u=i.makeOutput(o.shape,t||o.dtype),p=i.dataIdMap.get(u.dataId).id;return v.sizeFromShape(u.shape)===0||a(l,Tt[o.dtype],p),u}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:r}}var qJ=Bt(wl);function la(e,t,a){let n;function r(i){n=i.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function s(i){let{backend:o,inputs:l}=i,{a:u,b:p}=l,c=o.dataIdMap.get(u.dataId).id,d=o.dataIdMap.get(p.dataId).id,h=a!=null?a:u.dtype,f=T.assertAndGetBroadcastShape(u.shape,p.shape),m=o.makeOutput(f,h);if(v.sizeFromShape(f)===0)return m;let g=new Uint8Array(new Int32Array(u.shape).buffer),x=new Uint8Array(new Int32Array(p.shape).buffer),A=o.dataIdMap.get(m.dataId).id;return n(c,g,u.shape.length,d,x,p.shape.length,Tt[u.dtype],A),m}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:s}}var XJ=!0,KJ=la(ts,XJ),wv;function ZJ(e){wv=e.wasm.cwrap(Ks,null,["array","number","number","number"])}function YJ(e){let{inputs:t,backend:a}=e,n=a.makeOutput(t[0].shape,t[0].dtype);if(v.sizeFromShape(n.shape)===0)return n;let r=t.map(o=>a.dataIdMap.get(o.dataId).id),s=new Uint8Array(new Int32Array(r).buffer),i=a.dataIdMap.get(n.dataId).id;return wv(s,r.length,Tt[n.dtype],i),n}var JJ={kernelName:Ks,backendName:"wasm",setupFunc:ZJ,kernelFunc:YJ};function Bh(e){let{inputs:{x:t},backend:a}=e;if(t.dtype==="string")return Be(a.readSync(t.dataId),t.shape,t.dtype);let n=a.makeOutput(t.shape,t.dtype),r=a.typedArrayFromHeap(t);return a.typedArrayFromHeap(n).set(r),n}var QJ={kernelName:ki,backendName:"wasm",kernelFunc:Bh},kv;function eQ(e){kv=e.wasm.cwrap(Ar,null,["number","array","number","number","number","array","number"])}function Qr(e){let{inputs:t,backend:a,attrs:n}=e,[r,s]=aQ(t.x.shape,n.perm),i=!0;for(let f=0;f<s.length;f++)s[f]!==f&&(i=!1);let o=tQ(t.x.shape,n.perm),l={dataId:t.x.dataId,shape:r,dtype:t.x.dtype};if(i){let f=Bh({inputs:t,backend:a});return f.shape=o,f}let u=a.makeOutput(o,l.dtype),p=a.dataIdMap.get(l.dataId).id,c=a.dataIdMap.get(u.dataId).id,d=new Uint8Array(new Int32Array(s).buffer),h=new Uint8Array(new Int32Array(l.shape).buffer);return kv(p,h,l.shape.length,Tt[l.dtype],c,d,s.length),u}function tQ(e,t){let a=new Array(e.length);for(let n=0;n<a.length;n++)a[n]=e[t[n]];return a}function aQ(e,t){let a=[],n=[];for(let r=0;r<e.length;++r)e[r]!==1&&a.push(e[r]),e[t[r]]!==1&&n.push(t[r]);for(let r=0;r<n.length;++r){let s=-1;for(let i=0;i<n.length;++i)n[i]>=r&&(s===-1||n[s]>n[i])&&(s=i);n[s]=r}return[a,n]}var nQ={kernelName:Ar,backendName:"wasm",kernelFunc:Qr,setupFunc:eQ};function us(e,t,a){let n=e.shape,r=e.shape.length,s=v.parseAxisParam(t,n),i=s,o=T.getAxesPermutation(i,r),l=null,u=!1;if(o!=null){let p=new Array(r);for(let d=0;d<p.length;d++)p[d]=n[o[d]];i=T.getInnerMostAxes(i.length,r),l=Qr({inputs:{x:e},attrs:{perm:o},backend:a});let c=a.dataIdMap.get(e.dataId).id;a.dataIdMap.get(l.dataId).id!==c&&(u=!0)}return{transposed:l,originalAxes:s,axes:i,inputWasTransposed:u}}var Iv;function rQ(e){Iv=e.wasm.cwrap(Zs,null,["number, number, number"])}function sQ(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:c,inputWasTransposed:d}=us(i,r,t);if(d){let A=t.dataIdMap.get(u.dataId).id;l=u,o=A}let h=l.shape.length;T.assertAxesAreInnerMostDims("all",p,h);let[f,m]=T.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(m),x=t.makeOutput(f,i.dtype);if(v.sizeFromShape(l.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;Iv(o,g,A)}if(d&&t.disposeData(u.dataId),s){let A=T.expandShapeToKeepDim(x.shape,c);x.shape=A}return x}var iQ={kernelName:Zs,backendName:"wasm",setupFunc:rQ,kernelFunc:sQ},Sv;function oQ(e){Sv=e.wasm.cwrap(Ys,null,["number, number, number"])}function lQ(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:c,inputWasTransposed:d}=us(i,r,t);if(d){let A=t.dataIdMap.get(u.dataId).id;l=u,o=A}let h=l.shape.length;T.assertAxesAreInnerMostDims("any",p,h);let[f,m]=T.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(m),x=t.makeOutput(f,i.dtype);if(v.sizeFromShape(l.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;Sv(o,g,A)}if(d&&t.disposeData(u.dataId),s){let A=T.expandShapeToKeepDim(x.shape,c);x.shape=A}return x}var uQ={kernelName:Ys,backendName:"wasm",setupFunc:oQ,kernelFunc:lQ},Tv;function dQ(e){Tv=e.wasm.cwrap(Js,null,["number","number","number","number","number"])}function pQ(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r}=n,{x:s}=a,i=t.dataIdMap.get(s.dataId).id,o=i,l=s,{transposed:u,axes:p,inputWasTransposed:c}=us(s,r,t);if(c){let x=t.dataIdMap.get(u.dataId).id;x!==i&&(l=u,o=x)}let d=l.shape.slice(0,-1),h=t.makeOutput(d,"int32"),f=t.dataIdMap.get(h.dataId).id,m=v.sizeFromShape(h.shape),g=l.shape[p[0]];return Tv(o,Tt[l.dtype],m,g,f),c&&t.disposeData(u.dataId),h}var cQ={kernelName:Js,backendName:"wasm",kernelFunc:pQ,setupFunc:dQ},Cv;function hQ(e){Cv=e.wasm.cwrap(Qs,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function fQ(e){let{inputs:t,attrs:a,backend:n}=e,r=t.x,s=n.dataIdMap.get(r.dataId).id,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=a,p=T.computePool2DInfo(r.shape,i,o,1,l,u),c=p.filterHeight,d=p.filterWidth,h=p.padInfo.top,f=p.padInfo.right,m=p.padInfo.bottom,g=p.padInfo.left,x=p.strideHeight,A=p.strideWidth,y=p.inChannels;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. 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QQ(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s}=t,i=n.dataIdMap.get(r.dataId).id,o=n.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:p,dimRoundingMode:c}=a,d=u==null?[1,1]:u,h=T.computeConv2DInfo(r.shape,s.shape,l,d,p,c,!0),f=h.filterHeight,m=h.filterWidth,g=h.padInfo.top,x=h.padInfo.right,A=h.padInfo.bottom,y=h.padInfo.left,b=h.dilationHeight,w=h.dilationWidth,S=h.strideHeight,C=h.strideWidth,E=h.inChannels,_=h.outChannels,$=h.padInfo.type==="SAME"?1:0;if(h.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${h.dataFormat}'. Please use 'channelsLast'.`);let M=n.makeOutput(h.outShape,"float32"),I=n.dataIdMap.get(M.dataId).id;return Dv(i,r.shape[0],r.shape[1],r.shape[2],o,f,m,g,x,A,y,$,b,w,S,C,E,_,I),M}var eee={kernelName:pi,backendName:"wasm",setupFunc:JQ,kernelFunc:QQ},tee=Bt(hi),aee=!1,nee=la(fi,aee,"bool"),ree=Bt(mi,"float32");function R1(e){let{inputs:t,attrs:a,backend:n}=e,{input:r}=t,{dim:s}=a,i=r.shape.length,o=r.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),za({inputs:{x:r},backend:n,attrs:{shape:o}})}var see={kernelName:_l,backendName:"wasm",kernelFunc:R1};function zv(e){let{attrs:{shape:t,value:a,dtype:n},backend:r}=e,s=r.makeOutput(t,n);return r.typedArrayFromHeap(s).fill(a),s}var iee={kernelName:Fl,backendName:"wasm",kernelFunc:zv},Lv;function oee(e){Lv=e.wasm.cwrap(gi,null,["number","number","number","number","number","number"])}function lee(e){let{inputs:t,backend:a}=e,{image:n}=t,r=a.makeOutput(n.shape,n.dtype),s=a.dataIdMap.get(n.dataId).id,i=a.dataIdMap.get(r.dataId).id,[o,l,u,p]=n.shape;return Lv(s,o,l,u,p,i),r}var uee={kernelName:gi,backendName:"wasm",kernelFunc:lee,setupFunc:oee},dee=Bt(xi),pee=!1,cee=la(Ai,pee),Bv;function hee(e){Bv=e.wasm.cwrap(yi,null,["number","number","number","number","number","number","number"])}function fee(e){let{backend:t,inputs:a,attrs:n}=e,{varianceEpsilon:r}=n,{x:s,mean:i,variance:o,offset:l,scale:u}=a,p=t.dataIdMap.get(s.dataId).id,c=t.dataIdMap.get(i.dataId).id,d=t.dataIdMap.get(o.dataId).id,h=l!=null?t.dataIdMap.get(l.dataId).id:0,f=u!=null?t.dataIdMap.get(u.dataId).id:0,m=t.makeOutput(s.shape,s.dtype);if(v.sizeFromShape(s.shape)===0)return m;let g=t.dataIdMap.get(m.dataId).id;return Bv(p,c,d,h,f,r,g),m}var mee={kernelName:yi,backendName:"wasm",setupFunc:hee,kernelFunc:fee},Wv;function gee(e){Wv=e.wasm.cwrap(qr,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function xee(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:c,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=a,m=T.computeConv2DInfo(r.shape,s.shape,l,p,u,d),g=yd[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedConv2D in the wasm backend.`);let x=n.dataIdMap.get(r.dataId).id,A=n.dataIdMap.get(s.dataId).id,y=m.outChannels,b=0;if(i!=null){let Z=n.dataIdMap.get(i.dataId);if(Z.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${Z.shape.length}.`);if(Z.shape[0]!==y)throw new Error(`FusedConv2D bias shape (${Z.shape}) does not match the number of output channels (${y})`);b=Z.id}let w=m.filterHeight,S=m.filterWidth,C=m.padInfo.top,E=m.padInfo.right,_=m.padInfo.bottom,$=m.padInfo.left,M=m.dilationHeight,I=m.dilationWidth,N=m.strideHeight,O=m.strideWidth,L=m.inChannels,B=m.padInfo.type==="SAME"?1:0,G=m.batchSize,j=m.inHeight,U=m.inWidth;if(c!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${c}'. 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b=T.expandShapeToKeepDim(y.shape,d);y.shape=b}return u.dtype!=="float32"&&t.disposeData(A.dataId),y}var rte={kernelName:Pi,backendName:"wasm",setupFunc:ate,kernelFunc:nte},Kv;function ste(e){Kv=e.wasm.cwrap(Fi,null,["number","number","number","number"])}function ite(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:c,originalAxes:d,inputWasTransposed:h}=us(i,r,t);if(h){let y=t.dataIdMap.get(p.dataId).id;y!==o&&(u=p,l=y)}let f=u.shape.length;T.assertAxesAreInnerMostDims("min",c,f);let[m,g]=T.computeOutAndReduceShapes(u.shape,c),x=v.sizeFromShape(g),A=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let y=t.dataIdMap.get(A.dataId).id;Kv(l,Tt[i.dtype],x,y)}if(h&&t.disposeData(p.dataId),s){let y=T.expandShapeToKeepDim(A.shape,d);A.shape=y}return A}var ote={kernelName:Fi,backendName:"wasm",setupFunc:ste,kernelFunc:ite},lte=!1,ute=la(Oi,lte),M1;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(M1||(M1={}));var Zv;function dte(e){Zv=e.wasm.cwrap(Di,null,["number","array","number","number","array","array","number","number"])}function pte(e){let{inputs:{x:t},backend:a,attrs:{paddings:n,mode:r}}=e,s=n.map((f,m)=>f[0]+t.shape[m]+f[1]),i=a.dataIdMap.get(t.dataId).id,o=a.makeOutput(s,t.dtype),l=a.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),p=n.map(f=>f[0]),c=n.map(f=>f[1]),d=new Uint8Array(new Int32Array(p).buffer),h=new Uint8Array(new Int32Array(c).buffer);return Zv(i,u,t.shape.length,Tt[t.dtype],d,h,M1[r],l),o}var cte={kernelName:Di,backendName:"wasm",kernelFunc:pte,setupFunc:dte},hte=!0,fte=la(zi,hte),mte=Bt(Vl);function _3(e,t){let a=new Int32Array(e.wasm.HEAPU8.buffer,t,4),n=a[0],r=a[1],s=a[2],i=a[3];return e.wasm._free(t),{pSelectedIndices:n,selectedSize:r,pSelectedScores:s,pValidOutputs:i}}var Yv;function gte(e){Yv=e.wasm.cwrap(Bi,"number",["number","number","number","number","number"])}function xte(e){let{backend:t,inputs:a,attrs:n}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i}=n,{boxes:o,scores:l}=a,u=t.dataIdMap.get(o.dataId).id,p=t.dataIdMap.get(l.dataId).id,c=Yv(u,p,s,r,i),{pSelectedIndices:d,selectedSize:h,pSelectedScores:f,pValidOutputs:m}=_3(t,c);return t.wasm._free(f),t.wasm._free(m),t.makeOutput([h],"int32",d)}var Ate={kernelName:Bi,backendName:"wasm",setupFunc:gte,kernelFunc:xte},Jv;function yte(e){Jv=e.wasm.cwrap(Ul,"number",["number","number","number","number","number","bool"])}function bte(e){let{backend:t,inputs:a,attrs:n}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,padToMaxOutputSize:o}=n,{boxes:l,scores:u}=a,p=t.dataIdMap.get(l.dataId).id,c=t.dataIdMap.get(u.dataId).id,d=Jv(p,c,s,r,i,o),{pSelectedIndices:h,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=_3(t,d);t.wasm._free(m);let x=t.makeOutput([f],"int32",h),A=t.makeOutput([],"int32",g);return[x,A]}var vte={kernelName:Ul,backendName:"wasm",setupFunc:yte,kernelFunc:bte},Qv;function wte(e){Qv=e.wasm.cwrap(Wi,"number",["number","number","number","number","number","number"])}function kte(e){let{backend:t,inputs:a,attrs:n}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,softNmsSigma:o}=n,{boxes:l,scores:u}=a,p=t.dataIdMap.get(l.dataId).id,c=t.dataIdMap.get(u.dataId).id,d=Qv(p,c,s,r,i,o),{pSelectedIndices:h,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=_3(t,d);t.wasm._free(g);let x=t.makeOutput([f],"int32",h),A=t.makeOutput([f],"float32",m);return[x,A]}var Ite={kernelName:Wi,backendName:"wasm",setupFunc:wte,kernelFunc:kte},Ste=!1,Tte=la(Li,Ste,"bool"),e8;function Cte(e){e8=e.wasm.cwrap(Vi,null,["number","number","number","number","number"])}function Nte(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=n,u=a.makeOutput([...r.shape,i],s),p=a.dataIdMap.get(u.dataId).id,c=a.dataIdMap.get(r.dataId).id;return e8(c,i,o,l,p),u}var Ete={kernelName:Vi,backendName:"wasm",setupFunc:Cte,kernelFunc:Nte};function Rte(e){let{inputs:{x:t},backend:a}=e,n=a.makeOutput(t.shape,t.dtype);return a.typedArrayFromHeap(n).fill(1),n}var Mte={kernelName:Gl,backendName:"wasm",kernelFunc:Rte};function $te(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return R1({inputs:{input:t[0]},backend:a,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{v.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===p.dtype,()=>"All tensors passed to stack must have matching 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Dae={kernelName:Ql,backendName:"wasm",kernelFunc:Oae},zae=Bt(no),Lae=Bt(Bd),Bae=!0,Wae=la(io,Bae),A8;function Vae(e){A8=e.wasm.cwrap(fo,null,["number","number","number","number"])}function Uae(e){let{backend:t,inputs:a,attrs:n}=e,{alpha:r}=n,{x:s}=a,i=t.dataIdMap.get(s.dataId).id,o=t.makeOutput(s.shape,s.dtype),l=t.dataIdMap.get(o.dataId).id;return A8(i,r,Tt[s.dtype],l),o}var Gae={kernelName:fo,backendName:"wasm",setupFunc:Vae,kernelFunc:Uae},y8;function Hae(e){y8=e.wasm.cwrap(oo,null,["number","array","number","array","array","array","array","array","number","number"])}function jae(e){let{backend:t,inputs:a,attrs:n}=e,{x:r}=a,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:p,newAxisMask:c,shrinkAxisMask:d}=n,{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:x,begin:A,end:y,strides:b}=It.sliceInfo(r.shape,s,i,o,l,u,p,c,d),w;if(m)w=za({inputs:{x:r},backend:t,attrs:{shape:f}});else if(g||x){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, 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Ane(e){let{inputs:{x:t},backend:a}=e,n=a.makeOutput(t.shape,t.dtype);return a.typedArrayFromHeap(n).fill(0),n}var yne={kernelName:nu,backendName:"wasm",kernelFunc:Ane},bne=[jJ,qJ,KJ,JJ,iQ,uQ,cQ,mQ,yQ,SQ,TQ,CQ,RQ,MQ,PQ,DQ,zQ,LQ,VQ,HQ,XQ,YQ,eee,tee,nee,ree,see,iee,uee,dee,cee,mee,Aee,vee,Iee,Cee,Eee,Mee,QJ,$ee,Fee,Dee,Lee,Bee,Vee,Uee,Hee,qee,Zee,Jee,tte,rte,ote,ute,cte,fte,mte,Ate,vte,Ite,Tte,Ete,Mte,_te,a8,Dte,Bte,Ute,Hte,qte,Xte,Kte,Zte,gQ,Qte,aae,sae,lae,uae,dae,hae,gae,yae,bae,kQ,kae,Sae,Nae,Mae,_ae,Fae,Dae,zae,Lae,Wae,Gae,qae,Kae,Yae,Qae,tne,rne,sne,ine,une,cne,mne,nQ,xne,yne];for(let e of bne)mn(e);var $1=W();$1.registerFlag("WASM_HAS_SIMD_SUPPORT",async()=>{try{return WebAssembly.validate(new Uint8Array([0,97,115,109,1,0,0,0,1,4,1,96,0,0,3,2,1,0,10,9,1,7,0,65,0,253,15,26,11]))}catch(e){return!1}});$1.registerFlag("WASM_HAS_MULTITHREAD_SUPPORT",async()=>{if($1.get("IS_NODE"))return!1;try{return new MessageChannel().port1.postMessage(new SharedArrayBuffer(1)),WebAssembly.validate(new Uint8Array([0,97,115,109,1,0,0,0,1,4,1,96,0,0,3,2,1,0,5,4,1,3,1,1,10,11,1,9,0,65,0,254,16,2,0,26,11]))}catch(e){return!1}});var Ox=yl(nS()),vne=yl(rS()),Dx=yl(sS()),zx=Ox.default||Ox,wne=Dx.default||Dx,I8=class extends bl{constructor(e){super(),this.wasm=e,this.dataIdNextNumber=1,this.wasm.tfjs.initWithThreadsCount(S8),_1=this.wasm.tfjs.getThreadsCount(),this.dataIdMap=new vd(this,kt())}write(e,t,a){let n={id:this.dataIdNextNumber++};return this.move(n,e,t,a,1),n}numDataIds(){return this.dataIdMap.numDataIds()}async time(e){let t=v.now();return e(),{kernelMs:v.now()-t}}move(e,t,a,n,r){let s=this.dataIdNextNumber++;if(n==="string"){let u=t;this.dataIdMap.set(e,{id:s,stringBytes:u,shape:a,dtype:n,memoryOffset:null,refCount:r});return}let i=v.sizeFromShape(a),o=i*v.bytesPerElement(n),l=this.wasm._malloc(o);this.dataIdMap.set(e,{id:s,memoryOffset:l,shape:a,dtype:n,refCount:r}),this.wasm.tfjs.registerTensor(s,i,l),t!=null&&this.wasm.HEAPU8.set(new Uint8Array(t.buffer,t.byteOffset,o),l)}async read(e){return this.readSync(e)}readSync(e,t,a){let{memoryOffset:n,dtype:r,shape:s,stringBytes:i}=this.dataIdMap.get(e);if(r==="string")return(t==null||t===0)&&(a==null||a>=i.length)?i:i.slice(t,a);t=t||0,a=a||v.sizeFromShape(s);let o=v.bytesPerElement(r),l=this.wasm.HEAPU8.slice(n+t*o,n+a*o);return Sne(l.buffer,r)}disposeData(e,t=!1){if(this.dataIdMap.has(e)){let a=this.dataIdMap.get(e);if(a.refCount--,!t&&a.refCount>0)return!1;this.wasm._free(a.memoryOffset),this.wasm.tfjs.disposeData(a.id),this.dataIdMap.delete(e)}return!0}refCount(e){return this.dataIdMap.has(e)?this.dataIdMap.get(e).refCount:0}incRef(e){let t=this.dataIdMap.get(e);t!=null&&t.refCount++}floatPrecision(){return 32}getMemoryOffset(e){return this.dataIdMap.get(e).memoryOffset}dispose(){this.wasm.tfjs.dispose(),"PThread"in this.wasm&&this.wasm.PThread.terminateAllThreads(),this.wasm=null}memory(){return{unreliable:!1}}makeOutput(e,t,a){let n;if(a==null)n=this.write(null,e,t);else{let r=this.dataIdNextNumber++;n={id:r},this.dataIdMap.set(n,{id:r,memoryOffset:a,shape:e,dtype:t,refCount:1});let s=v.sizeFromShape(e);this.wasm.tfjs.registerTensor(r,s,a)}return{dataId:n,shape:e,dtype:t}}typedArrayFromHeap({shape:e,dtype:t,dataId:a}){let n=this.wasm.HEAPU8.buffer,{memoryOffset:r}=this.dataIdMap.get(a),s=v.sizeFromShape(e);switch(t){case"float32":return new Float32Array(n,r,s);case"int32":return new Int32Array(n,r,s);case"bool":return new Uint8Array(n,r,s);default:throw new Error(`Unknown dtype ${t}`)}}};function kne(e){return(t,a)=>(v.fetch(e,{credentials:"same-origin"}).then(n=>{n.ok||t.env.a(`failed to load wasm binary file at '${e}'`),n.arrayBuffer().then(r=>{WebAssembly.instantiate(r,t).then(s=>{a(s.instance,s.module)})})}),{})}function Lx(e,t,a){if(Bc!=null)return Bc;let n="tfjs-backend-wasm.wasm";return e&&t?n="tfjs-backend-wasm-threaded-simd.wasm":e&&(n="tfjs-backend-wasm-simd.wasm"),ed!=null&&ed[n]!=null?ed[n]:a+n}async function Ine(){let[e,t]=await Promise.all([W().getAsync("WASM_HAS_SIMD_SUPPORT"),W().getAsync("WASM_HAS_MULTITHREAD_SUPPORT")]);return new Promise((a,n)=>{let r={};r.locateFile=(o,l)=>{if(o.endsWith(".worker.js")){let u=vne.wasmWorkerContents.replace(/\n/g,"\\n"),p=new Blob([u],{type:"application/javascript"});return URL.createObjectURL(p)}return o.endsWith(".wasm")?Lx(e,t,Yu!=null?Yu:l):l+o},P3&&(r.instantiateWasm=kne(Lx(e,t,Yu!=null?Yu:"")));let s=!1;r.onAbort=()=>{s||td||(td=!0,n({message:"Make sure the server can serve the `.wasm` file relative to the bundled js file. 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Make sure you call `setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`");Bc=e,P3=t}function Wh(e,t=!1){if(td)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPaths()` before you call `tf.setBackend()` or `tf.ready()`");if(typeof e=="string")Yu=e;else{ed=e;let a=Tne.filter(n=>ed[n]==null);if(a.length>0)throw new Error(`There were no entries found for the following binaries: ${a.join(",")}. Please either call setWasmPaths with a map providing a path for each binary, or with a string indicating the directory where all the binaries can be found.`)}P3=t}var S8=-1,_1=-1;function Nne(e){S8=e}function Ene(){if(_1===-1)throw new Error("WASM backend not initialized.");return _1}var Rne="4.1.0",Mne=2;go("wasm",async()=>{let{wasm:e}=await Ine();return new I8(e)},Mne);var zn=W();zn.registerFlag("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE",()=>15);zn.registerFlag("WEBGPU_CPU_FORWARD",()=>!0);zn.registerFlag("WEBGPU_MATMUL_PROGRAM_TYPE",()=>-1);zn.registerFlag("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE",()=>!1);zn.registerFlag("WEBGPU_USE_LOW_POWER_GPU",()=>!1);zn.registerFlag("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e3);zn.registerFlag("WEBGPU_USE_PROFILE_TOOL",()=>!1);zn.registerFlag("WEBGPU_IMPORT_EXTERNAL_TEXTURE",()=>!0);zn.registerFlag("WEBGPU_USE_NAIVE_CONV2D_DEBUG",()=>!1);zn.registerFlag("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL",()=>0);zn.registerFlag("WEBGPU_CONV_SEPARATE_IM2COL_SHADER",()=>!1);var $ne=class{constructor(e){e&&(this.vendor=e.vendor,this.architecture=e.architecture,this.intelGPUGeneration=this.getIntelGPUGeneration())}getIntelGPUGeneration(){if(this.isIntel()){if(this.architecture.startsWith("gen"))return Number(this.architecture.match(/\d+/));if(this.architecture.startsWith("xe"))return 12}return 0}isIntel(){return this.vendor==="intel"}},_ne=class{constructor(e){this.device=e,this.numUsedBuffers=0,this.numFreeBuffers=0,this.freeBuffers=new Map,this.usedBuffers=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireUploadBuffer(e,t){return this.acquireBuffer(e,t,!0)}acquireBuffer(e,t,a=!1){let n=Bx(e,t);if(this.freeBuffers.has(n)||this.freeBuffers.set(n,[]),this.usedBuffers.has(n)||this.usedBuffers.set(n,[]),this.numBytesUsed+=e,this.numUsedBuffers++,this.freeBuffers.get(n).length>0){this.numFreeBuffers--;let s=this.freeBuffers.get(n).shift();return this.usedBuffers.get(n).push(s),s}this.numBytesAllocated+=e;let r=this.device.createBuffer({size:e,usage:t,mappedAtCreation:a});return this.usedBuffers.get(n).push(r),r}releaseBuffer(e,t,a){if(this.freeBuffers.size===0)return;let n=Bx(t,a);this.freeBuffers.has(n)||this.freeBuffers.set(n,[]),this.freeBuffers.get(n).push(e),this.numFreeBuffers++,this.numUsedBuffers--;let r=this.usedBuffers.get(n),s=r.indexOf(e);if(s<0)throw new Error("Cannot release a buffer that was never provided by this buffer manager");r.splice(s,1),this.numBytesUsed-=t}releaseUploadBuffer(e,t,a){e.mapAsync(GPUMapMode.WRITE).then(()=>{this.releaseBuffer(e,t,a)},n=>{})}getNumUsedBuffers(){return this.numUsedBuffers}getNumFreeBuffers(){return this.numFreeBuffers}dispose(){this.freeBuffers.forEach((e,t)=>{e.forEach(a=>{a.destroy()})}),this.usedBuffers.forEach((e,t)=>{e.forEach(a=>{a.destroy()})}),this.freeBuffers=new Map,this.usedBuffers=new Map,this.numUsedBuffers=0,this.numFreeBuffers=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function Bx(e,t){return`${e}_${t}`}var Pne=class{constructor(e){this.device=e,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures=new Map,this.usedTextures=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireTexture(e,t,a,n){let r=Vx(a),s=e*t*r,i=Wx(e,t,a,n);if(this.freeTextures.has(i)||this.freeTextures.set(i,[]),this.usedTextures.has(i)||this.usedTextures.set(i,[]),this.numBytesUsed+=s,this.numUsedTextures++,this.freeTextures.get(i).length>0){this.numFreeTextures--;let l=this.freeTextures.get(i).shift();return this.usedTextures.get(i).push(l),l}this.numBytesAllocated+=s;let o=this.device.createTexture({size:[e,t],format:a,usage:n});return this.usedTextures.get(i).push(o),o}releaseTexture(e,t,a,n,r){if(this.freeTextures.size===0)return;let s=Wx(t,a,n,r);this.freeTextures.has(s)||this.freeTextures.set(s,[]),this.freeTextures.get(s).push(e),this.numFreeTextures++,this.numUsedTextures--;let i=this.usedTextures.get(s),o=i.indexOf(e);if(o<0)throw new Error("Cannot release a texture that was never provided by this texture manager");i.splice(o,1);let l=Vx(n),u=t*a*l;this.numBytesUsed-=u}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){this.freeTextures.forEach((e,t)=>{e.forEach(a=>{a.destroy()})}),this.usedTextures.forEach((e,t)=>{e.forEach(a=>{a.destroy()})}),this.freeTextures=new Map,this.usedTextures=new Map,this.numUsedTextures=0,this.numFreeTextures=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function Wx(e,t,a,n){return`${e}_${t}_${a}_${n}`}function Vx(e){if(e==="rgba8unorm")return 16;throw new Error(`${e} is not supported!`)}function Fne(e,t){if(Math.max(...e)>3)throw new Error("Cannot symbolically compute strides for rank > 4 tensor.");let a=e.length,n=e.map(s=>`${t}[${s}]`),r=new Array(a-1);r[a-2]=n[a-1];for(let s=a-3;s>=0;--s)r[s]=`(${r[s+1]} * ${n[s+1]})`;return r}var One=(e,t,a,n)=>{let r={dtype:n.dtype,shape:n.shape},s=zne(a,r,t),i=e.createShaderModule({code:s,label:t.constructor.name});return e.createComputePipeline({compute:{module:i,entryPoint:"_start"},label:t.constructor.name,layout:"auto"})};function ra(e){if(e<=1)return"i32";if(e===2)return"vec2<i32>";if(e===3)return"vec3<i32>";if(e===4)return"vec4<i32>";if(e===5)return"vec5";if(e===6)return"vec6";throw Error(`GPU for rank ${e} is not yet supported`)}function yr(e){if(e===0)return"x";if(e===1)return"y";if(e===2)return"z";if(e===3)return"w";if(e===4)return"u";if(e===5)return"v";throw Error(`Index ${e} is not yet supported`)}function Ce(...e){let t;switch(e.length){case 0:t=`
fn main()
`;break;case 1:t=`
fn main(${e[0]} : i32)
`;break;default:throw Error("Unreachable")}return t}function Ux(e){let t;return t=`
${Dne()}
fn _start(@builtin(local_invocation_id) LocalId : vec3<u32>,
@builtin(global_invocation_id) GlobalId : vec3<u32>,
@builtin(local_invocation_index) LocalIndex: u32,
@builtin(workgroup_id) WorkgroupId : vec3<u32>,
@builtin(num_workgroups) NumWorkgroups : vec3<u32>) {
localId = LocalId;
localIndex = LocalIndex;
globalId = GlobalId;
numWorkgroups = NumWorkgroups;
workgroupId = WorkgroupId;
${e?"main(getGlobalIndex());":"main();"};
}
`,t}function Dne(){return`
@compute @workgroup_size(workgroupSizeX, workgroupSizeY, workgroupSizeZ)
`}function zne(e,t,a){let n=[],r=a.workgroupSize[0]*a.workgroupSize[1]*a.workgroupSize[2];if(n.push(`
const workgroupSizeX = ${a.workgroupSize[0]}u;
const workgroupSizeY = ${a.workgroupSize[1]}u;
const workgroupSizeZ = ${a.workgroupSize[2]}u;
var<private> localId: vec3<u32>;
var<private> localIndex: u32;
var<private> globalId: vec3<u32>;
var<private> numWorkgroups: vec3<u32>;
var<private> workgroupId: vec3<u32>;
// Only used when the y/z dimension of workgroup size is 1.
fn getGlobalIndex() -> i32 {
${T8(a)?" return i32(globalId.x);":` return i32((workgroupId.z * numWorkgroups.x * numWorkgroups.y +
workgroupId.y * numWorkgroups.x + workgroupId.x) * ${r} +
localIndex);
`}
}
`),a.isFromPixels){n.push(`
struct Uniform {
size : i32,
numChannels : i32,
outShapeStrides : vec2<i32>,
};
@group(0) @binding(0) var<storage, read_write> result: array<${ad(t.dtype,a.isVec4)}>;
@group(0) @binding(2) var<uniform> uniforms: Uniform;
`);let h=jx(a);return[Gx,n.join(`
`),Hx(t.shape),a.getUserCode(),Ux(h)].join(`
`)}let s="struct Uniforms { NAN : f32, INFINITY : f32, ";a.variableNames.forEach((h,f)=>{let m=ra(e[f].shape.length);s+=`${h.charAt(0).toLowerCase()+h.slice(1)}Shape : ${m}, `});let i=ra(t.shape.length);s+=`outShape : ${i}, `;let o=t.shape.length-1,l=ra(o);s+=`
outShapeStrides: ${l}, `,a.size&&(s+="size : i32, "),a.uniforms&&(s+=a.uniforms),s+="};",s=qne(s),n.push(s),a.atomic?n.push(`
@group(0) @binding(0) var<storage, read_write> result: array<atomic<i32>>;
`):n.push(`
@group(0) @binding(0) var<storage, read_write> result: array<${ad(t.dtype,a.isVec4)}>;
`),a.variableNames.forEach((h,f)=>{n.push(`
@group(0) @binding(${1+f}) var<storage, read> ${h}: array<${a.variableTypes?a.variableTypes[f]:ad(e[f].dtype,a.isVec4)}>;
`)}),s!==""&&n.push(`
@group(0) @binding(${1+a.variableNames.length}) var<uniform> uniforms: Uniforms;
`);let u=Gne(t.shape,a.dispatchLayout),p=[Gx+Bne,n.join(`
`),Hx(t.shape),u,Hne(t.shape.length)];a.atomic||p.push(jne(t.shape,t.dtype,a.isVec4));let c=e.map((h,f)=>Une(h,t.shape,a.variableTypes?a.variableTypes[f]==="vec4<f32>":a.isVec4,a.dispatchLayout.x.length===t.shape.length)).join(`
`);p.push(c),p.push(a.getUserCode());let d=jx(a);return p.push(Ux(d)),p.join(`
`)}function Lne(e,t,a,n){let r=e.shaderKey;if(e.isFromPixels)return r;let s=a.map(p=>p.dtype).concat(n.dtype),i=a.map(p=>T.getBroadcastDims(p.shape,n.shape)),o=a.map(p=>v.arraysEqual(p.shape,n.shape)).join("_"),l=i.map(p=>p.join("_")).join(";"),u=T8(e)?"flatDispatch":"";return r+="_"+(e.workgroupSize?e.workgroupSize.join(","):"")+t.map(p=>p.length).join(",")+s.join(",")+e.variableNames.join(",")+l+o+u,r}var Gx=`
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]));
}
`,Bne=`
fn isinf(val: f32) -> bool {
return abs(val) == uniforms.INFINITY;
}
`;function Hx(e){let t=e.length;if(t<=1)return"fn getCoordsFromIndex(index : i32) -> i32 { return index; }";let a=v.computeStrides(e),n=ra(t),r=[];for(let i=0;i<t;i++)r.push(`d${i}`);if(a.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;"+a.map((i,o)=>{let l=`let ${r[o]} = index2 / uniforms.outShapeStrides.${yr(o)}`,u=o===a.length-1?`let ${r[o+1]} = index2 - ${r[o]} * uniforms.outShapeStrides.${yr(o)}`:`index2 = index2 - ${r[o]} * uniforms.outShapeStrides.${yr(o)}`;return`${l}; ${u};`}).join(""),`
fn getCoordsFromIndex(index : i32) -> ${n} {
${s}
return ${n}(${r.join(",")});
}
`}function Wne(e,t){let a=e.name,n=e.shape.length,r=ra(n),s="get"+a.charAt(0).toUpperCase()+a.slice(1),i=["d0","d1","d2","d3","d4","d5"].slice(0,n),o=i.map(p=>`${p} : i32`).join(", ");if(n<1)return t?`
fn ${s}() -> vec4<f32> {
return vec4<f32>(${a}[0]);
}
`:`
fn ${s}() ->f32 {
return f32(${a}[0]);
}
`;let l=`uniforms.${a.charAt(0).toLowerCase()+a.slice(1)}Shape`,u=`${n}D`;return n===0&&(u="1D"),t?`
fn ${s}(${o}) -> vec4<f32> {
return vec4<f32>(${a}[getIndexFromCoords${u}(${r}(${i.join(",")}),
${l}) / 4]);
}
`:`
fn ${s}(${o}) -> f32 {
return f32(${a}[getIndexFromCoords${u}(${r}(${i.join(",")}),
${l})]);
}
`}function Vne(e,t,a,n){let r=e.name,s=r.charAt(0).toUpperCase()+r.slice(1),i="get"+s+"ByOutput",o=e.shape.length,l=t.length,u=ra(l);if(v.arraysEqual(e.shape,t)&&n)return a?`
fn ${i}Index(globalIndex : i32) -> vec4<f32> {
return vec4<f32>(${r}[globalIndex]);
}
fn ${i}Coords(coords : ${u}) -> vec4<f32> {
return vec4<f32>(${r}[${l>1?"getOutputIndexFromCoords(coords)":"coords"} / 4]);
}
`:`
fn ${i}Index(globalIndex : i32) -> f32 {
return f32(${r}[globalIndex]);
}
fn ${i}Coords(coords : ${u}) -> f32 {
return f32(${r}[${l>1?"getOutputIndexFromCoords(coords)":"coords"}]);
}
`;let p=T.getBroadcastDims(e.shape,t),c=l-o,d="";if(o===0)return a?`
fn ${i}Index(globalIndex : i32) -> vec4<f32> {
return get${s}();
}
fn ${i}Coords(coords : ${u}) -> vec4<f32> {
return get${s}();
}
`:`
fn ${i}Index(globalIndex : i32) -> f32{
return get${s}();
}
fn ${i}Coords(coords : ${u}) -> f32{
return get${s}();
}
`;l<2&&p.length>=1?d="coords = 0;":d=p.map(g=>`coords.${yr(g+c)} = 0;`).join(`
`);let h="";if(l<2&&o>0)h="coords";else if(l>1){let g=ra(o),x=e.shape.map((A,y)=>`coords.${yr(y+c)}`).join(", ");h=`${g}(${x})`}else h="coords";let f=`uniforms.${r.charAt(0).toLowerCase()+r.slice(1)}Shape`,m=`${o}D`;return a?`
fn ${i}Index(globalIndex : i32) -> vec4<f32> {
var coords = getCoordsFromIndex(globalIndex);
${d}
return ${r}[getIndexFromCoords${m}(${h}, ${f}) / 4];
}
fn ${i}Coords(coordsIn : ${u}) -> vec4<f32> {
var coords = coordsIn;
${d}
return ${r}[getIndexFromCoords${m}(${h}, ${f}) / 4];
}
`:`
fn ${i}Index(globalIndex : i32) -> f32 {
var coords = getCoordsFromIndex(globalIndex);
${d}
return f32(${r}[getIndexFromCoords${m}(${h}, ${f})]);
}
fn ${i}Coords(coordsIn : ${u}) -> f32 {
var coords = coordsIn;
${d}
return f32(${r}[getIndexFromCoords${m}(${h}, ${f})]);
}
`}function Une(e,t,a,n){let r=Wne(e,a);return e.shape.length<=t.length&&(r+=Vne(e,t,a,n)),r}function Gne(e,t){let{x:a,y:n=[],z:r=[]}=t,s=e.length,i=a.length+n.length+r.length;if(i!==s)return"";if(a.length===s)return`fn getOutputCoords() -> ${ra(s)}{
let globalIndex = getGlobalIndex();
return getCoordsFromIndex(globalIndex);
}
`;let o="",l=[a,n,r];for(let d=0;d<l.length;d++){let h=l[d];if(h.length!==0)if(h.length===1)o+=`let d${h[0]} = i32(globalId[${d}]);`;else{let f=Fne(h,"uniforms.outShape");o+=`var index${d} = i32(globalId[${d}]);`;for(let m=0;m<f.length;m++)o+=`let d${h[m]} = index${d} / ${f[m]};`,m===f.length-1?o+=`let d${h[m+1]} = index${d} - d${h[m]} * ${f[m]};`:o+=`index${d} = index${d} - d${h[m]} * ${f[m]};`}}let u=[];for(let d=0;d<i;d++)u.push(`d${d}`);let p=ra(i),c=`fn getOutputCoords() -> ${p} {
${o}
`;return u.length===0?c+=`return ${p}(0); }`:c+=`return ${p}(${u.join(",")}); }`,c}function Hne(e){let t="";switch(e){case 0:case 1:t+=`
fn getOutputIndexFromCoords(coords : i32) -> i32 {
return coords;
}
`;break;case 2:t+=`
fn getOutputIndexFromCoords(coords : vec2<i32>) -> i32 {
return dot(coords, vec2<i32>(uniforms.outShapeStrides, 1));
}
`;break;case 3:t+=`
fn getOutputIndexFromCoords(coords : vec3<i32>) -> i32 {
return dot(coords, vec3<i32>(uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, 1));
}
`;break;case 4:t+=`
fn getOutputIndexFromCoords(coords : vec4<i32>) -> i32 {
return dot(coords, vec4<i32>(
uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, uniforms.outShapeStrides.z, 1));
}
`;break;case 5:t+=`
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:t+=`
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:v.assert(!1,()=>`Unsupported ${e}D shape`);break}return t}function T8(e){return e.dispatch[1]===1&&e.dispatch[2]===1}function ad(e,t){return e==="float32"?t?"vec4<f32>":"f32":e==="int32"||e==="bool"?t?"vec4<i32>":"i32":e}function jne(e,t,a){let n=e.length,r=ad(t,a),s;if(a?s=`fn setOutputAtIndex(flatIndex : i32, value : vec4<f32>) {
result[flatIndex] = ${r}(value);
}
fn setOutputAtIndexI32(flatIndex : i32, value : vec4<i32>) {
result[flatIndex] = ${r}(value);
}`:s=`fn setOutputAtIndex(flatIndex : i32, value : f32) {
result[flatIndex] = ${r}(value);
}
fn setOutputAtIndexI32(flatIndex : i32, value : i32) {
result[flatIndex] = ${r}(value);
}`,n>=2){let i=["d0","d1","d2","d3","d4","d5"].slice(0,n),o=ra(n);a?s+=`
fn setOutputAtCoords(${i.map(l=>`${l} : i32`).join(", ")}, value : vec4<f32>) {
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
setOutputAtIndex(flatIndex / 4, value);
}
fn setOutputAtCoordsI32(${i.map(l=>`${l} : i32`).join(", ")}, value : vec4<i32>) {
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
setOutputAtIndexI32(flatIndex / 4, value);
}
`:s+=`
fn setOutputAtCoords(${i.map(l=>`${l} : i32`).join(", ")}, value : f32) {
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
setOutputAtIndex(flatIndex, value);
}
fn setOutputAtCoordsI32(${i.map(l=>`${l} : i32`).join(", ")}, value : i32) {
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
setOutputAtIndexI32(flatIndex, value);
}
`}return s}function qne(e){let t=/(\w+)\s*:\s*vec(5|6)/g;e=e.replace(t,n=>"@align(16) "+n);let a=/vec(5|6)\s*,\s*(\w+)/g;return e=e.replace(a,(n,r,s)=>`vec${r}, @align(16) ${s}`),e}function jx(e){return!(e.dispatchLayout.hasOwnProperty("y")&&e.dispatchLayout.y.length!==0||e.dispatchLayout.hasOwnProperty("z")&&e.dispatchLayout.z.length!==0)}var C8={};Xe(C8,{ArrayBufferToTypedArray:()=>R8,GPUBytesPerElement:()=>E8,MatMulProgramType:()=>Pn,computeDispatch:()=>Ne,computeWorkPerThreadForConv2d:()=>O3,computeWorkgroupInfoForMatMul:()=>N8,computeWorkgroupSizeForConv2d:()=>F3,flatDispatchLayout:()=>Ve,isWebGPUSupported:()=>D3,tilesFitEvenlyIntoShape:()=>Xne});var Ds=e=>{let t=1;for(let a=0;a<e.length;a++)t*=e[a];return t};function Xne(e,t){if(e.length!==t.length)throw new Error(`Cannot compute whether rank ${e.length} tiles fit evenly into rank ${t.length} shape - ranks must match.`);return t.every((a,n)=>a%e[n]===0)}function Ne(e,t,a=[1,1,1],n=[1,1,1]){let[r,s,i]=[Math.ceil(Ds(e.x.map(o=>t[o]))/(a[0]*n[0])),e.y?Math.ceil(Ds(e.y.map(o=>t[o]))/(a[1]*n[1])):1,e.z?Math.ceil(Ds(e.z.map(o=>t[o]))/(a[2]*n[2])):1];return[r,s,i]}function N8(e,t,a,n=!1){let r=[8,8,1],s=[4,4,1];return n||(e<=8&&(s[1]=1),t<=16&&a<=16&&(r[0]=4)),{workgroupSize:r,elementsPerThread:s}}function F3(e,t,a=!1){if(a)return[8,8,1];let n=Ds(e.x.map(s=>t[s])),r=Ds(e.y.map(s=>t[s]));return n<=4?[4,16,1]:r<=4?[16,4,1]:[16,16,1]}function O3(e,t,a=!1){if(a)return[4,4,1];let n=Ds(e.x.map(s=>t[s])),r=Ds(e.y.map(s=>t[s]));return n<=4?[1,2,1]:r<=4?[2,1,1]:[2,2,1]}function Ve(e){return{x:e.map((t,a)=>a)}}function E8(e){if(e==="float32"||e==="int32"||e==="bool"||e==="string")return 4;if(e==="complex64")return 8;throw new Error(`Unknown dtype ${e}`)}function R8(e,t){if(t==="float32")return new Float32Array(e);if(t==="int32")return new Int32Array(e);if(t==="bool"||t==="string")return Uint8Array.from(new Int32Array(e));throw new Error(`Unknown dtype ${t}`)}function D3(){return(typeof window!="undefined"||typeof WorkerGlobalScope!="undefined")&&!!navigator.gpu}var Pn;(function(e){e[e.MatMulReduceProgram=0]="MatMulReduceProgram",e[e.MatMulSplitKProgram=1]="MatMulSplitKProgram",e[e.MatMulSmallOutputSizeProgram=2]="MatMulSmallOutputSizeProgram",e[e.MatMulPackedProgram=3]="MatMulPackedProgram",e[e.MatMulMax=4]="MatMulMax"})(Pn||(Pn={}));var Kne=W().getNumber("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD"),Zne=(e,t)=>{let a=e.limits.maxComputeWorkgroupsPerDimension,n=t.dispatchLayout,r=t.dispatch;if(r.every(i=>i<=a))return r;v.assert(r[0]>a&&n.y===void 0&&n.z===void 0,()=>"Dispatch size exceeds WebGPU limits in Y or Z dimension.");let s=Math.ceil(Math.sqrt(r[0]));return s>a?(s=Math.ceil(Math.cbrt(r[0])),v.assert(s<=a,()=>"Total dispatch size exceeds WebGPU maximum."),[s,s,s]):[s,s,1]},Vh=class extends bl{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,!D3())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 $ne(t),this.thresholdToIncreaseWorkgroups=this.adapterInfo.intelGPUGeneration>=12?16:8,this.bufferManager=new _ne(this.device),this.textureManager=new Pne(this.device),this.tensorMap=new vd(this,kt()),this.supportTimeQuery&&(this.querySet=this.device.createQuerySet({type:"timestamp",count:2})),W().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 Vh.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 a=this.tensorMap.get(e);if(this.decRef(e),!t&&a.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 a=t.resourceInfo;a.texture instanceof GPUTexture&&this.textureManager.releaseTexture(a.texture,a.width,a.height,a.format,a.usage),a.texture=null}else{let a=t.resourceInfo;this.bufferManager.releaseBuffer(a.buffer,a.size,a.usage),a.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,a){if(a==="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:a,shape:t,values:e,refCount:1}),n}move(e,t,a,n,r){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:a,values:t,refCount:r})}submitQueue(){this.ensureComputePassEnded(),this.queue.submit([this.currentCommandEncoder.finish()]),this.currentCommandEncoder=null,this.dispatchNumberInEncoder=0,this.commandQueueOwnedIds=new WeakSet,this.tensorDataPendingDisposal.forEach(e=>{this.releaseResource(e),this.tensorMap.delete(e)}),this.uniformPendingDisposal.forEach(e=>this.bufferManager.releaseBuffer(e.buffer,e.size,e.usage)),this.stagingPendingDisposal.forEach(e=>this.bufferManager.releaseUploadBuffer(e.buffer,e.size,e.usage)),this.tensorDataPendingDisposal=[],this.uniformPendingDisposal=[],this.stagingPendingDisposal=[]}ensureCommandEncoderReady(){this.currentCommandEncoder||(this.currentCommandEncoder=this.device.createCommandEncoder())}ensureComputePassEnded(){this.currentComputePass&&(this.currentComputePass.end(),this.currentComputePass=null)}getComputePass(){return this.currentComputePass||(this.currentComputePass=this.currentCommandEncoder.beginComputePass()),this.currentComputePass}async getBufferData(e,t){let a=this.bufferManager.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(e,0,a,0,t),this.submitQueue(),await a.mapAsync(GPUMapMode.READ);let n=a.getMappedRange().slice(0);return a.unmap(),a!=null&&this.bufferManager.releaseBuffer(a,t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ),W().getBool("WEBGPU_USE_PROFILE_TOOL")&&(v.assert(this.dummyContext!==void 0,()=>"Fail to get context for profiling tool"),this.dummyContext.getCurrentTexture()),n}convertAndCacheOnCPU(e,t){let a=this.tensorMap.get(e);return this.releaseResource(e),a.values=t,a.values}readSync(e){let t=this.tensorMap.get(e),{values:a}=t;if(a==null)throw new Error("WebGPU readSync is only available for CPU-resident tensors.");return a}async read(e){if(!this.tensorMap.has(e))throw new Error(`Tensor ${e} was not registered!`);let t=this.tensorMap.get(e),{values:a}=t;if(a!=null)return this.convertAndCacheOnCPU(e,a);let n;if(t.dtype==="complex64"){let r=await Promise.all([this.read(t.complexTensorInfos.real.dataId),this.read(t.complexTensorInfos.imag.dataId)]),s=r[0],i=r[1];n=T.mergeRealAndImagArrays(s,i)}else{let r=t.resourceInfo,s=await this.getBufferData(r.buffer,r.size);n=R8(s,t.dtype)}return this.convertAndCacheOnCPU(e,n),n}readToGPU(e){let t=this.tensorMap.get(e),{values:a,dtype:n,shape:r,resourceInfo:s}=t;if(n==="complex64")throw new Error("Does not support reading buffer for complex64 dtype.");if(s==null)throw a!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let i=s.size,o=this.bufferManager.acquireBuffer(i,s.usage);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(s.buffer,0,o,0,i),this.submitQueue();let l=this.makeTensorInfo(r,n),u=kt().makeTensorFromTensorInfo(l),p=this.tensorMap.get(l.dataId);return p.resourceInfo={size:i,usage:this.defaultGpuBufferUsage(),buffer:o},{tensorRef:u,buffer:o,bufSize:i}}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let a=t.map(n=>v.decodeString(n));return Me(e.shape,e.dtype,a)}catch(a){throw new Error("Failed to decode encoded string bytes into utf-8")}return Me(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,a=[],n=!1;this.programTimersStack==null?(this.programTimersStack=a,n=!0):this.activeTimers.push(a),this.activeTimers=a,e();let r=v.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),s=v.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=t,n&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},o=await Promise.all(r);return i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", "),this.uploadWaitMs=0,this.downloadWaitMs=0,i}makeTensorInfo(e,t,a){return t==="string"&&a!=null&&a.length>0&&v.isString(a[0])&&(a=a.map(n=>v.encodeString(n))),{dataId:this.write(a,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 a=t.resourceInfo;return{offset:0,size:a.size,buffer:a.buffer}}async getQueryTime(e){return this.supportTimeQuery?this.getTimeFromQuerySet(e):0}uploadToGPU(e){let t=this.tensorMap.get(e);if(t.resourceInfo)return;let a=E8(t.dtype)*v.sizeFromShape(t.shape),n=this.bufferManager.acquireBuffer(a,this.defaultGpuBufferUsage());if(t.resourceInfo={size:a,usage:this.defaultGpuBufferUsage(),buffer:n},t.values){let r=this.bufferManager.acquireUploadBuffer(a,GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC),s=r.getMappedRange();t.dtype==="int32"||t.dtype==="bool"?new Int32Array(s).set(t.values):new Float32Array(s).set(t.values),r.unmap(),this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(r,0,n,0,a);let i={size:a,usage:GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC,buffer:r};this.stagingPendingDisposal.push(i)}}makeUniforms(e){let t=0,a=0,n=[];e.forEach(o=>{o.data.length===0&&(o.data=[1]);let l;switch(o.data.length){case 1:l=4;break;case 2:l=8;break;case 3:l=16;break;case 4:l=16;break;case 5:l=16;break;case 6:l=16;break;default:v.assert(!1,()=>`Unsupported ${o.data.length}D shape`)}(a===5||a===6)&&(l=16),t=Math.ceil(t/l)*l,a=o.data.length,n.push(t),t+=o.data.length*4});let r=new ArrayBuffer(t);e.forEach((o,l)=>{let u=n[l];o.type==="int32"?new Int32Array(r,u,o.data.length).set(o.data):o.type==="uint32"?new Uint32Array(r,u,o.data.length).set(o.data):new Float32Array(r,u,o.data.length).set(o.data)});let s=this.bufferManager.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM);this.queue.writeBuffer(s,0,r,0,t);let i={size:t,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM,buffer:s};return this.uniformPendingDisposal.push(i),{offset:0,size:t,buffer:s}}runWebGPUProgram(e,t,a,n,r){if(r||(r=this.makeTensorInfo(e.outputShape,a)),v.sizeFromShape(r.shape)===0)return this.tensorMap.get(r.dataId).values=v.getTypedArrayFromDType(r.dtype,0),r;this.uploadToGPU(r.dataId),e.dispatch=Zne(this.device,e);let s=[],i=[];if(!e.isFromPixels){s.push({type:"float32",data:[NaN]},{type:"float32",data:[1/0]}),i=t.concat(r).map(g=>g.shape);let f="int32";i.map(g=>{s.push({type:f,data:g})});let m=v.computeStrides(r.shape);if(s.push({type:f,data:m}),e.size){let g=v.sizeFromShape(e.outputShape);s.push({type:f,data:[e.isVec4?g/4:g]})}}let o=t.map((f,m)=>{if(f.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");return this.uploadToGPU(f.dataId),{dtype:this.tensorMap.get(f.dataId).dtype,shape:f.shape,name:e.variableNames[m]}}),l=Lne(e,i,o,r),u;l in this.pipelineCache?u=this.pipelineCache[l]:(u=One(this.device,e,o,r),this.pipelineCache[l]=u),n&&(s=[...s,...n]);let p=[this.tensorToBinding(r),...t.map(f=>this.tensorToBinding(f)),this.makeUniforms(s)],c=this.device.createBindGroup({layout:u.getBindGroupLayout(0),entries:p.map((f,m)=>({binding:m,resource:f}))});this.ensureCommandEncoderReady();let d=this.getComputePass(),h=this.activeTimers!=null;return h&&this.supportTimeQuery&&d.writeTimestamp(this.querySet,0),d.setPipeline(u),d.setBindGroup(0,c),d.dispatchWorkgroups(e.dispatch[0],e.dispatch[1],e.dispatch[2]),h&&this.supportTimeQuery&&d.writeTimestamp(this.querySet,1),this.dispatchNumberInEncoder++,t.forEach(f=>{this.commandQueueOwnedIds.add(f.dataId)}),this.commandQueueOwnedIds.add(r.dataId),W().get("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE")<=this.dispatchNumberInEncoder&&this.submitQueue(),h&&this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(this.querySet)}),r}async getTimeFromQuerySet(e){let t=this.bufferManager.acquireBuffer(16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),a=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,a,0,16),this.submitQueue(),await a.mapAsync(GPUMapMode.READ);let n=new BigUint64Array(a.getMappedRange()),r=Number(n[1]-n[0]);return a.unmap(),this.bufferManager.releaseBuffer(a,16,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST),this.bufferManager.releaseBuffer(t,16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),r/1e6}shouldExecuteOnCPU(e,t=Kne){return W().getBool("WEBGPU_CPU_FORWARD")&&e.every(a=>this.tensorMap.get(a.dataId).resourceInfo==null&&v.sizeFromShape(a.shape)<t)}numDataIds(){return this.tensorMap.numDataIds()-this.tensorDataPendingDisposal.length}dispose(){this.disposed||(this.bufferManager.dispose(),this.textureManager.dispose(),this.disposed=!0)}};Vh.nextDataId=0;D3()&&go("webgpu",async()=>{W().set("CHECK_COMPUTATION_FOR_ERRORS",!1);let e={powerPreference:W().get("WEBGPU_USE_LOW_POWER_GPU")?"low-power":"high-performance"},t=await navigator.gpu.requestAdapter(e),a={};t.features.has("timestamp-query-inside-passes")&&(a.requiredFeatures=["timestamp-query-inside-passes"]);let n=t.limits;a.requiredLimits={maxComputeWorkgroupStorageSize:n.maxComputeWorkgroupStorageSize,maxComputeWorkgroupsPerDimension:n.maxComputeWorkgroupsPerDimension,maxStorageBufferBindingSize:n.maxStorageBufferBindingSize};let r=await t.requestDevice(a),s=await t.requestAdapterInfo();return new Vh(r,s)},3);var De;(function(e){e[e.ADD=0]="ADD",e[e.ATAN2=1]="ATAN2",e[e.COMPLEX_MULTIPLY_IMAG=2]="COMPLEX_MULTIPLY_IMAG",e[e.COMPLEX_MULTIPLY_REAL=3]="COMPLEX_MULTIPLY_REAL",e[e.DIV=4]="DIV",e[e.EQUAL=5]="EQUAL",e[e.GREATER=6]="GREATER",e[e.GREATER_EQUAL=7]="GREATER_EQUAL",e[e.INT_DIV=8]="INT_DIV",e[e.LESS=9]="LESS",e[e.LESS_EQUAL=10]="LESS_EQUAL",e[e.LOGICAL_AND=11]="LOGICAL_AND",e[e.MAX=12]="MAX",e[e.MIN=13]="MIN",e[e.MOD=14]="MOD",e[e.MUL=15]="MUL",e[e.NOT_EQUAL=16]="NOT_EQUAL",e[e.POW=17]="POW",e[e.PRELU=18]="PRELU",e[e.SQUARED_DIFFERENCE=19]="SQUARED_DIFFERENCE",e[e.SUB=20]="SUB"})(De||(De={}));var M8=`
if (isnan(a)) { return a; }
if (isnan(b)) { return b; }
`,$8=`
if (isNaN.r) {
resultTemp.r = valueForNaN;
}
if (isNaN.g) {
resultTemp.g = valueForNaN;
}
if (isNaN.b) {
resultTemp.b = valueForNaN;
}
if (isNaN.a) {
resultTemp.a = valueForNaN;
}
`,z3=`
let isNaN = isnanVec4(a) | isnanVec4(b);
${$8}
`,Yne="return a + b;",Jne="return areal * breal - aimag * bimag;",Qne="return areal * bimag + aimag * breal;",ere="return a / b;",tre="return f32(a == b);",are="return vec4<f32>(a == b);",nre="return f32(a > b);",rre="return vec4<f32>(a > b);",sre="return f32(a >= b);",ire="return vec4<f32>(a >= b);",ore=`
let s = sign(a) * sign(b);
let ia = i32(round(a));
let ib = i32(round(b));
return f32(idiv(ia, ib, s));
`,lre=`
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);
`,ure="return f32(a < b);",dre="return vec4<f32>(a < b);",pre="return f32(a <= b);",cre="return vec4<f32>(a <= b);",hre="return f32(f32(a) >= 1.0 && f32(b) >= 1.0);",fre=`return (vec4<f32>(a >= vec4<f32>(1.0)) *
vec4<f32>(b >= vec4<f32>(1.0)));`,mre=`
${M8}
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;
}
`,gre=`
let valueForNaN = uniforms.NAN;
var resultTemp = vec4<f32>(a % b);
${z3}
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;
`,xre="return a * b;",Are=`
if (isnan(a) || isnan(b)) {
return 1.0;
}
return f32(a != b);
`,yre=`
var resultTemp = vec4<f32>(a != b);
let valueForNaN = 1.0;
${z3}
return resultTemp;
`,bre=`
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);
`,vre=`
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;
${$8}
return resultTemp;
`,wre="if (a < 0.0) { return b * a; } return a;",kre=`
let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
return (aLessThanZero * (b * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
`,Ire="return (a - b) * (a - b);",Sre="return a - b;";function Bm(e,t,a="uniforms.NAN"){let n=t?z3:M8;return t?`
let valueForNaN = ${a};
var resultTemp = vec4<f32>(${e}(a, b));
`+n+`
return resultTemp;
`:n+`
return ${e}(a, b);
`}function L3(e,t){switch(e){case De.ADD:return Yne;case De.ATAN2:return Bm("atan2",t);case De.COMPLEX_MULTIPLY_IMAG:return Qne;case De.COMPLEX_MULTIPLY_REAL:return Jne;case De.DIV:return ere;case De.EQUAL:return t?are:tre;case De.GREATER:return t?rre:nre;case De.GREATER_EQUAL:return t?ire:sre;case De.INT_DIV:return t?lre:ore;case De.LESS:return t?dre:ure;case De.LESS_EQUAL:return t?cre:pre;case De.LOGICAL_AND:return t?fre:hre;case De.MAX:return Bm("max",t);case De.MIN:return Bm("min",t);case De.MOD:return t?gre:mre;case De.MUL:return xre;case De.NOT_EQUAL:return t?yre:Are;case De.POW:return t?vre:bre;case De.PRELU:return t?kre:wre;case De.SQUARED_DIFFERENCE:return Ire;case De.SUB:return Sre;default:throw new Error(`BinaryType ${e} is not implemented!`)}}var de;(function(e){e[e.ABS=0]="ABS",e[e.ACOS=1]="ACOS",e[e.ACOSH=2]="ACOSH",e[e.ASIN=3]="ASIN",e[e.ASINH=4]="ASINH",e[e.ATAN=5]="ATAN",e[e.ATANH=6]="ATANH",e[e.CEIL=7]="CEIL",e[e.COS=8]="COS",e[e.COSH=9]="COSH",e[e.ELU=10]="ELU",e[e.ERF=11]="ERF",e[e.EXP=12]="EXP",e[e.EXPM1=13]="EXPM1",e[e.FLOOR=14]="FLOOR",e[e.IS_FINITE=15]="IS_FINITE",e[e.IS_INF=16]="IS_INF",e[e.IS_NAN=17]="IS_NAN",e[e.LINEAR=18]="LINEAR",e[e.LOG=19]="LOG",e[e.LOG1P=20]="LOG1P",e[e.LOGICAL_NOT=21]="LOGICAL_NOT",e[e.NEG=22]="NEG",e[e.RELU=23]="RELU",e[e.RELU6=24]="RELU6",e[e.LEAKYRELU=25]="LEAKYRELU",e[e.RECIPROCAL=26]="RECIPROCAL",e[e.RSQRT=27]="RSQRT",e[e.SIN=28]="SIN",e[e.SINH=29]="SINH",e[e.SIGMOID=30]="SIGMOID",e[e.SQRT=31]="SQRT",e[e.SQUARE=32]="SQUARE",e[e.TAN=33]="TAN",e[e.TANH=34]="TANH",e[e.TO_INT=35]="TO_INT"})(de||(de={}));var Tre="return abs(a);",Cre=`
if (abs(a) > 1.) {
return uniforms.NAN;
}
return acos(a);
`,Nre=`
if (a < 1.) {
return uniforms.NAN;
}
return acosh(a);
`,Ere=`
if (abs(a) > 1.) {
return uniforms.NAN;
}
return asin(a);
`,Rre="return asinh(a);",Mre=`
if (isnan(a)) {
return uniforms.NAN;
}
return atan(a);
`,$re=`
if (abs(a) > 1.) {
return uniforms.NAN;
}
if (a == 1.) {
return uniforms.INFINITY;
}
if (a == -1.) {
return -uniforms.INFINITY;
}
return atanh(a);
`,_re="return ceil(a);",Pre="return cos(a);",Fre=`
let e2x = exp(-a);
return (e2x + 1.0 / e2x) / 2.0;
`,Ore="return exp(a) - 1.0;",Dre="if (a >= 0.0) { return a; } return (exp(a) - 1.0);",zre=`
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;
`,Lre=`
// Error function is calculated approximately with elementary function.
// See "Handbook of Mathematical Functions with Formulas,
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
let p = ${T.ERF_P};
let a1 = ${T.ERF_A1};
let a2 = ${T.ERF_A2};
let a3 = ${T.ERF_A3};
let a4 = ${T.ERF_A4};
let a5 = ${T.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));
`,Bre="return exp(a);",Wre="return floor(a);",Vre="return f32(!isnan(a) && !isinf(a));",Ure="return f32(isinf(a));",Gre="return f32(isnan(a));",Hre="return a;",jre=`if (a < 0.0) { return uniforms.NAN; }
return log(a);`,qre=`
if (isnan(a)) { return a; }
return log(1.0 + a);
`,Xre="return f32(!(a >= 1.0));",Kre="return -a;",Zre="if (a < 0.0) { return uniforms.alpha * a; } return a;",Yre=`
let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
return (aLessThanZero * (uniforms.alpha * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
`,Jre="return 1.0 / a;",Qre="return select(a, 0.0, a < 0.0);",ese="return clamp(a, 0.0, 6.0);",tse="return clamp(a, vec4<f32>(0.0, 0.0, 0.0, 0.0), vec4<f32>(6.0, 6.0, 6.0, 6.0));",ase=`
return select(a, vec4<f32>(0.0), a < vec4<f32>(0.0));
`,nse="return inverseSqrt(a);",rse="return 1.0 / (1.0 + exp(-1.0 * a));",sse="return sin(a);",ise=`
let e2x = exp(a);
return (e2x - 1.0 / e2x) / 2.0;
`,ose="return sqrt(a);",lse="return a * a;",use="return tan(a);",dse=`
let e2x = exp(-2.0 * abs(a));
return sign(a) * (1.0 - e2x) / (1.0 + e2x);
`,pse="return f32(i32((a)));";function Ms(e,t){switch(e){case de.ABS:return Tre;case de.ACOS:return Cre;case de.ACOSH:return Nre;case de.ASIN:return Ere;case de.ASINH:return Rre;case de.ATAN:return Mre;case de.ATANH:return $re;case de.COS:return Pre;case de.COSH:return Fre;case de.CEIL:return _re;case de.ELU:return t?zre:Dre;case de.ERF:return Lre;case de.EXP:return Bre;case de.EXPM1:return Ore;case de.FLOOR:return Wre;case de.IS_FINITE:return Vre;case de.IS_INF:return Ure;case de.IS_NAN:return Gre;case de.LINEAR:return Hre;case de.LOG:return jre;case de.LOG1P:return qre;case de.LOGICAL_NOT:return Xre;case de.NEG:return Kre;case de.LEAKYRELU:return t?Yre:Zre;case de.RECIPROCAL:return Jre;case de.RELU:return t?ase:Qre;case de.RELU6:return t?tse:ese;case de.RSQRT:return nse;case de.SIGMOID:return rse;case de.SIN:return sse;case de.SINH:return ise;case de.SQRT:return ose;case de.SQUARE:return lse;case de.TAN:return use;case de.TANH:return dse;case de.TO_INT:return pse;default:throw new Error(`BinaryType ${e} is not implemented!`)}}var Mt=e=>{switch(e){case 1:return"f32";case 2:return"vec2<f32>";case 3:return"vec3<f32>";case 4:return"vec4<f32>";default:throw new Error(`${e}-component is not supported.`)}};function Tr(e,t=!1,a=!1,n=3){if(e===null)return"";let r="";if(e==="linear")r=Ms(de.LINEAR);else if(e==="relu")r=Ms(de.RELU,a);else if(e==="elu")r=Ms(de.ELU,a);else if(e==="relu6")r=Ms(de.RELU6,a);else if(e==="prelu")r=L3(De.PRELU,a);else if(e==="sigmoid")r=Ms(de.SIGMOID,a);else if(e==="leakyrelu")r=Ms(de.LEAKYRELU,a);else throw new Error(`Activation ${e} has not been implemented for the WebGPU backend.`);let s=Mt(a?4:1),i="";return t?i=`
fn activation(a : ${s}, coords : vec${n}<i32>) -> ${s} {
let b = getPreluActivationWeightsByOutputCoords(coords);
${r}
}`:i=`
fn activation(a : ${s}, coords : vec${n}<i32>) -> ${s} {
${r}
}`,i}function vo(e,t){return`
${e?"value = value + getBiasByOutputCoords(coords);":""}
${t?"value = activation(value, coords);":""}
`}function _8(e,t,a,n,r=!1,s=!1,i=!1,o=1){v.assert(a&&o===1||!a,()=>`transposeA ${a} is not compatible with component size ${o}`);let l=`
let batch = ${e?"0":"batchIn"};
${a?"value = getA(batch, col, row);":"value = getA(batch, row, col);"}
`,u=n?"value = getB(batch, col, row);":"value = getB(batch, row, col);";return`
fn mm_readA(batchIn: i32, row: i32, colIn: i32) -> ${Mt(o)} {
var value = ${Mt(o)}(0.0);
let col = colIn * ${o};
${r&&i?l:`
${a?"if(row < uniforms.dimAOuter && col < uniforms.dimInner)":"if(row < uniforms.aShape[1] && col < uniforms.aShape[2])"}
{
${l}
}
`}
return value;
}
fn mm_readB(batchIn: i32, row: i32, colIn: i32) -> ${Mt(o)} {
let col = colIn * ${o};
let batch = ${t?"0":"batchIn"};
var value = ${Mt(o)}(0.0);
${u}
return value;
}
`}function B3(e,t,a,n,r,s,i=!1,o=!1,l=!1,u=1){return`
${_8(a,n,r,s,i,o,l,u)}
fn mm_write(batch: i32, row: i32, colIn: i32, valueIn: ${Mt(u)}) {
let col = colIn * ${u};
${i&&o?"":"if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)"}
{
var value = valueIn;
let coords = vec3<i32>(batch, row, col);
${vo(e,t)}
setOutputAtCoords(coords[0], coords[1], coords[2], value);
}
}
`}var cse=e=>e?`
mm_Asub[inputRow][inputCol] = mm_readA(batch,
kStart + inputRow,
globalRowStart / innerElementSize + inputCol);
`:`
mm_Asub[inputRow][inputCol] = mm_readA(batch,
globalRow + innerRow,
kStart / innerElementSize + inputCol);
`,hse=(e,t)=>e?`
let ACached0 = mm_Asub[k * innerElementSize][localRow];
let ACached1 = mm_Asub[k * innerElementSize + 1][localRow];
let ACached2 = mm_Asub[k * innerElementSize + 2][localRow];
${t===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];
${t===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];
${t===3?"":"acc[i] = BCached3 * ACached.w + acc[i];"}
}`;function Uh(e,t,a=!1,n=32,r=!1,s=32,i=!1){let o=t[1]*e[1],l=t[0]*e[0],u=a?o:n,p=a?n:o,c=u/t[0],d=n/t[1];return v.assert((a&&c===4&&e[1]===4||!a&&(c===3||c===4))&&u%t[0]===0&&n%t[1]===0&&e[0]===4,()=>`If transposeA ${a} is true, innerElementSize ${c} and workPerThread[1] ${e[1]} must be 4.
Otherwise, innerElementSize ${c} must be 3 or 4.
tileAWidth ${u} must be divisible by workgroupSize[0]${t[0]}. tileInner ${n} must be divisible by workgroupSize[1] ${t[1]}. colPerThread ${e[0]} must be 4.`),`
var<workgroup> mm_Asub : array<array<vec${c}<f32>, ${u/c}>, ${p}>;
var<workgroup> mm_Bsub : array<array<vec4<f32>, ${l/e[0]}>, ${n}>;
const rowPerThread = ${e[1]};
const colPerThread = ${e[0]};
const innerElementSize = ${c};
const tileInner = ${n};
${Ce()} {
let localRow = i32(localId.y);
let tileRow = ${i?"0":"localRow * rowPerThread"};
let tileCol = i32(localId.x);
let globalRow = ${i?"0":"i32(globalId.y) * rowPerThread"};
let globalCol = i32(globalId.x);
let batch = ${r?"0":"i32(globalId.z)"};
let globalRowStart = i32(workgroupId.y) * ${o};
let numTiles = ${r?`${Math.ceil(s/n)}`:"(uniforms.dimInner - 1) / tileInner + 1"};
var kStart = ${r?`i32(globalId.z) * ${s}`:"0"};
var acc: array<vec4<f32>, rowPerThread>;
// Loop over shared dimension.
let tileRowB = localRow * ${d};
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;
${cse(a)}
}
// Load one tile of B into local memory.
for (var innerRow = 0; innerRow < ${d}; 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];
${c===3?"":"let BCached3 = mm_Bsub[k * innerElementSize + 3][tileCol];"}
${hse(a,c)}
}
workgroupBarrier();
}
for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]);
}
}`}var qx=e=>e?`
mm_Asub[inputRow][inputCol] = mm_readA(batch,
kStart + inputRow,
globalRowStart + inputCol);
`:`
mm_Asub[inputRow][inputCol] = mm_readA(batch,
globalRowStart + inputRow,
kStart + inputCol);
`,fse=e=>e?"let ACached = mm_Asub[k][tileRow + innerRow];":"let ACached = mm_Asub[tileRow + innerRow][k];";function Gh(e,t,a=!1,n=32,r=!1,s=32,i=!1){let o=e[1]*t[1],l=e[0]*t[0],u=a?o:n,p=a?n:o;v.assert(p%t[1]===0&&u%t[0]===0&&n%t[1]===0,()=>`tileAHight ${p} must be divisible by workgroupSize[1]${t[1]}, tileAWidth ${u} must be divisible by workgroupSize[0]${t[0]}, tileInner ${n} must be divisible by workgroupSize[1]${t[1]}`);let c=p/t[1],d=u/t[0],h=n/t[1],f=i?`
let localRow = i32(localId.y);
let localCol = i32(localId.x);
let globalRowStart = i32(workgroupId.y) * ${o};
let globalColStart = i32(workgroupId.x) * ${l};
// 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 < ${p}; inputRow = inputRow + ${t[1]}) {
for (var inputCol = localCol; inputCol < ${u}; inputCol = inputCol + ${t[0]}) {
${qx(a)}
}
}
// Load one tile of B into local memory.
for (var inputRow = localRow; inputRow < ${n}; inputRow = inputRow + ${t[1]}) {
for (var inputCol = localCol; inputCol < ${l}; inputCol = inputCol + ${t[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 * ${t[0]}];
}
for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
let ACached = ${a?`mm_Asub[k][localRow + innerRow * ${t[1]}];`:`mm_Asub[localRow + innerRow * ${t[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 * ${t[1]};
for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) {
let gCol = globalColStart + localCol + innerCol * ${t[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) * ${o};
let tileRowA = i32(localId.y) * ${c};
let tileColA = i32(localId.x) * ${d};
let tileRowB = i32(localId.y) * ${h};
// 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 < ${c}; innerRow = innerRow + 1) {
for (var innerCol = 0; innerCol < ${d}; innerCol = innerCol + 1) {
let inputRow = tileRowA + innerRow;
let inputCol = tileColA + innerCol;
${qx(a)}
}
}
// Load one tile of B into local memory.
for (var innerRow = 0; innerRow < ${h}; 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) {
${fse(a)}
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}>, ${p}>;
var<workgroup> mm_Bsub : array<array<f32, ${l}>, ${n}>;
const rowPerThread = ${e[1]};
const colPerThread = ${e[0]};
const tileInner = ${n};
${Ce()} {
let batch = ${r?"0":"i32(globalId.z)"};
let numTiles = ${r?`${Math.ceil(s/n)}`:"(uniforms.dimInner - 1) / tileInner + 1"};
var kStart = ${r?`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 mse=e=>e?`
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 gse(e,t=!1){return v.assert(e[1]===1&&e[2]===1,()=>`A linear work group size is required. But got ${e}.`),`
const tileSize = ${e[0]*4};
var<workgroup> mm_Asub : array<vec4<f32>, ${e[0]}>;
${Ce()} {
let tileCol = i32(localId.x);
let globalCol = i32(globalId.x);
let globalRow = i32(globalId.y);
let numTiles = (uniforms.dimInner - 1) / tileSize + 1;
let batch = i32(globalId.z);
// Without this initialization strange values show up in acc.
var acc = 0.0;
// Loop over shared dimension.
for (var t = 0; t < numTiles; t = t + 1) {
// Load one tile of A into local memory.
let colA = t * tileSize + tileCol * 4;
mm_Asub[tileCol] = vec4<f32>(${mse(t)});
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 xse=class{constructor(e,t,a,n,r=!1,s=!1,i=null,o=null,l=null,u=!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 p=r?e[1]:e[2];if(this.isVec4=(p%4===0&&!r||t[1]%4===0&&r)&&t[2]%4===0&&!s,this.isVectorA=t[1]===1&&!r,!this.isVec4&&this.isVectorA)this.elementsPerThread=[1,1,1],this.workgroupSize=[32,1,1];else{let h=N8(t[1],p,t[2],r);this.workgroupSize=h.workgroupSize,this.elementsPerThread=h.elementsPerThread}this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread);let c=i!=null,d=l!=null;c&&this.variableNames.push("bias"),d&&this.variableNames.push("preluActivationWeights"),this.sequentialAccessByThreads=u,this.transposeA=r,this.transposeB=s,this.addBias=c,this.activation=o,this.hasPreluActivationWeights=d,this.batchAEqualOne=a,this.batchBEqualOne=n,[this.fitAOuter,this.fitBOuter,this.fitInner]=this.getShapeFit(t[1],t[2],p),this.shaderKey=`matMulPacked_${this.elementsPerThread}_${r}_${s}_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.isVectorA}_${this.batchAEqualOne}_${this.batchBEqualOne}_${this.sequentialAccessByThreads}`}getShapeFit(e,t,a){let n=this.workgroupSize[1]*this.elementsPerThread[1],r=this.workgroupSize[0]*this.elementsPerThread[0];!this.isVec4&&this.isVectorA?this.tileInner=this.workgroupSize[0]*4:this.tileInner=r;let s=e%n===0,i=t%r===0,o=a%this.tileInner===0;return[s,i,o]}getUserCode(){return`
${Tr(this.activation,this.hasPreluActivationWeights,this.isVec4)}
${B3(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,!1,this.transposeB,this.fitAOuter,this.fitBOuter,this.fitInner,this.isVec4?4:1)}
${this.isVec4?Uh(this.elementsPerThread,this.workgroupSize,this.transposeA,this.tileInner,!1,null,this.isVectorA):this.isVectorA?gse(this.workgroupSize,this.transposeA):Gh(this.elementsPerThread,this.workgroupSize,this.transposeA,this.tileInner,!1,null,this.sequentialAccessByThreads)}
`}};function Ase(){return`
var<workgroup> sumValues : array<f32, workgroupSizeX>;
${Ce()} {
let coords = getOutputCoords();
let batch = coords[0];
let row = coords[1];
let col = coords[2];
var sum = 0.0;
let Length = uniforms.dimInner;
for (var k = i32(localId.x); k < Length; k = k + i32(workgroupSizeX)) {
let dataA = mm_readA(batch, row, k);
let dataB = mm_readB(batch, k, col);
sum = sum + dataA * dataB;
}
sumValues[localId.x] = sum;
workgroupBarrier();
for(var currentSize = workgroupSizeX / 2u; currentSize > 1u;
currentSize = currentSize / 2u) {
if (localId.x < currentSize)
{
sumValues[localId.x] = sumValues[localId.x] + sumValues[localId.x + currentSize];
}
workgroupBarrier();
}
if (localId.x == 0u) {
sum = sumValues[0] + sumValues[1];
mm_write(batch, row, col, sum);
}
}
`}var yse=class{constructor(e,t,a,n=!1,r=!1,s=null,i=null,o=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout={x:[],y:[1,2],z:[0]},this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize);let l=s!=null,u=o!=null;l&&this.variableNames.push("bias"),u&&this.variableNames.push("preluActivationWeights"),this.transposeA=n,this.transposeB=r,this.addBias=l,this.activation=i,this.hasPreluActivationWeights=u,this.batchAEqualOne=t,this.batchBEqualOne=a,this.shaderKey=`matMulReduce_${this.activation}_${n}_${r}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getUserCode(){return`
${Tr(this.activation,this.hasPreluActivationWeights)}
${B3(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,this.transposeA,this.transposeB)}
${Ase()}
`}};function bse(e){let t=e[1],a=e[0],n=t>a?t:a;return`
var<workgroup> mm_Asub : array<array<f32, ${n}>, ${t}>;
var<workgroup> mm_Bsub : array<array<f32, ${a}>, ${n}>;
// 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.
${Ce()} {
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) / ${n} + 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 + ${n};
globalRowB = globalRowB + ${n};
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 + ${n};
globalRowB = globalRowB + ${n};
for (var k = 0; k < ${n}; k = k + 1) {
acc = acc + mm_Asub[tileRow][k] * mm_Bsub[k][tileCol];
}
workgroupBarrier();
}
mm_write(batch, globalRow, globalCol, acc);
}
`}var vse=class{constructor(e,t,a,n=!1,r=!1,s=null,i=null,o=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[16,8,1],this.outputShape=a,this.dispatchLayout={x:[2],y:[1],z:[0]},this.dispatch=[Math.ceil(a[2]/this.workgroupSize[0]),Math.ceil(a[1]/this.workgroupSize[1]),a[0]];let l=s!=null;l&&this.variableNames.push("bias");let u=o!=null;u&&this.variableNames.push("preluActivationWeights"),this.transposeA=n,this.transposeB=r,this.addBias=l,this.activation=i,this.hasPreluActivationWeights=u,this.batchAEqualOne=e[0]===1,this.batchBEqualOne=t[0]===1,this.shaderKey=`matMulSmallOutputSize_${this.activation}_${n}_${r}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getUserCode(){return`
${Tr(this.activation,this.hasPreluActivationWeights)}
${B3(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,this.transposeA,this.transposeB)}
${bse(this.workgroupSize)}
`}},wse=class{constructor(e,t,a,n,r=!1,s=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[8,8,1],this.atomic=!0,this.isVec4=!1,this.splitedDimInner=128,v.assert(e[0]===1,()=>"MatMulSplitKProgram only supports batch = 1."),this.outputShape=e,this.dispatchLayout={x:[2],y:[1],z:[0,3]},this.isVec4=(r&&this.outputShape[1]%4===0||!r&&t%4===0)&&this.outputShape[2]%4===0,this.elementsPerThread=[4,4,this.splitedDimInner],this.isVec4||(this.outputShape[1]<16&&(this.elementsPerThread[1]=1),this.outputShape[2]<16&&(this.elementsPerThread[0]=1)),this.dispatch=Ne(this.dispatchLayout,[this.outputShape[0],this.outputShape[1],this.outputShape[2],t],this.workgroupSize,this.elementsPerThread),this.transposeA=r,this.transposeB=s,this.batchAEqualOne=a,this.batchBEqualOne=n,this.shaderKey=`matMulSplitK_${r}_${s}_${a}_${n}_${this.elementsPerThread}_${this.isVec4}`}getUserCode(){let e=a=>`
for (var i = 0; i < ${a}; i = i + 1)
{
var oldValue = atomicLoad(&(result[flatIndex + i]));
var exchanged = false;
for (; !exchanged;) {
let newValueF32 = bitcast<f32>(oldValue) + ${a>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`
${_8(this.batchAEqualOne,this.batchBEqualOne,!1,this.transposeB,!1,!1,!1,t)}
fn mm_write(batch: i32, row : i32, colIn : i32, value : ${Mt(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)}
}
}
${this.isVec4?Uh(this.elementsPerThread,this.workgroupSize,this.transposeA,32,!0,this.splitedDimInner):Gh(this.elementsPerThread,this.workgroupSize,this.transposeA,32,!0,this.splitedDimInner)}
`}},kse=class{constructor(e,t=null,a=null,n=null){this.uniforms="",this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.addBias=t!=null,this.hasPreluActivationWeights=n!=null,this.activation=a,this.addBias&&this.variableNames.push("bias"),this.hasPreluActivationWeights&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`biasActivation_${a}`}getUserCode(){return`
${Tr(this.activation,this.hasPreluActivationWeights)}
${Ce("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
var value = getXByOutputIndex(index);
${vo(this.addBias,this.activation)}
setOutputAtIndex(index, value);
}
}
`}},Ise=class{constructor(e){this.variableNames=[],this.outputShape=[],this.uniforms="value : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="fill"}getUserCode(){return`
${Ce("index")} {
if (index < uniforms.size) {
setOutputAtIndex(index, uniforms.value);
}
}
`}};function Cr(e){let{backend:t,attrs:a}=e,{shape:n,value:r}=a,{dtype:s}=a;if(s=s||v.inferDtype(r),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(n));return i.fill(r),t.makeTensorInfo(n,s,i)}else{let i=new Ise(n),o=[{type:"float32",data:[r]}];return t.runWebGPUProgram(i,[],s,o)}}var Sse={kernelName:Fl,backendName:"webgpu",kernelFunc:Cr};function Ie(e){let{inputs:t,attrs:a}=e,{x:n}=t,{shape:r}=a,s=v.sizeFromShape(n.shape),i=v.inferFromImplicitShape(r,s),o=v.sizeFromShape(i);return v.assert(s===o,()=>`The new shape (${i}) has ${o} elements and the old shape (${n.shape}) has ${s} elements. The new shape and old shape must have the same number of elements.`),e.backend.incRef(n.dataId),{dataId:n.dataId,shape:i,dtype:n.dtype}}var Tse={kernelName:ql,backendName:"webgpu",kernelFunc:Ie};function Hh({a:e,b:t,transposeA:a,transposeB:n,backend:r,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,p=t.shape.length,c=a?e.shape[u-2]:e.shape[u-1],d=n?t.shape[p-1]:t.shape[p-2],h=a?e.shape[u-1]:e.shape[u-2],f=n?t.shape[p-2]:t.shape[p-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),x=v.sizeFromShape(m),A=v.sizeFromShape(g),y=xo.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,f]);v.assert(c===d,()=>`Error in matMul: inner shapes (${c}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${a} and transposeB=${n} must match.`);let b=a?[x,c,h]:[x,h,c],w=n?[A,f,d]:[A,d,f],S=Ie({inputs:{x:e},backend:r,attrs:{shape:b}}),C=Ie({inputs:{x:t},backend:r,attrs:{shape:w}}),E=[S,C],_=Math.max(x,A),$=x===1,M=A===1,I=[S,C],N=[{type:"int32",data:[h]},{type:"int32",data:[f]},{type:"int32",data:[c]}],O,L,B=[_,h,f],G=W().get("WEBGPU_MATMUL_PROGRAM_TYPE");if(G<0){let U=W().getNumber("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL"),H=U>0?U:r.thresholdToIncreaseWorkgroups,V=_*Math.ceil(h/32)*Math.ceil(f/32);V<=H||h<=8&&V<=H*2?_*h*f<=128?G=Pn.MatMulReduceProgram:_===1&&d>=2e3?G=Pn.MatMulSplitKProgram:G=Pn.MatMulSmallOutputSizeProgram:G=Pn.MatMulPackedProgram}switch(G){case Pn.MatMulReduceProgram:O=new yse(B,$,M,a,n,s,l,i);break;case Pn.MatMulSplitKProgram:{if(L=Cr({backend:r,attrs:{shape:B,value:0,dtype:e.dtype}}),O=new wse(B,d,$,M,a,n),s||l){L=r.runWebGPUProgram(O,I,e.dtype,N,L);let H=new kse(L.shape,s,l,i),V=null,Q=[L];s&&Q.push(s),i&&Q.push(i),l==="leakyrelu"&&(V=[{type:"float32",data:[o]}],H.uniforms+=" alpha : f32,");let Z=r.runWebGPUProgram(H,Q,L.dtype,V);E.push(L);let re=Ie({inputs:{x:Z},backend:r,attrs:{shape:y}});E.push(Z);for(let ee of E)r.disposeData(ee.dataId);return re}break}case Pn.MatMulSmallOutputSizeProgram:O=new vse(b,w,B,a,n,s,l,i);break;case Pn.MatMulPackedProgram:let U=r.adapterInfo.isIntel();O=new xse(b,B,$,M,a,n,s,l,i,U);break;default:throw new Error(`Unsupported MatMulProgramType ${G}.`)}s&&I.push(s),i&&I.push(i),l==="leakyrelu"&&(N.push({type:"float32",data:[o]}),O.uniforms+=" alpha : f32,"),L=r.runWebGPUProgram(O,I,e.dtype,N,L);let j=Ie({inputs:{x:L},backend:r,attrs:{shape:y}});E.push(L);for(let U of E)r.disposeData(U.dataId);return j}function Cse(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:c}=n;return Hh({a:r,b:s,transposeA:l,transposeB:u,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:c,activation:p})}var Nse={kernelName:jr,backendName:"webgpu",kernelFunc:Cse},Xx=class{constructor(e,t,a){this.variableNames=["AReal","AImag","BReal","BImag"],this.workgroupSize=[128,1,1],this.size=!0,this.outputShape=T.assertAndGetBroadcastShape(t,a),this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`binaryOpComplex_${e}`,this.op=e}getUserCode(){return`
fn binaryOpComplex(
areal : f32, aimag : f32, breal : f32, bimag : f32) -> f32 {
${L3(this.op,!1)}
}
${Ce("index")} {
if(index < uniforms.size) {
let areal = getARealByOutputIndex(index);
let aimag = getAImagByOutputIndex(index);
let breal = getBRealByOutputIndex(index);
let bimag = getBImagByOutputIndex(index);
setOutputAtIndex(index, binaryOpComplex(areal, aimag, breal, bimag));
}
}
`}},P1=class{constructor(e,t,a){this.size=!0,this.variableNames=["A","B"],this.outputShape=T.assertAndGetBroadcastShape(t,a),this.dispatchLayout=Ve(this.outputShape),this.op=e,this.useSharedMemoryWithA=t.length<=1&&a.length>1&&t[0]<128,this.useSharedMemoryWithB=a.length<=1&&t.length>1&&a[0]<128,this.useSharedMemoryWithA||this.useSharedMemoryWithB?(this.isVec4=!1,this.lastDimensionSize=this.useSharedMemoryWithB?a[0]:t[0],this.shaderKey=`binary_${this.type}_${e}_${this.lastDimensionSize}_${this.useSharedMemoryWithB}`,this.type="shared",this.workgroupSize=[256,1,1],this.workPerThread=1):(v.arraysEqual(t,a)&&v.sizeFromShape(t)%4===0?(this.isVec4=!0,this.type="vec4",this.workPerThread=4):(this.isVec4=!1,this.type="plain",this.workPerThread=1),this.shaderKey=`binary_${this.type}_${e}`,this.workgroupSize=[128,1,1]),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1])}getUserCode(){let e,t=this.isVec4?"vec4<f32>":"f32",a=`
fn binaryOperation(a : ${t}, b : ${t}) -> ${t} {
${L3(this.op,this.isVec4)}
};
`;if(this.type==="shared"){let n=this.lastDimensionSize>1?`coords[${this.outputShape.length-1}]`:"0",r=this.useSharedMemoryWithB?`let a = getAByOutputIndex(index);
let b = sharedBuf[${n}];`:`let a = sharedBuf[${n}];
let b = getBByOutputIndex(index);`;e=`
${a}
var<workgroup> sharedBuf : array<f32, ${this.lastDimensionSize}>;
${Ce("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);
${r}
setOutputAtIndex(index, binaryOperation(a, b));
}
}
`}else e=`
${a}
${Ce("index")} {
if (index < uniforms.size) {
let a = getAByOutputIndex(index);
let b = getBByOutputIndex(index);
setOutputAtIndex(index, binaryOperation(a, b));
}
}
`;return e}};function Ya(e){let{inputs:t}=e,{x:a}=t;return e.backend.incRef(a.dataId),{dataId:a.dataId,shape:a.shape,dtype:a.dtype}}var Ese={kernelName:ki,backendName:"webgpu",kernelFunc:Ya};function wo(e){let{inputs:t,backend:a}=e,{real:n,imag:r}=t,s=a.makeTensorInfo(n.shape,"complex64"),i=a.tensorMap.get(s.dataId),o=Ya({inputs:{x:n},backend:a}),l=Ya({inputs:{x:r},backend:a});return i.complexTensorInfos={real:o,imag:l},s}var Rse={kernelName:Sd,backendName:"webgpu",kernelFunc:wo},mp=class{constructor(e,t){this.variableNames=["A"],this.size=!0;let a=128;this.workgroupSize=[a,1,1],this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.op=t,this.shaderKey=`unary_${t}`}getUserCode(){return`
fn unaryOperation(a : f32) -> f32 {
${Ms(this.op,!1)}
}
${Ce("index")} {
if (index < uniforms.size) {
let a = getAByOutputIndex(index);
setOutputAtIndex(index, unaryOperation(a));
}
}
`}};function it({opType:e,cpuKernelImpl:t,dtype:a}){return({inputs:n,backend:r})=>{let{x:s}=n,i=r,o=a||s.dtype;if(i.shouldExecuteOnCPU([s])&&t!=null){let u=i.tensorMap.get(s.dataId),p=t(u.values,o);return i.makeTensorInfo(s.shape,o,p)}let l=new mp(s.shape,e);return i.runWebGPUProgram(l,[s],o)}}function ua({opType:e,cpuKernelImpl:t,supportsComplex:a=!1,dtype:n}){return({inputs:r,backend:s})=>{let{a:i,b:o}=r,l=s;if(a&&i.dtype==="complex64"){let c=l.tensorMap.get(i.dataId),d=l.tensorMap.get(o.dataId),h,f;if(e!==De.MUL)[h,f]=[[c.complexTensorInfos.real,d.complexTensorInfos.real],[c.complexTensorInfos.imag,d.complexTensorInfos.imag]].map(g=>{let[x,A]=g,y={dataId:x.dataId,dtype:x.dtype,shape:i.shape},b={dataId:A.dataId,dtype:A.dtype,shape:o.shape},w=new P1(e,i.shape,o.shape);return l.runWebGPUProgram(w,[y,b],ca(x.dtype,A.dtype))});else{let g=new Xx(De.COMPLEX_MULTIPLY_REAL,i.shape,o.shape),x=new Xx(De.COMPLEX_MULTIPLY_IMAG,i.shape,o.shape),A=[{dataId:c.complexTensorInfos.real.dataId,dtype:c.complexTensorInfos.real.dtype,shape:i.shape},{dataId:c.complexTensorInfos.imag.dataId,dtype:c.complexTensorInfos.imag.dtype,shape:i.shape},{dataId:d.complexTensorInfos.real.dataId,dtype:d.complexTensorInfos.real.dtype,shape:o.shape},{dataId:d.complexTensorInfos.imag.dataId,dtype:d.complexTensorInfos.imag.dtype,shape:o.shape}];h=l.runWebGPUProgram(g,A,"float32"),f=l.runWebGPUProgram(x,A,"float32")}let m=wo({inputs:{real:h,imag:f},backend:l});return l.disposeData(h.dataId),l.disposeData(f.dataId),m}let u=n||ca(i.dtype,o.dtype);if((i.dtype==="string"||o.dtype==="string"||l.shouldExecuteOnCPU([i,o]))&&t!=null){let c=l.tensorMap.get(i.dataId).values,d=l.tensorMap.get(o.dataId).values,h=i.dtype==="string"?T.fromUint8ToStringArray(c):c,f=i.dtype==="string"?T.fromUint8ToStringArray(d):d,[m,g]=t(i.shape,o.shape,h,f,u);return l.makeTensorInfo(g,u,m)}let p=new P1(e,i.shape,o.shape);return l.runWebGPUProgram(p,[i,o],u)}}var{addImpl:Mse,castImpl:$se,ceilImpl:_se,concatImpl:Pse,equalImpl:Fse,expImpl:Ose,expm1Impl:Dse,floorImpl:zse,gatherNdImpl:Lse,gatherV2Impl:Bse,greaterEqualImpl:Wse,greaterImpl:Vse,lessEqualImpl:Use,lessImpl:Gse,logImpl:Hse,maxImpl:jse,maximumImpl:qse,minimumImpl:Xse,multiplyImpl:Kse,negImpl:Zse,notEqualImpl:Yse,prodImpl:Jse,rangeImpl:Qse,rsqrtImpl:eie,scatterImpl:tie,simpleAbsImpl:aie,sliceImpl:nie,stridedSliceImpl:rie,stringNGramsImpl:sie,subImpl:iie,tileImpl:oie,topKImpl:lie,transposeImpl:uie,uniqueImpl:I0e}=_h,die=it({opType:de.ABS,cpuKernelImpl:aie}),pie={kernelName:wl,backendName:"webgpu",kernelFunc:die},cie=it({opType:de.ACOS}),hie={kernelName:kl,backendName:"webgpu",kernelFunc:cie},fie=it({opType:de.ACOSH}),mie={kernelName:Il,backendName:"webgpu",kernelFunc:fie},gie=ua({opType:De.ADD,cpuKernelImpl:Mse,supportsComplex:!0}),xie={kernelName:ts,backendName:"webgpu",kernelFunc:gie},Aie=class{constructor(e){this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e[0],this.variableNames=e.map((t,a)=>`T${a}`),this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.shaderKey="addN"}getUserCode(){let e=[];this.variableNames.forEach(a=>{e.push(`let v${a} = get${a}ByOutputCoords(coords);`)});let t=this.variableNames.map(a=>`v${a}`).join(" + ");return`
${Ce("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 yie(e){let{inputs:t,backend:a}=e,n=t;if(n.length===1)return Ya({inputs:{x:n[0]},backend:a});let r=n.map(o=>o.dtype).reduce((o,l)=>ca(o,l)),s=n.map(o=>o.shape),i=new Aie(s);return a.runWebGPUProgram(i,n,r)}var bie={kernelName:Ks,backendName:"webgpu",kernelFunc:yie},vie=class{constructor(e,t){this.variableNames=["A"],this.workgroupSize=[16,16,1];let a=new Array(e.length);for(let n=0;n<a.length;n++)a[n]=e[t[n]];this.outputShape=a,this.dispatchLayout={x:[0],y:[1]},this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize,[1,1,1]),this.shaderKey="transposeShared"}getUserCode(){return v.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]}>;
${Ce()} {
var x = i32(workgroupId.x) * tileSize + i32(localId.x);
var y = i32(workgroupId.y) * tileSize + i32(localId.y);
let width = uniforms.outShape[0];
let height = uniforms.outShape[1];
if (x < width && y < height) {
tile[localId.y][localId.x] = f32(A[y * width + x]);
}
workgroupBarrier();
x = i32(workgroupId.y) * tileSize + i32(localId.x);
y = i32(workgroupId.x) * tileSize + i32(localId.y);
if (x < height && y < width) {
setOutputAtIndex((y * height + x), tile[localId.x]
[localId.y]);
}
}
`}},wie=class{constructor(e,t){this.variableNames=["A"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0;let a=new Array(e.length);for(let n=0;n<a.length;n++)a[n]=e[t[n]];this.outputShape=a,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.newDim=t,this.shaderKey=`transpose_${t}`}getUserCode(){let e=ra(this.outputShape.length),t=kie(this.newDim);return`
${Ce("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 kie(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let a=new Array(t);for(let n=0;n<e.length;n++)a[e[n]]=`resRC.${yr(n)}`;return a.join()}function vr(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{perm:s}=n,i=a,o=r.shape.length,l=new Array(o);for(let p=0;p<l.length;p++)l[p]=r.shape[s[p]];if(a.shouldExecuteOnCPU([r])){let p=i.tensorMap.get(r.dataId).values,c=uie(p,r.shape,r.dtype,s,l);return a.makeTensorInfo(l,r.dtype,c)}if(r.shape.length===2&&v.arraysEqual(s,[1,0])){let p=new vie(r.shape,s);return i.runWebGPUProgram(p,[r],r.dtype)}let u=new wie(r.shape,s);return i.runWebGPUProgram(u,[r],r.dtype)}var Iie={kernelName:Ar,backendName:"webgpu",kernelFunc:vr},Sie=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[a]=T.computeOutAndReduceShapes(this.inputShape,[1]);this.outputShape=a.length===0?[1]:a,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(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 a=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;
}
${Ce("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) {
${a}
}
}
`}};function ko(e,t,a,n,r){let s=e.shape.length,i=[],o=v.parseAxisParam(t,e.shape),l=o,u=T.getAxesPermutation(l,s),p=e;u!=null&&(p=vr({inputs:{x:e},attrs:{perm:u},backend:r}),l=T.getInnerMostAxes(l.length,s),i.push(p)),T.assertAxesAreInnerMostDims(n,l,s);let[c,d]=T.computeOutAndReduceShapes(p.shape,l),h=c;a&&(h=T.expandShapeToKeepDim(c,o));let f;if((n==="max"||n==="prod")&&r.shouldExecuteOnCPU([p])){let m=r.tensorMap.get(p.dataId).values;switch(n){case"max":let g=jse(m,v.sizeFromShape(d),h,e.dtype);f=r.makeTensorInfo(h,e.dtype,g);break;case"prod":let{outVals:x,outShape:A,outDtype:y}=Jse(p.shape,p.dtype,m,l);f=r.makeTensorInfo(A,y,x);break;default:throw new Error(`${n} CPU implementation is not yet supported.`)}}else{let m=v.sizeFromShape(d),g=v.sizeFromShape(p.shape)/m,x={windowSize:m,inSize:m,batchSize:g,outSize:1},A=n==="mean"?"float32":Hd(e.dtype),y=[{type:"int32",data:[m]}],b=new Sie(x,n),w=r.runWebGPUProgram(b,[p],A,y);i.push(w),f=Ie({inputs:{x:w},attrs:{shape:h},backend:r})}return i.forEach(m=>r.disposeData(m.dataId)),f}function Tie(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return ko(r,i,s,"all",a)}var Cie={kernelName:Zs,backendName:"webgpu",kernelFunc:Tie};function Nie(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return ko(r,i,s,"any",a)}var Eie={kernelName:Ys,backendName:"webgpu",kernelFunc:Nie},P8=class{constructor(e,t,a){this.workgroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="infinityValue : f32,",this.size=!0;let n=[t];this.op=a==="min"?"<":">";let[r,s]=T.computeOutAndReduceShapes(e,n);this.outputShape=r.length===0?[1]:r,this.dispatchLayout=Ve(this.outputShape),v.sizeFromShape(s)<32||v.sizeFromShape(r)>1e3?(this.type="plain",this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize)):(this.type="shared",this.dispatch=Ne(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.${yr(this.inputShape.length-1)}`,t=()=>{let a="";if(this.outputShape.length===1)this.inputShape.length!==1&&(a+="outputCoords,");else for(let n=0;n<this.outputShape.length;n++)a+=`outputCoords.${yr(n)},`;return a};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]}>;
`}
${Ce("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]);
}
}
`:`
${Ce("index")} {
if (index < uniforms.size) {
let outputCoords = getCoordsFromIndex(index);
var bestIndex = 0;
var bestValue = getX(${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 Rie(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=T.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=vr({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=T.getInnerMostAxes(i.length,l.shape.length)),T.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let p=new P8(l.shape,i[0],"max"),c=[{type:"float32",data:[Number.NEGATIVE_INFINITY]}],d=a.runWebGPUProgram(p,[l],"int32",c);return u.forEach(h=>a.disposeData(h.dataId)),d}var Mie={kernelName:Js,backendName:"webgpu",kernelFunc:Rie};function $ie(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=T.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=vr({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=T.getInnerMostAxes(i.length,l.shape.length)),T.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let p=new P8(l.shape,i[0],"min"),c=[{type:"float32",data:[Number.POSITIVE_INFINITY]}],d=a.runWebGPUProgram(p,[l],"int32",c);return u.forEach(h=>a.disposeData(h.dataId)),d}var _ie={kernelName:kd,backendName:"webgpu",kernelFunc:$ie},Pie=it({opType:de.ASIN}),Fie={kernelName:Sl,backendName:"webgpu",kernelFunc:Pie},Oie=it({opType:de.ASINH}),Die={kernelName:Tl,backendName:"webgpu",kernelFunc:Oie},zie=it({opType:de.ATAN}),Lie={kernelName:Cl,backendName:"webgpu",kernelFunc:zie},Bie=ua({opType:De.ATAN2}),Wie={kernelName:El,backendName:"webgpu",kernelFunc:Bie},Vie=it({opType:de.ATANH}),Uie={kernelName:Nl,backendName:"webgpu",kernelFunc:Vie},Kx=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=Ve(this.outputShape),this.dispatch=Ne(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"),`
${Ce("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});
}
}
`}},Gie=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=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="poolWithFilterSizeEqualsOne"}getUserCode(){return`
${Ce("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 W3(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reductionIndices:s,keepDims:i}=n;return ko(r,s,i,"max",a)}var Hie={kernelName:Mi,backendName:"webgpu",kernelFunc:W3};function F8(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return ko(r,i,s,"mean",a)}var jie={kernelName:Pi,backendName:"webgpu",kernelFunc:F8};function O8(e,t,a,n){if(t.filterWidth===1&&t.filterHeight===1&&v.arraysEqual(t.inShape,t.outShape))return Ya({inputs:{x:e},backend:n});if(t.filterWidth===t.inWidth&&t.filterHeight===t.inHeight&&t.batchSize===1&&t.padInfo.type==="VALID"){let i=e.shape.length,o=Ie({inputs:{x:e},backend:n,attrs:{shape:[e.shape[i-3]*e.shape[i-2],e.shape[i-1]]}}),l;a==="avg"?l=F8({inputs:{x:o},backend:n,attrs:{axis:0,keepDims:!1}}):(v.assert(a==="max",()=>`Invalid pool type ${a}`),l=W3({inputs:{x:o},backend:n,attrs:{reductionIndices:0,keepDims:!1}}));let u=Ie({inputs:{x:l},backend:n,attrs:{shape:t.outShape}});return n.disposeData(o.dataId),n.disposeData(l.dataId),u}let r,s=[{type:"int32",data:[t.strideHeight,t.strideWidth]}];return t.filterHeight===1&&t.filterWidth===1?r=new Gie(t):(a==="avg"?r=new Kx(t,"avg"):(v.assert(a==="max",()=>`Invalid pool type ${a}`),r=new Kx(t,"max")),s.push({type:"int32",data:[t.padInfo.top,t.padInfo.left]},{type:"int32",data:[t.dilationHeight,t.dilationWidth]},{type:"int32",data:[t.inHeight,t.inWidth]},{type:"int32",data:[t.effectiveFilterHeight,t.effectiveFilterWidth]})),n.runWebGPUProgram(r,[e],e.dtype,s)}function qie(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1,p=T.computePool2DInfo(r.shape,s,i,u,o,l);return O8(r,p,"avg",a)}var Xie={kernelName:Qs,backendName:"webgpu",kernelFunc:qie};function Kie(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;return Hh({a:r,b:s,transposeA:i,transposeB:o,backend:a})}var Zie={kernelName:ei,backendName:"webgpu",kernelFunc:Kie},Yie=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=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.start=e,this.uniforms=`start : ${ra(e.length)}, `,this.shaderKey="slice"}getUserCode(){let e=ra(this.rank),t=Jie(this.rank),a;return this.start.length===1?a=this.outputShape.map((n,r)=>"sourceLoc = uniforms.start + coords;"):a=this.outputShape.map((n,r)=>`sourceLoc.${F1[r]} = uniforms.start.${yr(r)} + coords.${F1[r]};`),`
${Ce("index")} {
if (index < uniforms.size) {
var sourceLoc : ${e};
let coords = getCoordsFromIndex(index);
${a.join(`
`)}
setOutputAtIndex(index, getSource(${t}));
}
}
`}},F1=["x","y","z","w","u","v"];function Jie(e){if(e===1)return"sourceLoc";if(e<=6)return F1.slice(0,e).map(t=>`sourceLoc.${t}`).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}function Au(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,size:i}=n,[o,l]=It.parseSliceParams(r,s,i);if(It.assertParamsValid(r,o,l),a.shouldExecuteOnCPU([r])||r.dtype==="string"){let c=a.tensorMap.get(r.dataId),d=nie(c.values,o,l,r.shape,r.dtype);return a.makeTensorInfo(l,r.dtype,d)}if(v.sizeFromShape(l)===0)return a.makeTensorInfo(l,r.dtype,[]);let u=new Yie(o,l),p=[{type:"int32",data:o}];return a.runWebGPUProgram(u,[r],r.dtype,p)}var Qie={kernelName:Zl,backendName:"webgpu",kernelFunc:Au},eoe=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,crops:i}=n;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGPU backend not implemented yet");let o=s.reduce((A,y)=>A*y),l=T.getReshaped(r.shape,s,o),u=T.getPermuted(l.length,s.length),p=T.getReshapedPermuted(r.shape,s,o),c=T.getSliceBeginCoords(i,s.length),d=T.getSliceSize(p,i,s.length),h=[],f=Ie({inputs:{x:r},backend:a,attrs:{shape:l}}),m=vr({inputs:{x:f},backend:a,attrs:{perm:u}}),g=Ie({inputs:{x:m},backend:a,attrs:{shape:p}}),x=Au({inputs:{x:g},backend:a,attrs:{begin:c,size:d}});return h.push(f),h.push(m),h.push(g),h.forEach(A=>a.disposeData(A.dataId)),x},toe={kernelName:Rl,backendName:"webgpu",kernelFunc:eoe},aoe=`
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;
}
}
`,noe=`
fn bincount_write(index: i32, value: f32) {
result[index] = value;
}
`,D8=class{constructor(e,t,a=!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=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.binaryOutput=a,a&&(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?noe:aoe}
${Ce("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 = ${this.binaryOutput?1:this.hasWeights?"f32(getW(coord[0], coord[1]))":"1."};
bincount_write(coord.x * uniforms.binCountSize + indexVal, value);
}
}`}
}
`}};function roe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i}=n,o=v.sizeFromShape(r.shape),l=v.sizeFromShape(s.shape)>0,u=[i],p=s.dtype,c=Cr({backend:a,attrs:{shape:u,value:0,dtype:p}}),d=new D8([o],l),h=[{type:"int32",data:[i]}],f=l?[r,s]:[r];return a.runWebGPUProgram(d,f,p,h,c)}var soe={kernelName:Id,backendName:"webgpu",kernelFunc:roe},z8=ua({opType:De.NOT_EQUAL,dtype:"bool",cpuKernelImpl:Yse}),ioe={kernelName:Li,backendName:"webgpu",kernelFunc:z8};function gp(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.tensorMap.get(n.dataId);return Ya({inputs:{x:r.complexTensorInfos.real},backend:a})}var ooe={kernelName:Md,backendName:"webgpu",kernelFunc:gp};function loe(e,t){let a=new mp(e.shape,de.TO_INT),n=t.runWebGPUProgram(a,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function O1(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dtype:s}=n;if(s==="complex64"){if(r.dtype==="complex64")return Ya({inputs:{x:r},backend:a});let i=fn(r.shape),o=O1({inputs:{x:r},backend:a,attrs:{dtype:"float32"}}),l=wo({inputs:{real:o,imag:i},backend:a});return i.dispose(),a.disposeData(o.dataId),l}if(r.dtype==="complex64"){let i=gp({inputs:{input:r},backend:a}),o=O1({inputs:{x:i},backend:a,attrs:{dtype:s}});return a.disposeData(i.dataId),o}if(!v.hasEncodingLoss(r.dtype,s)){let i=Ya({inputs:{x:r},backend:a});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(a.shouldExecuteOnCPU([r])){let i=a.tensorMap.get(r.dataId).values,[o,l,u]=$se(i,r.shape,r.dtype,s);return a.makeTensorInfo(o,l,u)}if(s==="int32")return loe(r,a);if(s==="bool"){let i=a.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=z8({inputs:{a:r,b:i},backend:a});return a.disposeData(i.dataId),o}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${s}`)}var uoe={kernelName:ti,backendName:"webgpu",kernelFunc:O1},doe=it({opType:de.CEIL,cpuKernelImpl:_se}),poe={kernelName:ai,backendName:"webgpu",kernelFunc:doe},coe=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=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.shaderKey="clipVec4"}getUserCode(){return`
${Ce("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);
}
}
`}},hoe=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=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="clip"}getUserCode(){return`
${Ce("index")} {
if(index < uniforms.size) {
let value = getAByOutputIndex(index);
if (isnan(value)) {
setOutputAtIndex(index, value);
return;
}
setOutputAtIndex(index, clamp(value, uniforms.minVal, uniforms.maxVal));
}
}
`}};function foe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=n,o,l=[{type:"float32",data:[s]},{type:"float32",data:[i]}];return v.sizeFromShape(r.shape)%4===0?o=new coe(r.shape):o=new hoe(r.shape),a.runWebGPUProgram(o,[r],r.dtype,l)}var moe={kernelName:as,backendName:"webgpu",kernelFunc:foe},goe=class{constructor(e){this.uniforms="",this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=T.computeOutShape(e,1),this.variableNames=e.map((t,a)=>`T${a}`),this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(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${t} : i32,`;this.shaderKey="concat"}getUserCode(){let e=[];if(this.offsetLength>0){e.push("if (yC < uniforms.offset0){ setOutputAtCoords(coords.x, coords.y, getT0(yR, yC)); }");for(let n=1;n<this.offsetLength;n++)e.push(`else if (yC < uniforms.offset${[n]}){ setOutputAtCoords(coords.x, coords.y, getT${n}(yR, yC - uniforms.offset${n-1})); }`);let t=this.offsetLength,a=this.offsetLength-1;e.push(`else { setOutputAtCoords(coords.x, coords.y, getT${t}(yR, yC - uniforms.offset${a})); }`)}else e.push("setOutputAtCoords(coords.x, coords.y, getT0(yR, yC));");return`
${Ce("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 jh(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.tensorMap.get(n.dataId);return Ya({inputs:{x:r.complexTensorInfos.imag},backend:a})}var xoe={kernelName:Rd,backendName:"webgpu",kernelFunc:jh};function Ju(e,t,a){let n=e[0].dtype;if(n==="complex64"){let f=e.map(y=>gp({inputs:{input:y},backend:a})),m=e.map(y=>jh({inputs:{input:y},backend:a})),g=Ju(f,t,a),x=Ju(m,t,a),A=wo({inputs:{real:g,imag:x},backend:a});return f.forEach(y=>a.disposeData(y.dataId)),m.forEach(y=>a.disposeData(y.dataId)),a.disposeData(g.dataId),a.disposeData(x.dataId),A}let r=a.shouldExecuteOnCPU(e);if(n==="string"&&(r=!0),r){let f=e.map(w=>{let S=[-1,v.sizeFromShape(w.shape.slice(t))];return Ie({inputs:{x:w},backend:a,attrs:{shape:S}})}),m=f.map(w=>({vals:a.readSync(w.dataId),shape:w.shape})),g=T.computeOutShape(f.map(w=>w.shape),1),x=f[0].shape[0]===1,A=Pse(m,g,n,x),y=T.computeOutShape(e.map(w=>w.shape),t),b=a.makeTensorInfo(y,n,A);return f.forEach(w=>a.disposeData(w.dataId)),b}let s=a.device.limits.maxStorageBuffersPerShaderStage-1;if(e.length>s){let f=[];for(let g=0;g<e.length;g+=s){let x=e.slice(g,g+s);f.push(Ju(x,t,a))}let m=Ju(f,t,a);for(let g of f)a.disposeData(g.dataId);return m}let{tensors2D:i,outShape:o}=Aoe(e,t,a),l=i.map(f=>f.shape),u=new goe(l),p=[],c=new Array(l.length-1);if(c.length>0){c[0]=l[0][1],p.push({type:"int32",data:[c[0]]});for(let f=1;f<c.length;f++)c[f]=c[f-1]+l[f][1],p.push({type:"int32",data:[c[f]]})}let d=a.runWebGPUProgram(u,i,i[0].dtype,p);i.forEach(f=>a.disposeData(f.dataId));let h=Ie({inputs:{x:d},backend:a,attrs:{shape:o}});return a.disposeData(d.dataId),h}function Aoe(e,t,a){let n=T.computeOutShape(e.map(r=>r.shape),t);return{tensors2D:e.map(r=>Ie({inputs:{x:r},backend:a,attrs:{shape:[v.sizeFromShape(r.shape.slice(0,t)),v.sizeFromShape(r.shape.slice(t))]}})),outShape:n}}function L8(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(u=>u.shape);T.assertParamsConsistent(i,s);let o=T.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(o)===0)return a.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(u=>v.sizeFromShape(u.shape)>0);return l.length===1?Ya({inputs:{x:l[0]},backend:a}):Ju(l,s,a)}var yoe={kernelName:Ml,backendName:"webgpu",kernelFunc:L8};function boe(e,t,a,n,r=!1,s=null,i=!1,o=4,l=4,u=4){let p=E=>{switch(E){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 ${E} is not supported.`)}},c=E=>{switch(E){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 ${E} is not supported.`)}},d=e?`
let coord = vec4<i32>(batch, xRow, xCol, xCh);
`:`
let coord = vec4<i32>(batch, xCh, xRow, xCol);
`,h=e?`
let coords = vec4<i32>(
batch,
row / outWidth,
row % outWidth,
col);
`:`
let coords = vec4<i32>(
batch,
row,
col / outWidth,
col % outWidth);
`,f=e?"uniforms.xShape[1]":"uniforms.xShape[2]",m=e?"uniforms.xShape[2]":"uniforms.xShape[3]",g=e?"row":"col",x=e?"col":"row",A=`
let inChannels = uniforms.wShape[2];
let outWidth = ${e?"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 = ${Mt(o)}(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 < ${m}) {
${d}
let xIndex = getIndexFromCoords4D(coord, uniforms.xShape);
${p(o)}
}
return resData;`,y=e?t&&n?`
let col = colIn * ${o};
${A}`:`
let col = colIn * ${o};
if (row < uniforms.dimAOuter && col < uniforms.dimInner) {
${A}
}
return ${Mt(o)}(0.0);`:n&&a?`
let col = colIn * ${o};
${A}`:`
let col = colIn * ${o};
if (row < uniforms.dimInner && col < uniforms.dimBOuter) {
${A}
}
return ${Mt(o)}(0.0);`,b=`${c(l)}`,w=Mt(u),S=Mt(e?o:l),C=Mt(e?l:o);return`
${Tr(s,i,u===4,4)}
fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${S} {
${e?y:b}
}
fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${C} {
${e?b:y}
}
fn mm_write(batch: i32, row : i32, colIn : i32, valueIn : ${w}) {
let col = colIn * ${u};
if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)
{
var value = valueIn;
let outWidth = ${e?"uniforms.outShape[2]":"uniforms.outShape[3]"};
${h}
${vo(r,s)}
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
}
}`}var voe=class{constructor(e,t,a,n,r=!1,s=null,i=!1,o=!1){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.isVec4=((e.inChannels%4===0||e.inChannels%3===0)&&this.isChannelsLast||e.outWidth%4===0&&!this.isChannelsLast)&&e.outChannels%4===0,this.dispatchLayout=this.isChannelsLast?{x:[3],y:[1,2],z:[0]}:{x:[2,3],y:[1],z:[0]},this.workgroupSize=F3(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=O3(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread),this.isVec4?(this.isChannelsLast&&e.inChannels%4!==0?(this.innerElementSize=3,this.variableTypes=["f32","vec4<f32>"]):(this.innerElementSize=4,this.variableTypes=["vec4<f32>","vec4<f32>"]),r&&(this.variableNames.push("bias"),this.variableTypes.push("vec4<f32>")),i&&(this.variableNames.push("preluActivationWeights"),this.variableTypes.push("vec4<f32>"))):(this.innerElementSize=this.elementsPerThread[0],r&&this.variableNames.push("bias"),i&&this.variableNames.push("preluActivationWeights")),this.sequentialAccessByThreads=o,this.addBias=r,this.activation=s,this.hasPreluActivationWeights=i,this.tileAOuter=this.workgroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workgroupSize[0]*this.elementsPerThread[0],this.tileInner=Math.max(this.workgroupSize[0]*this.innerElementSize,this.workgroupSize[1]),this.fitAOuter=t%this.tileAOuter===0,this.fitBOuter=a%this.tileBOuter===0,this.fitInner=n%this.tileInner===0,this.shaderKey=`conv2DMM_${this.elementsPerThread}_${this.activation}}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.innerElementSize}_${this.isChannelsLast}_${this.sequentialAccessByThreads}`}getUserCode(){let e=this.isVec4?Uh(this.elementsPerThread,this.workgroupSize,!this.isChannelsLast,this.tileInner):Gh(this.elementsPerThread,this.workgroupSize,!this.isChannelsLast,this.tileInner,!1,null,this.sequentialAccessByThreads),t=this.isVec4?[this.innerElementSize,4,4]:[1,1,1];return`
${boe(this.isChannelsLast,this.fitAOuter,this.fitBOuter,this.fitInner,this.addBias,this.activation,this.hasPreluActivationWeights,t[0],t[1],t[2])}
${e}
`}},woe=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms="filterDims: vec2<i32>, pad: vec2<i32>, stride: vec2<i32>, dilation: vec2<i32>,",this.workgroupSize=[4,4,8],this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.dispatchLayout=this.isChannelsLast?{x:[2],y:[1],z:[0,3]}:{x:[3],y:[2],z:[0,1]},this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.addBias=t,this.activation=a,this.hasPreluActivationWeights=n,t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`conv2dnaive_${this.activation}_${this.isChannelsLast}`}getUserCode(){return`
${Tr(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;
${vo(this.addBias,this.activation)}
setOutputAtCoords(coords.x, coords.y, coords.z, coords.w, value);
}
}
${Ce("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) {
${this.isChannelsLast?"let v = readInp(batch, xRow, xCol, xChannel);":"let v = readInp(batch, xChannel, xRow, xCol);"}
let f = readFilt(row, col, xChannel, outChannel);
acc = acc + v * f;
}
}
}
writeResult(batch, outRow, outCol, outChannel, acc);
}
`}},koe=class{constructor(e,t){this.variableNames=["x"],this.uniforms=`pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>, outWidth : i32, itemsPerBlockRow : i32,
inChannels : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=t,this.shaderKey=`im2col_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?1:2,t=this.isChannelsLast?2:3,a=this.isChannelsLast?"coords[1]":"coords[2]",n=this.isChannelsLast?"coords[2]":"coords[1]",r=this.isChannelsLast?"getX(batch, xRow, xCol, ch)":"getX(batch, ch, xRow, xCol)";return`
${Ce("index")} {
let coords = getCoordsFromIndex(index);
if(index < uniforms.size) {
let batch = coords[0];
let row = ${a};
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 = ${r};
}
}
setOutputAtIndex(index, value);
}
}
`}};function Wc(e,t){let a=e.length;return a>=3?t?[...e.slice(0,-3),e[a-3]*e[a-2],e[a-1]]:[...e.slice(0,-3),e[a-3],e[a-2]*e[a-1]]:!t&&a===1&&e[0]>1?[e[0],1]:null}function Ioe({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=a.dataFormat==="channelsLast",u=!l,p=!1,c=l&&a.filterHeight===a.inHeight&&a.filterWidth===a.inWidth&&a.padInfo.type==="VALID",d=[],h,f;if(c){let x=a.inHeight*a.inWidth*a.inChannels;h=Ie({inputs:{x:e},backend:n,attrs:{shape:[1,a.batchSize,x]}}),f=Ie({inputs:{x:t},backend:n,attrs:{shape:[1,x,a.outChannels]}})}else h=Ie({inputs:{x:e},backend:n,attrs:{shape:l?[a.batchSize,a.inHeight*a.inWidth,a.inChannels]:[a.batchSize,a.inChannels,a.inHeight*a.inWidth]}}),f=Ie({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}});if(d.push(h),d.push(f),s!=null){let x=Wc(s.shape,l);x!=null&&(s=Ie({inputs:{x:s},backend:n,attrs:{shape:x}}),d.push(s))}if(r!=null){let x=Wc(r.shape,l);x!=null&&(r=Ie({inputs:{x:r},backend:n,attrs:{shape:x}}),d.push(r))}let m=Hh({a:l?h:f,b:l?f:h,transposeA:u,transposeB:p,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),g=Ie({inputs:{x:m},backend:n,attrs:{shape:a.outShape}});d.push(m);for(let x of d)n.disposeData(x.dataId);return g}function Soe({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:p,strideWidth:c,strideHeight:d,padInfo:h,outWidth:f,outHeight:m,dilationWidth:g,dilationHeight:x,dataFormat:A}=a,y=A==="channelsLast",b=l*u*p,w=m*f,S=y?[a.batchSize,w,b]:[a.batchSize,b,w],C=new koe(S,y),E=[{type:"int32",data:[h.top,h.left]},{type:"int32",data:[d,c]},{type:"int32",data:[x,g]},{type:"int32",data:[f]},{type:"int32",data:[p*l]},{type:"int32",data:[p]}],_=n.runWebGPUProgram(C,[e],e.dtype,E),$=[];$.push(_);let M=Ie({inputs:{x:t},backend:n,attrs:{shape:[1,b,-1]}});if($.push(M),s!=null){let O=Wc(s.shape,y);O!=null&&(s=Ie({inputs:{x:s},backend:n,attrs:{shape:O}}),$.push(s))}if(r!=null){let O=Wc(r.shape,y);O!=null&&(r=Ie({inputs:{x:r},backend:n,attrs:{shape:O}}),$.push(r))}let I=Hh({a:y?_:M,b:y?M:_,transposeA:!y,transposeB:!1,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),N=Ie({inputs:{x:I},backend:n,attrs:{shape:a.outShape}});$.push(I);for(let O of $)n.disposeData(O.dataId);return N}function B8({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=r!=null,u=s!=null,p=a.dataFormat==="channelsLast",c=p&&a.filterHeight===a.inHeight&&a.filterWidth===a.inWidth&&a.padInfo.type==="VALID",d=W().getBool("WEBGPU_USE_NAIVE_CONV2D_DEBUG");if(!d&&(c||a.filterHeight===1&&a.filterWidth===1&&a.dilationHeight===1&&a.dilationWidth===1&&a.strideHeight===1&&a.strideWidth===1&&(a.padInfo.type==="SAME"||a.padInfo.type==="VALID")))return Ioe({x:e,filter:t,convInfo:a,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i});let h=W().getNumber("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL"),f=h>0?h:n.thresholdToIncreaseWorkgroups,m=a.batchSize*Math.ceil(a.outHeight*a.outWidth/32)*Math.ceil(a.outChannels/32);if(W().getBool("WEBGPU_CONV_SEPARATE_IM2COL_SHADER")||m<=f)return Soe({x:e,filter:t,convInfo:a,backend:n,bias:r,preluActivationWeights:s,leakyreluAlpha:i,activation:o});let g,x=[a.padInfo.top,a.padInfo.left],A=[{type:"int32",data:[a.filterHeight,a.filterWidth]},{type:"int32",data:[...x]},{type:"int32",data:[a.strideHeight,a.strideWidth]},{type:"int32",data:[a.dilationHeight,a.dilationWidth]}];if(d)g=new woe(a,l,o,u);else{let S=p?a.outHeight*a.outWidth:a.outChannels,C=p?a.outChannels:a.outHeight*a.outWidth,E=a.filterHeight*a.filterWidth*a.inChannels;A.push({type:"int32",data:[S]},{type:"int32",data:[C]},{type:"int32",data:[E]});let _=n.adapterInfo.isIntel();g=new voe(a,S,C,E,l,o,u,_)}let y=[],b=[e,t];l&&(!p&&r.shape.length===1&&(r=Ie({inputs:{x:r},backend:n,attrs:{shape:[r.shape[0],1,1]}}),y.push(r)),b.push(r)),u&&(!p&&s.shape.length===1&&(s=Ie({inputs:{x:s},backend:n,attrs:{shape:[s.shape[0],1,1]}}),y.push(s)),b.push(s)),o==="leakyrelu"&&(A.push({type:"float32",data:[i]}),g.uniforms+=" alpha : f32,");let w=n.runWebGPUProgram(g,b,e.dtype,A);for(let S of y)n.disposeData(S.dataId);return w}function Toe(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:p}=a,c=T.convertConv2DDataFormat(l),d=T.computeConv2DInfo(r.shape,s.shape,i,u,o,p,!1,c);return B8({x:r,filter:s,convInfo:d,backend:n})}var Coe={kernelName:ni,backendName:"webgpu",kernelFunc:Toe};function Noe(e=4){let t=n=>{switch(n){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 ${n} is not supported.`)}},a=`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 ${Mt(e)}(0.0);
}
if (xC < 0.0 || xC >= f32(uniforms.outBackprop[2]) || fract(xC) > 0.0) {
return ${Mt(e)}(0.0);
}
let coord = vec4<i32>(
batch,
i32(xR),
i32(xC),
col % uniforms.outBackprop[3]);
return x[getIndexFromCoords4D(coord, uniforms.xShape)/${e}];`}
}
return ${Mt(e)}(0.0);`;return`
fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${Mt(e)} {
let col = colIn * ${e};
${a}
}
fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${Mt(e)} {
let col = colIn * ${e};
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);
${t(e)}
}
return ${Mt(e)}(0.0);
}
fn mm_write(batch: i32, row : i32, colIn : i32, valueInput : ${Mt(e)}) {
let col = colIn * ${e};
if (row < uniforms.dimAOuter && (col + ${e-1}) < uniforms.dimBOuter) {
var value = valueInput;
let outCoord = vec4<i32>(
batch,
row / uniforms.outShape[2],
row % uniforms.outShape[2],
col);
result[getIndexFromCoords4D(outCoord, uniforms.outShape)/${e}] = value;
}
}`}var Eoe=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,v.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=F3(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=O3(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=Ne(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?Uh(this.elementsPerThread,this.workgroupSize):Gh(this.elementsPerThread,this.workgroupSize);return`
${Noe(this.isVec4?4:1)}
${e}
`}},Roe=class{constructor(e){this.variableNames=["dy","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, stride : vec2<i32>, outBackprop : vec4<i32>,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",this.shaderKey=`conv2DDerInput_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?1:2,t=this.isChannelsLast?2:3,a=this.isChannelsLast?3:1;return`
${Ce("index")} {
if(index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords[0];
let d1 = coords[${a}];
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 Moe(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=n,c=T.convertConv2DDataFormat(u),d=T.computeConv2DInfo(i,s.shape,o,1,l,p,!1,c),h=[{type:"int32",data:[d.filterHeight,d.filterWidth]},{type:"int32",data:[d.filterHeight-1-d.padInfo.top,d.filterWidth-1-d.padInfo.left]},{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.batchSize,d.outHeight,d.outWidth,d.outChannels]}],f;if(W().getBool("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE")||d.filterHeight<=2&&d.filterWidth<=2&&d.outChannels<=16&&d.inChannels===1)f=new Roe(d);else{f=new Eoe(d);let m=d.inHeight*d.inWidth,g=d.inChannels,x=d.filterHeight*d.filterWidth*d.outChannels;h.push({type:"uint32",data:[m]},{type:"uint32",data:[g]},{type:"uint32",data:[x]})}return a.runWebGPUProgram(f,[r,s],"float32",h)}var $oe={kernelName:ri,backendName:"webgpu",kernelFunc:Moe},_oe=it({opType:de.COS}),Poe={kernelName:si,backendName:"webgpu",kernelFunc:_oe},Foe=it({opType:de.COSH}),Ooe={kernelName:ii,backendName:"webgpu",kernelFunc:Foe},Doe=class{constructor(e,t,a,n){this.variableNames=["Image","Boxes","BoxInd"],this.uniforms="extrapolationValue : f32,",this.workgroupSize=[64,1,1],this.size=!0;let[r]=t;this.outputShape=[r,a[0],a[1],e],this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.methodId=n==="bilinear"?1:0,this.cropHeightBiggerThan1=this.outputShape[1]>1,this.cropWidthBiggerThan1=this.outputShape[2]>1,this.shaderKey=`cropAndResize_${this.methodId}_${this.cropHeightBiggerThan1}_${this.cropWidthBiggerThan1}`}getUserCode(){let[e,t]=["f32(uniforms.imageShape[1] - 1)","f32(uniforms.imageShape[2] - 1)"],[a,n,r]=this.cropHeightBiggerThan1?[`(${e} / f32(uniforms.outShape[1] - 1))`,"(y2-y1) * height_ratio",`y1*${e} + f32(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${e}`],[s,i,o]=this.cropWidthBiggerThan1?[`(${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`
${Ce("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let height_ratio = f32(${a});
let width_ratio = f32(${s});
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 = ${r};
if( in_y < 0.0 || in_y > ${e} ) {
setOutputAtIndex(index, uniforms.extrapolationValue);
return;
}
let in_x = ${o};
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);
}
}
}
`}},zoe=e=>{let{inputs:t,backend:a,attrs:n}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,p=new Doe(r.shape[3],s.shape,o,l),c=[{type:"float32",data:[u]}];return a.runWebGPUProgram(p,[r,s,i],"float32",c)},Loe={kernelName:ui,backendName:"webgpu",kernelFunc:zoe},bd;(function(e){e.Prod="*",e.Sum="+"})(bd||(bd={}));var Zx=class{constructor(e,t,a,n){this.variableNames=["x"],this.uniforms="index : f32,",this.size=!0,this.workgroupSize=[128,1,1],this.outputShape=t,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.exclusive=a,this.reverse=n,this.op=e,this.shaderKey=`cum_${this.op}_${this.exclusive}_${this.reverse}`}getUserCode(){let e=this.outputShape.length,t=this.op===bd.Prod?"1.0":"0.0",a=this.exclusive?t:`getX(${Yx(e,"coords",this.op)})`,n=this.outputShape[this.outputShape.length-1],r="",s="";return this.exclusive?(r=this.reverse?`end != ${n-1}`:"end != 0",s=this.reverse?"end + 1":"end - 1"):(r=this.reverse?`end + pow2 < ${n}`:"end >= pow2",s=this.reverse?"end + pow2":"end - pow2"),`
${Ce("index")} {
if (index < uniforms.size) {
var coords = getCoordsFromIndex(index);
let end = ${Jx(e,"coords",this.op)};
var val = ${a};
let pow2 = i32(pow(2.0, uniforms.index));
if (${r}) {
let idx = ${s};
${Jx(e,"coords",this.op)} = idx;
val ${this.op}= getX(${Yx(e,"coords",this.op)});
}
setOutputAtIndex(index, val);
}
}
`}};function Yx(e,t,a){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw Error(`Cumulative ${a} for rank ${e} is not yet supported`)}function Jx(e,t,a){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative ${a} for rank ${e} is not yet supported`)}function W8(e,t,a,n,r,s){let i=t.shape.length,o=T.getAxesPermutation([n],i),l=t;o!=null&&(l=vr({inputs:{x:t},backend:a,attrs:{perm:o}}));let u=T.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGPU cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let p=l.shape[u],c=Ya({inputs:{x:l},backend:a});for(let d=0;d<=Math.ceil(Math.log2(p))-1;d++){let h=new Zx(e,l.shape,!1,s),f=c,m=[{type:"float32",data:[d]}];c=a.runWebGPUProgram(h,[c],c.dtype,m),a.disposeData(f.dataId)}if(r){let d=new Zx(e,l.shape,r,s),h=c,f=[{type:"float32",data:[0]}];c=a.runWebGPUProgram(d,[c],c.dtype,f),a.disposeData(h.dataId)}if(o!=null){let d=T.getUndoAxesPermutation(o),h=vr({inputs:{x:c},backend:a,attrs:{perm:d}});return a.disposeData(c.dataId),a.disposeData(l.dataId),h}return c}function Boe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return W8(bd.Prod,r,a,s,i,o)}var Woe={kernelName:oi,backendName:"webgpu",kernelFunc:Boe};function Voe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return W8(bd.Sum,r,a,s,i,o)}var Uoe={kernelName:li,backendName:"webgpu",kernelFunc:Voe};function Goe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n,l=r.shape.length===1,u=v.sizeFromShape(s.shape)>0,p=s.dtype,c=l?[r.shape[0]]:[r.shape[0],r.shape[1]],d=l?[i]:[r.shape[0],i],h=Cr({backend:a,attrs:{shape:d,value:0,dtype:p}}),f=new D8(c,u,o),m=[{type:"int32",data:[i]}],g=u?[r,s]:[r];return a.runWebGPUProgram(f,g,p,m,h)}var Hoe={kernelName:Td,backendName:"webgpu",kernelFunc:Goe},joe=class{constructor(e,t){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.uniforms="blockSize : i32,",this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`depthToSpace_${t}`,this.dataFormat=t}getUserCode(){return`
${Ce("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 = ${this.getInputSamplingString()};
setOutputAtIndex(index, rlt);
}
}`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?"uniforms.outShape[3]":"uniforms.outShape[1]"}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function qoe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockSize:s,dataFormat:i}=n,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],c=l*s,d=u*s,h=p/(s*s),f=i==="NHWC"?[o,c,d,h]:[o,h,c,d],m=[{type:"int32",data:[s]}],g=new joe(f,i);return a.runWebGPUProgram(g,[r],r.dtype,m)}var Xoe={kernelName:di,backendName:"webgpu",kernelFunc:qoe},Koe=class{constructor(e,t,a,n=!1,r=null,s=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, inDims : vec2<i32>,",this.workgroupSize=[16,16,1],this.outputShape=e,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),n&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),this.addBias=n,this.activation=r,this.hasPreluActivation=s,this.filterHeight=t,this.filterWidth=a,this.shaderKey=`depthwiseNCHW_${this.activation}_${this.filterHeight}_${this.filterWidth}`}getUserCode(){let e=this.filterWidth*this.filterHeight,t=this.workgroupSize[0]*this.workgroupSize[1]*this.workgroupSize[2],a=this.workgroupSize[1]+this.filterHeight-1,n=this.workgroupSize[0]+this.filterWidth-1;return`
${Tr(this.activation,this.hasPreluActivation,!1,4)}
var<workgroup> mm_Asub : array<array<f32, ${n}>, ${a}>;
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;
}
${Ce()} {
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 < ${a}; 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);
}
}
${vo(this.addBias,this.activation)}
if (coordsInBounds4D(coords, uniforms.outShape)) {
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
}
}
`}},V8=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, inDims : vec2<i32>,",this.workgroupSize=[4,4,4],this.workPerThread=4,this.isVec4=!0,this.outputShape=e.outShape,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize,[4,this.workPerThread,1]),v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=a,this.hasPreluActivation=n,this.shaderKey=`depthwiseVec4_${a}_${this.convInfo.filterHeight}_${this.convInfo.filterWidth}_${this.convInfo.strideHeight}_${this.convInfo.strideWidth}_${this.workPerThread}`}getUserCode(){let e=(this.workPerThread-1)*this.convInfo.strideWidth+this.convInfo.filterWidth;return`
${Tr(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};
${Ce()} {
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];
${vo(this.addBias,this.activation)}
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
}
}
}
`}},U8=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms=`pad : vec2<i32>, inDims : vec2<i32>, filterHeight : i32,
filterWidth : i32, stride : vec2<i32>, dilation : vec2<i32>,`,this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=a,this.hasPreluActivation=n,this.shaderKey=`depthwise_${this.activation}_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?"getX(batch, xR, xC, d1);":"getX(batch, d1, xR, xC);";return`
${Tr(this.activation,this.hasPreluActivation,!1,4)}
${Ce("index")} {
if (index < uniforms.size) {
let coords = getOutputCoords();
let batch = coords[0];
let xRCCorner = vec2<i32>(coords.${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;
}
}
}
${vo(this.addBias,this.activation)}
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
}
}
`}};function Zoe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:p}=n,c=T.convertConv2DDataFormat(l),d=u;d==null&&(d=[1,1]);let h=T.computeConv2DInfo(r.shape,s.shape,i,d,o,p,!0,c),f=[{type:"int32",data:[h.padInfo.top,h.padInfo.left]},{type:"int32",data:[h.inHeight,h.inWidth]}],m=h.dataFormat==="channelsLast",g;return!m&&h.inHeight>16&&h.inWidth>16&&h.strideHeight===1&&h.strideWidth===1&&h.dilationWidth===1&&h.dilationHeight===1&&h.inChannels===h.outChannels?g=new Koe(h.outShape,h.filterHeight,h.filterWidth):m&&h.outHeight>4&&h.outWidth>4&&h.strideWidth<=2&&h.inChannels===h.outChannels&&h.dilationHeight===1&&h.dilationWidth===1&&h.inChannels%4===0?g=new V8(h):(g=new U8(h),f.push({type:"int32",data:[h.filterHeight]},{type:"int32",data:[h.filterWidth]},{type:"int32",data:[h.strideHeight,h.strideWidth]},{type:"int32",data:[h.dilationHeight,h.dilationWidth]})),a.runWebGPUProgram(g,[r,s],r.dtype,f)}var Yoe={kernelName:pi,backendName:"webgpu",kernelFunc:Zoe},G8=ua({opType:De.MUL,cpuKernelImpl:Kse,supportsComplex:!0}),Joe={kernelName:zi,backendName:"webgpu",kernelFunc:G8};function V3(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return ko(r,s,i,"sum",a)}var Qoe={kernelName:ro,backendName:"webgpu",kernelFunc:V3};function ele(e){let{inputs:t,backend:a,attrs:n}=e,{equation:r}=n,s=t,{allDims:i,summedDims:o,idDims:l}=T.decodeEinsumEquation(r,s.length);T.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:p}=T.getEinsumComputePath(o,l),c=p.length,d=null,h=i.length,f=[];for(let m=0;m<c;++m){for(let g of p[m]){let{permutationIndices:x,expandDims:A}=T.getEinsumPermutation(h,l[g]),y;T.isIdentityPermutation(x)?y=s[g]:(y=vr({inputs:{x:s[g]},backend:a,attrs:{perm:x}}),f.push(y));let b=y.shape.slice();for(let w=0;w<A.length;++w)b.splice(A[w],0,1);v.arraysEqual(y.shape,b)||(y=Ie({inputs:{x:y},backend:a,attrs:{shape:b}}),f.push(y)),d===null?d=y:(d=G8({inputs:{a:y,b:d},backend:a}),f.push(d))}m<c-1&&(u[m]>=0&&(d=V3({inputs:{x:d},backend:a,attrs:{axis:u[m]-(i.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&a.disposeData(m.dataId);return d}var tle={kernelName:Cd,backendName:"webgpu",kernelFunc:ele},ale=it({opType:de.ELU}),nle={kernelName:hi,backendName:"webgpu",kernelFunc:ale},rle=ua({opType:De.EQUAL,dtype:"bool",cpuKernelImpl:Fse}),sle={kernelName:fi,backendName:"webgpu",kernelFunc:rle},ile=it({opType:de.ERF}),ole={kernelName:$l,backendName:"webgpu",kernelFunc:ile},H8=it({opType:de.EXP,cpuKernelImpl:Ose,dtype:"float32"}),lle={kernelName:mi,backendName:"webgpu",kernelFunc:H8};function D1(e){let{inputs:t,attrs:a,backend:n}=e,{dim:r}=a,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=r;return r<0&&(v.assert(-(i+1)<=r,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+r+1),o.splice(l,0,1),Ie({inputs:{x:s},backend:n,attrs:{shape:o}})}var ule={kernelName:_l,backendName:"webgpu",kernelFunc:D1},dle=it({opType:de.EXPM1,cpuKernelImpl:Dse}),ple={kernelName:Pl,backendName:"webgpu",kernelFunc:dle},Qx=class{constructor(e,t){this.variableNames=["real","imag"],this.outputShape=[],this.uniforms="exponentMultiplier : f32, denominator: f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.component=e,this.shaderKey=`fft_${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;
}
${Ce("index")} {
if (index < uniforms.size) {
let coords = getOutputCoords();
setOutputAtIndex(index, mulMatDFT(coords[0], coords[1]));
}
}
`}};function j8(e,t,a){let n=a.tensorMap.get(e.dataId),r=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=r/s,o=[],l=Ie({inputs:{x:e},backend:a,attrs:{shape:[i,s]}});o.push(l);let u=l.shape,p=new Qx("real",u),c=new Qx("imag",u),d=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:u},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:u}],h=t?2*Math.PI:-2*Math.PI,f=t?u[1]:1,m=[{type:"float32",data:[h]},{type:"float32",data:[f]}],g=a.runWebGPUProgram(p,d,"float32",m);o.push(g);let x=a.runWebGPUProgram(c,d,"float32",m);o.push(x);let A=wo({inputs:{real:g,imag:x},backend:a});o.push(A);let y=Ie({inputs:{x:A},backend:a,attrs:{shape:e.shape}});return o.forEach(b=>a.disposeData(b.dataId)),y}function cle(e){let{inputs:t,backend:a}=e,{input:n}=t;return j8(n,!1,a)}var hle={kernelName:Nd,backendName:"webgpu",kernelFunc:cle},fle=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="flipLeftRight"}getUserCode(){return`
${Ce("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let coordX = uniforms.xShape[2] - coords[2] - 1;
let outputValue = getX(coords[0], coords[1], coordX, coords[3]);
setOutputAtIndex(index, outputValue);
}
}
`}},mle={kernelName:gi,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{image:a}=e,n=t,r=new fle(a.shape);return n.runWebGPUProgram(r,[a],a.dtype)}},gle=it({opType:de.FLOOR,cpuKernelImpl:zse}),xle={kernelName:xi,backendName:"webgpu",kernelFunc:gle},Ale=ua({opType:De.INT_DIV,dtype:"int32"}),yle={kernelName:Ai,backendName:"webgpu",kernelFunc:Ale},ble=class{constructor(e,t,a=!1){this.isFromPixels=!0,this.outputShape=[0],this.variableNames=[],this.workgroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize,[t,1,1]),this.importVideo=a,this.shaderKey=`fromPixels_${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>"};
${Ce("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]));
}
}
}
`}},vle={kernelName:rd,backendName:"webgpu",kernelFunc:wle},Yo,Wm=W().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU"),cc=new Map;function wle(e){let{inputs:t,backend:a,attrs:n}=e,{pixels:r}=t,{numChannels:s}=n;if(r==null)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");let i=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,l=typeof HTMLCanvasElement!="undefined"&&r instanceof HTMLCanvasElement||typeof OffscreenCanvas!="undefined"&&r instanceof OffscreenCanvas,u=typeof ImageBitmap!="undefined"&&r instanceof ImageBitmap,[p,c]=i?[r.videoWidth,r.videoHeight]:[r.width,r.height],d=[c,p,s],h=!1,f=i||o;if(u||l||f){let A;if(h){let $=r;if(!cc.has($)||cc.get($).expired){let M={source:$};cc.set($,a.device.importExternalTexture(M))}A={width:p,height:c,format:null,usage:null,texture:cc.get($)}}else{if(f){let N=W().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(Yo==null||N!==Wm)&&(Wm=N,Yo=document.createElement("canvas").getContext("2d",{willReadFrequently:Wm})),Yo.canvas.width=p,Yo.canvas.height=c,Yo.drawImage(r,0,0,p,c),r=Yo.canvas}let $=GPUTextureUsage.COPY_DST|GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING,M="rgba8unorm",I=a.textureManager.acquireTexture(d[1],d[0],M,$);a.queue.copyExternalImageToTexture({source:r},{texture:I},[d[1],d[0]]),A={width:p,height:c,format:M,usage:$,texture:I}}let y=v.sizeFromShape(d),b=v.computeStrides(d),w=new ble(d,s,h),S=[{type:"uint32",data:[y]},{type:"uint32",data:[s]},{type:"uint32",data:[...b]}],C=a.makeTensorInfo([c,p],"int32"),E=a.tensorMap.get(C.dataId);E.resourceInfo=A;let _=a.runWebGPUProgram(w,[C],"int32",S);return a.disposeData(C.dataId),_}let m=r.data,g=m;if(s!=null&&s!==4){g=new Uint8Array(r.width*r.height*s);let A=m.length,y=0;for(let b=0;b<A;b++)b%4<s&&(g[y++]=m[b])}let x=a.makeTensorInfo(d,"int32",new Int32Array(g));return a.uploadToGPU(x.dataId),x}var kle=class{constructor(e,t,a,n,r){this.uniforms="varianceEpsilon : f32,",this.workgroupSize=[128,1,1],this.size=!0,this.variableNames=["x","mean","variance"],T.assertAndGetBroadcastShape(e,t),T.assertAndGetBroadcastShape(e,a),this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),n!=null&&(T.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset")),r!=null&&(T.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale")),this.offsetShape=n,this.scaleShape=r,this.shaderKey="batchNorm"}getUserCode(){let e="0.0";this.offsetShape!=null&&(e="getOffsetByOutputIndex(index)");let t="1.0";return this.scaleShape!=null&&(t="getScaleByOutputIndex(index)"),`
${Ce("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)));
}
}
`}},Ile={kernelName:yi,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n,scale:r,offset:s,mean:i,variance:o}=e,{varianceEpsilon:l}=t,u=a,p=[n,i,o],c=null;s!=null&&(c=s.shape,p.push(s));let d=null;r!=null&&(d=r.shape,p.push(r));let h=new kle(n.shape,i.shape,o.shape,c,d),f=[{type:"float32",data:[l]}];return u.runWebGPUProgram(h,p,n.dtype,f)}};function Sle(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:p,dilations:c,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=n,m=T.convertConv2DDataFormat(p),g=T.computeConv2DInfo(r.shape,s.shape,l,c,u,d,!1,m);return B8({x:r,filter:s,convInfo:g,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:f,activation:h})}var Tle={kernelName:qr,backendName:"webgpu",kernelFunc:Sle};function Cle(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dimRoundingMode:c,activation:d,leakyreluAlpha:h}=n,f=p;f==null&&(f=[1,1]),v.assert(T.eitherStridesOrDilationsAreOne(l,f),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${f}'`);let m=T.computeConv2DInfo(r.shape,s.shape,l,f,u,c,!0),g=[r,s],x=i!=null,A=o!=null;x&&g.push(i),A&&g.push(o);let y=[{type:"int32",data:[m.padInfo.top,m.padInfo.left]},{type:"int32",data:[m.inHeight,m.inWidth]}],b;return m.outHeight>4&&m.outWidth>4&&m.strideWidth<=2&&m.inChannels===m.outChannels&&m.dilationHeight===1&&m.dilationWidth===1&&m.inChannels%4===0?b=new V8(m,x,d,A):(b=new U8(m,x,d,A),y.push({type:"int32",data:[m.filterHeight]},{type:"int32",data:[m.filterWidth]},{type:"int32",data:[m.strideHeight,m.strideWidth]},{type:"int32",data:[m.dilationHeight,m.dilationWidth]})),d==="leakyrelu"&&(y.push({type:"float32",data:[h]}),b.uniforms+=" alpha : f32,"),a.runWebGPUProgram(b,g,"float32",y)}var Nle={kernelName:Xr,backendName:"webgpu",kernelFunc:Cle},Ele=class{constructor(e,t){this.variableNames=["A","indices"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`gathernd_${e}`,this.sliceDim=e,this.uniforms=`sliceDim : i32, strides : ${ra(e)},`}getUserCode(){let e;return this.sliceDim>1?e="uniforms.strides[j]":e="uniforms.strides",`
${Ce("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 = ${e};
flattenIndex = flattenIndex + indexTemp * strideNum;
}
setOutputAtIndex(index, getA(flattenIndex, coords[1]));
}
}
`}};function Rle(e){let{inputs:t,backend:a}=e,{params:n,indices:r}=t,s=r.shape,i=s[s.length-1],o=v.sizeFromShape(n.shape),[l,u,p,c]=T.prepareAndValidate(n,r),d=Ie({inputs:{x:r},backend:a,attrs:{shape:[u,i]}}),h=Ie({inputs:{x:n},backend:a,attrs:{shape:[v.sizeFromShape(n.shape)/p,p]}});if(a.shouldExecuteOnCPU([n,r])||n.dtype==="string"){let A=a.readSync(r.dataId),y=a.bufferSync(n),b=Lse(A,y,n.dtype,u,i,p,c,n.shape,o);return a.makeTensorInfo(l,n.dtype,b.values)}let f=new Ele(i,[u,p]),m=[{type:"int32",data:[i]},{type:"int32",data:c}],g=a.runWebGPUProgram(f,[h,d],h.dtype,m),x=Ie({inputs:{x:g},backend:a,attrs:{shape:l}});return a.disposeData(d.dataId),a.disposeData(h.dataId),a.disposeData(g.dataId),x}var Mle={kernelName:bi,backendName:"webgpu",kernelFunc:Rle},$le=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=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="gather"}getUserCode(){let e=_le(this.aShape);return`
${Ce("index")} {
if (index < uniforms.size) {
let resRC = getCoordsFromIndex(index);
let indexZ = i32(getIndices(resRC.x, resRC.z));
let inBounds = select(0.0, 1.0, indexZ >= 0 && indexZ < uniforms.aShape[2]);
setOutputAtIndex(index, inBounds * getA(${e}));
}
}
`}};function _le(e){let t=["resRC.x","resRC.y","resRC.z","resRC.w"],a=[];for(let n=0;n<e.length;n++)n===2?a.push("indexZ"):a.push(`${t[n]}`);return a.join()}function q8(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,indices:s}=t,{axis:i,batchDims:o}=n,l=v.parseAxisParam(i,r.shape)[0],u=T.segment_util.collectGatherOpShapeInfo(r,s,l,o),p=v.sizeFromShape(s.shape),c=[],d=Ie({inputs:{x:r},backend:a,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=Ie({inputs:{x:s},backend:a,attrs:{shape:[u.batchSize,p/u.batchSize]}});c.push(d),c.push(h);let f=[u.batchSize,u.outerSize,p/u.batchSize,u.sliceSize];if(a.shouldExecuteOnCPU([r,s])){let A=a.tensorMap.get(h.dataId).values,y=Me(h.shape,h.dtype,A),b=a.tensorMap.get(d.dataId).values,w=Me(d.shape,d.dtype,b),S=Bse(w,y,f);return c.forEach(C=>a.disposeData(C.dataId)),a.makeTensorInfo(u.outputShape,S.dtype,S.values)}let m=new $le(d.shape,f),g=a.runWebGPUProgram(m,[d,h],d.dtype);c.push(g);let x=Ie({inputs:{x:g},backend:a,attrs:{shape:u.outputShape}});return c.forEach(A=>a.disposeData(A.dataId)),x}var Ple={kernelName:Ol,backendName:"webgpu",kernelFunc:q8},Fle=ua({opType:De.GREATER,cpuKernelImpl:Vse,dtype:"bool"}),Ole={kernelName:vi,backendName:"webgpu",kernelFunc:Fle},Dle=ua({opType:De.GREATER_EQUAL,dtype:"bool",cpuKernelImpl:Wse}),zle={kernelName:wi,backendName:"webgpu",kernelFunc:Dle};function Lle(e){let{inputs:t,backend:a}=e,{input:n}=t;return j8(n,!0,a)}var Ble={kernelName:Ed,backendName:"webgpu",kernelFunc:Lle},Wle=it({opType:de.IS_FINITE,dtype:"bool"}),Vle={kernelName:Dl,backendName:"webgpu",kernelFunc:Wle},Ule=it({opType:de.IS_INF,dtype:"bool"}),Gle={kernelName:zl,backendName:"webgpu",kernelFunc:Ule},Hle=it({opType:de.IS_NAN,dtype:"bool"}),jle={kernelName:Ii,backendName:"webgpu",kernelFunc:Hle};function qle(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{alpha:s}=n,i=[{type:"float32",data:[s]}],o=new mp(r.shape,de.LEAKYRELU);return o.uniforms="alpha : f32,",a.runWebGPUProgram(o,[r],"float32",i)}var Xle={kernelName:Si,backendName:"webgpu",kernelFunc:qle},Kle=ua({opType:De.LESS,dtype:"bool",cpuKernelImpl:Gse}),Zle={kernelName:Ti,backendName:"webgpu",kernelFunc:Kle},Yle=ua({opType:De.LESS_EQUAL,dtype:"bool",cpuKernelImpl:Use}),Jle={kernelName:Ci,backendName:"webgpu",kernelFunc:Yle},Qle=it({opType:de.LOG,cpuKernelImpl:Hse}),eue={kernelName:Ni,backendName:"webgpu",kernelFunc:Qle},tue=it({opType:de.LOG1P}),aue={kernelName:Ll,backendName:"webgpu",kernelFunc:tue},nue=ua({opType:De.LOGICAL_AND,dtype:"bool"}),rue={kernelName:Ei,backendName:"webgpu",kernelFunc:nue},sue=it({opType:de.LOGICAL_NOT}),iue={kernelName:Ri,backendName:"webgpu",kernelFunc:sue},oue=ua({opType:De.MAX,cpuKernelImpl:qse}),lue={kernelName:$i,backendName:"webgpu",kernelFunc:oue};function uue(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1,p=T.computePool2DInfo(r.shape,s,i,u,o,l);return O8(r,p,"max",a)}var due={kernelName:_i,backendName:"webgpu",kernelFunc:uue};function pue(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return ko(r,s,i,"min",a)}var cue={kernelName:Fi,backendName:"webgpu",kernelFunc:pue},hue=ua({opType:De.MIN,cpuKernelImpl:Xse}),fue={kernelName:Oi,backendName:"webgpu",kernelFunc:hue},mue=class{constructor(e,t,a){this.uniforms="",this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((n,r)=>n[0]+e[r]+n[1]),this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.xShape=e,t.map((n,r)=>{this.uniforms+=` pad${r} : vec2<i32>,`}),this.offset=a==="reflect"?0:1,this.shaderKey=`mirrorPad_${a}`}getUserCode(){let e=this.xShape.length,t=this.xShape.map((l,u)=>`uniforms.pad${u}[0]`).join(","),a=this.xShape.map((l,u)=>`uniforms.pad${u}[0] + uniforms.xShape${e>1?`[${u}]`:""}`).join(","),n=e===1?"start":"start[i]",r=e===1?"end":"end[i]",s=e===1?"outC":"outC[i]",i=ra(e),o=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
${Ce("index")} {
if (index < uniforms.size) {
let start = ${i}(${t});
let end = ${i}(${a});
var outC = getCoordsFromIndex(index);
for (var i = 0; i < ${e}; i = i + 1) {
if (${s} < ${n}) {
${s} = ${n} * 2 - ${s} - ${this.offset};
} else if(${s} >= ${r}) {
${s} = (${r} - 1) * 2 - ${s} + ${this.offset};
}
}
let coords = outC - start;
setOutputAtIndex(index, getX(${o}));
}
}
`}},gue={kernelName:Di,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n}=e,{paddings:r,mode:s}=t,i=a,o=r.map(u=>({type:"int32",data:[u[0],u[1]]})),l=new mue(n.shape,r,s);return i.runWebGPUProgram(l,[n],n.dtype,o)}},xue=ua({opType:De.MOD}),Aue={kernelName:Wl,backendName:"webgpu",kernelFunc:xue};function yue(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])){let s=a.tensorMap.get(n.dataId),[i,o]=Zse(s.values,n.shape,n.dtype);return a.makeTensorInfo(o,n.dtype,i)}let r=new mp(n.shape,de.NEG);return a.runWebGPUProgram(r,[n],n.dtype)}var bue={kernelName:Vl,backendName:"webgpu",kernelFunc:yue};function vue(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=n,u=a.readSync(r.dataId),p=a.readSync(s.dataId),{selectedIndices:c}=Tn.nonMaxSuppressionV3Impl(u,p,i,o,l);return a.makeTensorInfo([c.length],"int32",new Int32Array(c))}var wue={kernelName:Bi,backendName:"webgpu",kernelFunc:vue};function kue(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=n,p=a.readSync(r.dataId),c=a.readSync(s.dataId),d=i,h=o,f=l,m=u,{selectedIndices:g,selectedScores:x}=Tn.nonMaxSuppressionV5Impl(p,c,d,h,f,m);return[a.makeTensorInfo([g.length],"int32",new Int32Array(g)),a.makeTensorInfo([x.length],"float32",new Float32Array(x))]}var Iue={kernelName:Wi,backendName:"webgpu",kernelFunc:kue},Sue=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=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="onehot"}getUserCode(){return`
${Ce("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 Tue(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=n,u=v.sizeFromShape(r.shape),p=new Sue(u,i),c=Ie({inputs:{x:r},backend:a,attrs:{shape:[u]}}),d=[{type:"float32",data:[o]},{type:"float32",data:[l]}],h=a.runWebGPUProgram(p,[c],s,d);a.disposeData(c.dataId);let f=[...r.shape,i],m=Ie({inputs:{x:h},backend:a,attrs:{shape:f}});return a.disposeData(h.dataId),m}var Cue={kernelName:Vi,backendName:"webgpu",kernelFunc:Tue};function Vc(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="complex64"){let r=gp({inputs:{input:n},backend:a}),s=Vc({inputs:{x:r},backend:a}),i=jh({inputs:{input:n},backend:a}),o=Vc({inputs:{x:i},backend:a}),l=wo({inputs:{real:s,imag:o},backend:a});return a.disposeData(r.dataId),a.disposeData(s.dataId),a.disposeData(i.dataId),a.disposeData(o.dataId),l}else return Cr({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:a})}var Nue={kernelName:nu,backendName:"webgpu",kernelFunc:Vc};function X8(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(n.dtype==="complex64"){let r=gp({inputs:{input:n},backend:a}),s=X8({inputs:{x:r},backend:a}),i=jh({inputs:{input:n},backend:a}),o=Vc({inputs:{x:i},backend:a}),l=wo({inputs:{real:s,imag:o},backend:a});return a.disposeData(r.dataId),a.disposeData(s.dataId),a.disposeData(i.dataId),a.disposeData(o.dataId),l}else return Cr({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:a})}var Eue={kernelName:Gl,backendName:"webgpu",kernelFunc:X8};function Rue(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return D1({inputs:{input:t[0]},backend:a,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{v.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===p.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(p=>{let c=D1({inputs:{input:p},backend:a,attrs:{dim:r}});return o.push(c),c}),u=L8({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(p=>a.disposeData(p.dataId)),u}var Mue={kernelName:Hl,backendName:"webgpu",kernelFunc:Rue},$ue=class{constructor(e,t){this.variableNames=["x"],this.uniforms="constantValue : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((a,n)=>a[0]+e[n]+a[1]),this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),t.map((a,n)=>{this.uniforms+=` pad${n} : vec2<i32>,`}),this.xShape=e,this.shaderKey="pad"}getUserCode(){let e=this.xShape.length,t=ra(e),a=this.xShape.map((u,p)=>`uniforms.pad${p}[0]`).join(","),n=this.xShape.map((u,p)=>`uniforms.pad${p}[0] + uniforms.xShape${e>1?`[${p}]`:""}`).join(","),r=e>1?`${t}(${a})`:`${a}`,s=e>1?`${t}(${n})`:`${n}`,i=e>1?"any(outC < start)":"outC < start",o=e>1?"any(outC >= end)":"outC >= end",l=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
${Ce("index")} {
if (index < uniforms.size) {
let start = ${r};
let end = ${s};
let outC = getCoordsFromIndex(index);
if (${i} || ${o}) {
setOutputAtIndex(index, uniforms.constantValue);
} else {
let coords = outC - start;
setOutputAtIndex(index, getX(${l}));
}
}
}
`}},K8=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{paddings:s,constantValue:i}=n;if(s.every(u=>v.arraysEqual(u,[0,0])))return Ya({inputs:{x:r},backend:a});if(v.sizeFromShape(r.shape)===0){let u=s.map((p,c)=>p[0]+r.shape[c]+p[1]);return Cr({backend:a,attrs:{shape:u,value:i,dtype:r.dtype}})}let o=[{type:"float32",data:[i]}];s.map(u=>o.push({type:"int32",data:[u[0],u[1]]}));let l=new $ue(r.shape,s);return a.runWebGPUProgram(l,[r],r.dtype,o)},_ue={kernelName:Ui,backendName:"webgpu",kernelFunc:K8},Pue=ua({opType:De.POW}),Fue={kernelName:Gi,backendName:"webgpu",kernelFunc:Pue};function Oue(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t,s=new P1(De.PRELU,n.shape,r.shape);return a.runWebGPUProgram(s,[n,r],"float32")}var Due={kernelName:Hi,backendName:"webgpu",kernelFunc:Oue};function zue(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return ko(r,s,i,"prod",a)}var Lue={kernelName:ji,backendName:"webgpu",kernelFunc:zue},Bue=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=Qse(n,r,s,i);return t.makeTensorInfo([o.length],i,o)},Wue={kernelName:jl,backendName:"webgpu",kernelFunc:Bue},Z8=ua({opType:De.DIV}),Vue={kernelName:ci,backendName:"webgpu",kernelFunc:Z8},Uue=it({opType:de.RECIPROCAL}),Gue={kernelName:qi,backendName:"webgpu",kernelFunc:Uue},Hue=it({opType:de.RELU}),jue={kernelName:Xi,backendName:"webgpu",kernelFunc:Hue},que=it({opType:de.RELU6}),Xue={kernelName:Yi,backendName:"webgpu",kernelFunc:que},Kue=class{constructor(e,t,a){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, halfPixelCenters : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,a,e[3]],this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="resizeBilinear"}getUserCode(){return`
${Ce("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 Zue(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,size:i,halfPixelCenters:o}=n,[l,u]=i,p=s&&l>1?1:0,c=s&&u>1?1:0,d=[{type:"float32",data:[p,c]},{type:"float32",data:[o?.5:0]}],h=new Kue(r.shape,l,u);return a.runWebGPUProgram(h,[r],"float32",d)}var Yue={kernelName:Zi,backendName:"webgpu",kernelFunc:Zue},Jue=class{constructor(e,t,a,n){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, roundBase : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,a,e[3]],this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(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",`
${Ce("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 Que(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,p=s&&l>1?1:0,c=s&&u>1?1:0,d=[{type:"float32",data:[p,c]},{type:"float32",data:[s?.5:0]}],h=new Jue(r.shape,l,u,i);return a.runWebGPUProgram(h,[r],r.dtype,d)}var ede={kernelName:Ki,backendName:"webgpu",kernelFunc:Que},tde=class{constructor(e){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(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;
}
${Ce("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 ade(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dims:s}=n,i=r.shape.length;if(i===0)return Ya({inputs:{x:r},backend:a});let o=r.shape,l=[1,1,1,1];o.forEach((g,x)=>{let A=x+4-i;l[A]=g});let u=v.parseAxisParam(s,r.shape),p=[0,0,0,0];u.forEach(g=>{let x=g+4-i;p[x]=1});let c=[{type:"int32",data:p}],d=Ie({inputs:{x:r},backend:a,attrs:{shape:l}}),h=new tde(l),f=a.runWebGPUProgram(h,[d],d.dtype,c);a.disposeData(d.dataId);let m=Ie({inputs:{x:f},backend:a,attrs:{shape:o}});return a.disposeData(f.dataId),m}var nde={kernelName:Ji,backendName:"webgpu",kernelFunc:ade},rde=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(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`
${Ce("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));
${this.fillSnippet}
if(coordX >= 0 && coordX < uniforms.xShape[2] && coordY >= 0 &&
coordY < uniforms.xShape[1]) {
outputValue = getX(coords[0], coordY, coordX, coords[3]);
}
setOutputAtIndex(index, outputValue);
}
}
`}},sde={kernelName:mo,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{image:n}=e,{radians:r,fillValue:s,center:i}=t,o=a,l=new rde(n.shape,s),[u,p]=T.getImageCenter(i,n.shape[1],n.shape[2]),c=[{type:"float32",data:[u]},{type:"float32",data:[p]},{type:"float32",data:[Math.sin(r)]},{type:"float32",data:[Math.cos(r)]}];return typeof s=="number"?c.push({type:"float32",data:[Number.parseFloat(s.toFixed(2))]}):c.push({type:"float32",data:s}),o.runWebGPUProgram(l,[n],n.dtype,c)}},ide=it({opType:de.RSQRT,cpuKernelImpl:eie}),ode={kernelName:Qi,backendName:"webgpu",kernelFunc:ide},vc=class{constructor(e,t,a,n,r,s,i,o=!0){this.variableNames=["updates","indices"],this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=s,this.type=i,this.sumDupeIndices=o,this.dispatchLayout=Ve(e),this.dispatch=Ne(this.dispatchLayout,e,this.workgroupSize),this.sliceDimGreaterThanOne=t>1,this.shaderKey=`scatter_${a}_${n}_${this.sliceDimGreaterThanOne}_${i}_${o}`;let l=ra(r.length);this.uniforms=`sliceDim : i32, strides: ${l}, updatesSize: i32,`,this.updatesRank=n,this.indicesRank=a}getUserCode(){let e="";this.indicesRank===1?e="coords[0]":this.indicesRank===2&&(e="coords[0], j");let t=`getIndices(${e})`,a=this.sliceDimGreaterThanOne?"uniforms.strides[j]":"uniforms.strides",n="",r="";this.dispatchLayout.x.length===1?(n="flattenedIndex",r=`
fn getUpdatesCoordsFromFlatIndex(index : i32) -> i32 {
return index;
}
`):this.dispatchLayout.x.length===2&&(n="vec2<i32>(flattenedIndex, coords[1])",r=`
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 s=`getUpdates(${Array.from({length:this.updatesRank},(o,l)=>`coords[${l}]`).join(", ")})`,i=(o,l)=>{let u=`atomicAdd(${o}, bitcast<i32>(${l}))`;this.type==="float32"&&(u=`
{
var oldBits = 0;
var newBits = bitcast<i32>(${l});
loop {
let info = atomicCompareExchangeWeak(${o}, oldBits, newBits);
if (info.exchanged) {
break;
}
oldBits = info.old_value;
let oldValue = bitcast<f32>(oldBits);
let newValue = oldValue + (${l});
newBits = bitcast<i32>(newValue);
}
}
`);let p=`atomicStore(${o}, bitcast<i32>(${l}));`;return this.sumDupeIndices?u:p};return`
${r}
${Ce("index")} {
if (index < uniforms.updatesSize) {
let coords = getUpdatesCoordsFromFlatIndex(index);
var flattenedIndex = 0;
for (var j = 0; j < uniforms.sliceDim; j = j + 1) {
let indexInside = i32(round(${t}));
flattenedIndex = flattenedIndex + indexInside * ${a};
}
let updateValue =
${ad(this.type,!1)}(${s});
let flatIndex = getOutputIndexFromCoords(${n});
${i("&result[flatIndex]","updateValue")};
}
}`}};function lde(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r,updates:s}=t,{shape:i}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:c}=T.calculateShapes(s,r,i),d=[c/u,u];if(c===0)return a.makeTensorInfo(i,r.dtype);let h=Ie({inputs:{x:r},backend:a,attrs:{shape:[l,o]}}),f=Ie({inputs:{x:s},backend:a,attrs:{shape:[l,u]}}),m=f.dtype,g=Cr({backend:a,attrs:{shape:d,value:0,dtype:m}}),x=v.sizeFromShape(f.shape),A=[{type:"int32",data:[o]},{type:"int32",data:p},{type:"int32",data:[x]}],y=new vc(f.shape,o,h.shape.length,f.shape.length,p,d,m),b=a.runWebGPUProgram(y,[f,h],m,A,g),w=Ie({inputs:{x:b},backend:a,attrs:{shape:i}});return a.disposeData(h.dataId),a.disposeData(f.dataId),a.disposeData(b.dataId),w}var ude={kernelName:eo,backendName:"webgpu",kernelFunc:lde},dde=class{constructor(e,t){this.outputShape=[],this.variableNames=["sortedSequence","values"],this.uniforms="numInputs : i32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.side=t,this.shaderKey=`search_sorted_${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;
}
${Ce("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let value = getValuesByOutputIndex(index);
setOutputAtIndexI32(index, findBound(coords[0], value));
}
}
`}};function pde(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n,o=new dde([s.shape[0],s.shape[1]],i),l=[{type:"int32",data:[r.shape[1]]}];return a.runWebGPUProgram(o,[r,s],"int32",l)}var cde={kernelName:$d,backendName:"webgpu",kernelFunc:pde},hde=class{constructor(e,t,a){this.variableNames=["c","a","b"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.cRank=e,this.rank=a,this.shaderKey="select"}getUserCode(){let e,t;if(this.rank>4)throw Error(`Where for rank ${this.rank} is not yet supported`);if(this.rank===1)t="resRC",e="resRC";else{let a=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[],r=[];for(let s=0;s<this.outputShape.length;s++)r.push(`${a[s]}`),s<this.cRank&&n.push(`${a[s]}`);e=n.join(),t=r.join()}return`
${Ce("index")} {
if (index < uniforms.size) {
let resRC = getCoordsFromIndex(index);
let cVal = getC(${e});
if (cVal >= 1.0) {
setOutputAtIndex(index, getA(${t}));
} else {
setOutputAtIndex(index, getB(${t}));
}
}
}
`}};function fde(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t,i=new hde(n.shape.length,r.shape,r.shape.length);return a.runWebGPUProgram(i,[n,r,s],ca(r.dtype,s.dtype))}var mde={kernelName:Kl,backendName:"webgpu",kernelFunc:fde},gde=it({opType:de.SIGMOID}),xde={kernelName:ao,backendName:"webgpu",kernelFunc:gde},Ade=it({opType:de.SIN}),yde={kernelName:to,backendName:"webgpu",kernelFunc:Ade},bde=it({opType:de.SINH}),vde={kernelName:Yl,backendName:"webgpu",kernelFunc:bde},Y8=ua({opType:De.SUB,cpuKernelImpl:iie,supportsComplex:!0}),wde={kernelName:lo,backendName:"webgpu",kernelFunc:Y8};function kde(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{dim:s}=n,i=v.parseAxisParam([s],r.shape),o=W3({inputs:{x:r},backend:a,attrs:{reductionIndices:i,keepDims:!1}}),l=T.expandShapeToKeepDim(o.shape,i),u=Ie({inputs:{x:o},backend:a,attrs:{shape:l}}),p=Y8({inputs:{a:r,b:u},backend:a}),c=H8({inputs:{x:p},backend:a}),d=V3({inputs:{x:c},backend:a,attrs:{axis:i,keepDims:!1}}),h=Ie({inputs:{x:d},backend:a,attrs:{shape:l}}),f=Z8({inputs:{a:c,b:h},backend:a});return a.disposeData(o.dataId),a.disposeData(u.dataId),a.disposeData(p.dataId),a.disposeData(c.dataId),a.disposeData(d.dataId),a.disposeData(h.dataId),f}var Ide={kernelName:so,backendName:"webgpu",kernelFunc:kde},Sde=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,paddings:i}=n;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGPU backend not implemented yet");let o=s.reduce((x,A)=>x*A),l=[[0,0]];l.push(...i);for(let x=1+s.length;x<r.shape.length;++x)l.push([0,0]);let u=[],p=K8({inputs:{x:r},backend:a,attrs:{paddings:l,constantValue:0}}),c=T.getReshaped(p.shape,s,o,!1),d=T.getPermuted(c.length,s.length,!1),h=T.getReshapedPermuted(p.shape,s,o,!1),f=Ie({inputs:{x:p},backend:a,attrs:{shape:c}}),m=vr({inputs:{x:f},backend:a,attrs:{perm:d}}),g=Ie({inputs:{x:m},backend:a,attrs:{shape:h}});return u.push(p),u.push(f),u.push(m),u.forEach(x=>a.disposeData(x.dataId)),g},Tde={kernelName:Jl,backendName:"webgpu",kernelFunc:Sde},Cde=class{constructor(e,t){this.variableNames=["A"],this.workgroupSize=[64,1,1],this.size=!0;let a=new Array(e.length);for(let n=0;n<a.length;n++)a[n]=e[n]*t[n];this.outputShape=a,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.rank=this.outputShape.length,this.shaderKey="tile"}getUserCode(){let e=Nde(this.rank,"uniforms.");return`
${Ce("index")} {
if (index < uniforms.size) {
let resRC = getCoordsFromIndex(index);
setOutputAtIndex(index, getA(${e}));
}
}
`}};function Nde(e,t=""){if(e>=5)throw Error(`Tile for rank ${e} is not yet supported`);if(e===1)return`(resRC % ${t}aShape)`;let a=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let r=0;r<e;r++)n.push(`(${a[r]} % ${t}aShape[${r}])`);return n.join()}function J8(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reps:s}=n;if(a.shouldExecuteOnCPU([r])||r.dtype==="string"||r.shape.length>=5){let o=a.readSync(r.dataId),l=r.dtype==="string"?o.map(c=>v.decodeString(c)):o,u=Me(r.shape,r.dtype,l),p=oie(u,s);return a.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new Cde(r.shape,s);return a.runWebGPUProgram(i,[r],r.dtype)}var Ede={kernelName:ns,backendName:"webgpu",kernelFunc:J8};function Rde(e){let{inputs:t,backend:a,attrs:n}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=t,{outputShape:o}=n,{sliceRank:l,numUpdates:u,sliceSize:p,strides:c,outputSize:d}=T.calculateShapes(s,r,o),h=!1;if(s.dtype==="string"){let E=a.bufferSync(r),_=a.bufferSync(s),$=v.decodeString(a.readSync(i.dataId)[0]),M=tie(E,_,o,d,p,u,l,c,$,h);return a.makeTensorInfo(o,M.dtype,M.values)}let f=[d/p,p],m=Ie({inputs:{x:r},backend:a,attrs:{shape:[u,l]}}),g=s.shape.length?Ie({inputs:{x:s},backend:a,attrs:{shape:[u,p]}}):Ya({inputs:{x:s},backend:a}),x=g.dtype,A=a.makeTensorInfo([],x,v.makeZerosTypedArray(1,x)),y=Ie({inputs:{x:i},backend:a,attrs:{shape:Array(f.length).fill(1)}}),b=J8({inputs:{x:y},backend:a,attrs:{reps:f}}),w=v.sizeFromShape([u,p]),S=[{type:"int32",data:[l]},{type:"int32",data:c},{type:"int32",data:[w]}];switch(u){case 0:break;case 1:{let E=new vc([u,p],l,m.shape.length,g.shape.length,c,f,x,h);a.runWebGPUProgram(E,[g,m],x,S,b)}break;default:{let E=new vc([u,p],l,m.shape.length,A.shape.length,c,f,x,h);a.runWebGPUProgram(E,[A,m],x,S,b)}{let E=new vc([u,p],l,m.shape.length,g.shape.length,c,f,x);a.runWebGPUProgram(E,[g,m],x,S,b)}}let C=Ie({inputs:{x:b},backend:a,attrs:{shape:o}});return a.disposeData(m.dataId),a.disposeData(g.dataId),a.disposeData(y.dataId),a.disposeData(A.dataId),a.disposeData(b.dataId),C}var Mde={kernelName:Ld,backendName:"webgpu",kernelFunc:Rde};function $de(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=n,o=v.parseAxisParam(i,r.shape)[0],l=T.prepareSplitSize(r,s,o),u=r.shape.length,p=new Array(u).fill(0),c=r.shape.slice();return l.map(d=>{let h=[...c];h[o]=d;let f=Au({inputs:{x:r},backend:a,attrs:{begin:p,size:h}});return p[o]+=d,f})}var _de={kernelName:Ql,backendName:"webgpu",kernelFunc:$de},Pde=it({opType:de.SQRT}),Fde={kernelName:no,backendName:"webgpu",kernelFunc:Pde},Ode={kernelName:Bd,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{x:a}=e,n=t,r=new mp(a.shape,de.SQUARE);return n.runWebGPUProgram(r,[a],a.dtype)}},Dde=ua({opType:De.SQUARED_DIFFERENCE}),zde={kernelName:io,backendName:"webgpu",kernelFunc:Dde},Lde=class{constructor(e){this.variableNames=["x"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]);let t=ra(this.outputShape.length);this.uniforms=`begin : ${t}, strides : ${t}, `,this.shaderKey="stridedSlice"}getUserCode(){let e=this.outputShape.length,t="";if(e===1)t="coords * uniforms.strides + uniforms.begin";else{let a=0;t=this.outputShape.map((n,r)=>(a++,this.outputShape.length===1?`coords * uniforms.strides[${r}] + uniforms.begin[${r}]`:`coords[${a-1}] * uniforms.strides[${r}] + uniforms.begin[${r}]`)).join(",")}return`
${Ce("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
setOutputAtIndex(index, getX(${t}));
}
}
`}};function Bde(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:p,newAxisMask:c,shrinkAxisMask:d}=n,{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:x,begin:A,end:y,strides:b}=It.sliceInfo(r.shape,s,i,o,l,u,p,c,d),w;if(m)w=Ie({inputs:{x:r},backend:a,attrs:{shape:f}});else if(g||x){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let S=It.computeOutShape(A,y,b),C=Au({inputs:{x:r},backend:a,attrs:{begin:A,size:S}});w=Ie({inputs:{x:C},backend:a,attrs:{shape:f}}),a.disposeData(C.dataId)}else if(a.shouldExecuteOnCPU([r])){let S=a.readSync(r.dataId),C=Me(r.shape,r.dtype,S),E=rie(h,C,b,A);w=a.makeTensorInfo(f,r.dtype,E.values)}else{let S=new Lde(h),C=[{type:"int32",data:A},{type:"int32",data:b}],E=a.runWebGPUProgram(S,[r],r.dtype,C);w=Ie({inputs:{x:E},backend:a,attrs:{shape:f}}),a.disposeData(E.dataId)}return w}var Wde={kernelName:oo,backendName:"webgpu",kernelFunc:Bde};function Vde(e){let{inputs:t,backend:a,attrs:n}=e,{separator:r,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:u}=n,{data:p,dataSplits:c}=t,d=a.readSync(p.dataId),h=a.readSync(c.dataId),[f,m]=sie(d,h,r,s,i,o,l,u);return[a.makeTensorInfo([f.length],"string",f),a.makeTensorInfo(c.shape,"int32",m)]}var Ude={kernelName:tu,backendName:"webgpu",kernelFunc:Vde},Gde=it({opType:de.TAN}),Hde={kernelName:uo,backendName:"webgpu",kernelFunc:Gde},jde=it({opType:de.TANH}),qde={kernelName:po,backendName:"webgpu",kernelFunc:jde},Xde=class{constructor(e){this.variableNames=["x","indices"],this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms=`inputSize : i32, firstPass : i32, negativeInf : f32,
dir : i32, inc : i32,`,this.shaderKey="swap"}getUserCode(){return`
${Ce("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));
}
}
}
`}},Kde=class{constructor(e){this.variableNames=["x","indices"],this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Ve(this.outputShape),this.dispatch=Ne(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms="inputSize : i32, firstPass : i32, k : i32,",this.shaderKey="merge"}getUserCode(){return`
${Ce("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 Jo(e,t){t!==null&&e.disposeData(t.dataId)}function eA(e){let t=1;for(;t<e;)t*=2;return t}function Zde(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{k:s,sorted:i}=n,o=r.shape,l=o[o.length-1];if(a.shouldExecuteOnCPU([r])){let b=a.readSync(r.dataId),[w,S]=lie(b,o,r.dtype,s,i);return[a.makeTensorInfo(w.shape,w.dtype,w.values),a.makeTensorInfo(S.shape,S.dtype,S.values)]}if(s===0)return o[o.length-1]=0,[a.makeTensorInfo(o,r.dtype,[]),a.makeTensorInfo(o,"int32",[])];if(l===1)return[r,Cr({attrs:{shape:o,dtype:"int32",value:0},backend:a})];let u=v.sizeFromShape(o)/l,p=Ie({inputs:{x:r},attrs:{shape:[u,l]},backend:a}),c=eA(s),d=eA(l),h=null,f=()=>h===null?[p,p]:[p,h],m=(b,w,S)=>{let C=f(),E=new Xde(S),_=[{type:"int32",data:[l]},{type:"int32",data:[h===null?1:0]},{type:"float32",data:[Number.NEGATIVE_INFINITY]},{type:"int32",data:[b]},{type:"int32",data:[w]}],$=h;h=a.runWebGPUProgram(E,C,"int32",_),Jo(a,$)};for(let b=1;b<c;b*=2){let w=b*2;for(let S=b;S>=1;S/=2)m(w,S,[u,d])}for(let b=d;b>c;b/=2){let w=f(),S=new Kde([u,b/2]),C=[{type:"int32",data:[l]},{type:"int32",data:[h===null?1:0]},{type:"int32",data:[c]}],E=h;h=a.runWebGPUProgram(S,w,"int32",C),Jo(a,E);let _=c/2,$=_*2;for(let M=_;M>=1;M/=2)m($,M,h.shape)}let g=h;h=Au({inputs:{x:h},backend:a,attrs:{begin:0,size:[u,s]}}),Jo(a,g);let x=q8({inputs:{x:p,indices:h},backend:a,attrs:{axis:1,batchDims:1}});Jo(a,p);let A=o.slice(0,-1);A.push(s),g=h,h=Ie({inputs:{x:h},attrs:{shape:A},backend:a}),Jo(a,g);let y=x;return x=Ie({inputs:{x},attrs:{shape:A},backend:a}),Jo(a,y),[x,h]}var Yde={kernelName:co,backendName:"webgpu",kernelFunc:Zde},Jde=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=Ve(this.outputShape),this.dispatch=Ne(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;
}
${Ce("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);
}
}
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attribute vec2 pos;
attribute vec2 uv;
varying vec2 vUv;
uniform float flipY;
void main(void) {
vUv = uv;
gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);
}
`;var t9=`
precision highp float;
varying vec2 vUv;
uniform sampler2D texture;
uniform float m[20];
void main(void) {
vec4 c = texture2D(texture, vUv);
gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];
gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];
gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];
gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];
}
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precision highp float;
varying vec2 vUv;
uniform sampler2D texture;
uniform float m[20];
void main(void) {
vec4 c = texture2D(texture, vUv);
gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];
gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];
gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];
gl_FragColor.a = c.a;
}
`,n9=`
precision highp float;
varying vec2 vUv;
uniform vec2 size;
uniform sampler2D texture;
vec2 pixelate(vec2 coord, vec2 size) {
return floor( coord / size ) * size;
}
void main(void) {
gl_FragColor = vec4(0.0);
vec2 coord = pixelate(vUv, size);
gl_FragColor += texture2D(texture, coord);
}
`,r9=`
precision highp float;
varying vec2 vUv;
uniform sampler2D texture;
uniform vec2 px;
void main(void) {
gl_FragColor = vec4(0.0);
gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;
gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;
gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;
gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;
gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;
gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;
gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;
gl_FragColor += texture2D(texture, vUv )*0.159576912161;
gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x, 1.0*px.y))*0.147308056121;
gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x, 2.0*px.y))*0.115876621105;
gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x, 3.0*px.y))*0.0776744219933;
gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x, 4.0*px.y))*0.0443683338718;
gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x, 5.0*px.y))*0.0215963866053;
gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x, 6.0*px.y))*0.00895781211794;
gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x, 7.0*px.y))*0.0044299121055113265;
}
`,s9=`
precision highp float;
varying vec2 vUv;
uniform sampler2D texture;
uniform vec2 px;
uniform float m[9];
void main(void) {
vec4 c11 = texture2D(texture, vUv - px); // top left
vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y)); // top center
vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y)); // top right
vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) ); // mid left
vec4 c22 = texture2D(texture, vUv); // mid center
vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) ); // mid right
vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) ); // bottom left
vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) ); // bottom center
vec4 c33 = texture2D(texture, vUv + px ); // bottom right
gl_FragColor =
c11 * m[0] + c12 * m[1] + c22 * m[2] +
c21 * m[3] + c22 * m[4] + c23 * m[5] +
c31 * m[6] + c32 * m[7] + c33 * m[8];
gl_FragColor.a = c22.a;
}
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_ce=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Pce=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Fce=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],Oce=[[474,475],[475,476],[476,477],[477,474]],Dce=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],zce=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],Lce=[[469,470],[470,471],[471,472],[472,469]],Bce=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]];function ps(e){let t=e.map(a=>a[0]);return t.push(e[e.length-1][1]),t}var Wce={lips:ps(_ce),leftEye:ps(Pce),leftEyebrow:ps(Fce),leftIris:ps(Oce),rightEye:ps(Dce),rightEyebrow:ps(zce),rightIris:ps(Lce),faceOval:ps(Bce)},Vce=Object.entries(Wce).map(([e,t])=>t.map(a=>[a,e])).flat(),P2e=new 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C
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${n} ${e.box[1]+e.box[3]},
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`),i=new Path2D(`
M ${e.box[0]} ${e.box[1]+e.box[3]/2}
C
${e.box[0]} ${r},
${e.box[0]+e.box[2]} ${r},
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age: [age] years
distance: [distance]cm
real: [real]%
live: [live]%
[emotions]
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t={};t.boxStarts=Pe(e,[0,1],[-1,2]),t.centers=be(t.boxStarts,xg),t.boxSizes=Pe(e,[0,3],[-1,2]),t.boxSizesNormalized=me(t.boxSizes,wu),t.centersNormalized=me(t.centers,wu),t.halfBoxSize=me(t.boxSizesNormalized,ze.tf2),t.starts=fe(t.centersNormalized,t.halfBoxSize),t.ends=be(t.centersNormalized,t.halfBoxSize),t.startNormalized=ae(t.starts,wu),t.endNormalized=ae(t.ends,wu);let a=ru([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>Y(t[n])),a}async function G9(e,t){var o,l,u,p;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let a={};a.resized=ge.resizeBilinear(e,[fs,fs]),a.div=me(a.resized,ze.tf127),a.normalized=fe(a.div,ze.tf05);let n=Ln==null?void 0:Ln.execute(a.normalized);if(Array.isArray(n)&&n.length>2){let c=n.sort((d,h)=>d.size-h.size);a.concat384=at([c[0],c[2]],2),a.concat512=at([c[1],c[3]],2),a.concat=at([a.concat512,a.concat384],1),a.batch=_e(a.concat,[0])}else 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Qa,ms=0,xhe=2.3,Ag=Rn.leftEyeLower0,yg=Rn.rightEyeLower0,Iu={leftBounds:[Ag[0],Ag[Ag.length-1]],rightBounds:[yg[0],yg[yg.length-1]]},Su={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function K9(e){var t,a;return ne.initial&&(Qa=null),Qa?e.debug&&K("cached model:",Qa.modelUrl):Qa=await Ee((t=e.face.iris)==null?void 0:t.modelPath),ms=(Qa==null?void 0:Qa.executor)&&((a=Qa.inputs)==null?void 0:a[0].shape)?Qa.inputs[0].shape[2]:0,ms===-1&&(ms=64),Qa}function x0(e,t,a,n){for(let r=0;r<J3.length;r++){let{key:s,indices:i}=J3[r],o=Rn[`${a}${s}`];if(!n||n.includes(s))for(let l=0;l<i.length;l++){let u=i[l];e[o[l]]=[t[u][0],t[u][1],(t[u][2]+e[o[l]][2])/2]}}}var Ahe=e=>{let t=e[Iu.leftBounds[0]][2],a=e[Iu.rightBounds[0]][2];return t-a},j9=(e,t,a,n,r,s=!1)=>{let i=g0(m0(O9([e[a],e[n]]),xhe)),o=vu(i),l=ge.cropAndResize(t,[[i.startPoint[1]/r,i.startPoint[0]/r,i.endPoint[1]/r,i.endPoint[0]/r]],[0],[ms,ms]);if(s&&ne.kernels.includes("flipleftright")){let 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y=ir.boxes[A],b=0,w,S={id:i++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([b,w,S.tensor]=B9((p=t.face.detector)==null?void 0:p.rotation,y,e,(c=t.face.mesh)!=null&&c.enabled?Sp:ku()),t.filter.equalization){let C=S.tensor?await qh(S.tensor):void 0;Y(S.tensor),C&&(S.tensor=C)}if(S.boxScore=Math.round(100*y.confidence)/100,(d=t.face.mesh)!=null&&d.enabled)if(!wt)t.debug&&K("face mesh detection requested, but model is not loaded");else{if(((h=t.face.attention)==null?void 0:h.enabled)&&!ne.kernels.includes("atan2"))return t.face.attention.enabled=!1,Y(S.tensor),r;let C=wt.execute(S.tensor),_=await C.find($=>$.shape[$.shape.length-1]===1).data();if(S.faceScore=Math.round(100*_[0])/100,S.faceScore<(((f=t.face.detector)==null?void 0:f.minConfidence)||1)){if(y.confidence=S.faceScore,t.face.mesh.keepInvalid){S.box=h0(y,e),S.boxRaw=f0(y,e),S.score=S.boxScore,S.mesh=y.landmarks.map($=>[(y.startPoint[0]+y.endPoint[0])/2+(y.endPoint[0]+y.startPoint[0])*$[0]/ku(),(y.startPoint[1]+y.endPoint[1])/2+(y.endPoint[1]+y.startPoint[1])*$[1]/ku()]),S.meshRaw=S.mesh.map($=>[$[0]/(e.shape[2]||1),$[1]/(e.shape[1]||1),($[2]||0)/o]);for(let $ of Object.keys(Co))S.annotations[$]=[S.mesh[Co[$]]]}}else{let $=C.find(O=>O.shape[O.shape.length-1]===1404),M=J($,[-1,3]),I=await M.array();Y(M),(m=t.face.attention)!=null&&m.enabled?I=await J9(I,C):(g=t.face.iris)!=null&&g.enabled&&(I=await Z9(I,S.tensor,Sp)),S.mesh=L9(I,y,b,w,Sp),S.meshRaw=S.mesh.map(O=>[O[0]/(e.shape[2]||0),O[1]/(e.shape[1]||0),(O[2]||0)/o]);for(let O of Object.keys(Rn))S.annotations[O]=Rn[O].map(L=>S.mesh[L]);S.score=S.faceScore;let N={...W9(S.mesh,y),confidence:y.confidence,landmarks:y.landmarks};S.box=h0(N,e),S.boxRaw=f0(N,e),s.push(N)}Y(C)}else{S.box=h0(y,e),S.boxRaw=f0(y,e),S.score=S.boxScore,S.mesh=y.landmarks.map(C=>[(y.startPoint[0]+y.endPoint[0])/2+(y.endPoint[0]+y.startPoint[0])*C[0]/ku(),(y.startPoint[1]+y.endPoint[1])/2+(y.endPoint[1]+y.startPoint[1])*C[1]/ku()]),S.meshRaw=S.mesh.map(C=>[C[0]/(e.shape[2]||0),C[1]/(e.shape[1]||0),(C[2]||0)/o]);for(let C of Object.keys(Co))S.annotations[C]=[S.mesh[Co[C]]]}S.score>(((x=t.face.detector)==null?void 0:x.minConfidence)||1)?r.push(S):Y(S.tensor)}return ir.boxes=s,r}async function ew(e){var t,a,n,r,s,i;return ne.initial&&(wt=null),((t=e.face.attention)==null?void 0:t.enabled)&&(wt==null?void 0:wt.signature)&&Object.keys(((a=wt==null?void 0:wt.signature)==null?void 0:a.outputs)||{}).length<6&&(wt=null),wt?e.debug&&K("cached model:",wt.modelUrl):(n=e.face.attention)!=null&&n.enabled?wt=await Ee(e.face.attention.modelPath):wt=await Ee((r=e.face.mesh)==null?void 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t},Qw=e=>{if(!e)return[];let t=[];for(let a=0;a<e.length;a++)if(e[a].mesh&&e[a].mesh.length>450){let n=(e[a].mesh[33][2]||0)-(e[a].mesh[263][2]||0),r=e[a].mesh[33][0]-e[a].mesh[263][0];Math.abs(n/r)<=.15?t.push({face:a,gesture:"facing center"}):t.push({face:a,gesture:`facing ${n<0?"left":"right"}`}),Math.abs(e[a].mesh[374][1]-e[a].mesh[386][1])/Math.abs(e[a].mesh[443][1]-e[a].mesh[450][1])<.2&&t.push({face:a,gesture:"blink left eye"}),Math.abs(e[a].mesh[145][1]-e[a].mesh[159][1])/Math.abs(e[a].mesh[223][1]-e[a].mesh[230][1])<.2&&t.push({face:a,gesture:"blink right eye"});let o=Math.min(100,500*Math.abs(e[a].mesh[13][1]-e[a].mesh[14][1])/Math.abs(e[a].mesh[10][1]-e[a].mesh[152][1]));o>10&&t.push({face:a,gesture:`mouth ${Math.trunc(o)}% open`});let l=e[a].mesh[152][2]||0;Math.abs(l)>10&&t.push({face:a,gesture:`head ${l<0?"up":"down"}`})}return t},ek=e=>{var a,n,r,s;if(!e)return[];let t=[];for(let i=0;i<e.length;i++){if(!((n=(a=e[i].annotations)==null?void 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I0(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function Tp(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function rk(e,t,a){let n=t.shape[1],r=t.shape[2],s=[[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r]];return ge.cropAndResize(t,s,[0],a)}function sk(e,t){let a=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],r=e.palmLandmarks.map(s=>[s[0]*t[0],s[1]*t[1]]);return{startPoint:a,endPoint:n,palmLandmarks:r,confidence:e.confidence}}function S0(e,t=1.5){let a=Tp(e),n=I0(e),r=[t*n[0]/2,t*n[1]/2],s=[a[0]-r[0],a[1]-r[1]],i=[a[0]+r[0],a[1]+r[1]];return{startPoint:s,endPoint:i,palmLandmarks:e.palmLandmarks}}function T0(e){let t=Tp(e),a=I0(e),r=Math.max(...a)/2,s=[t[0]-r,t[1]-r],i=[t[0]+r,t[1]+r];return{startPoint:s,endPoint:i,palmLandmarks:e.palmLandmarks}}function Ohe(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function ik(e,t){let a=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return Ohe(a)}var ak=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function ws(e,t){let a=0;for(let n=0;n<e.length;n++)a+=e[n]*t[n];return a}function Dhe(e,t){let a=[];for(let n=0;n<e.length;n++)a.push(e[n][t]);return a}function nk(e,t){let a=[],n=e.length;for(let r=0;r<n;r++){a.push([]);for(let s=0;s<n;s++)a[r].push(ws(e[r],Dhe(t,s)))}return a}function Hg(e,t){let a=Math.cos(e),n=Math.sin(e),r=[[a,-n,0],[n,a,0],[0,0,1]],s=ak(t[0],t[1]),i=nk(s,r),o=ak(-t[0],-t[1]);return nk(i,o)}function ok(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],a=[e[0][2],e[1][2]],n=[-ws(t[0],a),-ws(t[1],a)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]}function jg(e,t){return[ws(e,t[0]),ws(e,t[1])]}var 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Object.keys(a).forEach(r=>Y(a[r])),n}normalizeLandmarks(t,a){let n={};n.reshape=J(t,[-1,7,2]),n.div=me(n.reshape,this.inputSizeTensor),n.landmarks=be(n.div,this.anchors[a]?this.anchors[a]:0);let r=ae(n.landmarks,this.inputSizeTensor);return Object.keys(n).forEach(s=>Y(n[s])),r}async predict(t,a){var o;let n={};n.resize=ge.resizeBilinear(t,[this.inputSize,this.inputSize]),n.div=me(n.resize,ze.tf127),n.image=fe(n.div,ze.tf1),n.batched=this.model.execute(n.image),n.predictions=_e(n.batched),n.slice=Pe(n.predictions,[0,0],[-1,1]),n.sigmoid=Da(n.slice),n.scores=_e(n.sigmoid);let r=await n.scores.data();n.boxes=Pe(n.predictions,[0,1],[-1,4]),n.norm=this.normalizeBoxes(n.boxes),n.nms=await ge.nonMaxSuppressionAsync(n.norm,n.scores,3*(((o=a.hand)==null?void 0:o.maxDetected)||1),a.hand.iouThreshold,a.hand.minConfidence);let s=await n.nms.array(),i=[];for(let l of s){let u={};u.box=Pe(n.norm,[l,0],[1,-1]),u.slice=Pe(n.predictions,[l,5],[1,14]),u.norm=this.normalizeLandmarks(u.slice,l),u.palmLandmarks=J(u.norm,[-1,2]);let p=await u.box.data(),c=p.slice(0,2),d=p.slice(2,4),h=await u.palmLandmarks.array(),f={startPoint:c,endPoint:d,palmLandmarks:h,confidence:r[l]},m=sk(f,[(t.shape[2]||1)/this.inputSize,(t.shape[1]||0)/this.inputSize]);i.push(m),Object.keys(u).forEach(g=>Y(u[g]))}return Object.keys(n).forEach(l=>Y(n[l])),i}};var Bhe=5,dk=1.65,pk=[0,5,9,13,17,1,2],Whe=0,Vhe=2,ck=0,N0=class{constructor(t,a){ue(this,"handDetector");ue(this,"handPoseModel");ue(this,"inputSize");ue(this,"storedBoxes");ue(this,"skipped");ue(this,"detectedHands");var n,r,s;this.handDetector=t,this.handPoseModel=a,this.inputSize=((s=(r=(n=this.handPoseModel)==null?void 0:n.inputs)==null?void 0:r[0].shape)==null?void 0:s[2])||0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let a=t.map(i=>i[0]),n=t.map(i=>i[1]),r=[Math.min(...a),Math.min(...n)],s=[Math.max(...a),Math.max(...n)];return{startPoint:r,endPoint:s}}getBoxForPalmLandmarks(t,a){let n=t.map(s=>jg([...s,1],a)),r=this.calculateLandmarksBoundingBox(n);return S0(T0(r),Bhe)}getBoxForHandLandmarks(t){let a=this.calculateLandmarksBoundingBox(t),n=S0(T0(a),dk);n.palmLandmarks=[];for(let r=0;r<pk.length;r++)n.palmLandmarks.push(t[pk[r]].slice(0,2));return n}transformRawCoords(t,a,n,r){let s=I0(a),i=[s[0]/this.inputSize,s[1]/this.inputSize,(s[0]+s[1])/this.inputSize/2],o=t.map(h=>[i[0]*(h[0]-this.inputSize/2),i[1]*(h[1]-this.inputSize/2),i[2]*h[2]]),l=Hg(n,[0,0]),u=o.map(h=>[...jg(h,l),h[2]]),p=ok(r),c=[...Tp(a),1],d=[ws(c,p[0]),ws(c,p[1])];return u.map(h=>[Math.trunc(h[0]+d[0]),Math.trunc(h[1]+d[1]),Math.trunc(h[2])])}async estimateHands(t,a){let n=!1,r,s=(a.hand.skipTime||0)>te()-ck,i=this.skipped<(a.hand.skipFrames||0);a.skipAllowed&&s&&i&&(r=await this.handDetector.predict(t,a),this.skipped=0),a.skipAllowed&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==a.hand.maxDetected||!a.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(n=!0));let o=[];for(let l=0;l<this.storedBoxes.length;l++){let u=this.storedBoxes[l];if(!!u)if(a.hand.landmarks){let p=a.hand.rotation?ik(u.palmLandmarks[Whe],u.palmLandmarks[Vhe]):0,c=Tp(u),d=[c[0]/t.shape[2],c[1]/t.shape[1]],h=a.hand.rotation&&ne.kernels.includes("rotatewithoffset")?ge.rotateWithOffset(t,p,0,d):t.clone(),f=Hg(-p,c),m=n?this.getBoxForPalmLandmarks(u.palmLandmarks,f):u,g=rk(m,h,[this.inputSize,this.inputSize]),x=me(g,ze.tf255);Y(g),Y(h);let[A,y]=this.handPoseModel.execute(x);ck=te(),Y(x);let b=(await A.data())[0];if(Y(A),b>=a.hand.minConfidence/4){let w=J(y,[-1,3]),S=await w.array();Y(y),Y(w);let C=this.transformRawCoords(S,m,p,f),E=this.getBoxForHandLandmarks(C);this.storedBoxes[l]={...E,confidence:b};let _={landmarks:C,confidence:b,boxConfidence:u.confidence,fingerConfidence:b,box:{topLeft:E.startPoint,bottomRight:E.endPoint}};o.push(_)}else this.storedBoxes[l]=null;Y(y)}else{let p=S0(T0(u),dk),c={confidence:u.confidence,boxConfidence:u.confidence,fingerConfidence:0,box:{topLeft:p.startPoint,bottomRight:p.endPoint},landmarks:[]};o.push(c)}}return this.storedBoxes=this.storedBoxes.filter(l=>l!==null),this.detectedHands=o.length,o.length>a.hand.maxDetected&&(o.length=a.hand.maxDetected),o}};var hk={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},Do,zo,fk;async function qg(e,t){let a=await fk.estimateHands(e,t);if(!a)return[];let n=[];for(let r=0;r<a.length;r++){let s={};if(a[r].landmarks)for(let p of Object.keys(hk))s[p]=hk[p].map(c=>a[r].landmarks[c]);let i=a[r].landmarks,o=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],l=[0,0,0,0];if(i&&i.length>0){for(let p of i)p[0]<o[0]&&(o[0]=p[0]),p[1]<o[1]&&(o[1]=p[1]),p[0]>o[2]&&(o[2]=p[0]),p[1]>o[3]&&(o[3]=p[1]);o[2]-=o[0],o[3]-=o[1],l=[o[0]/(e.shape[2]||0),o[1]/(e.shape[1]||0),o[2]/(e.shape[2]||0),o[3]/(e.shape[1]||0)]}else o=a[r].box?[Math.trunc(Math.max(0,a[r].box.topLeft[0])),Math.trunc(Math.max(0,a[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,a[r].box.bottomRight[0])-Math.max(0,a[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,a[r].box.bottomRight[1])-Math.max(0,a[r].box.topLeft[1]))]:[0,0,0,0],l=[a[r].box.topLeft[0]/(e.shape[2]||0),a[r].box.topLeft[1]/(e.shape[1]||0),(a[r].box.bottomRight[0]-a[r].box.topLeft[0])/(e.shape[2]||0),(a[r].box.bottomRight[1]-a[r].box.topLeft[1])/(e.shape[1]||0)];let u=k0(i);n.push({id:r,score:Math.round(100*a[r].confidence)/100,boxScore:Math.round(100*a[r].boxConfidence)/100,fingerScore:Math.round(100*a[r].fingerConfidence)/100,label:"hand",box:o,boxRaw:l,keypoints:i,annotations:s,landmarks:u})}return n}async function mk(e){var a,n;ne.initial&&(Do=null,zo=null),!Do||!zo?[Do,zo]=await Promise.all([e.hand.enabled?Ee((a=e.hand.detector)==null?void 0:a.modelPath):null,e.hand.landmarks?Ee((n=e.hand.skeleton)==null?void 0:n.modelPath):null]):(e.debug&&K("cached model:",Do.modelUrl),e.debug&&K("cached model:",zo.modelUrl));let t=Do?new C0(Do):void 0;return t&&zo&&(fk=new N0(t,zo)),[Do,zo]}var Pt=[null,null],Ghe=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],ks=[[0,0],[0,0]],Hhe=["hand","fist","pinch","point","face","tip","pinchtip"],xk=4,Ak=1.6,jhe=512,qhe=1.4,E0=Number.MAX_SAFE_INTEGER,Xg=0,$r=[0,0],_t={boxes:[],hands:[]},yk={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function bk(e){var t;if(ne.initial&&(Pt[0]=null),Pt[0])e.debug&&K("cached model:",Pt[0].modelUrl);else{Qh(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),Pt[0]=await Ee((t=e.hand.detector)==null?void 0:t.modelPath);let a=Pt[0].executor?Object.values(Pt[0].modelSignature.inputs):void 0;ks[0][0]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[1].size):0,ks[0][1]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[2].size):0}return Pt[0]}async function vk(e){var t;if(ne.initial&&(Pt[1]=null),Pt[1])e.debug&&K("cached model:",Pt[1].modelUrl);else{Pt[1]=await Ee((t=e.hand.skeleton)==null?void 0:t.modelPath);let a=Pt[1].executor?Object.values(Pt[1].modelSignature.inputs):void 0;ks[1][0]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[1].size):0,ks[1][1]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[2].size):0}return Pt[1]}async function Xhe(e,t){let a=[];if(!e||!Pt[0])return a;let n={},r=(e.shape[2]||1)/(e.shape[1]||1),s=Math.min(Math.round((e.shape[1]||0)/8)*8,jhe),i=Math.round(s*r/8)*8;n.resize=ge.resizeBilinear(e,[s,i]),n.cast=He(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await Pt[0].executeAsync(n.cast,Ghe),n.boxes=_e(n.rawBoxes,[0,2]),n.scores=_e(n.rawScores,[0]);let o=Ta(n.scores,1);Y(o[xk]),o.splice(xk,1),n.filtered=sa(o,1),Y(o),n.max=pa(n.filtered,1),n.argmax=ar(n.filtered,1);let l=0;n.nms=await ge.nonMaxSuppressionAsync(n.boxes,n.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let u=await n.nms.data(),p=await n.max.data(),c=await n.argmax.data();for(let d of Array.from(u)){let h=Pe(n.boxes,d,1),f=await h.data();Y(h);let m=[f[1],f[0],f[3]-f[1],f[2]-f[0]],g=l0(m,qhe),x=[Math.trunc(m[0]*$r[0]),Math.trunc(m[1]*$r[1]),Math.trunc(m[2]*$r[0]),Math.trunc(m[3]*$r[1])],A=p[d],y=Hhe[c[d]],b={id:l++,score:A,box:x,boxRaw:g,label:y};a.push(b)}return Object.keys(n).forEach(d=>Y(n[d])),a.sort((d,h)=>h.score-d.score),a.length>(t.hand.maxDetected||1)&&(a.length=t.hand.maxDetected||1),a}async function Kg(e,t,a){let n={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&Pt[1]&&a.hand.landmarks&&t.score>(a.hand.minConfidence||0)){let r={},s=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=ge.cropAndResize(e,[s],[0],[ks[1][0],ks[1][1]],"bilinear"),r.div=me(r.crop,ze.tf255),[r.score,r.keypoints]=Pt[1].execute(r.div,["Identity_1","Identity"]);let i=(await r.score.data())[0],o=(100-Math.trunc(100/(1+Math.exp(i))))/100;if(o>=(a.hand.minConfidence||0)){n.fingerScore=o,r.reshaped=J(r.keypoints,[-1,3]);let p=(await r.reshaped.array()).map(c=>[c[0]/ks[1][1],c[1]/ks[1][0],c[2]||0]).map(c=>[c[0]*t.boxRaw[2],c[1]*t.boxRaw[3],c[2]||0]);n.keypoints=p.map(c=>[$r[0]*(c[0]+t.boxRaw[0]),$r[1]*(c[1]+t.boxRaw[1]),c[2]||0]),n.landmarks=k0(n.keypoints);for(let c of Object.keys(yk))n.annotations[c]=yk[c].map(d=>n.landmarks&&n.keypoints[d]?n.keypoints[d]:null)}Object.keys(r).forEach(l=>Y(r[l]))}return n}async function Zg(e,t){var r,s;if(!((r=Pt[0])!=null&&r.executor)||!((s=Pt[1])!=null&&s.executor)||!Pt[0].inputs[0].shape||!Pt[1].inputs[0].shape)return[];$r=[e.shape[2]||0,e.shape[1]||0],E0++;let a=(t.hand.skipTime||0)>te()-Xg,n=E0<(t.hand.skipFrames||0);return t.skipAllowed&&a&&n?_t.hands:new Promise(async i=>{let o=3*(t.hand.skipTime||0)>te()-Xg,l=E0<3*(t.hand.skipFrames||0);t.skipAllowed&&_t.hands.length===t.hand.maxDetected?_t.hands=await Promise.all(_t.boxes.map(p=>Kg(e,p,t))):t.skipAllowed&&o&&l&&_t.hands.length>0?_t.hands=await Promise.all(_t.boxes.map(p=>Kg(e,p,t))):(_t.boxes=await Xhe(e,t),Xg=te(),_t.hands=await Promise.all(_t.boxes.map(p=>Kg(e,p,t))),E0=0);let u=[..._t.boxes];if(_t.boxes.length=0,t.cacheSensitivity>0)for(let p=0;p<_t.hands.length;p++){let c=b9(_t.hands[p].keypoints,$r);if(c.box[2]/(e.shape[2]||1)>.05&&c.box[3]/(e.shape[1]||1)>.05&&_t.hands[p].fingerScore&&_t.hands[p].fingerScore>(t.hand.minConfidence||0)){let d=l0(c.box,Ak),h=l0(c.boxRaw,Ak);_t.boxes.push({...u[p],box:d,boxRaw:h})}}for(let p=0;p<_t.hands.length;p++){let c=Er(_t.hands[p].keypoints,$r);_t.hands[p].box=c.box,_t.hands[p].boxRaw=c.boxRaw}i(_t.hands)})}var or=(e=null)=>({face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,width:0,height:0,error:e});var Cp={};hr(Cp,{connected:()=>M0,horizontal:()=>Yg,kpt:()=>R0,relative:()=>Qg,vertical:()=>Jg});var R0=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],Yg=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],Jg=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],Qg=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],M0={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var xe=or(),e5=0;function kk(e,t){var i,o,l,u,p,c,d,h,f,m,g,x,A,y,b,w,S,C,E,_,$,M,I;let a=te();if(!e)return or();let n=Date.now()-e.timestamp,r=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(xe.canvas=e.canvas),e.error&&(xe.error=e.error),!xe.body||e.body.length!==xe.body.length)xe.body=JSON.parse(JSON.stringify(e.body));else for(let N=0;N<e.body.length;N++){let O=e.body[N].box.map((U,H)=>((r-1)*xe.body[N].box[H]+U)/r),L=e.body[N].boxRaw.map((U,H)=>((r-1)*xe.body[N].boxRaw[H]+U)/r),B=e.body[N].keypoints.map((U,H)=>{var V,Q,Z,re,ee,he,oe,Ae,we;return{score:U.score,part:U.part,position:[xe.body[N].keypoints[H]?((r-1)*(xe.body[N].keypoints[H].position[0]||0)+(U.position[0]||0))/r:U.position[0],xe.body[N].keypoints[H]?((r-1)*(xe.body[N].keypoints[H].position[1]||0)+(U.position[1]||0))/r:U.position[1],xe.body[N].keypoints[H]?((r-1)*(xe.body[N].keypoints[H].position[2]||0)+(U.position[2]||0))/r:U.position[2]],positionRaw:[xe.body[N].keypoints[H]?((r-1)*(xe.body[N].keypoints[H].positionRaw[0]||0)+(U.positionRaw[0]||0))/r:U.positionRaw[0],xe.body[N].keypoints[H]?((r-1)*(xe.body[N].keypoints[H].positionRaw[1]||0)+(U.positionRaw[1]||0))/r:U.positionRaw[1],xe.body[N].keypoints[H]?((r-1)*(xe.body[N].keypoints[H].positionRaw[2]||0)+(U.positionRaw[2]||0))/r:U.positionRaw[2]],distance:[xe.body[N].keypoints[H]?((r-1)*(((V=xe.body[N].keypoints[H].distance)==null?void 0:V[0])||0)+(((Q=U.distance)==null?void 0:Q[0])||0))/r:(Z=U.distance)==null?void 0:Z[0],xe.body[N].keypoints[H]?((r-1)*(((re=xe.body[N].keypoints[H].distance)==null?void 0:re[1])||0)+(((ee=U.distance)==null?void 0:ee[1])||0))/r:(he=U.distance)==null?void 0:he[1],xe.body[N].keypoints[H]?((r-1)*(((oe=xe.body[N].keypoints[H].distance)==null?void 0:oe[2])||0)+(((Ae=U.distance)==null?void 0:Ae[2])||0))/r:(we=U.distance)==null?void 0:we[2]]}}),G={},j={connected:{}};(i=t.body.modelPath)!=null&&i.includes("efficientpose")?j=p0:(o=t.body.modelPath)!=null&&o.includes("blazepose")?j=i0:(l=t.body.modelPath)!=null&&l.includes("movenet")&&(j=Cp);for(let[U,H]of Object.entries(j.connected)){let V=[];for(let Q=0;Q<H.length-1;Q++){let Z=B.find(ee=>ee.part===H[Q]),re=B.find(ee=>ee.part===H[Q+1]);Z&&re&&V.push([Z.position,re.position])}G[U]=V}xe.body[N]={...e.body[N],box:O,boxRaw:L,keypoints:B,annotations:G}}if(!xe.hand||e.hand.length!==xe.hand.length)xe.hand=JSON.parse(JSON.stringify(e.hand));else for(let N=0;N<e.hand.length;N++){let O=e.hand[N].box.map((j,U)=>((r-1)*xe.hand[N].box[U]+j)/r),L=e.hand[N].boxRaw.map((j,U)=>((r-1)*xe.hand[N].boxRaw[U]+j)/r);xe.hand[N].keypoints.length!==e.hand[N].keypoints.length&&(xe.hand[N].keypoints=e.hand[N].keypoints);let B=e.hand[N].keypoints&&e.hand[N].keypoints.length>0?e.hand[N].keypoints.map((j,U)=>j.map((H,V)=>((r-1)*(xe.hand[N].keypoints[U][V]||1)+(H||0))/r)):[],G={};if(Object.keys(xe.hand[N].annotations).length!==Object.keys(e.hand[N].annotations).length)xe.hand[N].annotations=e.hand[N].annotations,G=xe.hand[N].annotations;else if(e.hand[N].annotations)for(let j of Object.keys(e.hand[N].annotations))G[j]=(c=(p=(u=e.hand[N])==null?void 0:u.annotations)==null?void 0:p[j])!=null&&c[0]?e.hand[N].annotations[j].map((U,H)=>U.map((V,Q)=>((r-1)*xe.hand[N].annotations[j][H][Q]+V)/r)):null;xe.hand[N]={...e.hand[N],box:O,boxRaw:L,keypoints:B,annotations:G}}if(!xe.face||e.face.length!==xe.face.length)xe.face=JSON.parse(JSON.stringify(e.face));else for(let N=0;N<e.face.length;N++){let O=e.face[N].box.map((B,G)=>((r-1)*xe.face[N].box[G]+B)/r),L=e.face[N].boxRaw.map((B,G)=>((r-1)*xe.face[N].boxRaw[G]+B)/r);if(e.face[N].rotation){let B={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};B.matrix=(d=e.face[N].rotation)==null?void 0:d.matrix,B.angle={roll:((r-1)*(((f=(h=xe.face[N].rotation)==null?void 0:h.angle)==null?void 0:f.roll)||0)+(((g=(m=e.face[N].rotation)==null?void 0:m.angle)==null?void 0:g.roll)||0))/r,yaw:((r-1)*(((A=(x=xe.face[N].rotation)==null?void 0:x.angle)==null?void 0:A.yaw)||0)+(((b=(y=e.face[N].rotation)==null?void 0:y.angle)==null?void 0:b.yaw)||0))/r,pitch:((r-1)*(((S=(w=xe.face[N].rotation)==null?void 0:w.angle)==null?void 0:S.pitch)||0)+(((E=(C=e.face[N].rotation)==null?void 0:C.angle)==null?void 0:E.pitch)||0))/r},B.gaze={bearing:((r-1)*(((_=xe.face[N].rotation)==null?void 0:_.gaze.bearing)||0)+((($=e.face[N].rotation)==null?void 0:$.gaze.bearing)||0))/r,strength:((r-1)*(((M=xe.face[N].rotation)==null?void 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Ue&&ia()==="tensorflow"){let r=(void 0).decodeJpeg(a),s=Gt(r,0);e.tf.dispose(r),n=await e.detect(s,e.config),e.tf.dispose(s)}else e.config.debug&&K("Warmup tfjs-node not loaded");return n}async function y0e(e){let t;return typeof createImageBitmap=="function"?t=await g0e(e):typeof Image!="undefined"||ne.Canvas!==void 0?t=await x0e(e):t=await A0e(e),t}async function b0e(e){var o,l,u,p;if(!W().flagRegistry.ENGINE_COMPILE_ONLY)return;let t=ia(),a=tr();if(t!=="webgl"&&t!=="humangl"||!(a!=null&&a.checkCompileCompletion))return;W().set("ENGINE_COMPILE_ONLY",!0);let n=kt().state.numTensors,r=[];for(let[c,d]of Object.entries(e.models.models)){if(!d)continue;let h=(d==null?void 0:d.modelSignature)&&((l=(o=d==null?void 0:d.inputs)==null?void 0:o[0])==null?void 0:l.shape)?[...d.inputs[0].shape]:[1,64,64,3],f=(d==null?void 0:d.modelSignature)&&((p=(u=d==null?void 0:d.inputs)==null?void 0:u[0])==null?void 0:p.dtype)?d.inputs[0].dtype:"float32";for(let g=0;g<h.length;g++)h[g]===-1&&(h[g]=g===0?1:64);let m=fn(h,f);try{let g=d.execute(m);r.push(c),Array.isArray(g)?g.forEach(x=>Y(x)):Y(g)}catch(g){e.config.debug&&K("compile fail model:",c)}Y(m)}let s=await a.checkCompileCompletionAsync();a.getUniformLocations(),e.config.debug&&K("compile pass:",{models:r,kernels:s.length}),W().set("ENGINE_COMPILE_ONLY",!1);let i=kt().state.numTensors;i-n>0&&K("tensor leak:",i-n)}async function Yk(e,t){await wp(e,!1);let a=te();return e.state="warmup",t&&(e.config=Ct(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?or():new Promise(async n=>{await e.models.load(),await b0e(e);let r=await y0e(e),s=te();e.config.debug&&K("warmup",e.config.warmup,Math.round(s-a),"ms"),e.emit("warmup"),n(r)})}var Mu,Mp,$p,V0,Is,A5=class{constructor(t){ue(this,"version");ue(this,"config");ue(this,"result");ue(this,"state");ue(this,"process");ue(this,"tf");ue(this,"env",ne);ue(this,"draw",s0);ue(this,"match",$0);ue(this,"models");ue(this,"events");ue(this,"faceTriangulation");ue(this,"faceUVMap");ue(this,"performance");Gn(this,Mu,void 0);Gn(this,Mp,void 0);Gn(this,$p,void 0);ue(this,"analyze",(...t)=>{if(!Ga(this,Mp))return;let a=this.tf.engine().state.numTensors,n=Ga(this,Mu);fr(this,Mu,a);let r=a-n;r!==0&&K(...t,r)});Gn(this,V0,t=>{if(!Ga(this,$p))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof pt))return"input must be a tensor";try{this.tf.getBackend()}catch(a){return"backend not loaded"}return null});ue(this,"webcam",new Jh);ue(this,"emit",t=>{var a;(a=this.events)!=null&&a.dispatchEvent&&this.events.dispatchEvent(new Event(t))});Gn(this,Is,{});let a=(xp.tfjs||A2).replace(/-(.*)/,"");Io.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${a}/dist/`,Io.modelBasePath=ne.browser?"../models/":"file://models/",this.version=X3,Object.defineProperty(this,"version",{value:X3}),this.config=JSON.parse(JSON.stringify(Io)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=Ct(this.config,t)),u9(this.config),this.tf=Ue,this.state="idle",fr(this,Mu,0),fr(this,Mp,!1),fr(this,$p,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new Rp(this),tg(),this.result=or(),this.process={tensor:null,canvas:null},this.faceTriangulation=tw,this.faceUVMap=aw,L0(this,null,""),this.emit("create"),(this.config.debug||this.env.browser)&&K(`version: ${this.version}`),this.config.debug&&K(`tfjs version: ${this.tf.version["tfjs-core"]}`);let n=JSON.parse(JSON.stringify(this.env));delete n.kernels,delete n.initial,delete n.perfadd,this.config.debug&&K("environment:",n)}reset(){let t=this.config.backend;this.config=JSON.parse(JSON.stringify(Io)),this.config.backend=t,j3(),ne.initial=!0}validate(t){let a=U3(Io,t||this.config);return a.length===0&&(this.config=Ct(this.config,t)),a}now(){return te()}image(t,a=!1){return Zh(t,this.config,a)}async segmentation(t,a){var s,i,o;if(a&&(this.config=Ct(this.config,a)),!this.config.segmentation.enabled)return null;let n=await Zh(t,this.config);if(!n.tensor)return null;let r=null;return(s=this.config.segmentation.modelPath)!=null&&s.includes("rvm")&&(r=await jk(n.tensor,this.config)),(i=this.config.segmentation.modelPath)!=null&&i.includes("meet")&&(r=await Ik(n.tensor,this.config)),(o=this.config.segmentation.modelPath)!=null&&o.includes("selfie")&&(r=await Xk(n.tensor,this.config)),Y(n.tensor),r}compare(t,a){return l9(this.config,t,a)}async init(){await wp(this,!0),await this.tf.ready(),j3()}async load(t){this.state="load";let a=te(),n=Object.values(this.models.models).filter(i=>i).length;t&&(this.config=Ct(this.config,t)),this.env.initial&&(await wp(this,!1)||K("error: backend check failed"),await Kd(),this.env.browser&&(this.config.debug&&K("configuration:",this.config),this.config.debug&&K("tf flags:",this.tf.ENV.flags))),await this.models.load(this),this.env.initial&&this.config.debug&&K("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models.models).filter(i=>i).length!==n&&(this.models.validate(),this.emit("load"));let s=Math.trunc(te()-a);s>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+s:s)}next(t=this.result){return kk(t,this.config)}async warmup(t){let a=te(),n=await Yk(this,t),r=te();return this.performance.warmup=Math.trunc(r-a),n}async profile(t,a){let n=await this.tf.profile(()=>this.detect(t,a)),r={},s=0;for(let o of n.kernels){let l=Number(o.kernelTimeMs)||0;r[o.name]?r[o.name]+=l:r[o.name]=l,s+=l}let i=[];Object.entries(r).forEach(o=>i.push({kernel:o[0],time:o[1],perc:0}));for(let o of i)o.perc=Math.round(1e3*o.time/s)/1e3,o.time=Math.round(1e3*o.time)/1e3;return i.sort((o,l)=>l.time-o.time),i.length=20,i}async detect(t,a){return this.state="detect",new Promise(async n=>{var g,x,A,y,b,w,S,C,E,_,$,M,I,N,O,L,B,G,j,U,H;this.state="config";let r;this.config=Ct(this.config,a),this.state="check";let s=Ga(this,V0).call(this,t);s&&(K(s,t),this.emit("error"),n(or(s)));let i=te();await this.load(),r=te(),this.state="image";let o=await Zh(t,this.config);if(this.process=o,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(te()-r):Math.trunc(te()-r),this.analyze("Get Image:"),!o.tensor){this.config.debug&&K("could not convert input to tensor"),this.emit("error"),n(or("could not convert input to tensor"));return}this.emit("image"),r=te(),this.config.skipAllowed=await o9(this.config,o.tensor),this.config.filter.autoBrightness=(this.config.filter.autoBrightness||!1)&&this.config.skipAllowed,this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(te()-r):Math.trunc(te()-r),this.analyze("Check Changed:");let l=[],u=[],p=[],c=[];this.state="detect:face",this.config.async?(l=this.config.face.enabled?Vg(this,o.tensor):[],this.performance.face&&delete this.performance.face):(r=te(),l=this.config.face.enabled?await Vg(this,o.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(te()-r):Math.trunc(te()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(l=await l),this.analyze("Start Body:"),this.state="detect:body";let d=this.config.body.maxDetected===-1?Ct(this.config,{body:{maxDetected:this.config.face.enabled?1*l.length:1}}):this.config;this.config.async?((g=this.config.body.modelPath)!=null&&g.includes("posenet")?u=this.config.body.enabled?c5(o.tensor,d):[]:(x=this.config.body.modelPath)!=null&&x.includes("blazepose")?u=this.config.body.enabled?ig(o.tensor,d):[]:(A=this.config.body.modelPath)!=null&&A.includes("efficientpose")?u=this.config.body.enabled?hg(o.tensor,d):[]:(y=this.config.body.modelPath)!=null&&y.includes("movenet")&&(u=this.config.body.enabled?s5(o.tensor,d):[]),this.performance.body&&delete this.performance.body):(r=te(),(b=this.config.body.modelPath)!=null&&b.includes("posenet")?u=this.config.body.enabled?await c5(o.tensor,d):[]:(w=this.config.body.modelPath)!=null&&w.includes("blazepose")?u=this.config.body.enabled?await ig(o.tensor,d):[]:(S=this.config.body.modelPath)!=null&&S.includes("efficientpose")?u=this.config.body.enabled?await hg(o.tensor,d):[]:(C=this.config.body.modelPath)!=null&&C.includes("movenet")&&(u=this.config.body.enabled?await s5(o.tensor,d):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(te()-r):Math.trunc(te()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let h=this.config.hand.maxDetected===-1?Ct(this.config,{hand:{maxDetected:this.config.face.enabled?2*l.length:1}}):this.config;this.config.async?((_=(E=this.config.hand.detector)==null?void 0:E.modelPath)!=null&&_.includes("handdetect")?p=this.config.hand.enabled?qg(o.tensor,h):[]:(M=($=this.config.hand.detector)==null?void 0:$.modelPath)!=null&&M.includes("handtrack")&&(p=this.config.hand.enabled?Zg(o.tensor,h):[]),this.performance.hand&&delete this.performance.hand):(r=te(),(N=(I=this.config.hand.detector)==null?void 0:I.modelPath)!=null&&N.includes("handdetect")?p=this.config.hand.enabled?await qg(o.tensor,h):[]:(L=(O=this.config.hand.detector)==null?void 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Object:"),this.state="detect:await",this.config.async&&([l,u,p,c]=await Promise.all([l,u,p,c])),this.state="detect:gesture";let f=[];this.config.gesture.enabled&&(r=te(),f=[...Qw(l),...Jw(u),...tk(p),...ek(l)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(te()-r):Math.trunc(te()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(te()-i):Math.trunc(te()-i);let m=((H=this.process.tensor)==null?void 0:H.shape)||[0,0,0,0];this.result={face:l,body:u,hand:p,gesture:f,object:c,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,width:m[2],height:m[1],get persons(){return Zk(l,u,p,f,m)}},Y(o.tensor),this.emit("detect"),this.state="idle",n(this.result)})}async sleep(t){return new Promise(a=>{setTimeout(a,t)})}async video(t,a=!0,n=0){a?(Ga(this,Is)[t.id]||(this.config.debug&&K("video start",t.id),Ga(this,Is)[t.id]=!0),!t.paused&&Ga(this,Is)[t.id]&&t.readyState>=2&&await this.detect(t),n>0&&await this.sleep(n),Ga(this,Is)[t.id]&&requestAnimationFrame(()=>this.video(t,a,n))):(this.config.debug&&K("video stop",t.id),Ga(this,Is)[t.id]=!1)}};Mu=new WeakMap,Mp=new WeakMap,$p=new WeakMap,V0=new WeakMap,Is=new WeakMap;return OI(w0e);})();
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