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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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r=this.backend.numDataIds(),s=0;n.forEach(l=>{s+=l.dtype==="complex64"?3:1});let i=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],o=r-a-s-i;if(o>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${o} data ids) after running '${t}'`)}runKernelFunc(t){let a,n=[],r=this.isTapeOn(),s=this.state.numBytes,i=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let o;this.backendName==null&&this.backend;let l,u=q2(t)?t.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(q2(t)){let{kernelName:m,inputs:f,attrs:g}=t;this.backendName==null&&this.backend;let y=Vd(m,this.backendName);F(y!=null,()=>`Cannot find registered kernel '${m}' for backend '${this.backendName}'`),o=()=>{let x=this.backend.numDataIds();l=y.kernelFunc({inputs:f,attrs:g,backend:this.backend});let A=Array.isArray(l)?l:[l];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(m,x,A);let b=A.map(w=>w.rank!=null?w:this.makeTensorFromTensorInfo(w));if(r){let w=this.getTensorsForGradient(m,f,b);n=this.saveTensorsForBackwardMode(w)}return b}}else{let{forwardFunc:m}=t,f=g=>{r&&(n=g.map(y=>this.keep(this.clone(y))))};o=()=>{let g=this.backend.numDataIds();l=this.tidy(()=>m(this.backend,f));let y=Array.isArray(l)?l:[l];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(u,g,y),y}}let{inputs:p,attrs:c}=t,d=q2(t)?null:t.backwardsFunc,h;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?a=o():(h=this.profiler.profileKernel(u,p,()=>o()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(h),a=h.outputs)}),r&&this.addTapeNode(u,p,a,d,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:u,bytesAdded:this.state.numBytes-s,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-i,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(p).map(m=>p[m]!=null?p[m].shape:null),outputShapes:a.map(m=>m.shape),kernelTimeMs:h.timeMs,extraInfo:h.extraInfo}),Array.isArray(l)?a:a[0]}saveTensorsForBackwardMode(t){return t.map(a=>this.keep(this.clone(a)))}getTensorsForGradient(t,a,n){let r=t1(t);if(r!=null){let s=r.inputsToSave||[],i=r.outputsToSave||[],o;r.saveAllInputs?(F(Array.isArray(a),()=>"saveAllInputs is true, expected inputs to be an array."),o=Object.keys(a).map(u=>a[u])):o=s.map(u=>a[u]);let 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this.state.registeredVariables[s.name]=s,this.incRef(s,this.backend),s}trackTensor(t,a){this.state.numTensors++,t.dtype==="string"&&this.state.numStringTensors++;let n=0;t.dtype!=="complex64"&&t.dtype!=="string"&&(n=t.size*dh(t.dtype)),this.state.numBytes+=n,this.state.tensorInfo.has(t.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(t.dataId,{backend:a||this.backend,dtype:t.dtype,shape:t.shape,bytes:n})),t instanceof Gd||this.track(t)}incRef(t,a){this.trackTensor(t,a),this.backend.incRef(t.dataId)}removeDataId(t,a){this.state.tensorInfo.has(t)&&this.state.tensorInfo.get(t).backend===a&&(this.state.tensorInfo.delete(t),this.state.numDataBuffers--)}disposeTensor(t){if(!this.state.tensorInfo.has(t.dataId))return;let a=this.state.tensorInfo.get(t.dataId);if(this.state.numTensors--,t.dtype==="string"&&(this.state.numStringTensors--,this.state.numBytes-=a.bytes),t.dtype!=="complex64"&&t.dtype!=="string"){let 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t=!1;this.accumulatedGrads=e.map(a=>({originalName:a.name,variable:a.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}},Qg=class extends hs{static get className(){return"Adam"}constructor(e,t,a,n=null){super(),this.learningRate=e,this.beta1=t,this.beta2=a,this.epsilon=n,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],De(()=>{this.accBeta1=Ge(t).variable(),this.accBeta2=Ge(a).variable()}),n==null&&(this.epsilon=L.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(a=>a.name):Object.keys(e);De(()=>{let a=xe(1,this.accBeta1),n=xe(1,this.accBeta2);t.forEach((r,s)=>{let i=L.registeredVariables[r],o=!1;this.accumulatedFirstMoment[s]==null&&(this.accumulatedFirstMoment[s]={originalName:`${r}/m`,variable:De(()=>Qa(i).variable(o))}),this.accumulatedSecondMoment[s]==null&&(this.accumulatedSecondMoment[s]={originalName:`${r}/v`,variable:De(()=>Qa(i).variable(o))});let l=Array.isArray(e)?e[s].tensor:e[r];if(l==null)return;let u=this.accumulatedFirstMoment[s].variable,p=this.accumulatedSecondMoment[s].variable,c=we(te(u,this.beta1),te(l,1-this.beta1)),d=we(te(p,this.beta2),te(Tn(l),1-this.beta2)),h=ve(c,a),m=ve(d,n);u.assign(c),p.assign(d);let 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t=e.length/2,a=!1;this.accumulatedFirstMoment=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(a)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(a)}))}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon)}},e3=class extends hs{static get className(){return"Adamax"}constructor(e,t,a,n=null,r=0){super(),this.learningRate=e,this.beta1=t,this.beta2=a,this.epsilon=n,this.decay=r,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],De(()=>{this.iteration=Ge(0).variable(),this.accBeta1=Ge(t).variable()}),n==null&&(this.epsilon=L.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(a=>a.name):Object.keys(e);De(()=>{let a=xe(1,this.accBeta1),n=ve(-this.learningRate,we(te(this.iteration,this.decay),1));t.forEach((r,s)=>{let 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Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}},Qh=class extends hs{static get className(){return"SGD"}constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,a)=>{let n=Array.isArray(e)?e[a].tensor:e[t];if(n==null)return;let r=L.registeredVariables[t];De(()=>{let s=we(te(this.c,n),r);r.assign(s)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Ln(Ge(-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 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r=k("strides",e,t,a),s=ah(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}=m5(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}=m5(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=ah(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=ah(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 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implemented`)}},CO=(e,t,a,n=ea)=>{switch(e.op){case"RaggedGather":{let{outputNestedSplits:r,outputDenseValues:s}=n.raggedGather(k("paramsNestedSplits",e,t,a),k("paramsDenseValues",e,t,a),k("indices",e,t,a),k("outputRaggedRank",e,t,a));return r.concat(s)}case"RaggedRange":{let{rtNestedSplits:r,rtDenseValues:s}=n.raggedRange(k("starts",e,t,a),k("limits",e,t,a),k("splits",e,t,a));return[r,s]}case"RaggedTensorToTensor":return[n.raggedTensorToTensor(k("shape",e,t,a),k("values",e,t,a),k("defaultValue",e,t,a),k("rowPartitionTensors",e,t,a),k("rowPartitionTypes",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},TO=(e,t,a,n=ea)=>{switch(e.op){case"Max":{let o=k("axis",e,t,a),l=k("keepDims",e,t,a);return[n.max(k("x",e,t,a),o,l)]}case"Mean":{let o=k("axis",e,t,a),l=k("keepDims",e,t,a);return[n.mean(k("x",e,t,a),o,l)]}case"Min":{let o=k("axis",e,t,a),l=k("keepDims",e,t,a);return[n.min(k("x",e,t,a),o,l)]}case"Sum":{let 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r=k("indices",e,t,a),s=k("values",e,t,a),i=k("tensor",e,t,a);return[n.tensorScatterUpdate(i,r,s)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},RO=(e,t,a,n=ea)=>{switch(e.op){case"SparseFillEmptyRows":{let{outputIndices:r,outputValues:s,emptyRowIndicator:i,reverseIndexMap:o}=n.sparse.sparseFillEmptyRows(k("indices",e,t,a),k("values",e,t,a),k("denseShape",e,t,a),k("defaultValue",e,t,a));return[r,s,i,o]}case"SparseReshape":{let{outputIndices:r,outputShape:s}=n.sparse.sparseReshape(k("inputIndices",e,t,a),k("inputShape",e,t,a),k("newShape",e,t,a));return[r,s]}case"SparseSegmentMean":return[n.sparse.sparseSegmentMean(k("data",e,t,a),k("indices",e,t,a),k("segmentIds",e,t,a))];case"SparseSegmentSum":return[n.sparse.sparseSegmentSum(k("data",e,t,a),k("indices",e,t,a),k("segmentIds",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},EO=(e,t,a,n=ea)=>{switch(e.op){case"FFT":return[n.fft(k("x",e,t,a))];case"IFFT":return[n.ifft(k("x",e,t,a))];case"RFFT":return[n.rfft(k("x",e,t,a))];case"IRFFT":return[n.irfft(k("x",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},MO=(e,t,a,n=ea)=>{switch(e.op){case"StaticRegexReplace":return[n.string.staticRegexReplace(k("input",e,t,a),k("pattern",e,t,a),k("rewrite",e,t,a),k("replaceGlobal",e,t,a))];case"StringNGrams":{let{nGrams:r,nGramsSplits:s}=n.string.stringNGrams(k("data",e,t,a),k("dataSplits",e,t,a),k("separator",e,t,a),k("nGramWidths",e,t,a),k("leftPad",e,t,a),k("rightPad",e,t,a),k("padWidth",e,t,a),k("preserveShortSequences",e,t,a));return[r,s]}case"StringSplit":{let{indices:r,values:s,shape:i}=n.string.stringSplit(k("input",e,t,a),k("delimiter",e,t,a),k("skipEmpty",e,t,a));return[r,s,i]}case"StringToHashBucketFast":return[n.string.stringToHashBucketFast(k("input",e,t,a),k("numBuckets",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},$O=(e,t,a,n=ea)=>{switch(e.op){case"Cast":return[n.cast(k("x",e,t,a),k("dtype",e,t,a))];case"ExpandDims":{let r=k("axis",e,t,a);return[n.expandDims(k("x",e,t,a),r)]}case"Squeeze":{let r=k("axis",e,t,a);return[n.squeeze(k("x",e,t,a),r)]}case"Reshape":return[n.reshape(k("x",e,t,a),k("shape",e,t,a))];case"EnsureShape":return[n.ensureShape(k("x",e,t,a),k("shape",e,t,a))];case"MirrorPad":return[n.mirrorPad(k("x",e,t,a),k("padding",e,t,a),k("mode",e,t,a))];case"PadV2":case"Pad":return[n.pad(k("x",e,t,a),k("padding",e,t,a),k("constantValue",e,t,a))];case"SpaceToBatchND":{let r=k("blockShape",e,t,a),s=k("paddings",e,t,a);return[n.spaceToBatchND(k("x",e,t,a),r,s)]}case"BatchToSpaceND":{let r=k("blockShape",e,t,a),s=k("crops",e,t,a);return[n.batchToSpaceND(k("x",e,t,a),r,s)]}case"DepthToSpace":{let r=k("blockSize",e,t,a),s=k("dataFormat",e,t,a).toUpperCase();return[n.depthToSpace(k("x",e,t,a),r,s)]}case"BroadcastTo":return[n.broadcastTo(k("x",e,t,a),k("shape",e,t,a))];case"BroadcastArgs":return[n.broadcastArgs(k("s0",e,t,a),k("s1",e,t,a))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function f5(e,t,a,n,r=De){let s=((i,o,l)=>{switch(i.category){case"arithmetic":return r(()=>oO(i,o,l));case"basic_math":return r(()=>lO(i,o,l));case"control":return mO(i,o,l);case"convolution":return r(()=>fO(i,o,l));case"creation":return r(()=>gO(i,o,l));case"dynamic":return yO(i,o,l);case"evaluation":return r(()=>xO(i,o,l));case"image":return r(()=>wO(i,o,l));case"graph":return r(()=>AO(i,o,l));case"logical":return r(()=>kO(i,o,l));case"matrices":return r(()=>IO(i,o,l));case"normalization":return r(()=>SO(i,o,l));case"ragged":return r(()=>CO(i,o,l));case"reduction":return r(()=>TO(i,o,l));case"slice_join":return r(()=>NO(i,o,l));case"sparse":return r(()=>RO(i,o,l));case"spectral":return r(()=>EO(i,o,l));case"string":return r(()=>MO(i,o,l));case"transformation":return r(()=>$O(i,o,l));case"hash_table":return vO(i,o,l,n);case"custom":let u=j7(i.op);if(u&&u.customExecutor)return u.customExecutor(new iO(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 g5=class{constructor(e={},t={},a={},n={},r){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=a,this.functionMap=n,this.parseNodeNameCache=r,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 y5(e,t,a,n){let r=new Set,s=[],i=null,o=null,l=new Set,u=new Set(Object.keys(e).map(d=>Ya(d)[0]));n=n||[];let p=new Set(n.map(d=>Ya(d.name)[0])),c=[...t];for(;c.length>0;){let d=c.pop();if((Us(d)||WO(d)||BO(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.has(d.name)&&!p.has(d.name)){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 PO(e,t){let{usedNodes:a,inputs:n}=t,r=Object.keys(n).map(g=>Ya(g)[0]).map(g=>e.nodes[g]),s=e.initNodes||[],i=g=>a.has(typeof g=="string"?g:g.name);function o(g){return[...new Map(g.map(y=>[y.name,y])).values()]}let l=o([...r,...e.weights,...s]).filter(i),u=o([...l,...Object.values(e.nodes)]).filter(i),p=new Map(u.map(g=>[g.name,g])),c={};for(let g of u){c[g.name]=c[g.name]||0;for(let y of g.children)i(y)||(c[y.name]=Number.POSITIVE_INFINITY),c[y.name]=(c[y.name]||0)+1}let d=Object.entries(c).filter(([,g])=>g===0).map(([g])=>g),h=[...d];for(;d.length>0;){let g=d.pop(),y=p.get(g);for(let x of y.children.filter(i))--c[x.name]===0&&(h.push(x.name),d.push(x.name))}let m=h.map(g=>p.get(g)),f=_O(m,l);return FO(f,l),f}function _O(e,t){let a=new Map(e.map(s=>[s.name,s])),n=t.map(s=>s.name),r=new Set(n);for(;n.length>0;){let s=n.pop(),i=a.get(s);for(let o of i.children)!a.has(o.name)||r.has(o.name)||(r.add(o.name),n.push(o.name))}return e.filter(s=>r.has(s.name))}var Kc=class extends Error{constructor(e){super(`NodesExecutionOrderError: ${e}`)}};function FO(e,t){let a=new Map(e.map((o,l)=>[o.name,l])),n=new Set(t.map(o=>o.name)),r=o=>n.has(typeof o=="string"?o:o.name),s=new Set(e.map(o=>o.name)),i=o=>s.has(typeof o=="string"?o:o.name);for(let o of e){for(let l of o.children.filter(i)){if(!a.has(l.name))throw new Kc(`Child ${l.name} of node ${o.name} is unreachable.`);if(a.get(o.name)>a.get(l.name))throw new Kc(`Node ${o.name} is scheduled to run after its child ${l.name}.`)}if(!r(o))for(let l of o.inputs){if(!a.has(l.name))throw new Kc(`Input ${l.name} of node ${o.name} is unreachable.`);if(a.get(l.name)>a.get(o.name))throw new Kc(`Node ${o.name} is scheduled to run before its input ${l.name}.`)}}}function DO(e){let t=new Map(e.map((o,l)=>[o.name,l])),a=Number.MAX_SAFE_INTEGER,n=e.map((o,l)=>Us(o)?a:l),r=o=>{let l=n[t.get(o.name)];return l==null?-1:l},s=e.map((o,l)=>o.children.map(r).reduce((u,p)=>Math.max(u,p),n[l])),i=new Map;for(let o=0;o<e.length;++o){let l=s[o];if(l===a)continue;let u=e[o],p=e[l];i.has(p.name)||i.set(p.name,[]),i.get(p.name).push(u)}return i}var OO=new Set(["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"]),zO=new Set(["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"]),LO=new Set(["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"]);function Us(e){return OO.has(e.op)}function WO(e){return zO.has(e.op)}function BO(e){return LO.has(e.op)}var x5=class m6{get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(t){let a=Object.keys(t).map(n=>t[n].map(r=>r.id));this._weightIds=[].concat(...a),this._weightMap=t}set resourceManager(t){this._resourceManager=t}get inputs(){return this._inputs.map(t=>({name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(t=>({name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(t=>t.signatureKey||t.name)}get outputNodes(){return this._outputs.map(t=>{let a=t.signatureKey||t.name;return t.defaultOutput?`${a}:${t.defaultOutput}`:a})}get functions(){return Object.keys(this._functions).reduce((t,a)=>(t[a]=this._functions[a].signature,t),{})}constructor(t,a){this.graph=t,this.parent=a,this.compiledMap=new Map,this.parseNodeNameCache=new Map,this._weightMap={},this.SEPARATOR=",",this._functions={},this._functionExecutorMap={},this.keepIntermediateTensors=!1,this._outputs=t.outputs,this._inputs=t.inputs,this._initNodes=t.initNodes,this._signature=t.signature,this._functions=t.functions,t.functions!=null&&Object.keys(t.functions).forEach(n=>{this._functionExecutorMap[n]=new m6(t.functions[n],this)})}getCompilationKey(t,a){let n=t.map(s=>s.name).sort(),r=a.map(s=>s.name).sort();return n.join(this.SEPARATOR)+"--"+r.join(this.SEPARATOR)}compile(t,a){let n=y5(t,a,this.weightMap,this._initNodes),{missingInputs:r,dynamicNode:s,syncInputs:i}=n;if(s!=null)throw new Error(`This execution contains the node '${s.name}', which has the dynamic op '${s.op}'. 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Missing the following inputs: [${r}]`)}let o=PO(this.graph,n),l=DO(o);return{orderedNodes:o,nodeLiveUntilMap:l}}cloneAndKeepTensor(t){if(t==null)return null;let a=t.clone();return Ln(a),a}cloneTensorList(t){return t?t.map(a=>this.cloneAndKeepTensor(a)):null}cloneTensorMap(t){return Object.fromEntries(Object.entries(t).map(([a,n])=>[a,this.cloneTensorList(n)]))}execute(t,a){this.disposeIntermediateTensors(),t=this.mapInputs(t);let n=Object.keys(t).sort();this.checkInputs(t),this.checkInputShapeAndType(t),a=this.mapOutputs(a),this.checkOutputs(a);let r=n.map(d=>this.graph.nodes[Ya(d)[0]]),s=a.map(d=>Ya(d)[0]),i=new Set(s),o=s.map(d=>this.graph.nodes[d]);o.length===0&&(o=this._outputs);let l=this.getCompilationKey(r,o),u=this.compiledMap.get(l);u==null&&(u=this.compile(t,o),this.compiledMap.set(l,u));try{this.keepIntermediateTensors=B().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(d){this.keepIntermediateTensors=!1,console.warn(d.message)}let p={},c={};return De(()=>{let d=new g5(this.weightMap,p,c,this.functionExecutorMap,this.parseNodeNameCache),h=Object.assign({},this.weightMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap)),Object.keys(t).forEach(y=>{let[x,A]=Ya(y,d),b=[];b[A]=t[y],h[x]=b,this.keepIntermediateTensors&&(this.clonedTensorsMap[x]=this.cloneTensorList(b))});let m=this.getFrozenTensorIds(h),{orderedNodes:f,nodeLiveUntilMap:g}=u;for(let y of f){if(h[y.name])continue;let x=f5(y,h,d,this._resourceManager);if(v.isPromise(x))throw new Error(`The execution of the op '${y.op}' returned a promise. Please use model.executeAsync() instead.`);h[y.name]=x,this.keepIntermediateTensors&&(this.clonedTensorsMap[y.name]=this.cloneTensorList(x)),this.checkTensorForDisposalWithNodeLiveUntilInfo(y,h,d,m,i,g.get(y.name))}return this.parent==null&&d.dispose(m),a.map(y=>ua(y,h,d))})}getFrozenTensorIds(t){let a=[].concat.apply([],Object.keys(t).map(n=>t[n]).map(n=>n.map(r=>r.id)));return new Set(a)}checkTensorForDisposal(t,a,n,r,s,i,o){if(!(Us(a)||i.has(t))){for(let l of n[t])l!=null&&(o[l.id]=(o[l.id]||0)+a.children.length);for(let l of a.inputs){if(Us(l))continue;let u=d5(l.name,n,r);if(u!=null)for(let p of u){if(!p||p.kept||s.has(p.id))continue;let c=o[p.id];c===1?(p.dispose(),delete o[p.id]):c!=null&&o[p.id]--}}}}checkTensorForDisposalWithNodeLiveUntilInfo(t,a,n,r,s,i){function o(l){return Us(l)||s.has(l.name)}if(!(Us(t)||i==null))for(let l of i){if(o(l))continue;let u=d5(l.name,a,n);for(let p of u)!p||p.kept||r.has(p.id)||p.dispose()}}async executeAsync(t,a){return this._executeAsync(t,a)}disposeIntermediateTensors(){this.clonedTensorsMap&&(Object.values(this.clonedTensorsMap).forEach(t=>{for(let a of t)a&&!a.isDisposed&&a.dispose()}),this.clonedTensorsMap=null)}getIntermediateTensors(){return this.clonedTensorsMap}async _executeAsync(t,a,n=!1,r={},s={}){this.disposeIntermediateTensors(),n||(t=this.mapInputs(t),this.checkInputs(t),this.checkInputShapeAndType(t),a=this.mapOutputs(a),this.checkOutputs(a));try{this.keepIntermediateTensors=B().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(d){this.keepIntermediateTensors=!1,console.warn(d.message)}let i=new g5(this.weightMap,r,s,this.functionExecutorMap,this.parseNodeNameCache);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap));let o=await this.executeWithControlFlow(t,i,a,n),l=a.map(d=>ua(d,o,i)),u=l.map(d=>d.id),p=Object.keys(t).map(d=>t[d].id),c=new Set([...u,...p,...this.weightIds]);return Object.values(o).forEach(d=>{d.forEach(h=>{h&&!h.isDisposed&&!c.has(h.id)&&h.dispose()})}),this.parent==null&&i.dispose(c),l}async executeFunctionAsync(t,a,n){let r=t.reduce((s,i,o)=>(s[this.inputs[o].name]=i,s),{});return this._executeAsync(r,this.outputNodes,!0,a,n)}async executeWithControlFlow(t,a,n,r){let s=Object.keys(t),i=s.map(b=>this.graph.nodes[Ya(b)[0]]),o=n.map(b=>Ya(b)[0]),l=new Set(o),u=o.map(b=>this.graph.nodes[b]);u.length===0&&(u=this._outputs);let{usedNodes:p,missingInputs:c,dynamicNode:d,syncInputs:h}=y5(t,u,this.weightMap,this._initNodes),m=[...i,...this.graph.weights,...this._initNodes||[]].map(b=>({node:b,contexts:a.currentContext})),f=Object.assign({},this.weightMap);Object.keys(t).forEach(b=>{let[w,I]=Ya(b),T=[];T[I]=t[b],f[w]=T});let g={},y=this.getFrozenTensorIds(f),x={};for(;m.length>0;){let b=this.processStack(i,m,a,f,x,y,l,g,p);await Promise.all(b)}d==null&&!r&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let A=u.filter(b=>!Us(b)&&!ua(b.name,f,a)).map(b=>b.name);if(A.length>0){let b="";throw d!=null&&(b=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${h}]`),new Error(`Cannot compute the outputs [${A}] from the provided inputs [${s}]. Consider providing the following inputs: [${c}]. ${b}`)}return f}processStack(t,a,n,r,s,i,o,l,u){let p=[];for(;a.length>0;){let c=a.pop();n.currentContext=c.contexts;let d="";if(c.node.op==="Enter"&&k("isConstant",c.node,r,n)&&([d]=br(c.node.name,n)),r[c.node.name]==null){let h=f5(c.node,r,n,this._resourceManager);d||([d]=br(c.node.name,n));let m=n.currentContext;v.isPromise(h)?p.push(h.then(f=>(r[d]=f,this.keepIntermediateTensors&&(this.clonedTensorsMap[d]=this.cloneTensorList(f)),n.currentContext=m,this.checkTensorForDisposal(d,c.node,r,n,i,o,l),this.processChildNodes(c.node,a,n,r,s,u),f))):(r[d]=h,this.keepIntermediateTensors&&(this.clonedTensorsMap[d]=this.cloneTensorList(h)),this.checkTensorForDisposal(d,c.node,r,n,i,o,l),this.processChildNodes(c.node,a,n,r,s,u))}else this.processChildNodes(c.node,a,n,r,s,u)}return p}processChildNodes(t,a,n,r,s,i){t.children.forEach(o=>{let[l]=br(o.name,n);s[l]||!i.has(o.name)||(o.op==="Merge"?o.inputNames.some(u=>!!ua(u,r,n))&&(s[l]=!0,a.push({contexts:n.currentContext,node:o})):o.inputNames.every(u=>!!ua(u,r,n))&&(s[l]=!0,a.push({contexts:n.currentContext,node:o})))})}dispose(){Object.keys(this.weightMap).forEach(t=>this.weightMap[t].forEach(a=>a.dispose()))}checkInputShapeAndType(t){Object.keys(t).forEach(a=>{let n=t[a],[r]=Ya(a),s=this.graph.nodes[r];if(s.attrParams.shape&&s.attrParams.shape.value){let i=s.attrParams.shape.value,o=i.length===n.shape.length&&n.shape.every((l,u)=>i[u]===-1||i[u]===l);v.assert(o,()=>`The shape of dict['${s.name}'] provided in model.execute(dict) must be [${i}], but was [${n.shape}]`)}s.attrParams.dtype&&s.attrParams.dtype.value&&v.assert(n.dtype===s.attrParams.dtype.value,()=>`The dtype of dict['${s.name}'] provided in model.execute(dict) must be ${s.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(t){var a,n;let r={};for(let s in t){let i=(n=(a=this._signature)===null||a===void 0?void 0:a.inputs)===null||n===void 0?void 0:n[s];i!=null?r[i.name]=t[s]:r[s]=t[s]}return r}checkInputs(t){let a=Object.keys(t).filter(n=>{let[r]=Ya(n);return this.graph.nodes[r]==null});if(a.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${a}] that are not part of graph`)}mapOutputs(t){return t.map(a=>{var n,r;let s=(r=(n=this._signature)===null||n===void 0?void 0:n.outputs)===null||r===void 0?void 0:r[a];return s!=null?s.name:a},{})}checkOutputs(t){t.forEach(a=>{let[n]=Ya(a);if(!this.graph.nodes[n])throw new Error(`The output '${a}' is not found in the graph`)})}},VO=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in 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this.loadWithWeightMap(e,t)}loadWithWeightMap(e,t){this.artifacts=e;let a=this.artifacts.modelTopology,n=this.artifacts.signature;if(this.artifacts.userDefinedMetadata!=null){let r=this.artifacts.userDefinedMetadata;r.signature!=null&&(n=r.signature),r.structuredOutputKeys!=null&&(this.structuredOutputKeys=r.structuredOutputKeys)}if(this.signature=n,this.version=`${a.versions.producer}.${a.versions.minConsumer}`,this.executor=new x5(p5.Instance.transformGraph(a,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(t),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let r=p5.Instance.transformGraph(e.modelInitializer);this.initializer=new x5(r),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializerSignature=e.initializerSignature}return!0}async save(e,t){if(typeof e=="string"){let a=this.io.getSaveHandlers(e);if(a.length===0)throw new Error(`Cannot find any save handlers for URL '${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 yt?[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 yt)&&!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 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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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ez={kernelName:bi,backendName:"cpu",kernelFunc:is};function Kt(e,t,a,n){return a==null?({inputs:r,backend:s})=>{let{a:i,b:o}=r,l=s;Ie([i,o],e);let u=l.data.get(i.dataId).values,p=l.data.get(o.dataId).values,c=i.dtype==="string"?C.fromUint8ToStringArray(u):u,d=i.dtype==="string"?C.fromUint8ToStringArray(p):p,h=n||i.dtype,[m,f]=t(i.shape,o.shape,c,d,h);return l.makeTensorInfo(f,h,m)}:({inputs:r,backend:s})=>{let{a:i,b:o}=r,l=s;if(i.dtype==="complex64"||o.dtype==="complex64"){let 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o=C.assertAndGetBroadcastShape(t,a),l=v.sizeFromShape(o),u=o.length,p=v.computeStrides(o),c=v.getTypedArrayFromDType("float32",l),d=v.getTypedArrayFromDType("float32",l),h=C.getBroadcastDims(t,o),m=C.getBroadcastDims(a,o),f=C.mergeRealAndImagArrays(n,r),g=C.mergeRealAndImagArrays(s,i),y=t.length,x=v.computeStrides(t),A=a.length,b=v.computeStrides(a);if(h.length+m.length===0)for(let w=0;w<c.length;w++){let I=w%f.length,T=w%g.length,N=e(f[I*2],f[I*2+1],g[T*2],g[T*2+1]);c[w]=N.real,d[w]=N.imag}else for(let w=0;w<c.length;w++){let I=v.indexToLoc(w,u,p),T=I.slice(-y);h.forEach(S=>T[S]=0);let N=v.locToIndex(T,y,x),M=I.slice(-A);m.forEach(S=>M[S]=0);let $=v.locToIndex(M,A,b),E=e(f[N*2],f[N*2+1],g[$*2],g[$*2+1]);c[w]=E.real,d[w]=E.imag}return[c,d,o]}}var x6=_t((e,t)=>e+t),tz=c3((e,t,a,n)=>({real:e+a,imag:t+n})),eu=Kt(ls,x6,tz),az={kernelName:ls,backendName:"cpu",kernelFunc:eu};function h3(e,t,a,n,r){let s=v.sizeFromShape(n),i=v.makeZerosTypedArray(r,a);for(let o=0;o<e.length;o++){let l=e[o];if(l<0)throw new Error("Input x must be non-negative!");l>=r||(s>0?i[l]+=t[o]:i[l]+=1)}return i}function A6(e,t,a,n=!1){let r=e.shape[0],s=e.shape[1],i=_e([r,a],t.dtype);for(let o=0;o<r;o++)for(let l=0;l<s;l++){let u=e.get(o,l);if(u<0)throw new Error("Input x must be non-negative!");u>=a||(n?i.set(1,o,u):t.size>0?i.set(i.get(o,u)+t.get(o,l),o,u):i.set(i.get(o,u)+1,o,u))}return i}var b6=_t((e,t)=>e&t),nz=Kt(cu,b6),rz={kernelName:cu,backendName:"cpu",kernelFunc:nz};function or(e){return(t,a,n)=>{let r=v.getArrayFromDType(a,t.length);for(let s=0;s<t.length;++s)r[s]=e(t[s],n);return r}}function ct(e,t,a){let n=or(t);return ms(e,n,a)}function ms(e,t,a){return({inputs:n,attrs:r,backend:s})=>{let{x:i}=n;Ie(i,e);let o=s,l=o.data.get(i.dataId).values,u;if(i.dtype==="string"){if(!Array.isArray(l))throw new Error("String tensor's value was not an instance of Array");u=C.fromUint8ToStringArray(l)}else u=l;let p=a||i.dtype,c=t(u,p,r);return o.makeTensorInfo(i.shape,p,c)}}var v6=or(e=>Math.ceil(e)),sz=ms(vi,v6),iz={kernelName:vi,backendName:"cpu",kernelFunc:sz};function m3(e,t,a,n){let r=v.getArrayFromDType(a,v.sizeFromShape(t));if(n&&a!=="string"){let s=0;e.forEach(i=>{let o=v.sizeFromShape(i.shape);r.set(i.vals,s),s+=o})}else{let s=0;e.forEach(i=>{let o=a==="string"?C.fromUint8ToStringArray(i.vals):i.vals,l=0;for(let u=0;u<i.shape[0];++u){let p=u*t[1]+s;for(let c=0;c<i.shape[1];++c)r[p+c]=o[l++]}s+=i.shape[1]})}return r}var w6=_t((e,t)=>e===t?1:0),k6=Kt(Oi,w6,null,"bool"),oz={kernelName:Oi,backendName:"cpu",kernelFunc:k6},I6=or(e=>Math.exp(e)),S6=ms(zi,I6,"float32"),lz={kernelName:zi,backendName:"cpu",kernelFunc:S6},C6=or(e=>Math.expm1(e)),uz=ms(Li,C6),dz={kernelName:Li,backendName:"cpu",kernelFunc:uz},T6=or(e=>Math.floor(e)),pz=ms(Bi,T6),cz={kernelName:Bi,backendName:"cpu",kernelFunc:pz},N6=_t((e,t)=>Math.floor(e/t)),hz=Kt(Vi,N6,null,"int32"),mz={kernelName:Vi,backendName:"cpu",kernelFunc:hz};function R6(e,t,a,n,r,s,i,o,l){let u=_e([n,s],a);for(let p=0;p<n;p++){let c=[],d=0;for(let h=0;h<r;h++){let m=e[p*r+h];d+=m*i[h],c.push(m)}if(d<0||d>=l/s)throw new Error(`Invalid indices: ${c} does not index into ${o}`);for(let h=0;h<s;h++)u.values[p*s+h]=t.get(...t.indexToLoc(d*s+h))}return u}function E6(e,t,a){let n=_e(a,e.dtype);for(let r=0;r<n.size;++r){let s=n.indexToLoc(r).slice(),i=s[0],o=s[2],l=t.locToIndex([i,o]);s[2]=t.values[l];let u=e.locToIndex(s);0<=u&&u<e.values.length&&(n.values[r]=e.values[u])}return n}var M6=_t((e,t)=>e>t?1:0),fz=Kt(Hi,M6,null,"bool"),gz={kernelName:Hi,backendName:"cpu",kernelFunc:fz},$6=_t((e,t)=>e>=t?1:0),yz=Kt(ji,$6,null,"bool"),xz={kernelName:ji,backendName:"cpu",kernelFunc:yz},P6=_t((e,t)=>e<t?1:0),Az=Kt(Ji,P6,null,"bool"),bz={kernelName:Ji,backendName:"cpu",kernelFunc:Az},_6=_t((e,t)=>e<=t?1:0),vz=Kt(Qi,_6,null,"bool"),wz={kernelName:Qi,backendName:"cpu",kernelFunc:vz};function F6(e,t,a){let n=(t-e)/(a-1),r=v.makeZerosTypedArray(a,"float32");r[0]=e;for(let s=1;s<r.length;s++)r[s]=r[s-1]+n;return r}var D6=or(e=>Math.log(e)),kz=ms(to,D6),Iz={kernelName:to,backendName:"cpu",kernelFunc:kz};function O6(e,t,a,n){let r=v.getTypedArrayFromDType(n,v.sizeFromShape(a));for(let s=0;s<r.length;++s){let i=s*t,o=e[i];for(let l=0;l<t;++l){let u=e[i+l];(Number.isNaN(u)||u>o)&&(o=u)}r[s]=o}return r}var z6=_t((e,t)=>Math.max(e,t)),Sz=Kt(lo,z6),Cz={kernelName:lo,backendName:"cpu",kernelFunc:Sz},L6=_t((e,t)=>Math.min(e,t)),Tz=Kt(ho,L6),Nz={kernelName:ho,backendName:"cpu",kernelFunc:Tz},f3=_t((e,t)=>e*t),Rz=c3((e,t,a,n)=>({real:e*a-t*n,imag:e*n+t*a})),a0=Kt(yo,f3,Rz),Ez={kernelName:yo,backendName:"cpu",kernelFunc:a0};function W6(e,t,a){let n=v.createScalarValue(-1,a);return f3([],t,n,e,a)}function Mz(e){let{inputs:t,backend:a}=e,{x:n}=t;Ie(n,"neg");let r=a.data.get(n.dataId).values,[s,i]=W6(r,n.shape,n.dtype);return a.makeTensorInfo(i,n.dtype,s)}var $z={kernelName:Su,backendName:"cpu",kernelFunc:Mz},B6=_t((e,t)=>e!==t?1:0),Pz=Kt(xo,B6,null,"bool"),_z={kernelName:xo,backendName:"cpu",kernelFunc:Pz};function g3(e,t,a,n,r){let s=t.length,i=v.sizeFromShape(t),o=v.computeStrides(t),l=v.computeStrides(r),u=v.getTypedArrayFromDType(a,v.sizeFromShape(r));for(let p=0;p<i;++p){let c=v.indexToLoc(p,s,o),d=new Array(c.length);for(let m=0;m<d.length;m++)d[m]=c[n[m]];let h=v.locToIndex(d,s,l);u[h]=e[p]}return u}function Va(e){let{inputs:t,attrs:a,backend:n}=e,{x:r}=t,{perm:s}=a;Ie(r,"transpose");let i=r.shape.length,o=new Array(i);for(let p=0;p<o.length;p++)o[p]=r.shape[s[p]];let l=n.data.get(r.dataId).values,u=g3(l,r.shape,r.dtype,s,o);return{dataId:n.write(u,o,r.dtype),shape:o,dtype:r.dtype}}var Fz={kernelName:kr,backendName:"cpu",kernelFunc:Va};function V6(e,t,a,n){let[r,s]=C.computeOutAndReduceShapes(e,n),i=pa(t,"int32"),o=v.makeZerosTypedArray(v.sizeFromShape(r),i),l=v.sizeFromShape(s);for(let u=0;u<o.length;++u){let p=u*l,c=1;for(let d=0;d<l;++d)c*=a[p+d];o[u]=c}return{outVals:o,outShape:r,outDtype:i}}function Dz(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ie(r,"prod");let o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=C.getAxesPermutation(l,o),p=l,c=r,d=[];u!=null&&(c=Va({inputs:{x:r},backend:a,attrs:{perm:u}}),d.push(c),p=C.getInnerMostAxes(p.length,o));let h=a.data.get(c.dataId).values,{outVals:m,outShape:f,outDtype:g}=V6(c.shape,c.dtype,h,p),y=f;return i&&(y=C.expandShapeToKeepDim(f,l)),d.forEach(x=>a.disposeIntermediateTensorInfo(x)),a.makeTensorInfo(y,g,m)}var Oz={kernelName:So,backendName:"cpu",kernelFunc:Dz};function zz(e,t,a){e.forEach((n,r)=>{if(n<0||n>=a){let s=v.indexToLoc(r,t.length,v.computeStrides(t)).join(",");throw new Error(`indices[${s}] = ${n} is not in [0, ${a})`)}})}function Lz(e,t){for(let a=0;a<e.length;++a){let n=e[a],r=a===e.length-1?t:e[a+1].length;if(n.length===0)throw new Error("Ragged splits may not be empty");if(n[0]<0)throw new Error("Ragged splits must be non-negative");if(n[n.length-1]>r)throw new Error("Ragged splits must not point past values");for(let s=1;s<n.length;++s)if(n[s-1]>n[s])throw new Error("Ragged splits must be sorted in ascending order")}}function Wz(e,t,a,n){let r=[],s=0,i=t.length-1+a.length,o=new Array(i).fill(null).map(()=>[0]);Lz(a,n);let l=1;for(let u=0;u<t.length-1;++u){l*=t[u];let p=t[u+1];for(let c=1;c<l+1;++c)o[u].push(c*p)}for(let u=0;u<e.length;++u){let p=e[u],c=e[u]+1;for(let d=0;d<a.length;++d){let h=a[d],m=d+t.length-1;if(m>=0){let f=o[m],g=f[f.length-1]-h[p];for(let y=p;y<c;++y)o[m].push(h[y+1]+g)}p=h[p],c=h[c]}c!==p&&(r.push([p,c]),s+=c-p)}return{outSplits:o,valueSlices:r,numValues:s}}function Bz(e){let t=[];for(let a=0;a<e.length;++a){let n=e[a].length,r=v.getArrayFromDType("int32",n);t.push(r),e[a].forEach((s,i)=>r[i]=s)}return t}function A5(e,t){let a=e.slice(0,t);for(;a.length<t;)a.push(1);for(let n=t;n<e.length;n++)a[t-1]*=e[n];return a}function Vz(e,t,a,n,r,s){let i=A5(t,2)[1],o=A5(s,2)[1],l=0;for(let u of a)for(let p=u[0];p<u[1];++p){for(let c=0;c<n;++c)r[l*o+c]=e[p*i+c];++l}}function Uz(e,t,a,n,r){let s=t.slice();s[0]=r;let i=v.getArrayFromDType(a,v.sizeFromShape(s)),o=e.length,l=o===0?0:o/t[0];return Vz(e,t,n,l,i,s),[i,s]}function U6(e,t,a,n,r,s,i,o){if(e.length===0)throw new Error("paramsNestedSplits must be non empty");if(t[0].length===0)throw new Error("Split tensors must not be scalars");let l=t[0][0]-1;if(zz(s,i,l),n.length===0)throw new Error("params.rank must be nonzero");let u=n[0],{outSplits:p,valueSlices:c,numValues:d}=Wz(s,i,e,u),h=Bz(p),m=Uz(a,n,r,c,d);return[h,m[0],m[1]]}var b5=2147483647;function G6(e,t,a,n,r,s,i){if(t.length>1)throw new Error("starts must be a scalar or vector");if(r.length>1)throw new Error("limits must be a scalar or vector");if(i.length>1)throw new Error("deltas must be a scalar or vector");let o=t.length===0,l=r.length===0,u=i.length===0,p=[];o||p.push(t[0]),l||p.push(r[0]),u||p.push(i[0]);for(let g=1;g<p.length;++g)if(p[g]!==p[g-1])throw new Error("starts, limits, and deltas must have the same shape");let c=p.length===0?1:p[0],d=v.getArrayFromDType("int32",c+1);d[0]=0;for(let g=0;g<c;++g){let y=o?e[0]:e[g],x=l?n[0]:n[g],A=u?s[0]:s[g];if(A===0)throw new Error("Requires delta != 0");let b;if(A>0&&x<y||A<0&&x>y)b=0;else if(b=Math.ceil(Math.abs((x-y)/A)),b>b5)throw new Error(`Requires ((limit - start) / delta) <= ${b5}`);d[g+1]=d[g]+b}let h=d[c],m=v.getArrayFromDType(a,h),f=0;for(let g=0;g<c;++g){let y=d[g+1]-d[g],x=o?e[0]:e[g],A=u?s[0]:s[g];for(let b=0;b<y;++b)m[f++]=x,x+=A}return[d,m]}var Sn=C.RowPartitionType,Gz=class $1{constructor(t,a,n,r,s,i,o,l,u,p){this.shape=t,this.shapeShape=a,this.values=n,this.valuesShape=r,this.valuesDType=s,this.defaultValue=i,this.defaultValueShape=o,this.rowPartitionValues=l,this.rowPartitionValuesShapes=u,this.rowPartitionTypes=C.getRowPartitionTypesHelper(p),this.raggedRank=C.getRaggedRank(this.rowPartitionTypes)}getRowPartitionTypeByDimension(t){return this.rowPartitionTypes[0]===Sn.FIRST_DIM_SIZE?this.rowPartitionTypes[t+1]:this.rowPartitionTypes[t]}getRowPartitionTensor(t){return this.rowPartitionTypes[0]===Sn.FIRST_DIM_SIZE?this.rowPartitionValues[t+1]:this.rowPartitionValues[t]}getMaxWidth(t){let a=this.getRowPartitionTensor(t-1);switch(this.getRowPartitionTypeByDimension(t-1)){case Sn.VALUE_ROWIDS:return $1.getMaxWidthValueRowID(a);case Sn.ROW_SPLITS:return $1.getMaxWidthRowSplit(a);default:throw new Error(`Cannot handle partition type ${Sn[this.getRowPartitionTypeByDimension(t-1)]}`)}}static getMaxWidthRowSplit(t){let a=t.length;if(a===0||a===1)return 0;let n=0;for(let r=0;r<a-1;++r){let s=t[r+1]-t[r];s>n&&(n=s)}return n}static getMaxWidthValueRowID(t){let a=t.length;if(a===0)return 0;let n=0,r=t[0],s=0;for(let i=1;i<a;++i){let o=t[i];o!==r&&(r=o,s=Math.max(i-n,s),n=i)}return Math.max(a-n,s)}tensorShapeFromTensor(t,a,n=!0){if(a.length===0){if(t[0]===-1)return[];throw new Error("The only valid scalar shape tensor is the fully unknown shape specified as -1.")}return w5(t,n)}calculateOutputSize(t){let a=this.valuesShape,n=this.defaultValueShape;C.validateDefaultValueShape(n,a);let r=this.tensorShapeFromTensor(this.shape,this.shapeShape),s=C.combineRaggedTensorToTensorShapes(this.raggedRank,r,a);s[0]<0&&(s[0]=t);for(let i=1;i<=this.raggedRank;++i)s[i]<0&&(s[i]=this.getMaxWidth(i));return s}calculateFirstParentOutputIndex(t,a,n){let r=Math.min(t,n),s=[],i=0;for(let o=0;o<r;++o,i+=a)s.push(i);for(let o=r;o<t;++o)s.push(-1);return v.assert(s.length===t,()=>"Final length of result must be equal to firstDimension."),s}calculateOutputIndexRowSplit(t,a,n,r){let s=t.length,i=[];for(let o=0;o<s-1;++o){let l=t[o+1]-t[o],u=Math.min(r,l),p=a[o];p===-1&&(u=0);for(let c=0;c<u;++c)i.push(p),p+=n;for(let c=0;c<l-u;++c)i.push(-1)}if(s>0&&i.length!==t[s-1])throw new Error("Invalid row split size.");return i}calculateOutputIndexValueRowID(t,a,n,r){let s=t.length,i=[];if(s===0)return[];let o=0,l=t[0];if(l>=a.length)throw new Error(`Got currentValueRowId=${l}, which is not less than ${a.length}`);let u=a[l];i.push(u);for(let p=1;p<s;++p){let c=t[p];if(c===l)u>=0&&(++o,o<r?u+=n:u=-1);else{if(o=0,l=c,c>=a.length)throw new Error(`Got nextValueRowId=${c} which is not less than ${a.length}`);u=a[c]}i.push(u)}if(i.length!==t.length)throw new Error("Invalid row ids.");return i}calculateOutputIndex(t,a,n,r){let s=this.getRowPartitionTensor(t),i=this.getRowPartitionTypeByDimension(t);switch(i){case Sn.VALUE_ROWIDS:return this.calculateOutputIndexValueRowID(s,a,n,r);case Sn.ROW_SPLITS:if(s.length-1>a.length)throw new Error(`Row partition size is greater than output size: ${s.length-1} > ${a.length}`);return this.calculateOutputIndexRowSplit(s,a,n,r);default:throw new Error(`Unsupported partition type: ${Sn[i]}`)}}getFirstDimensionSize(){let t=this.rowPartitionValues[0];if(this.rowPartitionTypes.length===0)throw new Error("No row_partition_types given.");let a=this.rowPartitionTypes[0];switch(a){case Sn.FIRST_DIM_SIZE:return t[0];case Sn.VALUE_ROWIDS:throw new Error("Cannot handle VALUE_ROWIDS in first dimension.");case Sn.ROW_SPLITS:return this.rowPartitionValuesShapes[0][0]-1;default:throw new Error(`Cannot handle type ${Sn[a]}`)}}compute(){if(this.rowPartitionValues[0].length<=0)throw new Error("Invalid first partition input. Tensor requires at least one element.");let t=this.getFirstDimensionSize(),a=this.calculateOutputSize(t),n=new Array(this.raggedRank+1);n[n.length-1]=1;for(let i=n.length-2;i>=0;--i)n[i]=n[i+1]*a[i+1];let r=w5(a,!1),s=v.getArrayFromDType(this.valuesDType,v.sizeFromShape(r));if(n[0]*a[0]>0){let i=this.calculateFirstParentOutputIndex(t,n[0],a[0]);for(let o=1;o<=this.raggedRank;++o)i=this.calculateOutputIndex(o-1,i,n[o],a[o]);this.setOutput(this.raggedRank,i,s,r)}return[r,s]}setOutput(t,a,n,r){if(n.length===0)return;let s=this.values,i=n,o=r.slice();o=o.slice(t+1);let l=v.sizeFromShape(o),u=a.length,p=this.defaultValue;if(p.length!==l&&p.length!==1){let m=this.defaultValueShape;De(()=>{let f=Q(p,m);p=Gl(f,o).dataSync()})}let c=0,d=0,h=0;for(let m=0;m<=u;++m){let f=m<u?a[m]:-1;if(f===h){++h;continue}if(d<h){let g=s.subarray(c*l),y=i.subarray(d*l),x=(h-d)*l;v5(y,g,x)}if(m>=u){let 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IL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ie(r,"all");let o=v.parseAxisParam(s,r.shape),l=o,u=C.getAxesPermutation(l,r.shape.length),p=r;u!=null&&(p=Va({inputs:{x:r},backend:a,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,r.shape.length)),C.assertAxesAreInnerMostDims("all",l,p.shape.length);let[c,d]=C.computeOutAndReduceShapes(p.shape,l),h=v.sizeFromShape(d),m=v.makeZerosTypedArray(v.sizeFromShape(c),p.dtype),f=a.data.get(p.dataId).values;for(let y=0;y<m.length;++y){let x=y*h,A=f[x];for(let b=0;b<h;++b){let w=f[x+b];A=A&&w}m[y]=A}u!=null&&a.disposeIntermediateTensorInfo(p);let g=a.makeTensorInfo(c,p.dtype,m);if(i){let y=C.expandShapeToKeepDim(c,o),x=bt({inputs:{x:g},backend:a,attrs:{shape:y}});return a.disposeIntermediateTensorInfo(g),x}return g}var SL={kernelName:di,backendName:"cpu",kernelFunc:IL};function CL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ie(r,"any");let o=v.parseAxisParam(s,r.shape),l=o,u=C.getAxesPermutation(l,r.shape.length),p=r;u!=null&&(p=Va({inputs:{x:r},backend:a,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,r.shape.length)),C.assertAxesAreInnerMostDims("any",l,p.shape.length);let[c,d]=C.computeOutAndReduceShapes(p.shape,l),h=v.sizeFromShape(d),m=v.makeZerosTypedArray(v.sizeFromShape(c),p.dtype),f=a.data.get(p.dataId).values;for(let y=0;y<m.length;++y){let x=y*h,A=f[x];for(let b=0;b<h;++b){let w=f[x+b];A=A||w}m[y]=A}u!=null&&a.disposeIntermediateTensorInfo(p);let g=a.makeTensorInfo(c,p.dtype,m);if(i){let y=C.expandShapeToKeepDim(c,o),x=bt({inputs:{x:g},backend:a,attrs:{shape:y}});return a.disposeIntermediateTensorInfo(g),x}return g}var TL={kernelName:pi,backendName:"cpu",kernelFunc:CL};function NL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n;Ie(r,"argMax");let i=v.parseAxisParam(s,r.shape),o=C.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Va({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],C.assertAxesAreInnerMostDims("argMax",i,l.shape.length);let[p,c]=C.computeOutAndReduceShapes(l.shape,i),d=v.sizeFromShape(p),h=v.makeZerosTypedArray(d,"int32"),m=v.sizeFromShape(c),f=a.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let y=g*m,x=f[y],A=0;for(let b=0;b<m;++b){let w=f[y+b];w>x&&(x=w,A=b)}h[g]=A}return u.forEach(g=>a.disposeIntermediateTensorInfo(g)),a.makeTensorInfo(p,"int32",h)}var RL={kernelName:lu,backendName:"cpu",kernelFunc:NL};function EL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n;Ie(r,"argMin");let i=v.parseAxisParam(s,r.shape),o=C.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Va({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],C.assertAxesAreInnerMostDims("argMin",i,l.shape.length);let[p,c]=C.computeOutAndReduceShapes(l.shape,i),d=v.sizeFromShape(p),h=v.makeZerosTypedArray(d,"int32"),m=v.sizeFromShape(c),f=a.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let y=g*m,x=f[y],A=0;for(let b=0;b<m;++b){let w=f[y+b];w<x&&(x=w,A=b)}h[g]=A}return u.forEach(g=>a.disposeIntermediateTensorInfo(g)),a.makeTensorInfo(p,"int32",h)}var ML={kernelName:uu,backendName:"cpu",kernelFunc:EL},$L=ct(ci,e=>Math.asin(e)),PL={kernelName:ci,backendName:"cpu",kernelFunc:$L},_L=ct(hi,e=>Math.asinh(e)),FL={kernelName:hi,backendName:"cpu",kernelFunc:_L},DL=ct(mi,e=>Math.atan(e)),OL={kernelName:mi,backendName:"cpu",kernelFunc:DL},zL=_t((e,t)=>Math.atan2(e,t)),LL=Kt(gi,zL),WL={kernelName:gi,backendName:"cpu",kernelFunc:LL},BL=ct(fi,e=>Math.atanh(e)),VL={kernelName:fi,backendName:"cpu",kernelFunc:BL};function I3(e,t,a,n,r,s){let i=r.strideHeight,o=r.strideWidth,l=r.dilationHeight,u=r.dilationWidth,p=r.effectiveFilterHeight,c=r.effectiveFilterWidth,d=r.padInfo.top,h=r.padInfo.left,m=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,f=_e(r.outShape,a),g=f.values,y=r.outShape[1]*r.outShape[2]*r.outShape[3],x=r.outShape[2]*r.outShape[3],A=r.outShape[3];for(let b=0;b<r.batchSize;++b){let w=b*y,I=b*n[0];for(let T=0;T<r.inChannels;++T)for(let N=0;N<r.outHeight;++N){let 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re=X*l-y,ee=re;for(;ee<0;)ee+=c;let ge=Math.min(r.inWidth,m+re),ie=Z+X*N,be=x,Ce=0,Re=0;for(let qe=W;qe<P;qe+=u){let gt=E+qe*n[1];for(let dt=H;dt<V;dt+=p){let st=gt+dt*n[2];for(let it=ee;it<ge;it+=c){let He=st+it*n[3],xt=e[He+S];if(s==="max"&&xt>be?be=xt:s==="avg"&&(Ce+=xt,Re++),isNaN(be))break}if(isNaN(be))break}if(isNaN(be))break}let Le=ie+S;b[Le]=s==="avg"?Ce/Math.max(Re,1):be}}}}return A}function UL(e,t){let a=_e(t.outShape,"int32"),n=t.strideDepth,r=t.strideHeight,s=t.strideWidth,i=t.dilationDepth,o=t.dilationHeight,l=t.dilationWidth,u=t.effectiveFilterDepth,p=t.effectiveFilterHeight,c=t.effectiveFilterWidth,d=t.padInfo.front,h=t.padInfo.top,m=t.padInfo.left;for(let f=0;f<t.batchSize;++f)for(let g=0;g<t.inChannels;++g)for(let y=0;y<t.outDepth;++y){let x=y*n-d,A=x;for(;A<0;)A+=i;let b=Math.min(t.inDepth,u+x);for(let w=0;w<t.outHeight;++w){let I=w*r-h,T=I;for(;T<0;)T+=o;let N=Math.min(t.inHeight,p+I);for(let M=0;M<t.outWidth;++M){let $=M*s-m,E=$;for(;E<0;)E+=l;let S=Math.min(t.inWidth,c+$),_=Number.NEGATIVE_INFINITY,O=-1;for(let W=A;W<b;W+=i){let P=W-x;for(let U=T;U<N;U+=o){let G=U-I;for(let q=E;q<S;q+=l){let H=q-$,V=e.get(f,W,U,q,g);V>=_&&(_=V,O=P*p*c+G*p+H)}}}a.set(O,f,y,w,M,g)}}}return a}function GL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;Ie(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(C.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=C.computePool2DInfo(r.shape,s,i,u,o,l),c;if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))c=nr({inputs:{x:r},backend:a});else{let d=a.data.get(r.dataId).values,h=v.computeStrides(r.shape),m=I3(d,r.shape,r.dtype,h,p,"avg");c=a.makeTensorInfo(p.outShape,r.dtype,m.values)}return c}var HL={kernelName:yi,backendName:"cpu",kernelFunc:GL};function jL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n;Ie(r,"avgPool3d");let p=C.computePool3DInfo(r.shape,s,i,1,o,l,u),c=a.data.get(r.dataId).values,d=dv(c,r.shape,r.dtype,v.computeStrides(r.shape),p,"avg");return a.makeTensorInfo(d.shape,"float32",d.values)}var qL={kernelName:du,backendName:"cpu",kernelFunc:jL};function XL(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n;Ie([r,s],"avgPool3DGrad");let p=C.computePool3DInfo(s.shape,i,o,1,l,u),c=p.strideDepth,d=p.strideHeight,h=p.strideWidth,m=p.filterDepth,f=p.filterHeight,g=p.filterWidth,y=p.dilationDepth,x=p.dilationHeight,A=p.dilationWidth,b=p.effectiveFilterDepth,w=p.effectiveFilterHeight,I=p.effectiveFilterWidth,T=b-1-p.padInfo.front,N=I-1-p.padInfo.left,M=w-1-p.padInfo.top,$=_e(s.shape,"float32"),E=1/(m*f*g),S=a.bufferSync(r);for(let _=0;_<p.batchSize;++_)for(let O=0;O<p.inChannels;++O)for(let W=0;W<p.inDepth;++W)for(let P=0;P<p.inHeight;++P)for(let U=0;U<p.inWidth;++U){let G=W-T,q=P-M,H=U-N,V=0;for(let Z=0;Z<b;Z+=y){let X=(G+Z)/c;if(!(X<0||X>=p.outDepth||Math.floor(X)!==X))for(let re=0;re<w;re+=x){let ee=(q+re)/d;if(!(ee<0||ee>=p.outHeight||Math.floor(ee)!==ee))for(let ge=0;ge<I;ge+=A){let ie=(H+ge)/h;if(ie<0||ie>=p.outWidth||Math.floor(ie)!==ie)continue;let be=S.get(_,X,ee,ie,O);V+=be}}}$.set(V*E,_,W,P,U,O)}return a.makeTensorInfo($.shape,$.dtype,$.values)}var KL={kernelName:pp,backendName:"cpu",kernelFunc:XL};function YL(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s;Ie([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,p=C.computePool2DInfo(i.shape,o,l,1,u),c=p.strideHeight,d=p.strideWidth,h=p.filterHeight,m=p.filterWidth,f=p.dilationHeight,g=p.dilationWidth,y=p.effectiveFilterHeight,x=p.effectiveFilterWidth,A=x-1-p.padInfo.left,b=y-1-p.padInfo.top,w=_e(i.shape,"float32"),I=1/(h*m),T=a.data.get(r.dataId).values,N=_e(r.shape,"float32",T);for(let M=0;M<p.batchSize;++M)for(let $=0;$<p.inChannels;++$)for(let E=0;E<p.inHeight;++E)for(let S=0;S<p.inWidth;++S){let _=E-b,O=S-A,W=0;for(let P=0;P<y;P+=f){let U=(_+P)/c;if(!(U<0||U>=p.outHeight||Math.floor(U)!==U))for(let G=0;G<x;G+=g){let q=(O+G)/d;if(q<0||q>=p.outWidth||Math.floor(q)!==q)continue;let H=N.get(M,U,q,$);W+=H}}w.set(W*I,M,E,S,$)}return a.makeTensorInfo(w.shape,w.dtype,w.values)}var ZL={kernelName:dp,backendName:"cpu",kernelFunc:YL};function JL(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,scale:s,offset:i,mean:o,variance:l}=t;v.assert(o.shape.length===l.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||o.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(s==null||o.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks."),Ie([r,o,l,s,i],"batchNorm");let{varianceEpsilon:u}=n;u==null&&(u=.001);let p=a.data.get(r.dataId).values,c=a.data.get(o.dataId).values,d=a.data.get(l.dataId).values,h=s?a.data.get(s.dataId).values:new Float32Array([1]),m=i?a.data.get(i.dataId).values:new Float32Array([0]),f=new Float32Array(p.length),g=m.length,y=h.length,x=d.length,A=c.length,b=0,w=0,I=0,T=0;for(let N=0;N<p.length;++N)f[N]=m[b++]+(p[N]-c[w++])*h[I++]/Math.sqrt(d[T++]+u),b>=g&&(b=0),w>=A&&(w=0),I>=y&&(I=0),T>=x&&(T=0);return a.makeTensorInfo(r.shape,r.dtype,f)}var QL={kernelName:Ui,backendName:"cpu",kernelFunc:JL};function eW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,crops:i}=n;Ie([r],"batchToSpaceND");let o=s.reduce((y,x)=>y*x),l=C.getReshaped(r.shape,s,o),u=C.getPermuted(l.length,s.length),p=C.getReshapedPermuted(r.shape,s,o),c=C.getSliceBeginCoords(i,s.length),d=C.getSliceSize(p,i,s.length),h=bt({inputs:{x:r},backend:a,attrs:{shape:l}}),m=Va({inputs:{x:h},backend:a,attrs:{perm:u}}),f=bt({inputs:{x:m},backend:a,attrs:{shape:p}}),g=ti({inputs:{x:f},backend:a,attrs:{begin:c,size:d}});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(f),g}var tW={kernelName:pu,backendName:"cpu",kernelFunc:eW};function aW(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=h3(o,l,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,u)}var nW={kernelName:Ai,backendName:"cpu",kernelFunc:aW};function rW(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t,s=a.data.get(n.dataId).values,i=a.data.get(r.dataId).values,o=C.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return a.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var sW={kernelName:hu,backendName:"cpu",kernelFunc:rW},iW=ct(us,(e,t)=>{let a=t;return e>a.clipValueMax?a.clipValueMax:e<a.clipValueMin?a.clipValueMin:e}),oW={kernelName:us,backendName:"cpu",kernelFunc:iW},lW=e=>{let{x:t}=e.inputs,a=e.backend,n=new Float32Array(v.sizeFromShape(t.shape)),r=a.data.get(t.dataId),s=r.complexTensorInfos.real,i=r.complexTensorInfos.imag,o=a.data.get(s.dataId).values,l=a.data.get(i.dataId).values;for(let u=0;u<o.length;u++){let p=o[u],c=l[u];n[u]=Math.hypot(p,c)}return a.makeOutput(n,t.shape,"float32")},uW={kernelName:hp,backendName:"cpu",kernelFunc:lW};function tu(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.data.get(n.dataId).complexTensorInfos.imag,s=a.data.get(r.dataId).values;return a.makeTensorInfo(r.shape,r.dtype,s)}var dW={kernelName:vp,backendName:"cpu",kernelFunc:tu};function au(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(f=>f.shape);C.assertParamsConsistent(i,s);let o=C.computeOutShape(t.map(f=>f.shape),s);if(v.sizeFromShape(o)===0)return a.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(f=>v.sizeFromShape(f.shape)>0);if(l.length===1)return nr({inputs:{x:l[0]},backend:a});if(l[0].dtype==="complex64"){let f=l.map(b=>ei({inputs:{input:b},backend:a})),g=l.map(b=>tu({inputs:{input:b},backend:a})),y=au({inputs:f,backend:a,attrs:{axis:s}}),x=au({inputs:g,backend:a,attrs:{axis:s}}),A=Ja({inputs:{real:y,imag:x},backend:a});return f.forEach(b=>a.disposeIntermediateTensorInfo(b)),g.forEach(b=>a.disposeIntermediateTensorInfo(b)),a.disposeIntermediateTensorInfo(y),a.disposeIntermediateTensorInfo(x),A}let u=l.map(f=>{let g=[-1,v.sizeFromShape(f.shape.slice(s))];return bt({inputs:{x:f},backend:a,attrs:{shape:g}})}),p=u.map(f=>({vals:a.data.get(f.dataId).values,shape:f.shape}));o=C.computeOutShape(u.map(f=>f.shape),1);let c=u[0].shape[0]===1,d=m3(p,o,t[0].dtype,c),h=C.computeOutShape(l.map(f=>f.shape),s),m=a.makeTensorInfo(h,t[0].dtype,d);return u.forEach(f=>a.disposeIntermediateTensorInfo(f)),m}var pW={kernelName:mu,backendName:"cpu",kernelFunc:au};function pv(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;Ie([r,s],"conv2d");let c=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,s.shape,i,u,o,p,!1,c),h=d.filterHeight,m=d.filterWidth,f=d.dilationHeight,g=d.dilationWidth,y=d.padInfo.left,x=d.padInfo.top,A=d.dataFormat==="channelsLast",b=new Vt(d.outShape,r.dtype),w=v.computeStrides(r.shape),I=v.computeStrides(s.shape),T=w[0],N=A?w[1]:w[2],M=A?w[2]:1,$=A?1:w[1],E=b.strides[0],S=A?b.strides[1]:b.strides[2],_=A?b.strides[2]:1,O=A?1:b.strides[1],W=a.data.get(r.dataId).values,P=a.data.get(s.dataId).values,U=b.values;for(let G=0;G<d.batchSize;++G){let q=G*T,H=G*E;for(let V=0;V<d.outHeight;++V){let Z=H+V*S,X=V*d.strideHeight-x;for(let re=0;re<h;++re){let ee=X+re*f;if(ee<0||ee>=d.inHeight)continue;let ge=re*I[0],ie=q+ee*N;for(let be=0;be<d.outWidth;++be){let Ce=Z+be*_,Re=be*d.strideWidth-y;for(let Le=0;Le<m;++Le){let qe=Re+Le*g;if(qe<0||qe>=d.inWidth)continue;let gt=ge+Le*I[1],dt=ie+qe*M,st=gt;for(let it=0;it<d.inChannels;++it){let He=W[dt+it*$];for(let xt=0;xt<d.outChannels;++xt)U[Ce+xt*O]+=He*P[st+xt];st+=d.outChannels}}}}}}return a.makeTensorInfo(b.shape,b.dtype,U)}var cW={kernelName:wi,backendName:"cpu",kernelFunc:pv};function hW(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;Ie([r,s],"conv2dBackpropFilter");let c=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,p,i,1,o,u,!1,c),{strideHeight:h,strideWidth:m,filterHeight:f,filterWidth:g}=d,y=d.dataFormat==="channelsLast",x=new Vt(d.filterShape,"float32"),A=d.padInfo.left,b=d.padInfo.top,w=a.data.get(r.dataId).values,I=a.data.get(s.dataId).values,T=new Vt(r.shape,r.dtype,w),N=new Vt(s.shape,s.dtype,I);for(let M=0;M<f;++M){let $=Math.max(0,Math.ceil((b-M)/h)),E=Math.min(d.outHeight,(d.inHeight+b-M)/h);for(let S=0;S<g;++S){let _=Math.max(0,Math.ceil((A-S)/m)),O=Math.min(d.outWidth,(d.inWidth+A-S)/m);for(let W=0;W<d.inChannels;++W)for(let P=0;P<d.outChannels;++P){let U=0;for(let G=0;G<d.batchSize;++G)for(let q=$;q<E;++q){let H=M+q*h-b;for(let V=_;V<O;++V){let Z=S+V*m-A;y?U+=T.get(G,H,Z,W)*N.get(G,q,V,P):U+=T.get(G,W,H,Z)*N.get(G,P,q,V)}}x.set(U,M,S,W,P)}}}return a.makeTensorInfo(x.shape,x.dtype,x.values)}var mW={kernelName:mp,backendName:"cpu",kernelFunc:hW};function fW(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;Ie([r,s],"conv2dBackpropInput");let c=v.computeStrides(s.shape),d=v.computeStrides(r.shape),h=C.convertConv2DDataFormat(u),m=C.computeConv2DInfo(i,s.shape,o,1,l,p,!1,h),f=new Vt(m.inShape,"float32"),g=f.values,y=a.data.get(r.dataId).values,x=a.data.get(s.dataId).values,[A,b,w]=c,{batchSize:I,filterHeight:T,filterWidth:N,inChannels:M,inHeight:$,inWidth:E,outChannels:S,outHeight:_,outWidth:O,strideHeight:W,strideWidth:P}=m;h=m.dataFormat;let U=T-1-m.padInfo.top,G=N-1-m.padInfo.left,q=h==="channelsLast",H=f.strides[0],V=q?f.strides[1]:f.strides[2],Z=q?f.strides[2]:1,X=q?1:f.strides[1],re=d[0],ee=q?d[1]:d[2],ge=q?d[2]:1,ie=q?1:d[1];for(let be=0;be<I;++be)for(let Ce=0;Ce<M;++Ce)for(let Re=0;Re<$;++Re){let Le=Re-U,qe=Math.max(0,Math.ceil(Le/W)),gt=Math.min(_,(T+Le)/W);for(let dt=0;dt<E;++dt){let st=dt-G,it=Math.max(0,Math.ceil(st/P)),He=Math.min(O,(N+st)/P),xt=0;for(let zt=qe;zt<gt;++zt){let un=zt*W-Le;for(let la=it;la<He;++la){let _a=la*P-st,dn=re*be+ee*zt+ge*la,Fa=A*(T-1-un)+b*(N-1-_a)+w*Ce;for(let ht=0;ht<S;++ht){let Da=y[dn+ie*ht],ja=x[Fa+ht];xt+=Da*ja}}}let Ha=H*be+V*Re+Z*dt+X*Ce;g[Ha]=xt}}return a.makeTensorInfo(f.shape,f.dtype,f.values)}var gW={kernelName:ki,backendName:"cpu",kernelFunc:fW};function yW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n;Ie([r,s],"conv3d");let u=C.computeConv3DInfo(r.shape,s.shape,i,l,o),{filterDepth:p,filterHeight:c,filterWidth:d,dilationDepth:h,dilationHeight:m,dilationWidth:f,padInfo:g}=u,y=g.front,x=g.left,A=g.top,b=new Vt(u.outShape,r.dtype),w=a.data.get(r.dataId).values,I=a.data.get(s.dataId).values,T=b.values,N=v.computeStrides(r.shape),M=v.computeStrides(s.shape);for(let $=0;$<u.batchSize;++$){let E=$*N[0],S=$*b.strides[0];for(let _=0;_<u.outDepth;++_){let O=S+_*b.strides[1],W=_*u.strideDepth-y;for(let P=0;P<p;++P){let U=W+P*h;if(U<0||U>=u.inDepth)continue;let G=P*M[0],q=E+U*N[1];for(let H=0;H<u.outHeight;++H){let V=O+H*b.strides[2],Z=H*u.strideHeight-A;for(let X=0;X<c;++X){let re=Z+X*m;if(re<0||re>=u.inHeight)continue;let ee=G+X*M[1],ge=q+re*N[2];for(let ie=0;ie<u.outWidth;++ie){let be=V+ie*u.outChannels,Ce=ie*u.strideWidth-x;for(let Re=0;Re<d;++Re){let Le=Ce+Re*f;if(Le<0||Le>=u.inWidth)continue;let qe=ee+Re*M[2],gt=ge+Le*u.inChannels,dt=qe;for(let st=0;st<u.inChannels;++st){let it=w[gt+st];for(let He=0;He<u.outChannels;++He)T[be+He]+=it*I[dt+He];dt+=u.outChannels}}}}}}}}return a.makeTensorInfo(b.shape,b.dtype,b.values)}var xW={kernelName:Ii,backendName:"cpu",kernelFunc:yW};function AW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=n;Ie([r,s],"conv3dBackpropFilterV2");let u=v.computeStrides(r.shape),p=v.computeStrides(s.shape),c=C.computeConv3DInfo(r.shape,l,i,1,o),d=c.strideDepth,h=c.strideHeight,m=c.strideWidth,f=c.filterDepth,g=c.filterHeight,y=c.filterWidth,x=new Vt(c.filterShape,"float32"),A=x.values,[b,w,I,T]=x.strides,N=a.data.get(s.dataId).values,[M,$,E,S]=p,_=a.data.get(r.dataId).values,[O,W,P,U]=u,G=c.padInfo.front,q=c.padInfo.left,H=c.padInfo.top;for(let V=0;V<f;++V){let Z=Math.max(0,Math.ceil((G-V)/d)),X=Math.min(c.outDepth,(c.inDepth+G-V)/d),re=V*b;for(let ee=0;ee<g;++ee){let ge=Math.max(0,Math.ceil((H-ee)/h)),ie=Math.min(c.outHeight,(c.inHeight+H-ee)/h),be=ee*w+re;for(let Ce=0;Ce<y;++Ce){let Re=Math.max(0,Math.ceil((q-Ce)/m)),Le=Math.min(c.outWidth,(c.inWidth+q-Ce)/m),qe=Ce*I+be;for(let gt=0;gt<c.inChannels;++gt){let dt=gt*T+qe;for(let st=0;st<c.outChannels;++st){let it=0;for(let He=0;He<c.batchSize;++He){let xt=He*O,Ha=He*M;for(let zt=Z;zt<X;++zt){let un=(V+zt*d-G)*W+xt,la=zt*$+Ha;for(let _a=ge;_a<ie;++_a){let dn=(ee+_a*h-H)*P+un,Fa=_a*E+la;for(let ht=Re;ht<Le;++ht){let Da=(Ce+ht*m-q)*U+dn,ja=ht*S+Fa;it+=_[Da+gt]*N[ja+st]}}}}A[dt+st]=it}}}}}return a.makeTensorInfo(x.shape,x.dtype,x.values)}var bW={kernelName:fu,backendName:"cpu",kernelFunc:AW};function vW(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=n;Ie([r],"conv3dBackpropInputV2");let u=v.computeStrides(r.shape),p=v.computeStrides(s.shape),c=C.computeConv3DInfo(l,s.shape,o,1,i),d=new Vt(c.inShape,"float32"),h=d.values,[m,f,g,y]=d.strides,x=a.data.get(r.dataId).values,[A,b,w,I]=u,T=a.data.get(s.dataId).values,[N,M,$,E]=p,{batchSize:S,filterDepth:_,filterHeight:O,filterWidth:W,inChannels:P,inDepth:U,inHeight:G,inWidth:q,outChannels:H,outDepth:V,outHeight:Z,outWidth:X,strideDepth:re,strideHeight:ee,strideWidth:ge}=c,ie=_-1-c.padInfo.front,be=O-1-c.padInfo.top,Ce=W-1-c.padInfo.left;for(let Re=0;Re<S;++Re)for(let Le=0;Le<P;++Le)for(let qe=0;qe<U;++qe){let gt=qe-ie,dt=Math.max(0,Math.ceil(gt/re)),st=Math.min(V,(_+gt)/re);for(let it=0;it<G;++it){let He=it-be,xt=Math.max(0,Math.ceil(He/ee)),Ha=Math.min(Z,(O+He)/ee);for(let zt=0;zt<q;++zt){let un=zt-Ce,la=Math.max(0,Math.ceil(un/ge)),_a=Math.min(X,(W+un)/ge),dn=0;for(let Fa=dt;Fa<st;++Fa){let ht=Fa*re-gt;for(let Da=xt;Da<Ha;++Da){let ja=Da*ee-He;for(let mr=la;mr<_a;++mr){let Tl=mr*ge-un,qn=A*Re+b*Fa+w*Da+I*mr,fd=N*(_-1-ht)+M*(O-1-ja)+$*(W-1-Tl)+E*Le;for(let In=0;In<H;++In){let Or=x[qn+In],Yt=T[fd+In];dn+=Or*Yt}}}}h[m*Re+f*qe+g*it+y*zt+Le]=dn}}}return a.makeTensorInfo(d.shape,d.dtype,d.values)}var wW={kernelName:Si,backendName:"cpu",kernelFunc:vW},kW=ct(Ci,e=>Math.cos(e)),IW={kernelName:Ci,backendName:"cpu",kernelFunc:kW},SW=ct(Ti,e=>Math.cosh(e)),CW={kernelName:Ti,backendName:"cpu",kernelFunc:SW};function TW(e){let{inputs:t,backend:a,attrs:n}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,[p,c,d,h]=r.shape,m=s.shape[0],[f,g]=o,y=_e([m,f,g,h],"float32"),x=a.data.get(s.dataId).values,A=a.data.get(i.dataId).values,b=a.data.get(r.dataId).values,w=v.computeStrides(r.shape),I=v.computeStrides(y.shape);for(let T=0;T<m;T++){let N=T*4,M=x[N],$=x[N+1],E=x[N+2],S=x[N+3],_=A[T];if(_>=p)continue;let O=f>1?(E-M)*(c-1)/(f-1):0,W=g>1?(S-$)*(d-1)/(g-1):0;for(let P=0;P<f;P++){let U=f>1?M*(c-1)+P*O:.5*(M+E)*(c-1);if(U<0||U>c-1){for(let G=0;G<g;G++)for(let q=0;q<h;q++){let H=q+G*I[2]+P*I[1]+T*I[0];y.values[H]=u}continue}if(l==="bilinear"){let G=Math.floor(U),q=Math.ceil(U),H=U-G;for(let V=0;V<g;V++){let Z=g>1?$*(d-1)+V*W:.5*($+S)*(d-1);if(Z<0||Z>d-1){for(let ge=0;ge<h;ge++){let ie=ge+V*I[2]+P*I[1]+T*I[0];y.values[ie]=u}continue}let X=Math.floor(Z),re=Math.ceil(Z),ee=Z-X;for(let ge=0;ge<h;ge++){let ie=ge+X*w[2]+G*w[1]+_*w[0],be=b[ie];ie=ge+re*w[2]+G*w[1]+_*w[0];let Ce=b[ie];ie=ge+X*w[2]+q*w[1]+_*w[0];let Re=b[ie];ie=ge+re*w[2]+q*w[1]+_*w[0];let Le=b[ie],qe=be+(Ce-be)*ee,gt=Re+(Le-Re)*ee;ie=ge+V*I[2]+P*I[1]+T*I[0],y.values[ie]=qe+(gt-qe)*H}}}else for(let G=0;G<g;++G){let q=g>1?$*(d-1)+G*W:.5*($+S)*(d-1);if(q<0||q>d-1){for(let Z=0;Z<h;Z++){let X=Z+G*I[2]+P*I[1]+T*I[0];y.values[X]=u}continue}let H=Math.round(q),V=Math.round(U);for(let Z=0;Z<h;Z++){let X=Z+H*w[2]+V*w[1]+_*w[0],re=Z+G*I[2]+P*I[1]+T*I[0];y.values[re]=b[X]}}}}return a.makeTensorInfo(y.shape,y.dtype,y.values)}var NW={kernelName:Ei,backendName:"cpu",kernelFunc:TW};function RW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;Ie(r,"cumprod");let l=C.getAxesPermutation([s],r.shape.length),u=r;l!=null&&(u=Va({inputs:{x:r},backend:a,attrs:{perm:l}}));let p=C.getInnerMostAxes(1,r.shape.length)[0];if(p!==u.shape.length-1)throw new Error(`backend.cumprod in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${p}`);let c=pa(u.dtype,"int32"),d=v.makeOnesTypedArray(v.sizeFromShape(u.shape),c),h=a.data.get(u.dataId).values,m=u.shape[u.shape.length-1],f=o?(y,x)=>y+m-x-1:(y,x)=>y+x;for(let y=0;y<h.length;y+=m)for(let x=0;x<m;x++){let A=f(y,x);if(x===0)d[A]=i?1:h[A];else{let b=f(y,x-1);d[A]=i?h[b]*d[b]:h[A]*d[b]}}let g=a.makeTensorInfo(u.shape,c,d);if(l!=null){let y=C.getUndoAxesPermutation(l),x=Va({inputs:{x:g},backend:a,attrs:{perm:y}});return a.disposeIntermediateTensorInfo(g),a.disposeIntermediateTensorInfo(u),x}return g}var EW={kernelName:Ni,backendName:"cpu",kernelFunc:RW};function MW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;Ie(r,"cumsum");let l=C.getAxesPermutation([s],r.shape.length),u=r;l!=null&&(u=Va({inputs:{x:r},backend:a,attrs:{perm:l}}));let p=C.getInnerMostAxes(1,r.shape.length)[0];if(p!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${p}`);let c=pa(u.dtype,"int32"),d=v.makeZerosTypedArray(v.sizeFromShape(u.shape),c),h=a.data.get(u.dataId).values,m=u.shape[u.shape.length-1],f=o?(y,x)=>y+m-x-1:(y,x)=>y+x;for(let y=0;y<h.length;y+=m)for(let x=0;x<m;x++){let A=f(y,x);if(x===0)d[A]=i?0:h[A];else{let b=f(y,x-1);d[A]=i?h[b]+d[b]:h[A]+d[b]}}let g=a.makeTensorInfo(u.shape,c,d);if(l!=null){let y=C.getUndoAxesPermutation(l),x=Va({inputs:{x:g},backend:a,attrs:{perm:y}});return a.disposeIntermediateTensorInfo(g),a.disposeIntermediateTensorInfo(u),x}return g}var $W={kernelName:Ri,backendName:"cpu",kernelFunc:MW};function PW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n;if(r.shape.length===1){let l=a.data.get(r.dataId).values,u=a.data.get(s.dataId).values,p=h3(l,u,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=a.bufferSync(r),u=a.bufferSync(s),p=A6(l,u,i,o);return a.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var _W={kernelName:gu,backendName:"cpu",kernelFunc:PW};function FW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockSize:s,dataFormat:i}=n;v.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. Got ${i}`);let o=r.shape[0],l=r.shape[1],u=r.shape[2],p=r.shape[3],c=l*s,d=u*s,h=p/(s*s),m=a.data.get(r.dataId).values,f=new Float32Array(o*c*d*h),g=0;for(let y=0;y<o;++y)for(let x=0;x<c;++x){let A=Math.floor(x/s),b=x%s;for(let w=0;w<d;++w){let I=Math.floor(w/s),T=w%s,N=(b*s+T)*h;for(let M=0;M<h;++M){let $=M+N+p*(I+u*(A+l*y));f[g++]=m[$]}}}return a.makeTensorInfo([o,c,d,h],r.dtype,f)}var DW={kernelName:Mi,backendName:"cpu",kernelFunc:FW};function cv(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=n;Ie([r,s],"depthwiseConv2DNative");let p=v.computeStrides(r.shape),c=v.computeStrides(s.shape),d=l;d==null&&(d=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(i,d),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${d}'`);let h=C.computeConv2DInfo(r.shape,s.shape,i,d,o,u,!0),{filterHeight:m,filterWidth:f,dilationHeight:g,dilationWidth:y,padInfo:x}=h,A=x.left,b=x.top,w=h.outChannels/h.inChannels,I=new Vt(h.outShape,r.dtype),T=a.data.get(r.dataId).values,N=a.data.get(s.dataId).values,M=I.values;for(let $=0;$<h.batchSize;++$){let E=$*p[0],S=$*I.strides[0];for(let _=0;_<h.outHeight;++_){let O=S+_*I.strides[1],W=_*h.strideHeight-b;for(let P=0;P<m;++P){let U=W+P*g;if(U<0||U>=h.inHeight)continue;let G=P*c[0],q=E+U*p[1];for(let H=0;H<h.outWidth;++H){let V=O+H*I.strides[2],Z=H*h.strideWidth-A;for(let X=0;X<f;++X){let re=Z+X*y;if(re<0||re>=h.inWidth)continue;let ee=G+X*c[1],ge=q+re*h.inChannels,ie=V,be=ee;for(let Ce=0;Ce<h.inChannels;++Ce){let Re=T[ge+Ce];for(let Le=0;Le<w;++Le)M[ie+Le]+=Re*N[be+Le];ie+=w,be+=w}}}}}}return a.makeTensorInfo(I.shape,I.dtype,I.values)}var OW={kernelName:$i,backendName:"cpu",kernelFunc:cv};function zW(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;Ie([r,s],"depthwiseConv2dNativeBackpropFilter");let c=C.computeConv2DInfo(r.shape,p,i,o,l,u,!0),{strideHeight:d,strideWidth:h,filterHeight:m,filterWidth:f}=c,g=new Vt(c.filterShape,"float32"),y=c.padInfo.left,x=c.padInfo.top,A=c.outChannels/c.inChannels,b=a.data.get(r.dataId).values,w=new Vt(r.shape,r.dtype,b),I=a.data.get(s.dataId).values,T=new Vt(s.shape,s.dtype,I);for(let N=0;N<m;++N){let M=Math.max(0,Math.ceil((x-N)/d)),$=Math.min(c.outHeight,(c.inHeight+x-N)/d);for(let E=0;E<f;++E){let S=Math.max(0,Math.ceil((y-E)/h)),_=Math.min(c.outWidth,(c.inWidth+y-E)/h);for(let O=0;O<c.outChannels;++O){let W=Math.trunc(O/A),P=O%A,U=0;for(let G=0;G<c.batchSize;++G)for(let q=M;q<$;++q){let H=N+q*d-x;for(let V=S;V<_;++V){let Z=E+V*h-y;U+=w.get(G,H,Z,W)*T.get(G,q,V,O)}}g.set(U,N,E,W,P)}}}return a.makeTensorInfo(g.shape,g.dtype,g.values)}var LW={kernelName:fp,backendName:"cpu",kernelFunc:zW};function WW(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;Ie([r,s],"depthwiseConv2DNativeBackpropInput");let c=v.computeStrides(r.shape),d=v.computeStrides(s.shape),h=C.computeConv2DInfo(p,s.shape,i,o,l,u,!0),m=new Vt(h.inShape,"float32"),f=m.values,[g,y,x]=m.strides,A=a.data.get(r.dataId).values,[b,w,I]=c,T=a.data.get(s.dataId).values,[N,M,$]=d,{batchSize:E,filterHeight:S,filterWidth:_,inChannels:O,inHeight:W,inWidth:P,outChannels:U,outHeight:G,outWidth:q,strideHeight:H,strideWidth:V}=h,Z=S-1-h.padInfo.top,X=_-1-h.padInfo.left,re=U/O;for(let ee=0;ee<E;++ee)for(let ge=0;ge<O;++ge)for(let ie=0;ie<W;++ie){let be=ie-Z,Ce=Math.max(0,Math.ceil(be/H)),Re=Math.min(G,(S+be)/H);for(let Le=0;Le<P;++Le){let qe=Le-X,gt=Math.max(0,Math.ceil(qe/V)),dt=Math.min(q,(_+qe)/V),st=0;for(let it=Ce;it<Re;++it){let He=it*H-be;for(let xt=gt;xt<dt;++xt){let 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UW={kernelName:yu,backendName:"cpu",kernelFunc:VW},GW={kernelName:Pi,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:a})=>{let{x:n,filter:r}=e,{strides:s,pad:i,dilations:o}=a,l=t,u=l.data.get(n.dataId).values,p=n.shape.length,c=l.data.get(r.dataId).values,d=r.shape.length,{batchSize:h,inHeight:m,inWidth:f,inChannels:g,outHeight:y,outWidth:x,padInfo:A,strideHeight:b,strideWidth:w,filterHeight:I,filterWidth:T,dilationHeight:N,dilationWidth:M,outShape:$}=C.computeDilation2DInfo(n.shape,r.shape,s,i,"NHWC",o),E=v.sizeFromShape($),S=$.length,_=v.getArrayFromDType(n.dtype,E);for(let O=0;O<h;++O)for(let W=0;W<y;++W){let P=W*b-A.top;for(let U=0;U<x;++U){let G=U*w-A.left;for(let q=0;q<g;++q){let H=Number.MIN_SAFE_INTEGER;for(let Z=0;Z<I;++Z){let X=P+Z*N;if(X>=0&&X<m)for(let re=0;re<T;++re){let ee=G+re*M;if(ee>=0&&ee<f){let ge=v.locToIndex([O,X,ee,q],p,v.computeStrides(n.shape)),ie=v.locToIndex([Z,re,q],d,v.computeStrides(r.shape)),be=u[ge]+c[ie];be>H&&(H=be)}}}let 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o;r.dtype==="bool"?o=is({inputs:{x:r},backend:a,attrs:{dtype:"int32"}}):o=nr({inputs:{x:r},backend:a});let l=o.shape.length,u=v.parseAxisParam(s,o.shape),p=C.getAxesPermutation(u,l),c=u,d=o;p!=null&&(d=Va({inputs:{x:o},backend:a,attrs:{perm:p}}),c=C.getInnerMostAxes(c.length,l)),C.assertAxesAreInnerMostDims("sum",c,d.shape.length);let[h,m]=C.computeOutAndReduceShapes(d.shape,c),f=C.upcastType(d.dtype,"int32"),g=xh(a,h,f),y=v.sizeFromShape(m),x=a.data.get(g.dataId).values,A=a.data.get(d.dataId).values;for(let b=0;b<x.length;++b){let w=b*y,I=0;for(let T=0;T<y;++T)I+=A[w+T];x[b]=I}if(i){let b=C.expandShapeToKeepDim(g.shape,u),w=g;g=bt({inputs:{x:g},backend:a,attrs:{shape:b}}),a.disposeIntermediateTensorInfo(w)}return a.disposeIntermediateTensorInfo(o),p!=null&&a.disposeIntermediateTensorInfo(d),g}var KW={kernelName:Go,backendName:"cpu",kernelFunc:Kp};function 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Float32Array(v.sizeFromShape(r.shape)),i=a.data.get(r.dataId).values,o=a.data.get(n.dataId).values;for(let l=0;l<i.length;++l){let u=i[l];u>=0?s[l]=o[l]:s[l]=o[l]*(u+1)}return a.makeTensorInfo(r.shape,"float32",s)}var QW={kernelName:xu,backendName:"cpu",kernelFunc:JW},eB=C.ERF_P,tB=C.ERF_A1,aB=C.ERF_A2,nB=C.ERF_A3,rB=C.ERF_A4,sB=C.ERF_A5,iB=ct(Di,e=>{let t=Math.sign(e),a=Math.abs(e),n=1/(1+eB*a);return t*(1-((((sB*n+rB)*n+nB)*n+aB)*n+tB)*n*Math.exp(-a*a))}),oB={kernelName:Di,backendName:"cpu",kernelFunc:iB};function vh(e){let{inputs:t,backend:a,attrs:n}=e,{input:r}=t,{dim:s}=n,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),bt({inputs:{x:r},backend:a,attrs:{shape:o}})}var lB={kernelName:Au,backendName:"cpu",kernelFunc:vh},uB=_t((e,t)=>e/t),S3=Kt(_i,uB),P1={kernelName:_i,backendName:"cpu",kernelFunc:S3};function hv(e,t,a){let n=e.shape,r=n[0],s=n[1],i=a.data.get(e.dataId),o=i.complexTensorInfos.real,l=i.complexTensorInfos.imag,u=[r,s],p=v.sizeFromShape(u),c=v.getTypedArrayFromDType("float32",p),d=v.getTypedArrayFromDType("float32",p);for(let g=0;g<r;g++){let y=ti({inputs:{x:o},backend:a,attrs:{begin:[g,0],size:[1,s]}}),x=ti({inputs:{x:l},backend:a,attrs:{begin:[g,0],size:[1,s]}}),A=Ja({inputs:{real:y,imag:x},backend:a}),{real:b,imag:w}=dB(A,t,a),I=C.mergeRealAndImagArrays(b,w);for(let T=0;T<s;T++){let N=C.getComplexWithIndex(I,T);c[g*s+T]=N.real,d[g*s+T]=N.imag}a.disposeIntermediateTensorInfo(y),a.disposeIntermediateTensorInfo(x),a.disposeIntermediateTensorInfo(A)}let h=a.makeTensorInfo(u,"float32",c),m=a.makeTensorInfo(u,"float32",d),f=Ja({inputs:{real:h,imag:m},backend:a});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),f}function dB(e,t,a){let n=v.sizeFromShape(e.shape),r=a.data.get(e.dataId),s=a.data.get(r.complexTensorInfos.real.dataId).values,i=a.data.get(r.complexTensorInfos.imag.dataId).values;if(pB(n)){let o=_1(s,i,n,t,a),l=[e.shape[0],e.shape[1]];if(t){let u=a.makeTensorInfo(l,"float32",o.real),p=a.makeTensorInfo(l,"float32",o.imag),c=a.makeTensorInfo([],"float32",v.createScalarValue(n,"float32")),d=nr({inputs:{x:c},backend:a}),h=P1.kernelFunc({inputs:{a:u,b:c},backend:a}),m=P1.kernelFunc({inputs:{a:p,b:d},backend:a}),f=a.data.get(h.dataId).values,g=a.data.get(m.dataId).values;return a.disposeIntermediateTensorInfo(u),a.disposeIntermediateTensorInfo(p),a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),{real:f,imag:g}}return o}else{let o=C.mergeRealAndImagArrays(s,i),l=cB(o,n,t);return C.splitRealAndImagArrays(l)}}function pB(e){return(e&e-1)===0}function _1(e,t,a,n,r){if(a===1)return{real:e,imag:t};let s=C.mergeRealAndImagArrays(e,t),i=a/2,o=C.complexWithEvenIndex(s),l=o.real,u=o.imag,p=[l.length],c=r.makeTensorInfo(p,"float32",l),d=r.makeTensorInfo(p,"float32",u),h=Ja({inputs:{real:c,imag:d},backend:r}),m=C.complexWithOddIndex(s),f=m.real,g=m.imag,y=[f.length],x=r.makeTensorInfo(y,"float32",f),A=r.makeTensorInfo(y,"float32",g),b=Ja({inputs:{real:x,imag:A},backend:r}),w=_1(l,u,i,n,r),I=w.real,T=w.imag,N=[I.length],M=r.makeTensorInfo(N,"float32",I),$=r.makeTensorInfo(N,"float32",T),E=Ja({inputs:{real:M,imag:$},backend:r}),S=_1(f,g,i,n,r),_=S.real,O=S.imag,W=[_.length],P=r.makeTensorInfo(W,"float32",_),U=r.makeTensorInfo(W,"float32",O),G=Ja({inputs:{real:P,imag:U},backend:r}),q=C.exponents(a,n),H=[q.real.length],V=r.makeTensorInfo(H,"float32",q.real),Z=r.makeTensorInfo(H,"float32",q.imag),X=Ja({inputs:{real:V,imag:Z},backend:r}),re=a0({inputs:{a:X,b:G},backend:r}),ee=eu({inputs:{a:E,b:re},backend:r}),ge=w3({inputs:{a:E,b:re},backend:r}),ie=ei({inputs:{input:ee},backend:r}),be=ei({inputs:{input:ge},backend:r}),Ce=tu({inputs:{input:ee},backend:r}),Re=tu({inputs:{input:ge},backend:r}),Le=au({inputs:[ie,be],backend:r,attrs:{axis:0}}),qe=au({inputs:[Ce,Re],backend:r,attrs:{axis:0}}),gt=r.data.get(Le.dataId).values,dt=r.data.get(qe.dataId).values;return r.disposeIntermediateTensorInfo(c),r.disposeIntermediateTensorInfo(d),r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(x),r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(b),r.disposeIntermediateTensorInfo(M),r.disposeIntermediateTensorInfo($),r.disposeIntermediateTensorInfo(E),r.disposeIntermediateTensorInfo(P),r.disposeIntermediateTensorInfo(U),r.disposeIntermediateTensorInfo(G),r.disposeIntermediateTensorInfo(V),r.disposeIntermediateTensorInfo(Z),r.disposeIntermediateTensorInfo(X),r.disposeIntermediateTensorInfo(re),r.disposeIntermediateTensorInfo(ee),r.disposeIntermediateTensorInfo(ge),r.disposeIntermediateTensorInfo(ie),r.disposeIntermediateTensorInfo(Ce),r.disposeIntermediateTensorInfo(be),r.disposeIntermediateTensorInfo(Re),r.disposeIntermediateTensorInfo(Le),r.disposeIntermediateTensorInfo(qe),{real:gt,imag:dt}}function cB(e,t,a){let n=new Float32Array(t*2);for(let r=0;r<t;r++){let s=0,i=0;for(let o=0;o<t;o++){let 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zV(e){let{inputs:t,backend:a,attrs:n}=e,{paramsNestedSplits:r,paramsDenseValues:s,indices:i}=t,{outputRaggedRank:o}=n,l=r.map(y=>a.data.get(y.dataId).values),u=r.map(y=>y.shape),p=a.data.get(s.dataId).values,c=a.data.get(i.dataId).values,[d,h,m]=U6(l,u,p,s.shape,s.dtype,c,i.shape,o),f=d.map(y=>a.makeTensorInfo([y.length],"int32",y)),g=a.makeTensorInfo(m,s.dtype,h);return f.concat([g])}var LV={kernelName:$h,backendName:"cpu",kernelFunc:zV};function WV(e){let{inputs:t,backend:a}=e,{starts:n,limits:r,deltas:s}=t,i=a.data.get(n.dataId).values,o=a.data.get(r.dataId).values,l=a.data.get(s.dataId).values,[u,p]=G6(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 BV={kernelName:Ph,backendName:"cpu",kernelFunc:WV};function 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nU={kernelName:Mo,backendName:"cpu",kernelFunc:aU},rU={kernelName:el,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{image:n}=e,{radians:r,fillValue:s,center:i}=t,o=a,l=v.getTypedArrayFromDType(n.dtype,v.sizeFromShape(n.shape)),[u,p,c,d]=n.shape,[h,m]=C.getImageCenter(i,p,c),f=255,g=Math.sin(r),y=Math.cos(r),x=o.data.get(n.dataId).values;for(let A=0;A<u;A++){let b=A*c*p*d;for(let w=0;w<p;w++){let I=w*(c*d);for(let T=0;T<c;T++){let N=T*d;for(let M=0;M<d;M++){let $=[u,w,T,M],E=$[2],S=$[1],_=(E-h)*y-(S-m)*g,O=(E-h)*g+(S-m)*y;_=Math.round(_+h),O=Math.round(O+m);let W=s;if(typeof s!="number"&&(M===3?W=f:W=s[M]),_>=0&&_<c&&O>=0&&O<p){let U=O*(c*d),G=_*d,q=b+U+G+M;W=x[q]}let P=b+I+N+M;l[P]=W}}}}return{dataId:o.write(l,n.shape,n.dtype),shape:n.shape,dtype:n.dtype}}},sU=ct($o,e=>{let t=Math.floor(e);return e-t<.5?Math.floor(e):e-t>.5?Math.ceil(e):t%2===0?t:t+1}),iU={kernelName:$o,backendName:"cpu",kernelFunc:sU};function 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hU={kernelName:Do,backendName:"cpu",kernelFunc:cU};function mU(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t;Ie([n,r,s],"select");let i=n.shape.length,o=a.data.get(n.dataId).values,l=a.data.get(r.dataId).values,u=a.data.get(s.dataId).values,p=pa(r.dtype,s.dtype),c=v.makeZerosTypedArray(v.sizeFromShape(r.shape),p),d=0,h=i===0||i>1||r.shape.length===1?1:v.sizeFromShape(r.shape.slice(1));for(let m=0;m<o.length;m++)for(let f=0;f<h;f++)o[m]===1?c[d++]=l[m]:c[d++]=u[m];return a.makeTensorInfo(r.shape,p,c)}var fU={kernelName:Pu,backendName:"cpu",kernelFunc:mU},gU=C.SELU_SCALEALPHA,yU=C.SELU_SCALE,xU=ct(Oo,e=>e>=0?yU*e:gU*(Math.exp(e)-1)),AU={kernelName:Oo,backendName:"cpu",kernelFunc:xU},bU=ct(Wo,e=>e<0?-1:e>0?1:0),vU={kernelName:Wo,backendName:"cpu",kernelFunc:bU},wU=ct(zo,e=>Math.sin(e)),kU={kernelName:zo,backendName:"cpu",kernelFunc:wU},IU=ct(Lo,e=>Math.sinh(e)),SU={kernelName:Lo,backendName:"cpu",kernelFunc:IU},CU=11920928955078125e-23,k5=Math.log(CU)+2,TU=ct(Vo,e=>{let 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saw:
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${n.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape
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${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
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$r(e,()=>e.createTexture(),"Unable to create WebGLTexture.")}function Rv(e,t){let a=B().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(e<=0||t<=0){let n=`[${e}x${t}]`;throw new Error("Requested texture size "+n+" is invalid.")}if(e>a||t>a){let n=`[${e}x${t}]`,r=`[${a}x${a}]`;throw new Error("Requested texture size "+n+" greater than WebGL maximum on this browser / GPU "+r+".")}}function Ev(e){return $r(e,()=>e.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function F1(e,t,a,n,r,s,i){let o=e.getAttribLocation(t,a);return o===-1?!1:(ce(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),ce(e,()=>e.vertexAttribPointer(o,r,e.FLOAT,!1,s,i)),ce(e,()=>e.enableVertexAttribArray(o)),!0)}function Mv(e,t,a){Dv(e,a),ce(e,()=>e.activeTexture(e.TEXTURE0+a)),ce(e,()=>e.bindTexture(e.TEXTURE_2D,t))}function _G(e,t){Dv(e,t),ce(e,()=>e.activeTexture(e.TEXTURE0+t)),ce(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function $v(e,t,a){return $r(e,()=>e.getUniformLocation(t,a),'uniform "'+a+'" not present in program.')}function Pv(e,t,a){return e.getUniformLocation(t,a)}function _v(e,t,a,n){ce(e,()=>Mv(e,t,n)),ce(e,()=>e.uniform1i(a,n))}function FG(e){ce(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),ce(e,()=>e.viewport(0,0,e.canvas.width,e.canvas.height)),ce(e,()=>e.scissor(0,0,e.canvas.width,e.canvas.height))}function rh(e,t,a){ce(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,a)),ce(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0))}function D1(e,t){ce(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,t)),ce(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,null,0))}function Ed(e){let t=e.checkFramebufferStatus(e.FRAMEBUFFER);if(t!==e.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+Fv(e,t))}function Fv(e,t){switch(t){case e.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case e.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${t}`}}function $r(e,t,a){let n=ce(e,()=>t());if(n==null)throw new Error(a);return n}function Dv(e,t){let a=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,n=t+e.TEXTURE0;if(n<e.TEXTURE0||n>a){let r=`[gl.TEXTURE0, gl.TEXTURE${a}]`;throw new Error(`textureUnit must be in ${r}.`)}}function ai(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function ni(e){if(e.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[e.length>1?e[e.length-2]:1,e[e.length-1]]}function Md(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[ai(e),...ni(e)]),t}function Ov(e,t=!1){let a=B().getNumber("WEBGL_MAX_TEXTURE_SIZE"),n=B().getNumber("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE");n===1/0&&B().getBool("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE")&&(n=a/2),t&&(a=a*2,n=n*2,e=e.map((o,l)=>l>=e.length-2?v.nearestLargerEven(e[l]):e[l]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=v.squeezeShape(e).newShape);let r=v.sizeFromShape(e),s=null;e.length<=1&&r<=a?s=[1,r]:e.length===2&&e[0]<=a&&e[1]<=a?s=e:e.length===3&&e[0]*e[1]<=a&&e[2]<=a?s=[e[0]*e[1],e[2]]:e.length===3&&e[0]<=a&&e[1]*e[2]<=a?s=[e[0],e[1]*e[2]]:e.length===4&&e[0]*e[1]*e[2]<=a&&e[3]<=a?s=[e[0]*e[1]*e[2],e[3]]:e.length===4&&e[0]<=a&&e[1]*e[2]*e[3]<=a&&(s=[e[0],e[1]*e[2]*e[3]]);let i=s!=null&&Math.max(...s)>n&&Math.min(...s)<=(t?2:1)&&Math.min(...s)>0;if(s==null||i)if(t){let o=ai(e),l=2,u=2;e.length&&([l,u]=ni(e)),r=o*(l/2)*(u/2),s=v.sizeToSquarishShape(r).map(p=>p*2)}else s=v.sizeToSquarishShape(r);return s}function Jc(e){return e%2===0}function ep(e,t){if(e=e.slice(-2),t=t.slice(-2),v.arraysEqual(e,t)||!e.length||!t.length||e[0]===0||e[1]===0||t[0]===0||t[1]===0)return!0;if(e.length!==t.length){let a=e[e.length-1],n=t[t.length-1];if(a===n||Jc(a)&&Jc(n)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&Jc(e[0])&&Jc(t[0])}var sh,ih;function zv(e){if(sh==null){let t=Bn(e);sh=t.getParameter(t.MAX_TEXTURE_SIZE)}return sh}function DG(){sh=null}function OG(){ih=null}function Lv(e){if(ih==null){let t=Bn(e);ih=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,ih)}function Wv(e){if(e===0)return 0;let t,a=Bn(e);return fn(a,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:fn(a,"EXT_disjoint_timer_query")?t=1:t=0,t}function fn(e,t){return e.getExtension(t)!=null}function O1(e){try{if(Bn(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function Bv(e){if(e===0)return!1;let t=Bn(e);if(e===1){if(!fn(t,"OES_texture_float"))return!1}else if(!fn(t,"EXT_color_buffer_float"))return!1;return z1(t)}function Vv(e){if(e===0)return!1;let t=Bn(e);if(e===1){if(!fn(t,"OES_texture_float")||!fn(t,"WEBGL_color_buffer_float"))return!1}else{if(fn(t,"EXT_color_buffer_float"))return z1(t);let a="EXT_color_buffer_half_float";if(fn(t,a)){let n=t.getExtension(a);return zG(t,n)}return!1}return z1(t)}function z1(e){let t=T3(e),a=e.createTexture();e.bindTexture(e.TEXTURE_2D,a),e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,1,1,0,t.textureFormatFloat,t.textureTypeFloat,null);let n=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,n),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,a,0);let r=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(a),e.deleteFramebuffer(n),r}function zG(e,t){let a=T3(e,t),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n),e.texImage2D(e.TEXTURE_2D,0,a.internalFormatHalfFloat,1,1,0,a.textureFormatFloat,a.textureTypeHalfFloat,null);let r=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,r),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let s=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(r),s}function Uv(e){return e!==2?!1:Bn(e).fenceSync!=null}function qu(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 Se=B();Se.registerFlag("HAS_WEBGL",()=>Se.getNumber("WEBGL_VERSION")>0);Se.registerFlag("WEBGL_VERSION",()=>O1(2)?2:O1(1)?1:0);Se.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Se.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Se.get("WEBGL_VERSION")===2);Se.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Se.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Se.registerFlag("WEBGL_PACK",()=>Se.getBool("HAS_WEBGL"));Se.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_CLIP",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_REDUCE",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_LAZILY_UNPACK",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_CONV_IM2COL",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_PACK_CONV2DTRANSPOSE",()=>Se.getBool("WEBGL_PACK"));Se.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>zv(Se.getNumber("WEBGL_VERSION")));Se.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>Lv(Se.getNumber("WEBGL_VERSION")));Se.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=Se.getNumber("WEBGL_VERSION");return e===0?0:Wv(e)});Se.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Se.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!Fp.isMobile());Se.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>Bv(Se.getNumber("WEBGL_VERSION")));Se.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Se.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Se.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Se.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>Vv(Se.getNumber("WEBGL_VERSION")));Se.registerFlag("WEBGL_FENCE_API_ENABLED",()=>Uv(Se.getNumber("WEBGL_VERSION")));Se.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Se.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Se.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,e=>{if(typeof e!="number")throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be a number but got ${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}.`)});Se.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>Fp.isMobile()?1:-1,e=>{if(typeof e!="number")throw new Error(`WEBGL_FLUSH_THRESHOLD must be a number but got ${e}.`);if(e<0&&e!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});Se.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);Se.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);Se.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);Se.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);Se.registerFlag("WEBGL_EXP_CONV",()=>!1);Se.registerFlag("SOFTWARE_WEBGL_ENABLED",()=>Se.getBool("IS_TEST"));Se.registerFlag("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE",()=>1/0);Se.registerFlag("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE",()=>!1);Se.registerFlag("WEBGL2_ISNAN_CUSTOM",()=>!1);Se.registerFlag("ENGINE_COMPILE_ONLY",()=>!1);function Ra(){let e,t,a,n,r,s,i,o,l,u;return B().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",a="out",n="in",r="texture",s="outputColor",i="out vec4 outputColor;",o=B().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 rl(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 r0(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}; ${o};`}).join("")}function LG(e,t){let a=e.length,n=e.map(s=>`${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 WG(e,t,a="index"){let n=e.map((s,i)=>i),r=LG(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 R3(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 E3(){return`
int getFlatIndex(ivec3 coords) {
return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
}
`}var Gv=`
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:Hv}=C;function BG(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:m}=M3(a.packedInputs,d.shapeInfo.logicalShape,d.shapeInfo.texShape);switch(m.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?`[${d.arrayIndex}]`:""};`)});let r=n.join(`
`),s=e.map(d=>VG(d,t,a.packedInputs,a.enableShapeUniforms)).join(`
`),i=t.texShape,o=Ra(),l=HG(o),u,p,c=XG(o);return t.isPacked?(u=UG(t.logicalShape,i,a.enableShapeUniforms),p=qG(o)):(u=GG(t.logicalShape,i,a.enableShapeUniforms),p=jG(o)),a.packedInputs&&(c+=JG),[c,l,p,r,u,s,a.userCode].join(`
`)}function Xu(e,t=!1){let a=e.shapeInfo.logicalShape;switch(a.length){case 0:return dH(e,t);case 1:return cH(e,t);case 2:return mH(e,t);case 3:return gH(e,t);case 4:return xH(e,t);case 5:return AH(e);case 6:return bH(e);default:throw new Error(`${a.length}-D input sampling is not yet supported`)}}function jv(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return uH(e);case 1:return pH(e,t);case 2:return hH(e,t);case 3:return fH(e,t);default:return yH(e,t)}}function VG(e,t,a=!1,n){let r="";a?r+=jv(e,n):r+=Xu(e,n);let s=e.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(a?r+=vH(e,t):r+=wH(e,t)),r}function UG(e,t,a){switch(e.length){case 0:return qv();case 1:return QG(e,t,a);case 2:return oH(e,t,a);case 3:return tH(e,t,a);default:return nH(e,t,a)}}function GG(e,t,a){switch(e.length){case 0:return qv();case 1:return eH(e,t,a);case 2:return lH(e,t,a);case 3:return aH(e,t,a);case 4:return rH(e,t,a);case 5:return sH(e,t);case 6:return iH(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function HG(e){return`
float sampleTexture(sampler2D textureSampler, vec2 uv) {
return ${e.texture2D}(textureSampler, uv).r;
}
`}function jG(e){return`
void setOutput(float val) {
${e.output} = vec4(val, 0, 0, 0);
}
`}function qG(e){return`
void setOutput(vec4 val) {
${e.output} = val;
}
`}function XG(e){return`${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);
}
${KG}
${YG}
${ZG}
`}var KG=`
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);
}
`,YG=`
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);
}
`,ZG=`
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);
}
`,JG=`
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 qv(){return`
int getOutputCoords() {
return 0;
}
`}function QG(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 eH(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 * ${t[1]} + resTexRC.y;
}
`}function tH(e,t,a){if(a)return`
ivec3 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec3(b, r, c);
}
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),s=r*Math.ceil(e[1]/2);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${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 aH(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;
${r0(["r","c","d"],e)}
return ivec3(r, c, d);
}
`;let n=rl(["r","c","d"],e);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec3(r, c, d);
}
`}function nH(e,t,a){if(a)return`
ivec4 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
int texelsInBatchN = texelsInBatch * outShape[1];
int b2 = index / texelsInBatchN;
index -= b2 * texelsInBatchN;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec4(b2, b, r, c);
}
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),s=r*Math.ceil(e[e.length-2]/2),i=s,o="",l="b, r, c";for(let u=2;u<e.length-1;u++)i*=e[e.length-u-1],o=`
int b${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 rH(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;
${r0(["r","c","d","d2"],e)}
return ivec4(r, c, d, d2);
}
`;let n=rl(["r","c","d","d2"],e);return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec4(r, c, d, d2);
}
`}function sH(e,t){let a=rl(["r","c","d","d2","d3"],e);return`
ivec5 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${a}
ivec5 outShape = ivec5(r, c, d, d2, d3);
return outShape;
}
`}function iH(e,t){let a=rl(["r","c","d","d2","d3","d4"],e);return`
ivec6 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${a}
ivec6 result = ivec6(r, c, d, d2, d3, d4);
return result;
}
`}function oH(e,t,a){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return a?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return 2 * ivec2(resultUV.yx * vec2(${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, ${r}) * 2;
return ivec2(r, c);
}
`}function lH(e,t,a){return v.arraysEqual(e,t)?a?`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(${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 * ${e[1]};
return ivec2(r, c);
}
`}function sl(e){return`offset${e}`}function uH(e){let t=e.name,a="get"+t.charAt(0).toUpperCase()+t.slice(1),n=Ra();return`
vec4 ${a}() {
return ${n.texture2D}(${t}, halfCR);
}
`}function dH(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=sl(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 pH(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1),r=e.shapeInfo.texShape,s=Ra();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 cH(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1);if(e.shapeInfo.isUniform)return`
float ${n}(int index) {
${Ku(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=sl(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 hH(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=Ra();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 mH(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=Yu(e,l),h=["row","col"];return`
${Xu(d,t)}
float ${r}(int row, int col) {
return ${r}(${Zu(h,o)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col) {
int index = round(dot(vec2(row, col), vec2(${a[1]}, 1)));
${Ku(e)}
}
`;let u=s[0],p=s[1],c=sl(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 fH(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],m=Yu(e,d),f=["b","row","col"];return`
${jv(m,t)}
vec4 ${r}(int b, int row, int col) {
return ${r}(${Zu(f,h)});
}
`}let o=Ra();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 gH(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 f=Yu(e,u),g=["row","col","depth"];return`
${Xu(f,t)}
float ${r}(int row, int col, int depth) {
return ${r}(${Zu(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)));
${Ku(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 m=sl(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 + ${m};
vec2 uv = uvFromFlat(${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 + ${m};
vec2 uv = uvFromFlat(${c}, ${d}, index);
return sampleTexture(${n}, uv);
}
`}function yH(e,t){let a=e.name,n="get"+a.charAt(0).toUpperCase()+a.slice(1),r=Ra();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",m=`b * ${d} + (row / 2) * ${c} + (col / 2)`;for(let f=2;f<i-1;f++)h=`int b${f}, `+h,d*=s[i-f-1],m=`b${f} * ${d} + `+m;return`
vec4 ${n}(${h}) {
int index = ${m};
int texR = index / ${p};
int texC = index - texR * ${p};
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${p}, ${u});
return ${r.texture2D}(${a}, uv);
}
`}function xH(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 x=Yu(e,l),A=["row","col","depth","depth2"];return`
${Xu(x,t)}
float ${r}(int row, int col, int depth, int depth2) {
return ${r}(${Zu(A,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)));
${Ku(e)}
}
`;let p=e.shapeInfo.flatOffset,c=e.shapeInfo.texShape,d=c[0],h=c[1],m=`int stride2 = ${n}Shape[3];`,f=`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) {
${m}
${f}
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(stride1, stride2, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${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 y=sl(n);return t?`
float ${r}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
${m}
${f}
${g}
int index = row * stride0 + col * stride1 +
depth * stride2 + depth2;
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index + ${y});
return sampleTexture(${n}, uv);
}
`:`
float ${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 + ${y});
return sampleTexture(${n}, uv);
}
`}function AH(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 f=Yu(e,l),g=["row","col","depth","depth2","depth3"];return`
${Xu(f)}
float ${n}(int row, int col, int depth, int depth2, int depth3) {
return ${n}(${Zu(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;
${Ku(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 m=sl(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 + ${m};
vec2 uv = uvFromFlat(${d}, ${h}, index);
return sampleTexture(${a}, uv);
}
`}function bH(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=Yu(e,r),y=["row","col","depth","depth2","depth3","depth4"];return`
${Xu(g)}
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
return ${n}(${Zu(y,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)));
${Ku(e)}
}
`;let c=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,h=d[0],m=d[1];if(m===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}, ${i})) +
float(depth4);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${m}.0, ${h}.0);
return sampleTexture(${a}, uv);
}
`;if(m===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]},
${t[4]})) + float(depth3);
int texC = depth4;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${m}.0, ${h}.0);
return sampleTexture(${a}, uv);
}
`;let f=sl(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 + ${f};
vec2 uv = uvFromFlat(${h}, ${m}, index);
return sampleTexture(${a}, uv);
}
`}function Ku(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 ${t}[i];
}
}
`}function vH(e,t){let a=e.name,n=a.charAt(0).toUpperCase()+a.slice(1),r="get"+n+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=Hv(e.shapeInfo.logicalShape,t.logicalShape),l=ft(i),u=i-s,p,c=["x","y","z","w","u","v"];s===0?p="":i<2&&o.length>=1?p="coords = 0;":p=o.map(g=>`coords.${c[g+u]} = 0;`).join(`
`);let d="";i<2&&s>0?d="coords":d=e.shapeInfo.logicalShape.map((g,y)=>`coords.${c[y+u]}`).join(", ");let h="return outputValue;",m=v.sizeFromShape(e.shapeInfo.logicalShape)===1,f=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!m&&!f)h=`
return vec4(outputValue.xy, outputValue.xy);
`;else if(m&&!f)i===1?h=`
return vec4(outputValue.x, outputValue.x, 0., 0.);
`:h=`
return vec4(outputValue.x);
`;else if(o.length){let g=s-2,y=s-1;o.indexOf(g)>-1&&o.indexOf(y)>-1?h="return vec4(outputValue.x);":o.indexOf(g)>-1?h="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":o.indexOf(y)>-1&&(h="return vec4(outputValue.xx, outputValue.zz);")}return`
vec4 ${r}() {
${l} coords = getOutputCoords();
${p}
vec4 outputValue = get${n}(${d});
${h}
}
`}function wH(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=ft(l),p=Hv(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(f=>`coords.${h[f+c]} = 0;`).join(`
`);let m="";return l<2&&o>0?m="coords":m=e.shapeInfo.logicalShape.map((f,g)=>`coords.${h[g+c]}`).join(", "),`
float ${r}() {
${u} coords = getOutputCoords();
${d}
return get${n}(${m});
}
`}function ft(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 ${e} is not yet supported`)}function M3(e,t,a){let{newShape:n,keptDims:r}=v.squeezeShape(t),s=t.length,i=e&&s===3&&t[0]===1,o=i?t.slice(1):n,l=!e&&s>1&&!v.arraysEqual(t,a)&&n.length<s||i;return{useSqueezeShape:l,uniformShape:l?o:t,keptDims:r}}function Yu(e,t){let a=JSON.parse(JSON.stringify(e));return a.shapeInfo.logicalShape=t,a}function Zu(e,t){return t.map(a=>e[a]).join(", ")}function kH(e,t,a,n){let r=a.map((p,c)=>{let d={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(d.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[c],shapeInfo:d}}),s=r.map(p=>p.shapeInfo),i={logicalShape:n.shape,texShape:n.texData.texShape,isUniform:!1,isPacked:n.texData.isPacked,flatOffset:null},o=BG(r,i,t),l=kv(e.gl,o),u=e.createProgram(l);return B().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i,variablesLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:(e.buildVao(u),Object.assign({program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i},Xv(e,t,u)))}function Xv(e,t,a){let n=[],r=[],s,i,o,l=null,u=null;u=e.getUniformLocation(a,"NAN",!1),B().getNumber("WEBGL_VERSION")===1&&(l=e.getUniformLocation(a,"INFINITY",!1));let p=!1;for(let c of t.variableNames){let d={name:c,uniform:e.getUniformLocation(a,c,p),offset:e.getUniformLocation(a,`offset${c}`,p)};t.enableShapeUniforms&&(d.shape=e.getUniformLocation(a,`${c}Shape`,p),d.texShape=e.getUniformLocation(a,`${c}TexShape`,p)),n.push(d)}if(t.enableShapeUniforms&&(s=e.getUniformLocation(a,"outShape",p),o=e.getUniformLocation(a,"outShapeStrides",p),i=e.getUniformLocation(a,"outTexShape",p)),t.customUniforms)for(let c of t.customUniforms)r.push(e.getUniformLocation(a,c.name,p));return{variablesLocations:n,customUniformLocations:r,infLoc:l,nanLoc:u,outShapeLocation:s,outShapeStridesLocation:o,outTexShapeLocation:i}}function S5(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 IH(e,t,a,n,r){t.program.enableShapeUniforms||(S5(t.inShapeInfos,a),S5([t.outShapeInfo],[n]));let s=n.texData.texture,i=n.texData.texShape;n.texData.isPacked?e.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):e.setOutputMatrixTexture(s.texture,i[0],i[1]),e.setProgram(t.webGLProgram),e.bindVertexArray(t.webGLProgram.vao),B().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN);for(let l=0;l<a.length;++l){let u=a[l],{uniform:p,offset:c,shape:d,texShape:h}=t.variablesLocations[l];if(d){let{uniformShape:m}=M3(t.program.packedInputs,u.shape,u.texData.texShape);switch(m.length){case 1:e.gl.uniform1iv(d,new Int32Array(m));break;case 2:e.gl.uniform2iv(d,new Int32Array(m));break;case 3:e.gl.uniform3iv(d,new Int32Array(m));break;case 4:e.gl.uniform4iv(d,new Int32Array(m));break;default:break}}if(h&&e.gl.uniform2i(h,u.texData.texShape[0],u.texData.texShape[1]),p!=null){if(u.isUniform){if(v.sizeFromShape(u.shape)<2)e.gl.uniform1f(p,u.uniformValues[0]);else{let m=u.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),e.gl.uniform1fv(p,m)}continue}u.texData.slice!=null&&c!=null&&e.gl.uniform1i(c,u.texData.slice.flatOffset),e.setInputMatrixTexture(u.texData.texture.texture,p,l)}}let o=t.outShapeLocation;if(o)switch(n.shape.length){case 1:e.gl.uniform1iv(o,new Int32Array(n.shape));break;case 2:e.gl.uniform2iv(o,new Int32Array(n.shape));break;case 3:e.gl.uniform3iv(o,new Int32Array(n.shape));break;case 4:e.gl.uniform4iv(o,new Int32Array(n.shape));break;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}}if(t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,n.texData.texShape[0],n.texData.texShape[1]),t.program.customUniforms&&r)for(let l=0;l<t.program.customUniforms.length;++l){let u=t.program.customUniforms[l],p=t.customUniformLocations[l],c=r[l];if(u.type==="float")e.gl.uniform1fv(p,c);else if(u.type==="vec2")e.gl.uniform2fv(p,c);else if(u.type==="vec3")e.gl.uniform3fv(p,c);else if(u.type==="vec4")e.gl.uniform4fv(p,c);else if(u.type==="int")e.gl.uniform1iv(p,c);else if(u.type==="ivec2")e.gl.uniform2iv(p,c);else if(u.type==="ivec3")e.gl.uniform3iv(p,c);else if(u.type==="ivec4")e.gl.uniform4iv(p,c);else throw Error(`uniform type ${u.type} is not supported yet.`)}e.executeProgram()}function SH(e,t,a){let n="";t.concat(a).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!i.isUniform){let l=i.texData.texShape,{useSqueezeShape:u,uniformShape:p,keptDims:c}=M3(e.packedInputs,i.shape,l),d="",h="",m="";if(p.length===1&&e.packedInputs){let w=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];d=`${w[0]>1}_${w[1]>1}`}else if(p.length===2&&!e.packedInputs)h=`${p[0]>1}_${p[1]>1}`;else if(p.length>2&&!e.packedInputs){let w=v.computeStrides(p);m=`${w[0]===l[1]}_${w[w.length-1]===l[1]}`}let f=i.shape.length,g=p.length===2&&v.arraysEqual(i.shape,l),y=v.sizeFromShape(i.shape)===1,x=C.getBroadcastDims(i.shape,a.shape),A=!e.packedInputs&&f===a.shape.length&&v.arraysEqual(l,a.texData.texShape),b=e.packedInputs||p.length>2?"":`${l[0]>1}_${l[1]>1}`;n+=`${f}_${A}_${u?c:""}_${p.length}_${y}_${x}_${g}_${d}_${h}_${m}_${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+`${B().getNumber("WEBGL_VERSION")}`,s}function ga(e){return B().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var CH=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Qd.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=Ra();this.outputShape=e,this.enableShapeUniforms=ga(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?r0(["r","c","d"],e):rl(["r","c","d"],e)}
return ivec3(r, c, d);
}
void main() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);
vec4 result = vec4(0.);
for (int i=0; i<4; i++) {
int flatIndex = index + i;
ivec3 rc = outCoordsFromFlatIndex(flatIndex);
result[i] = getA(rc.x, rc.y, rc.z);
}
${t.output} = result;
}
`}},TH=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Qd.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=Ra();this.outputShape=e,this.enableShapeUniforms=ga(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?r0(["r","c","d"],e):rl(["r","c","d"],e)}
return ivec3(r, c, d);
}
void main() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);
vec4 result = vec4(0.);
for (int i=0; i<4; i++) {
int flatIndex = index + i;
ivec3 rc = outCoordsFromFlatIndex(flatIndex);
result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));
}
${t.output} = result;
}
`}},NH=class{constructor(e){this.variableNames=["A"],this.outTexUsage=mn.DOWNLOAD;let t=Ra();this.outputShape=e,this.userCode=`
${Gv}
void main() {
float x = getAAtOutCoords();
${t.output} = encode_float(x);
}
`}},RH=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=mn.DOWNLOAD;let t=Ra();this.outputShape=e,this.userCode=`
${Gv}
void main() {
ivec3 coords = getOutputCoords();
float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
${t.output} = encode_float(x);
}
`}},EH={R:0,G:1,B:2,A:3},C5=class{constructor(e,t=!1,a="RGBA"){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=Ra();this.outputShape=e,this.enableShapeUniforms=ga(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 == ${i}) {
result = values[${EH[o]}];
}`}this.userCode=`
${this.enableShapeUniforms?E3():R3(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.);
}
`}},MH=class{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let a=Ra();this.outputShape=e,this.enableShapeUniforms=ga(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?E3():R3(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};
}
`}},Kv={};Ze(Kv,{bindVertexProgramAttributeStreams:()=>r8,createBufferFromOutputTexture:()=>o8,createFloat16MatrixTexture:()=>e8,createFloat16PackedMatrixTexture:()=>n8,createFloat32MatrixTexture:()=>Qv,createIndexBuffer:()=>Jv,createPackedMatrixTexture:()=>a8,createUnsignedBytesMatrixTexture:()=>t8,createVertexBuffer:()=>Zv,createVertexShader:()=>Yv,downloadByteEncodedFloatMatrixFromOutputTexture:()=>u8,downloadFloat32MatrixFromBuffer:()=>l8,downloadMatrixFromPackedOutputTexture:()=>p8,downloadPackedMatrixFromBuffer:()=>d8,getInternalFormatForFloat16MatrixTexture:()=>P3,getInternalFormatForFloat16PackedMatrixTexture:()=>D3,getInternalFormatForFloat32MatrixTexture:()=>$3,getInternalFormatForPackedMatrixTexture:()=>F3,getInternalFormatForUnsignedBytesMatrixTexture:()=>_3,uploadDenseMatrixToTexture:()=>s8,uploadPixelDataToTexture:()=>i8});function Yv(e){let t=Ra(),a=`${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 wv(e,a)}function Zv(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 Cv(e,t)}function Jv(e){let t=new Uint16Array([0,1,2,2,1,3]);return Tv(e,t)}function Zp(e,t,a,n,r,s){Rv(t,a);let i=Nv(e),o=e.TEXTURE_2D;return ce(e,()=>e.bindTexture(o,i)),ce(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),ce(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),ce(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),ce(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),B().getNumber("WEBGL_VERSION")===1?ce(e,()=>e.texImage2D(o,0,n,t,a,0,r,s,null)):ce(e,()=>e.texStorage2D(o,1,n,t,a)),ce(e,()=>e.bindTexture(e.TEXTURE_2D,null)),{texture:i,texShape:[a,t]}}function $3(e){return e.internalFormatFloat}function Qv(e,t,a,n){let[r,s]=Yp(t,a);return Zp(e,r,s,$3(n),n.textureFormatFloat,e.FLOAT)}function P3(e){return e.internalFormatHalfFloat}function e8(e,t,a,n){let[r,s]=Yp(t,a);return Zp(e,r,s,P3(n),n.textureFormatFloat,n.textureTypeHalfFloat)}function _3(e){return e.downloadTextureFormat}function t8(e,t,a,n){let[r,s]=Yp(t,a);return Zp(e,r,s,_3(n),e.RGBA,e.UNSIGNED_BYTE)}function F3(e){return e.internalFormatPackedFloat}function a8(e,t,a,n){let[r,s]=ju(t,a);return Zp(e,r,s,F3(n),e.RGBA,e.FLOAT)}function D3(e){return e.internalFormatPackedHalfFloat}function n8(e,t,a,n){let[r,s]=ju(t,a);return Zp(e,r,s,D3(n),e.RGBA,n.textureTypeHalfFloat)}function r8(e,t,a){return ce(e,()=>e.bindBuffer(e.ARRAY_BUFFER,a)),F1(e,t,"clipSpacePos",a,3,20,0)&&F1(e,t,"uv",a,2,20,12)}function s8(e,t,a,n,r,s){ce(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),B().getNumber("WEBGL_VERSION")===2?ce(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,a,n,e.RGBA,o,i)):ce(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,a,n,0,e.RGBA,o,i)),ce(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function i8(e,t,a){ce(e,()=>e.bindTexture(e.TEXTURE_2D,t)),a.data instanceof Uint8Array?B().getNumber("WEBGL_VERSION")===2?ce(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,a.width,a.height,e.RGBA,e.UNSIGNED_BYTE,a.data)):ce(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,a.width,a.height,0,e.RGBA,e.UNSIGNED_BYTE,a.data)):B().getNumber("WEBGL_VERSION")===2?ce(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,a)):ce(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,a)),ce(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function o8(e,t,a,n){let r=e.createBuffer();ce(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,r));let s=4*4*t*a;return ce(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),ce(e,()=>e.readPixels(0,0,a,t,e.RGBA,e.FLOAT,0)),ce(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),r}function l8(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 u8(e,t,a,n){let[r,s]=Yp(t,a),i=4,o=new Uint8Array(TG(t*a,i));return ce(e,()=>e.readPixels(0,0,r,s,n.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function d8(e,t,a,n,r,s,i,o){let l=e,u=new Float32Array(NG(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 p8(e,t,a){let n=new Float32Array(t*a*4);return ce(e,()=>e.readPixels(0,0,a,t,e.RGBA,e.FLOAT,n)),n}var Hl=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.itemsToPoll=[];let t=B().getNumber("WEBGL_VERSION");if(e!=null?(this.gl=e,n0(t,e)):this.gl=Bn(t),e=this.gl,B().getNumber("WEBGL_VERSION")===2){let r=e;this.createVertexArray=()=>ce(r,()=>r.createVertexArray()),this.bindVertexArray=s=>ce(r,()=>r.bindVertexArray(s)),this.deleteVertexArray=s=>ce(r,()=>r.deleteVertexArray(s)),this.getVertexArray=()=>ce(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=()=>ce(e,()=>r.createVertexArrayOES()),this.bindVertexArray=s=>ce(e,()=>r.bindVertexArrayOES(s)),this.deleteVertexArray=s=>ce(e,()=>r.deleteVertexArrayOES(s)),this.getVertexArray=()=>ce(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"),B().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=Rd(this.gl,r),fn(this.gl,s))this.textureHalfFloatExtension=Rd(this.gl,s);else if(B().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),fn(this.gl,n))this.colorBufferHalfFloatExtension=Rd(this.gl,n);else if(B().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",fn(this.gl,a))this.colorBufferFloatExtension=this.gl.getExtension(a);else if(fn(this.gl,n))this.colorBufferHalfFloatExtension=this.gl.getExtension(n);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=Zv(this.gl),this.indexBuffer=Jv(this.gl),this.framebuffer=Ev(this.gl),this.textureConfig=T3(this.gl,this.textureHalfFloatExtension)}get debug(){return B().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),this.outputTexture!=null&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture. This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let e=this.gl;ce(e,()=>e.finish()),ce(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),ce(e,()=>e.deleteFramebuffer(this.framebuffer)),ce(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),ce(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),ce(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),Qv(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),e8(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),t8(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),i8(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,a,n){this.throwIfDisposed(),s8(this.gl,e,t,a,n,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),n8(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),a8(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(D1(this.gl,this.framebuffer),this.outputTexture=null),ce(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,a){return this.downloadMatrixDriver(e,()=>u8(this.gl,t,a,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,a,n,r,s){return d8(this.gl,e,t,a,n,r,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return l8(this.gl,e,t)}createBufferFromTexture(e,t,a){this.bindTextureToFrameBuffer(e);let n=o8(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(B().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 B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),a=()=>this.isQueryAvailable(t,B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):a=()=>!0;return{query:t,isFencePassed:a}}downloadMatrixFromPackedTexture(e,t,a){return this.downloadMatrixDriver(e,()=>p8(this.gl,t,a))}createProgram(e){this.throwIfDisposed();let t=this.gl;this.vertexShader==null&&(this.vertexShader=Yv(t));let a=Iv(t);ce(t,()=>t.attachShader(a,this.vertexShader)),ce(t,()=>t.attachShader(a,e)),Sv(t,a);let n=Object.assign(a,{vao:this.createVertexArray()});return this.debug&&nh(t,n),n}buildVao(e){this.setProgram(e),this.bindVertexArray(e.vao);let t=this.gl;ce(t,()=>t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,this.indexBuffer)),r8(t,e,this.vertexBuffer)}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&(ce(this.gl,()=>this.gl.deleteProgram(e)),this.deleteVertexArray(e.vao))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&nh(this.gl,this.program),ce(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,a=!0){return this.throwIfDisposed(),a?$v(this.gl,e,t):Pv(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),ce(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,a){this.throwIfDisposed(),this.throwIfNoProgram(),_v(this.gl,e,t,a)}setOutputMatrixTexture(e,t,a){this.setOutputMatrixTextureDriver(e,a,t)}setOutputPackedMatrixTexture(e,t,a){this.throwIfDisposed();let[n,r]=ju(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&&nh(this.gl,this.program),Ed(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;if(this.debug){let t=this.getVertexArray();console.assert(t===this.program.vao,"VAO changed between setProgram and executeProgram!"),this.debugValidate()}ce(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),ce(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=Rd(this.gl,B().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(B().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(B().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,B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,B().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=$H(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 B().platform&&(a=B().platform.setTimeoutCustom.bind(B().platform)),v.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0),()=>0,null,a)}bindTextureToFrameBuffer(e){this.throwIfDisposed(),rh(this.gl,e,this.framebuffer),this.debug&&Ed(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(rh(this.gl,this.outputTexture,this.framebuffer),this.debug&&Ed(this.gl)):D1(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;rh(n,e,this.framebuffer),this.debug&&Ed(n),this.outputTexture=e,ce(n,()=>n.viewport(0,0,t,a)),ce(n,()=>n.scissor(0,0,t,a))}setOutputMatrixWriteRegionDriver(e,t,a,n){this.throwIfDisposed(),ce(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 $H(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:PH,bincountImpl:c8,bincountReduceImpl:_H,bitwiseAndImpl:FH,castImpl:DH,ceilImpl:OH,concatImpl:zH,equalImpl:LH,expImpl:WH,expm1Impl:BH,floorImpl:VH,gatherNdImpl:UH,gatherV2Impl:GH,greaterImpl:HH,greaterEqualImpl:jH,lessImpl:qH,lessEqualImpl:XH,linSpaceImpl:KH,logImpl:YH,maxImpl:ZH,maximumImpl:JH,minimumImpl:QH,multiplyImpl:ej,negImpl:tj,notEqualImpl:aj,prodImpl:nj,raggedGatherImpl:rj,raggedRangeImpl:sj,raggedTensorToTensorImpl:ij,rangeImpl:oj,rsqrtImpl:lj,scatterImpl:uj,sigmoidImpl:dj,simpleAbsImpl:h8,sliceImpl:pj,sparseFillEmptyRowsImpl:cj,sparseReshapeImpl:hj,sparseSegmentReductionImpl:m8,sqrtImpl:mj,staticRegexReplaceImpl:fj,stridedSliceImpl:gj,stringNGramsImpl:yj,stringSplitImpl:xj,stringToHashBucketFastImpl:Aj,subImpl:bj,tileImpl:vj,topKImpl:wj,transposeImpl:O3,uniqueImpl:kj}=t0;function f8(e,t){return["x","y","z","w","u","v"].slice(0,t).map(a=>`${e}.${a}`)}function ka(e,t){return t===1?[e]:f8(e,t)}function Ij(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 Sj=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=ga(this.outputShape.length),this.rank===0)this.userCode=`
void main() {
setOutput(vec4(getA(), 0., 0., 0.));
}
`;else{let t=ka("rc",this.rank),a=ft(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]})`}},g8=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=ga(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=`
${Cj(t,this.enableShapeUniforms)}
${this.enableShapeUniforms?E3():R3(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 Cj(e,t){return`
ivec3 inputCoordsFromReshapedOutCoords(int index) {
${t?WG(["r","c","d"],"inputShape"):rl(["r","c","d"],e)}
return ivec3(r, c, d);
}
`}var Tj=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.usedTextures={},this.logEnabled=!1}acquireTexture(e,t,a){let n=N5(t,a),r=R5(e,n,a);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let s=T5(e,n,this.gpgpu.gl,this.gpgpu.textureConfig,a);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[r].pop();return this.usedTextures[r].push(o),o}let i;return n===da.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):n===da.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):n===da.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):n===da.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):n===da.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,a,n){if(this.freeTextures==null)return;let r=N5(a,n),s=R5(t,r,n);s in this.freeTextures||(this.freeTextures[s]=[]);let i=T5(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,n),o=B().getNumber("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l&&l.indexOf(e);if(u==null||u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l[u]=l[l.length-1],l.pop(),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function Nj(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 T5(e,t,a,n,r){let s=Rj(t,n),i;if(r){let[l,u]=ju(e[0],e[1]);i=l*u}else{let[l,u]=Yp(e[0],e[1]);i=l*u}let o=Nj(a,s);return i*o}function Rj(e,t){switch(e){case da.PACKED_2X2_FLOAT32:return F3(t);case da.PACKED_2X2_FLOAT16:return D3(t);case da.UNPACKED_FLOAT32:return $3(t);case da.UNPACKED_FLOAT16:return P3(t);case da.PACKED_4X1_UNSIGNED_BYTE:return _3(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function Ej(e){return B().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?da.PACKED_2X2_FLOAT32:da.UNPACKED_FLOAT32:e?da.PACKED_2X2_FLOAT16:da.UNPACKED_FLOAT16}function N5(e,t){if(e===mn.UPLOAD)return da.PACKED_2X2_FLOAT32;if(e===mn.RENDER||e==null)return Ej(t);if(e===mn.DOWNLOAD||e===mn.PIXELS)return da.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function R5(e,t,a){return`${e[0]}_${e[1]}_${t}_${a}`}var Zn=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=ga(this.outputShape.length),this.userCode=`
float unaryOperation(float x) {
${t}
}
void main() {
float x = getAAtOutCoords();
float y = unaryOperation(x);
setOutput(y);
}
`}},Mn="if (isnan(x)) return x;",Mj="return x;",E5="return abs(x);",$j="return (x >= 0.0) ? x : (exp(x) - 1.0);",Pj=Mn+`
return (x < 0.0) ? 0.0 : x;
`,_j=Mn+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,Vr="return x;",Fj="return 1.0 / (1.0 + exp(-1.0 * x));",Dj="return x;",Oj=`
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;
`,zj=`
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;
`,Lj=`
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;
`,Wj="return 1.0 / (1.0 + exp(-1.0 * x));",qr=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=ga(this.outputShape.length),this.userCode=`
vec4 unaryOperation(vec4 x) {
${t}
}
void main() {
vec4 x = getAAtOutCoords();
vec4 y = unaryOperation(x);
setOutput(y);
}
`}},Bj=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=ga(this.outputShape.length);let t=e.length,a=ka("rc",t),n=ft(t),r=Ij(t,a),s=a.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
void main() {
${n} rc = getOutputCoords();
vec4 packedInput = getA(${r});
setOutput(getChannel(packedInput, ${i}));
}
`}},Vj=En.whereImpl,Uj=1e-7,Gj=1e-4,J2={};function Hj(e){return e in J2||(J2[e]={}),J2[e]}var jj=B().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),qj=600;function Xj(){return B().global.screen==null?1024:B().global.screen.height*B().global.screen.width*window.devicePixelRatio*qj/1024/1024}var Jp=class y8 extends su{nextDataId(){return y8.nextDataId++}constructor(t){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!B().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let a;if(t!=null){if(t instanceof Hl)a=t;else{let n=Bn(B().getNumber("WEBGL_VERSION"),t);a=new Hl(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Bn(B().getNumber("WEBGL_VERSION"));a=new Hl(n),this.binaryCache=Hj(B().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=a,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new Tj(this.gpgpu),this.numMBBeforeWarning=Xj(),this.texData=new op(this,It())}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}writeTexture(t,a,n,r,s,i){let o=this.makeTensorInfo(a,n),l=this.texData.get(o.dataId);l.isPacked=!1,l.texture={texture:t,texShape:[r,s]},l.texShape=[r,s];let u=Md(a),p=new C5(u,!1,i),c=this.runWebGLProgram(p,[o],n,[[r,s]]);return c.shape=a,l.texture=null,this.disposeIntermediateTensorInfo(o),c.dataId}write(t,a,n){if((B().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||B().getBool("DEBUG"))&&this.checkNumericalProblems(t),n==="complex64"&&t!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let r={id:this.nextDataId()};return this.texData.set(r,{shape:a,dtype:n,values:t,usage:mn.UPLOAD,refCount:1}),r}refCount(t){return this.texData.has(t)?this.texData.get(t).refCount:0}incRef(t){let a=this.texData.get(t);a.refCount++}decRef(t){if(this.texData.has(t)){let a=this.texData.get(t);a.refCount--}}move(t,a,n,r,s){if(B().getBool("DEBUG")&&this.checkNumericalProblems(a),r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(t,{shape:n,dtype:r,values:a,usage:mn.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(t){this.disposeData(t.dataId)}readSync(t){let a=this.texData.get(t),{values:n,dtype:r,complexTensorInfos:s,slice:i,shape:o,isPacked:l}=a;if(i!=null){let d;l?d=new qr(o,Vr):d=new Zn(o,Vr);let h=this.runWebGLProgram(d,[{dataId:t,shape:o,dtype:r}],r),m=this.readSync(h.dataId);return this.disposeIntermediateTensorInfo(h),m}if(n!=null)return this.convertAndCacheOnCPU(t);if(r==="string")return n;let u=this.activeTimers!=null,p;u&&(p=v.now());let c;if(r==="complex64"){let d=this.readSync(s.real.dataId),h=this.readSync(s.imag.dataId);c=C.mergeRealAndImagArrays(d,h)}else c=this.getValuesFromTexture(t);return u&&(this.downloadWaitMs+=v.now()-p),this.convertAndCacheOnCPU(t,c)}async read(t){if(this.pendingRead.has(t)){let m=this.pendingRead.get(t);return new Promise(f=>m.push(f))}let a=this.texData.get(t),{values:n,shape:r,slice:s,dtype:i,complexTensorInfos:o,isPacked:l}=a;if(s!=null){let m;l?m=new qr(r,Vr):m=new Zn(r,Vr);let f=this.runWebGLProgram(m,[{dataId:t,shape:r,dtype:i}],i),g=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),g}if(n!=null)return this.convertAndCacheOnCPU(t);if(B().getBool("DEBUG")&&!B().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&B().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let u=null,p;if(i!=="complex64"&&B().get("WEBGL_BUFFER_SUPPORTED")){p=this.decode(t);let m=this.texData.get(p.dataId);u=this.gpgpu.createBufferFromTexture(m.texture.texture,...Zc(r))}this.pendingRead.set(t,[]),i!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(i==="complex64"){let m=await Promise.all([this.read(o.real.dataId),this.read(o.imag.dataId)]),f=m[0],g=m[1];c=C.mergeRealAndImagArrays(f,g)}else if(u==null)c=this.getValuesFromTexture(t);else{let m=v.sizeFromShape(r);c=this.gpgpu.downloadFloat32MatrixFromBuffer(u,m)}if(p!=null&&this.disposeIntermediateTensorInfo(p),u!=null){let m=this.gpgpu.gl;ce(m,()=>m.deleteBuffer(u))}let d=this.convertAndCacheOnCPU(t,c),h=this.pendingRead.get(t);return this.pendingRead.delete(t),h.forEach(m=>m(d)),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t)&&It().removeDataId(t,this),this.pendingDeletes--),d}readToGPU(t,a={}){let n=this.texData.get(t),{values:r,shape:s,slice:i,dtype:o,isPacked:l,texture:u}=n;if(o==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(i!=null){let h;l?h=new qr(s,Vr):h=new Zn(s,Vr);let m=this.runWebGLProgram(h,[{dataId:t,shape:s,dtype:o}],o),f=this.readToGPU(m,a);return this.disposeIntermediateTensorInfo(m),f}if(u==null)throw r!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let p=this.decode(t,a.customTexShape),c=It().makeTensorFromTensorInfo(p),d=this.texData.get(p.dataId);return Object.assign({tensorRef:c},d.texture)}bufferSync(t){let a=this.readSync(t.dataId);if(t.dtype==="string")try{let n=a.map(r=>v.decodeString(r));return _e(t.shape,t.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return _e(t.shape,t.dtype,a)}checkNumericalProblems(t){if(t!=null)for(let a=0;a<t.length;a++){let n=t[a];if(!bv(n))throw B().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(t){let{shape:a,dtype:n,isPacked:r}=this.texData.get(t),s=v.sizeFromShape(a);if(B().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let d=this.decode(t),h=this.texData.get(d.dataId),m=this.gpgpu.downloadMatrixFromPackedTexture(h.texture.texture,...Zc(a)).subarray(0,s);return this.disposeIntermediateTensorInfo(d),m}let i=B().getBool("WEBGL_PACK")&&r===!0,o=i?Md(a):a,l=i?new RH(o):new NH(o),u=this.runWebGLProgram(l,[{shape:o,dtype:n,dataId:t}],"float32"),p=this.texData.get(u.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(p.texture.texture,p.texShape[0],p.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(u),c}timerAvailable(){return B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(t){let a=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,t();let s=v.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),i=v.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=a,r&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let l=await Promise.all(s);o.kernelMs=v.sum(l),o.getExtraProfileInfo=()=>l.map((u,p)=>({name:i[p],ms:u})).map(u=>`${u.name}: ${u.ms}`).join(", ")}else o.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,o})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(t){return B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),t):(t.endMs=v.now(),t)}async getQueryTime(t){if(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(t);let a=t;return a.endMs-a.startMs}disposeData(t,a=!1){if(this.pendingDisposal.has(t))return!1;if(!this.texData.has(t))return!0;if(a?this.texData.get(t).refCount=0:this.texData.get(t).refCount--,!a&&this.texData.get(t).refCount>0)return!1;if(this.pendingRead.has(t))return this.pendingDisposal.add(t),this.pendingDeletes++,!1;this.releaseGPUData(t);let{complexTensorInfos:n}=this.texData.get(t);return n!=null&&(this.disposeData(n.real.dataId,a),this.disposeData(n.imag.dataId,a)),this.texData.delete(t),!0}releaseGPUData(t){let{texture:a,dtype:n,texShape:r,usage:s,isPacked:i,slice:o}=this.texData.get(t),l=o&&o.origDataId||t,u=this.dataRefCount.get(l);u>1?this.dataRefCount.set(l,u-1):(this.dataRefCount.delete(l),a!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(a,r,s,i)));let p=this.texData.get(t);p.texture=null,p.texShape=null,p.isPacked=!1,p.slice=null}getTexture(t){return this.uploadToGPU(t),this.texData.get(t).texture.texture}getDataInfo(t){return this.texData.get(t)}shouldExecuteOnCPU(t,a=jj){return B().getBool("WEBGL_CPU_FORWARD")&&t.every(n=>this.texData.get(n.dataId).texture==null&&v.sizeFromShape(n.shape)<a)}getGPGPUContext(){return this.gpgpu}where(t){C.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let a=t.dataSync();return Vj(t.shape,a)}packedUnaryOp(t,a,n){let r=new qr(t.shape,a),s=this.compileAndRun(r,[t],n);return It().makeTensorFromTensorInfo(s)}abs(t){if(this.shouldExecuteOnCPU([t])&&t.dtype!=="complex64"){let r=h8(this.texData.get(t.dataId).values);return this.makeOutput(t.shape,t.dtype,r)}if(B().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,E5,t.dtype);let a=new Zn(t.shape,E5),n=this.compileAndRun(a,[t]);return It().makeTensorFromTensorInfo(n)}makeTensorInfo(t,a,n){let r;if(a==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let s=n.map(i=>v.encodeString(i));r=this.write(s,t,a)}else r=this.write(n,t,a);return this.texData.get(r).usage=null,{dataId:r,shape:t,dtype:a}}makeOutput(t,a,n){return It().makeTensorFromTensorInfo(this.makeTensorInfo(t,a,n),this)}unpackTensor(t){let a=new Bj(t.shape);return this.runWebGLProgram(a,[t],t.dtype)}packTensor(t){let a=new Sj(t.shape);return this.runWebGLProgram(a,[t],t.dtype,null,!0)}packedReshape(t,a){let n=[ai(t.shape),...ni(t.shape)],r={dtype:t.dtype,shape:n,dataId:t.dataId},s=[ai(a),...ni(a)],i=new g8(s,n),o=!0,l=[n],u=this.runWebGLProgram(i,[r],t.dtype,l,o);return{dataId:u.dataId,shape:a,dtype:u.dtype}}decode(t,a){let n=this.texData.get(t),{isPacked:r,shape:s,dtype:i}=n;if(a!=null){let d=v.sizeFromShape(s),h=a[0]*a[1]*4;v.assert(d<=h,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let o=Md(s),l;r?l=new TH(o):l=new CH(o);let u=!0,p=[a!=null?a:Zc(o)],c=this.runWebGLProgram(l,[{shape:o,dtype:i,dataId:t}],i,p,u,a);return{dtype:i,shape:s,dataId:c.dataId}}runWebGLProgram(t,a,n,r,s=!1,i){let o=this.makeTensorInfo(t.outputShape,n),l=this.texData.get(o.dataId);if(t.packedOutput&&(l.isPacked=!0),t.outPackingScheme===Qd.DENSE){let y=i!=null?i:Zc(t.outputShape);l.texShape=y.map(x=>x*2)}if(t.outTexUsage!=null&&(l.usage=t.outTexUsage),v.sizeFromShape(o.shape)===0)return l.values=v.getTypedArrayFromDType(o.dtype,0),o;let u=[],p=a.map(y=>{if(y.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let x=this.texData.get(y.dataId);if(x.texture==null){if(!t.packedInputs&&v.sizeFromShape(y.shape)<=B().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:y.shape,texData:null,isUniform:!0,uniformValues:x.values};t.packedInputs&&(x.isPacked=!0,x.shape=y.shape)}if(this.uploadToGPU(y.dataId),!!x.isPacked!=!!t.packedInputs)y=x.isPacked?this.unpackTensor(y):this.packTensor(y),u.push(y),x=this.texData.get(y.dataId);else if(x.isPacked&&!ep(x.shape,y.shape)){let A=y,b=y.shape;y.shape=x.shape,y=this.packedReshape(y,b),u.push(y),x=this.texData.get(y.dataId),A.shape=b}return{shape:y.shape,texData:x,isUniform:!1}});this.uploadToGPU(o.dataId);let c={shape:o.shape,texData:l,isUniform:!1},d=SH(t,p,c),h=this.getAndSaveBinary(d,()=>kH(this.gpgpu,t,p,c)),m=this.activeTimers!=null,f;m&&(f=this.startTimer()),B().get("ENGINE_COMPILE_ONLY")||IH(this.gpgpu,h,p,c,r),u.forEach(y=>this.disposeIntermediateTensorInfo(y)),m&&(f=this.endTimer(f),this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime(f)}));let g=B().getNumber("WEBGL_FLUSH_THRESHOLD");if(g>0){let y=v.now();y-this.lastGlFlushTime>g&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=y)}if(!B().getBool("WEBGL_LAZILY_UNPACK")&&l.isPacked&&s===!1){let y=this.unpackTensor(o);return this.disposeIntermediateTensorInfo(o),y}return o}compileAndRun(t,a,n,r,s=!1){return n=n||a[0].dtype,this.runWebGLProgram(t,a,n,r,s)}getAndSaveBinary(t,a){return t in this.binaryCache||(this.binaryCache[t]=a()),this.binaryCache[t]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(B().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(t=>{this.gpgpu.deleteProgram(this.binaryCache[t].webGLProgram),delete this.binaryCache[t]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=De(()=>{if(!B().get("WEBGL_RENDER_FLOAT32_ENABLED")){let t=B().getBool("DEBUG");B().set("DEBUG",!1);let a=this.abs(Ge(1e-8)).dataSync()[0];if(B().set("DEBUG",t),a>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?Uj:Gj}uploadToGPU(t){let a=this.texData.get(t),{shape:n,dtype:r,values:s,texture:i,usage:o,isPacked:l}=a;if(i!=null)return;let u=this.activeTimers!=null,p;u&&(p=v.now());let c=a.texShape;if(c==null&&(c=Ov(n,l),a.texShape=c),s!=null){let d=Md(n),h,m=c[1],f=c[0],g=s instanceof Uint8Array||s instanceof Uint8ClampedArray;(l||!g)&&([m,f]=ju(c[0],c[1])),l?h=new MH(d,g):h=new C5(d,g);let y=g?[f,m]:c,x=this.makeTensorInfo(y,r),A=this.texData.get(x.dataId);g?A.usage=mn.PIXELS:A.usage=mn.UPLOAD,A.texShape=y,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(x.dataId),m,f,s);let b=[[f,m]],w=this.runWebGLProgram(h,[x],r,b,!0),I=this.texData.get(w.dataId);a.texShape=I.texShape,a.isPacked=I.isPacked,a.usage=I.usage,B().get("ENGINE_COMPILE_ONLY")?this.disposeData(w.dataId):(a.texture=I.texture,a.values=null,this.texData.delete(w.dataId)),this.disposeIntermediateTensorInfo(x),u&&(this.uploadWaitMs+=v.now()-p)}else{let d=this.acquireTexture(c,o,r,l);a.texture=d}}convertAndCacheOnCPU(t,a){let n=this.texData.get(t),{dtype:r}=n;return a!=null&&(n.values=Kj(a,r)),n.values}acquireTexture(t,a,n,r){if(this.numBytesInGPU+=this.computeBytes(t,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let s=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${s} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(t,a,r)}computeBytes(t,a){return t[0]*t[1]*v.bytesPerElement(a)}checkCompileCompletion(){for(let[,t]of Object.entries(this.binaryCache))this.checkCompletion_(t)}async checkCompileCompletionAsync(){let t=[];if(this.gpgpu.parallelCompilationExtension){for(let[,a]of Object.entries(this.binaryCache))t.push(this.checkCompletionAsync_(a));return Promise.all(t)}else{for(let[,a]of Object.entries(this.binaryCache)){let n=new Promise(r=>{try{this.checkCompletion_(a),r(!0)}catch(s){throw s}});t.push(n)}return Promise.all(t)}}async checkCompletionAsync_(t){return this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(t):(await G7(),this.checkCompletionAsync_(t))}checkCompletion_(t){if(this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(t.webGLProgram)),this.gpgpu.gl.getShaderParameter(t.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(N3(t.source,this.gpgpu.gl.getShaderInfoLog(t.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let t of Object.values(this.binaryCache)){this.gpgpu.buildVao(t.webGLProgram);let{variablesLocations:a,customUniformLocations:n,infLoc:r,nanLoc:s,outShapeLocation:i,outShapeStridesLocation:o,outTexShapeLocation:l}=Xv(this.gpgpu,t.program,t.webGLProgram);t.variablesLocations=a,t.customUniformLocations=n,t.infLoc=r,t.nanLoc=s,t.outShapeLocation=i,t.outShapeStridesLocation=o,t.outTexShapeLocation=l}}createTensorFromGPUData(t,a,n){t.channels=t.channels||"RGBA";let{texture:r,height:s,width:i,channels:o}=t,l=It().backend;if(!l.gpgpu.gl.isTexture(r))throw new Error("The texture is invalid. Also, please make sure the texture and the TFJS WebGL backend are using the same canvas. If you want to use your own custom canvas, you have to create and use the custom TFJS WebGL backend created from the canvas through 'new tf.MathBackendWebGL(customCanvas)'.");let u=l.writeTexture(r,a,n,s,i,o);return It().makeTensorFromDataId(u,a,n,l)}};Jp.nextDataId=0;function Kj(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 Yj="4.21.0";function x8(){B().set("WEBGL_FORCE_F16_TEXTURES",!0)}Fp.isBrowser()&&al("webgl",()=>new Jp,2);var Zj={forceHalfFloat:x8},z3=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,ri=class{constructor(e,t,a){this.variableNames=["A","B"],this.outputShape=C.assertAndGetBroadcastShape(t,a),this.enableShapeUniforms=ga(this.outputShape.length),this.userCode=`
float binaryOperation(float a, float b) {
${e}
}
void main() {
float a = getAAtOutCoords();
float b = getBAtOutCoords();
setOutput(binaryOperation(a, b));
}
`}},il=`
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;
`,Ju=class{constructor(e,t,a,n=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=C.assertAndGetBroadcastShape(t,a);let r=this.outputShape.length;this.enableShapeUniforms=ga(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=`
${ft(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) >= ${this.outputShape[0]} ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`;else{let i=ka("coords",r);this.enableShapeUniforms?s+=`
bool nextRowOutOfBounds =
(${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 en(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 Jj={kernelName:qi,backendName:"webgl",kernelFunc:en};function fs(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=en({inputs:{x:n},backend:a}),l=en({inputs:{x:r},backend:a});return i.complexTensorInfos={real:o,imag:l},s}var Qj={kernelName:cp,backendName:"webgl",kernelFunc:fs},A8="return (a < 0.) ? b * a : a;",b8=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function eq(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{alpha:s}=n,i=a.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ju(b8,r.shape,i.shape):new ri(A8,r.shape,i.shape),l=a.runWebGLProgram(o,[r,i],"float32");return a.disposeIntermediateTensorInfo(i),l}var tq={kernelName:Zi,backendName:"webgl",kernelFunc:eq},v8="return (a < 0.) ? b * a : a;",w8=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function aq(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t,s=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ju(w8,n.shape,r.shape):new ri(v8,n.shape,r.shape);return a.runWebGLProgram(s,[n,r],"float32")}var nq={kernelName:Io,backendName:"webgl",kernelFunc:aq},Qu="if (isnan(x)) return x;";function tt({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=B().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,p;return u?p=new qr(i.shape,t):p=new Zn(i.shape,e),o.runWebGLProgram(p,[i],l)}}function ha({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 m=p.texData.get(l.dataId),f=p.texData.get(u.dataId),[g,y]=[[m.complexTensorInfos.real,f.complexTensorInfos.real],[m.complexTensorInfos.imag,f.complexTensorInfos.imag]].map(A=>{let[b,w]=A,I={dataId:b.dataId,dtype:b.dtype,shape:l.shape},T={dataId:w.dataId,dtype:w.dtype,shape:u.shape},N=new ri(e,l.shape,u.shape);return p.runWebGLProgram(N,[I,T],pa(b.dtype,w.dtype))}),x=fs({inputs:{real:g,imag:y},backend:p});return p.disposeIntermediateTensorInfo(g),p.disposeIntermediateTensorInfo(y),x}let c=s||pa(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||p.shouldExecuteOnCPU([l,u]))&&r!=null){let m=p.texData.get(l.dataId).values,f=p.texData.get(u.dataId).values,g=l.dtype==="string"?C.fromUint8ToStringArray(m):m,y=l.dtype==="string"?C.fromUint8ToStringArray(f):f,[x,A]=r(l.shape,u.shape,g,y,c),b=p.makeTensorInfo(A,c),w=p.texData.get(b.dataId);return w.values=x,b}let d=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,h;return d?h=new Ju(t,l.shape,u.shape,a):h=new ri(e,l.shape,u.shape),p.runWebGLProgram(h,[l,u],c)}}function tp(e,t=!1){if(e==="linear")return t?Dj:Mj;if(e==="relu")return t?zj:Pj;if(e==="elu")return t?Oj:$j;if(e==="relu6")return t?Lj:_j;if(e==="prelu")return t?w8:v8;if(e==="leakyrelu")return t?b8:A8;if(e==="sigmoid")return t?Wj:Fj;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var k8=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=ga(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"],m=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],f="",g="";i&&(o?f=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${i}
}`:l?f=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${i}
}`:f=`vec4 activation(vec4 x) {
${i}
}`,g="result = activation(result);");let y=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let x="rc.x",A="rc.x";e[0]<t[0]?x=`imod(rc.x, ${e[0]})`:t[0]<e[0]&&(A=`imod(rc.x, ${t[0]})`),this.userCode=`
${f}
// Don't use uniform for sharedDimensionPacked for performance.
const float sharedDimension = ${p}.0;
vec4 dot2x2ARowBCol(ivec3 rc) {
vec4 result = vec4(0);
int batchA = ${x};
int batchB = ${A};
for (int i = 0; i < ${p}; i++) {
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]} * ${m[0]});
result += (${h[1]} * ${m[1]});
}
return result;
}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = dot2x2ARowBCol(rc);
${y}
${g}
setOutput(result);
}
`}},M5={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},$5=class{constructor(e,t,a){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=C.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));
}
`}},P5="return a * b;";function L3(e){let{inputs:t,backend:a}=e,{a:n,b:r}=t,s=C.upcastType(n.dtype,r.dtype);if(n.dtype==="complex64"){let o=a.texData.get(n.dataId),l=a.texData.get(r.dataId),u=new $5(M5.REAL,n.shape,r.shape),p=new $5(M5.IMAG,n.shape,r.shape),c=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:n.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:n.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:r.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:r.shape}],d=a.runWebGLProgram(u,c,"float32"),h=a.runWebGLProgram(p,c,"float32"),m=fs({inputs:{real:d,imag:h},backend:a});return a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),m}if(a.shouldExecuteOnCPU([n,r])){let o=a.texData.get(n.dataId),l=a.texData.get(r.dataId),[u,p]=ej(n.shape,r.shape,o.values,l.values,s),c=a.makeTensorInfo(p,s),d=a.texData.get(c.dataId);return d.values=u,c}let i;return B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new Ju(P5,n.shape,r.shape):i=new ri(P5,n.shape,r.shape),a.runWebGLProgram(i,[n,r],s)}var rq={kernelName:yo,backendName:"webgl",kernelFunc:L3};function sq(e,t,a){let n=[ai(e.shape),...ni(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},s=[ai(t),...ni(t)],i=new g8(s,n),o=!0,l=[n],u=a.runWebGLProgram(i,[r],e.dtype,l,o);return{dataId:u.dataId,shape:t,dtype:u.dtype}}function pe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{shape:s}=n,i=a,o=v.sizeFromShape(r.shape),l=v.inferFromImplicitShape(s,o),u=v.sizeFromShape(l);v.assert(o===u,()=>`The new shape (${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&&!ep(r.shape,l)&&!(p.texture!==null&&ep(p.shape,l))?sq(r,l,i):(i.incRef(r.dataId),{dataId:r.dataId,shape:l,dtype:r.dtype})}var iq={kernelName:Eu,backendName:"webgl",kernelFunc:pe},_5=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);
${l}
}
setOutput(sumValue);
}
`}},oq=class{constructor(e,t){this.variableNames=["x"];let{windowSize:a,batchSize:n,inSize:r,outSize:s}=e;this.outputShape=[n,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${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 lq(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=C.computeOptimalWindowSize(a);t.push({inSize:a,windowSize:n,outSize:Math.ceil(a/n)})}return t}function ol(e,t,a,n){let r=lq(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 _5({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},o):new _5({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u}):p=new oq({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 uq=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=ft(this.rank),r=dq(t);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
setOutput(getA(${r}));
}
`}};function dq(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 pq=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 ${this.rank} is not yet supported.`);let n=ft(this.rank),r=f8("rc",this.rank),s=new Array(this.rank);for(let u=0;u<t.length;u++)s[t[u]]=r[u];let i=`vec2(${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] = ${l};
}
}
setOutput(result);
}
`}};function s0(e,t,a){let n=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new pq(e.shape,t):new uq(e.shape,t);return a.runWebGLProgram(n,[e],e.dtype)}function cq(e,t,a,n){let r=t,s=e.shape.length,i=v.parseAxisParam(r,e.shape),o=i,l=C.getAxesPermutation(o,s),u=l!=null,p=e;u&&(p=s0(e,l,n),o=C.getInnerMostAxes(o.length,s)),C.assertAxesAreInnerMostDims("sum",o,s);let[c,d]=C.computeOutAndReduceShapes(p.shape,o),h=c;a&&(h=C.expandShapeToKeepDim(c,i));let m=v.sizeFromShape(d),f=v.sizeFromShape(e.shape)/m,g=pe({inputs:{x:p},attrs:{shape:[f,m]},backend:n}),y=_p(e.dtype),x=ol(g,y,"sum",n),A=pe({inputs:{x},attrs:{shape:h},backend:n});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(x),u&&n.disposeIntermediateTensorInfo(p),A}function i0(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return cq(r,s,i,a)}var hq={kernelName:Go,backendName:"webgl",kernelFunc:i0};function Ca(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{perm:s}=n,i=a,o=r.shape.length,l=new Array(o);for(let p=0;p<l.length;p++)l[p]=r.shape[s[p]];let u;if(i.shouldExecuteOnCPU([r])){let p=i.texData.get(r.dataId).values,c=O3(p,r.shape,r.dtype,s,l);u=i.makeTensorInfo(l,r.dtype);let d=i.texData.get(u.dataId);d.values=c}else u=s0(r,s,i);return u}var mq={kernelName:kr,backendName:"webgl",kernelFunc:Ca},I8=1e3;function kh({a:e,b:t,transposeA:a,transposeB:n,backend:r,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,p=t.shape.length,c=a?e.shape[u-2]:e.shape[u-1],d=n?t.shape[p-1]:t.shape[p-2],h=a?e.shape[u-1]:e.shape[u-2],m=n?t.shape[p-2]:t.shape[p-1],f=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(f),x=v.sizeFromShape(g),A=nl.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,m]);v.assert(c===d,()=>`Error in matMul: inner shapes (${c}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${a} and transposeB=${n} must match.`);let b=a?[y,c,h]:[y,h,c],w=n?[x,m,d]:[x,d,m],I=pe({inputs:{x:e},backend:r,attrs:{shape:b}}),T=pe({inputs:{x:t},backend:r,attrs:{shape:w}}),N=[I,T],M=Math.max(y,x),$=a?I.shape[1]:I.shape[2],E=s!=null,S=i!=null,_=l==="leakyrelu",O=l!=null?tp(l,!0):null,W=E||S||_||O!=null,P;if((h===1||m===1)&&$>I8&&W===!1){let G=I,q=T;a&&(G=Ca({inputs:{x:I},backend:r,attrs:{perm:[0,2,1]}}),N.push(G)),n&&(q=Ca({inputs:{x:T},backend:r,attrs:{perm:[0,2,1]}}),N.push(q));let H=m!==1,V=m===1,Z=G;H&&(Z=pe({inputs:{x:G},backend:r,attrs:{shape:[M,$,1]}}),N.push(Z));let X=m===1?2:1,re=q;V&&(re=pe({inputs:{x:q},backend:r,attrs:{shape:[M,1,$]}}),N.push(re));let ee=L3({inputs:{a:Z,b:re},backend:r});P=i0({inputs:{x:ee},backend:r,attrs:{axis:X,keepDims:!0}}),N.push(ee)}else{let G=pa(e.dtype,t.dtype),q=new k8(b,w,[M,h,m],a,n,E,O,S,_),H=[I,T];if(s!=null&&H.push(s),S&&H.push(i),_){let V=r.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));H.push(V),N.push(V)}P=r.runWebGLProgram(q,H,G)}let U=pe({inputs:{x:P},backend:r,attrs:{shape:A}});N.push(P);for(let G of N)r.disposeIntermediateTensorInfo(G);return U}function fq(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:c}=n;return kh({a:r,b:s,transposeA:l,transposeB:u,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:c,activation:p})}var gq={kernelName:Zr,backendName:"webgl",kernelFunc:fq},F5="return abs(x);";function yq(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])&&n.dtype!=="complex64"){let s=a.texData.get(n.dataId),i=h8(s.values);return a.makeTensorInfo(n.shape,n.dtype,i)}let r;return B().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new qr(n.shape,F5):r=new Zn(n.shape,F5),a.runWebGLProgram(r,[n],n.dtype)}var xq={kernelName:ou,backendName:"webgl",kernelFunc:yq},Aq=Mn+`
if (abs(x) > 1.) {
return NAN;
}
return acos(x);
`,bq=tt({opSnippet:Aq}),vq={kernelName:oi,backendName:"webgl",kernelFunc:bq},wq=Mn+`
if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,kq=tt({opSnippet:wq}),Iq={kernelName:li,backendName:"webgl",kernelFunc:kq},D5="return a + b;",Sq=ha({opSnippet:D5,packedOpSnippet:D5,supportsComplex:!0,cpuKernelImpl:PH}),Cq={kernelName:ls,backendName:"webgl",kernelFunc:Sq},Tq=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((r,s)=>`T${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 = ${n};
setOutput(result);
}
`}},Nq=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((r,s)=>`T${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 oh(e){let{inputs:t,backend:a}=e,n=t;if(n.length===1)return en({inputs:{x:n[0]},backend:a});if(n.length>B().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(n.length/2),l=oh({inputs:n.slice(0,o),backend:a}),u=oh({inputs:n.slice(o),backend:a});return oh({inputs:[l,u],backend:a})}let r=n.map(o=>o.dtype).reduce((o,l)=>pa(o,l)),s=n.map(o=>o.shape),i=B().getBool("WEBGL_PACK")?new Nq(n[0].shape,s):new Tq(n[0].shape,s);return a.runWebGLProgram(i,n,r)}var Rq={kernelName:ui,backendName:"webgl",kernelFunc:oh};function Eq(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=C.getAxesPermutation(u,o),c=r;p!=null&&(c=Ca({inputs:{x:r},backend:a,attrs:{perm:p}}),u=C.getInnerMostAxes(u.length,o)),C.assertAxesAreInnerMostDims("all",u,o);let[d,h]=C.computeOutAndReduceShapes(c.shape,u),m=v.sizeFromShape(h),f=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,m]}}),g=ol(f,f.dtype,"all",a),y;if(i){let x=C.expandShapeToKeepDim(d,l);y=pe({inputs:{x:g},backend:a,attrs:{shape:x}})}else y=pe({inputs:{x:g},backend:a,attrs:{shape:d}});return a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(g),p!=null&&a.disposeIntermediateTensorInfo(c),y}var Mq={kernelName:di,backendName:"webgl",kernelFunc:Eq};function $q(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=C.getAxesPermutation(u,o),c=r;p!=null&&(c=Ca({inputs:{x:r},backend:a,attrs:{perm:p}}),u=C.getInnerMostAxes(u.length,o)),C.assertAxesAreInnerMostDims("any",u,o);let[d,h]=C.computeOutAndReduceShapes(c.shape,u),m=v.sizeFromShape(h),f=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,m]}}),g=ol(f,f.dtype,"any",a),y;if(i){let x=C.expandShapeToKeepDim(d,l);y=pe({inputs:{x:g},backend:a,attrs:{shape:x}})}else y=pe({inputs:{x:g},backend:a,attrs:{shape:d}});return a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(g),p!=null&&a.disposeIntermediateTensorInfo(c),y}var Pq={kernelName:pi,backendName:"webgl",kernelFunc:$q},_q=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 ${i} bestValue) {
bestValue = candidate;
bestIndex = inIdx;
}
}
setOutput(float(bestIndex));
}
`}},Fq=class{constructor(e,t,a,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${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=ft(o),u=ka("coords",o),p,c;if(s===1){c=o+1;let T=ft(c);p=`
${T} sourceLocR = ${T}(${u.join()}, 0);
++${u[o-1]};
${T} sourceLocG = ${T}(${u.join()}, 0);
++${u[o-2]};
${T} sourceLocA = ${T}(${u.join()}, 0);
--${u[o-1]};
${T} sourceLocB = ${T}(${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],m=d.map(T=>"int "+T),f=ka("sourceLocR",c-1).concat("inIdx.r"),g=ka("sourceLocG",c-1).concat("inIdx.g"),y=ka("sourceLocB",c-1).concat("inIdx.b"),x=ka("sourceLocA",c-1).concat("inIdx.a"),A=a==="max"?"greaterThan":"lessThan",b=n?"":`
inIdx = round(vec4(getBestIndicesAChannel(${f.join()}),
getBestIndicesAChannel(${g.join()}),
getBestIndicesAChannel(${y.join()}),
getBestIndicesAChannel(${x.join()})));`,w=`vec4(
getAChannel(${f.join()}),
hasNextCol ? getAChannel(${g.join()}) : 0.,
hasNextRow ? getAChannel(${y.join()}) : 0.,
hasNextRow && hasNextCol ? getAChannel(${x.join()}) : 0.)`,I=n?"":`
float getBestIndicesAChannel(${m.join()}) {
return getChannel(getBestIndicesA(${d.join()}),
vec2(${d.slice(-2).join()}));
}`;this.userCode=`
float getAChannel(${m.join()}) {
return getChannel(getA(${d.join()}),
vec2(${d.slice(-2).join()}));
}
${I}
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 = ${w};
bvec4 nan = isnan(candidate);
bvec4 replace = bvec4(
vec4(${A}(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 S8(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=C.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:r,outSize:Math.ceil(s/i)},l=new _q(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=S8(e,t,a,p);return e.disposeIntermediateTensorInfo(p),c}function C8(e,t,a,n=null){let r=n!=null?n.shape:t.shape,s=r[r.length-1],i=C.computeOptimalWindowSize(s),o=new Fq(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=C8(e,t,a,u);return e.disposeIntermediateTensorInfo(u),p}return u}function T8(e,t,a,n){let r=[a];if(C.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),r,t.shape.length),!B().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]=C.computeOutAndReduceShapes(l.shape,r),c=v.sizeFromShape(p),d=pe({inputs:{x:l},backend:e,attrs:{shape:[-1,c]}});s.push(d);let h=S8(e,d,n);s.push(h);let m=pe({inputs:{x:h},backend:e,attrs:{shape:u}});return s.forEach(f=>e.disposeIntermediateTensorInfo(f)),m}return C8(e,t,n)}function Dq(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=C.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Ca({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let p=T8(a,l,i[0],"max");return u.forEach(c=>a.disposeIntermediateTensorInfo(c)),p}var Oq={kernelName:lu,backendName:"webgl",kernelFunc:Dq};function zq(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=C.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Ca({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let p=T8(a,l,i[0],"min");return u.forEach(c=>a.disposeIntermediateTensorInfo(c)),p}var Lq={kernelName:uu,backendName:"webgl",kernelFunc:zq},Wq=Mn+`
if (abs(x) > 1.) {
return NAN;
}
return asin(x);
`,Bq=tt({opSnippet:Wq}),Vq={kernelName:ci,backendName:"webgl",kernelFunc:Bq},Uq=Mn+"return log(x + sqrt(x * x + 1.0));",Gq=tt({opSnippet:Uq}),Hq={kernelName:hi,backendName:"webgl",kernelFunc:Gq},jq=Mn+`
return atan(x);
`,qq=tt({opSnippet:jq}),Xq={kernelName:mi,backendName:"webgl",kernelFunc:qq},Kq=z3+`
return atan(a, b);
`,Yq=`
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);
`+il+`
return result;
`,Zq=ha({opSnippet:Kq,packedOpSnippet:Yq}),Jq={kernelName:gi,backendName:"webgl",kernelFunc:Zq},Qq=Mn+`
if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,eX=tt({opSnippet:Qq}),tX={kernelName:fi,backendName:"webgl",kernelFunc:eX},ap=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 m=t==="avg",f=`((batch * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(m||(y="-1.0 / 1e-20"),a){let T=">=";this.userCode=`
const ivec2 strides = ivec2(${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 ${T} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${n?r?f:g:`wR * ${c} + wC`};
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let x="max",A=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(A="avgValue / max(count, 1.0)");let b=Math.floor(s/4)*4,w=s%4,I=`
if (${m}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${x}(values, minMaxValue);
}
`;this.userCode=`
const ivec2 strides = ivec2(${i}, ${o});
const ivec2 pads = ivec2(${d}, ${h});
const float initializationValue = ${y};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float count = 0.0;
float getValue(int batch, int xR, int xC, int d) {
if (xC < 0 || xC >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xR, xC, d);
}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
vec4 minMaxValue = vec4(${y});
float avgValue = 0.0;
count = 0.0;
for (int wR = 0; wR < ${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)
);
${I}
}
int xC = xCCorner + ${b};
if (${w===1}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
initializationValue,
initializationValue,
initializationValue
);
${I}
} else if (${w===2}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${u}, d),
initializationValue,
initializationValue
);
${I}
} else if (${w===3}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${u}, d),
getValue(batch, xR, xC + 2 * ${u}, d),
initializationValue
);
${I}
}
}
setOutput(${A});
}
`}},W3=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,m=e.effectiveFilterWidth,f=e.padInfo.front,g=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let x=t==="avg",A="0.0";if(x||(A="-1.0 / 1e-20"),a){let M=">=";this.userCode=`
const ivec3 strides =
ivec3(${i}, ${o}, ${l});
const ivec3 pads = ivec3(${f}, ${g}, ${y});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xDCorner = xCorner.x;
int xRCorner = xCorner.y;
int xCCorner = xCorner.z;
// max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).
// ? = to be determined
float minMaxValue = 0.0;
float minMaxValueFound = 0.0;
int minMaxPosition = 0;
for (int wD = 0; wD < ${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 < ${m};
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 ${M} 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} * ${m} +
wR * ${m} + wC`};
}
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let b="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / max(count, 1.0)");let I=Math.floor(s/4)*4,T=s%4,N=`
if (${x}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${b}(values, minMaxValue);
}
`;this.userCode=`
const ivec3 strides =
ivec3(${i}, ${o}, ${l});
const ivec3 pads = ivec3(${f}, ${g}, ${y});
const float initializationValue = ${A};
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 >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xD, xR, xC, ch);
}
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xDCorner = xCorner.x;
int xRCorner = xCorner.y;
int xCCorner = xCorner.z;
// max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
// ? = to be determined
vec4 minMaxValue = vec4(${A});
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 < ${I}; 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)
);
${N}
}
int xC = xCCorner + ${I};
if (${T===1}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
initializationValue,
initializationValue,
initializationValue
);
${N}
} else if (${T===2}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${c}, ch),
initializationValue,
initializationValue
);
${N}
} else if (${T===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
);
${N}
}
}
}
setOutput(${w});
}
`}};function aX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;qu(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(C.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=C.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))return en({inputs:{x:r},backend:a});let c=new ap(p,"avg",!1);return a.runWebGLProgram(c,[r],"float32")}var nX={kernelName:yi,backendName:"webgl",kernelFunc:aX};function rX(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=C.computePool3DInfo(r.shape,s,i,p,o,l,u),d=new W3(c,"avg",!1);return a.runWebGLProgram(d,[r],"float32")}var sX={kernelName:du,backendName:"webgl",kernelFunc:rX},iX=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 >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
dotProd += dyValue * avgMultiplier;
}
}
setOutput(dotProd);
}
`}},oX=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,a=e.filterHeight,n=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterDepth,c=e.effectiveFilterHeight,d=e.effectiveFilterWidth,h=p-1-e.padInfo.front,m=c-1-e.padInfo.top,f=d-1-e.padInfo.left,g=1/(t*a*n);this.userCode=`
const ivec3 pads = ivec3(${h}, ${m}, ${f});
const float avgMultiplier = float(${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 lX(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=C.computePool3DInfo(i.shape,o,l,c,u,p),h=new oX(d);return a.runWebGLProgram(h,[r],i.dtype)}var uX={kernelName:pp,backendName:"webgl",kernelFunc:lX};function dX(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s;qu([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,p=C.computePool2DInfo(i.shape,o,l,1,u),c=new iX(p);return a.runWebGLProgram(c,[r],i.dtype)}var pX={kernelName:dp,backendName:"webgl",kernelFunc:dX};function cX(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;return kh({a:r,b:s,transposeA:i,transposeB:o,backend:a})}var hX={kernelName:xi,backendName:"webgl",kernelFunc:cX},mX=class{constructor(e,t,a,n,r,s){this.outputShape=[],this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,a);let i="0.0";n!=null&&(C.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";r!=null&&(C.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)));
}
`}},fX=class{constructor(e,t,a,n,r,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,a);let i="vec4(0.0)";n!=null&&(C.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";r!=null&&(C.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);
}
`}},gX=({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=B().getBool("WEBGL_PACK_NORMALIZATION")?new fX(n.shape,r.shape,s.shape,p,c,l):new mX(n.shape,r.shape,s.shape,p,c,l);return t.runWebGLProgram(d,u,u[0].dtype)},yX={kernelName:Ui,backendName:"webgl",kernelFunc:gX},xX=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ft(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let a=AX(this.rank),n,r=e.map((s,i)=>`sourceLoc.${L1[i]} = start[${i}] + coords.${L1[i]};`);n=`
${t} sourceLoc;
${t} coords = getOutputCoords();
${r.join(`
`)}
`,this.userCode=`
void main() {
${n}
setOutput(getSource(${a}));
}
`}},L1=["x","y","z","w","u","v"];function AX(e){if(e===1)return"sourceLoc";if(e<=6)return L1.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var bX=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=ft(this.rank),a=ka("coords",this.rank),n=ka("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${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 vX(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=Nt.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 ed(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,size:i}=n,[o,l]=Nt.parseSliceParams(r,s,i);if(Nt.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=pj(c.values,o,l,r.shape,r.dtype);return a.makeTensorInfo(l,r.dtype,d)}let{isPacked:u}=a.texData.get(r.dataId),p=Nt.isSliceContinous(r.shape,o,l);if(u||!p){let c=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new bX(l):new xX(l),d=[o];return a.runWebGLProgram(c,[r],r.dtype,d)}return a.uploadToGPU(r.dataId),vX(r,o,l,a)}var wX={kernelName:_u,backendName:"webgl",kernelFunc:ed},kX=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((x,A)=>x*A),l=C.getReshaped(r.shape,s,o),u=C.getPermuted(l.length,s.length),p=C.getReshapedPermuted(r.shape,s,o),c=C.getSliceBeginCoords(i,s.length),d=C.getSliceSize(p,i,s.length),h=[],m=pe({inputs:{x:r},backend:a,attrs:{shape:l}}),f=Ca({inputs:{x:m},backend:a,attrs:{perm:u}}),g=pe({inputs:{x:f},backend:a,attrs:{shape:p}}),y=ed({inputs:{x:g},backend:a,attrs:{begin:c,size:d}});return h.push(m),h.push(f),h.push(g),h.forEach(x=>a.disposeIntermediateTensorInfo(x)),y},IX={kernelName:pu,backendName:"webgl",kernelFunc:kX};function SX(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=c8(o,l,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,u)}var CX={kernelName:Ai,backendName:"webgl",kernelFunc:SX},TX=`
int r = int(a.r) & int(b.r);
int g = int(a.g) & int(b.g);
int rb = int(a.b) & int(b.b);
int ra = int(a.a) & int(b.a);
return vec4(r, g, rb, ra);
`,NX=`
return float(int(a.r) & int(b.r));
`;function RX(e){let{inputs:t,backend:a}=e,{a:n,b:r}=t,s=B().getBool("WEBGL_PACK_BINARY_OPERATIONS"),i=B().getNumber("WEBGL_VERSION");if(a.shouldExecuteOnCPU([n,r])||i===1){let l=a.texData.get(n.dataId).values,u=a.texData.get(r.dataId).values,[p,c]=FH(n.shape,r.shape,l,u,n.dtype),d=a.makeTensorInfo(c,n.dtype),h=a.texData.get(d.dataId);return h.values=p,d}let o;return s?o=new Ju(TX,n.shape,r.shape,!1):o=new ri(NX,n.shape,r.shape),a.runWebGLProgram(o,[n,r],n.dtype)}var EX={kernelName:cu,backendName:"webgl",kernelFunc:RX};function MX(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t,s=a.readSync(n.dataId),i=a.readSync(r.dataId),o=C.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return a.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var $X={kernelName:hu,backendName:"webgl",kernelFunc:MX},PX="return float(a != b);",N8=ha({opSnippet:PX,cpuKernelImpl:aj,dtype:"bool"}),_X={kernelName:xo,backendName:"webgl",kernelFunc:N8};function Qp(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.texData.get(n.dataId);return en({inputs:{x:r.complexTensorInfos.real},backend:a})}var FX={kernelName:Ip,backendName:"webgl",kernelFunc:Qp},DX="return float(int(x));";function OX(e,t){let a=new Zn(e.shape,DX),n=t.runWebGLProgram(a,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function W1(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dtype:s}=n;if(s==="complex64"){if(r.dtype==="complex64")return en({inputs:{x:r},backend:a});let i=yn(r.shape),o=W1({inputs:{x:r},backend:a,attrs:{dtype:"float32"}}),l=fs({inputs:{real:o,imag:i},backend:a});return i.dispose(),a.disposeIntermediateTensorInfo(o),l}if(r.dtype==="complex64"){let i=Qp({inputs:{input:r},backend:a}),o=W1({inputs:{x:i},backend:a,attrs:{dtype:s}});return a.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(r.dtype,s)){let i=en({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]=DH(i,r.shape,r.dtype,s);return a.makeTensorInfo(o,l,u)}if(s==="int32")return OX(r,a);if(s==="bool"){let i=a.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=N8({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 zX={kernelName:bi,backendName:"webgl",kernelFunc:W1},O5="return ceil(x);",LX=tt({opSnippet:O5,packedOpSnippet:O5,cpuKernelImpl:OH}),WX={kernelName:vi,backendName:"webgl",kernelFunc:LX},BX=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));
}
`}},VX=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 UX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=n,o;B().getBool("WEBGL_PACK_CLIP")?o=new VX(r.shape):o=new BX(r.shape);let l=[[s],[i]];return a.runWebGLProgram(o,[r],r.dtype,l)}var GX={kernelName:us,backendName:"webgl",kernelFunc:UX},HX=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 z5(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function jX(e){let{inputs:t,backend:a}=e,{x:n}=t,r=a.texData.get(n.dataId),s=new HX(n.shape),i=[z5(n,r.complexTensorInfos.real),z5(n,r.complexTensorInfos.imag)];return a.runWebGLProgram(s,i,i[0].dtype)}var qX={kernelName:hp,backendName:"webgl",kernelFunc:jX},XX=class{constructor(e){this.outputShape=[],this.outputShape=C.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;
${a.join(`
`)}
}
`}},KX=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=C.computeOutShape(e,t);let a=this.outputShape,n=a.length,r=ft(n),s=ka("coords",n),i=["x","y","z","w","u","v"].slice(0,n);this.variableNames=e.map((m,f)=>`T${f}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let m=1;m<o.length;m++)o[m]=o[m-1]+e[m][t];let l=i[t],u=i.slice(-2),p=i.join(),c=`if (${l} < ${o[0]}) {
return getChannel(
getT0(${p}), vec2(${u.join()}));
}`;for(let m=1;m<o.length;m++){let f=o[m-1];c+=`
if (${l} < ${o[m]} && ${l} >= ${o[m-1]}) {
return getChannel(
getT${m}(${Qc(i,l,f)}),
vec2(${Qc(u,l,f)}));
}`}let d=o.length,h=o[o.length-1];c+=`
return getChannel(
getT${d}(${Qc(i,l,h)}),
vec2(${Qc(u,l,h)}));`,this.userCode=`
float getValue(${i.map(m=>"int "+m)}) {
${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 Qc(e,t,a){let n=e.indexOf(t);return e.map((r,s)=>s===n?`${r} - ${a}`:r).join()}function o0(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.texData.get(n.dataId);return en({inputs:{x:r.complexTensorInfos.imag},backend:a})}var YX={kernelName:vp,backendName:"webgl",kernelFunc:o0};function $d(e,t,a){let n=e[0].dtype;if(n==="complex64"){let h=e.map(x=>Qp({inputs:{input:x},backend:a})),m=e.map(x=>o0({inputs:{input:x},backend:a})),f=$d(h,t,a),g=$d(m,t,a),y=fs({inputs:{real:f,imag:g},backend:a});return h.forEach(x=>a.disposeIntermediateTensorInfo(x)),m.forEach(x=>a.disposeIntermediateTensorInfo(x)),a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(g),y}let r=a.shouldExecuteOnCPU(e);if(n==="string"&&(r=!0),r){let h=e.map(b=>{let w=[-1,v.sizeFromShape(b.shape.slice(t))];return pe({inputs:{x:b},backend:a,attrs:{shape:w}})}),m=h.map(b=>({vals:a.readSync(b.dataId),shape:b.shape})),f=C.computeOutShape(h.map(b=>b.shape),1),g=h[0].shape[0]===1,y=zH(m,f,n,g),x=C.computeOutShape(e.map(b=>b.shape),t),A=a.makeTensorInfo(x,n,y);return h.forEach(b=>a.disposeIntermediateTensorInfo(b)),A}let s=e.filter(h=>v.sizeFromShape(h.shape)>0),i=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&s[0].shape.length>1;if(s.length===1){let h=i?new Zn(e[0].shape,Vr):new qr(e[0].shape,Vr);return a.runWebGLProgram(h,e,n)}let o=B().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(s.length>o){let h=[];for(let f=0;f<s.length;f+=o){let g=s.slice(f,f+o);h.push($d(g,t,a))}let m=$d(h,t,a);for(let f of h)a.disposeIntermediateTensorInfo(f);return m}if(i){let h=new KX(s.map(m=>m.shape),t);return a.runWebGLProgram(h,s,n)}let{tensors2D:l,outShape:u}=ZX(s,t,a),p=new XX(l.map(h=>h.shape)),c=a.runWebGLProgram(p,l,n);l.forEach(h=>a.disposeIntermediateTensorInfo(h));let d=pe({inputs:{x:c},attrs:{shape:u},backend:a});return a.disposeIntermediateTensorInfo(c),d}function ZX(e,t,a){let n=C.computeOutShape(e.map(r=>r.shape),t);return{tensors2D:e.map(r=>pe({inputs:{x:r},attrs:{shape:[-1,v.sizeFromShape(r.shape.slice(t))]},backend:a})),outShape:n}}function R8(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(u=>u.shape);C.assertParamsConsistent(i,s);let o=C.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(o)===0)return a.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(u=>v.sizeFromShape(u.shape)>0);return l.length===1?en({inputs:{x:l[0]},backend:a}):$d(l,s,a)}var JX={kernelName:mu,backendName:"webgl",kernelFunc:R8},E8=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,m=e.inChannels%4,f=e.dataFormat==="channelsLast",g=f?1:2,y=f?2:3,x=f?3:1,A="",b="";a&&(n?A=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${a}
}`:r?A=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${a}
}`:A=`
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=`
${A}
const ivec2 strides = ivec2(${o}, ${l});
const ivec2 pads = ivec2(${s}, ${i});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d2 = coords[${x}];
ivec2 xRCCorner =
ivec2(coords[${g}], coords[${y}]) * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${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 < ${h}; d1 += 4) {
vec4 wValues = vec4(
getW(wR, wC, d1, d2),
getW(wR, wC, d1 + 1, d2),
getW(wR, wC, d1 + 2, d2),
getW(wR, wC, d1 + 3, d2)
);
if (${f}) {
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 (${m===1}) {
if (${f}) {
dotProd +=
getX(batch, xR, xC, ${h}) *
getW(wR, wC, ${h}, d2);
} else {
dotProd +=
getX(batch, ${h}, xR, xC) *
getW(wR, wC, ${h}, d2);
}
} else if (${m===2}) {
vec2 wValues = vec2(
getW(wR, wC, ${h}, d2),
getW(wR, wC, ${h} + 1, d2)
);
if (${f}) {
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, ${h} + 1, xR, xC)
);
dotProd += dot(xValues, wValues);
}
} else if (${m===3}) {
vec3 wValues = vec3(
getW(wR, wC, ${h}, d2),
getW(wR, wC, ${h} + 1, d2),
getW(wR, wC, ${h} + 2, d2)
);
if (${f}) {
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}
${b}
setOutput(result);
}
`}},QX=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,a=e.padInfo.top,n=e.padInfo.left,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,p=e.filterDepth,c=e.filterHeight,d=e.filterWidth,h=Math.floor(e.inChannels/4)*4,m=e.inChannels%4;this.userCode=`
const ivec3 strides = ivec3(${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 < ${h}; d1 += 4) {
vec4 xValues = vec4(
getX(batch, xF, xR, xC, d1),
getX(batch, xF, xR, xC, d1 + 1),
getX(batch, xF, xR, xC, d1 + 2),
getX(batch, xF, xR, xC, d1 + 3)
);
vec4 wValues = vec4(
getW(wF, wR, wC, d1, d2),
getW(wF, wR, wC, d1 + 1, d2),
getW(wF, wR, wC, d1 + 2, d2),
getW(wF, wR, wC, d1 + 3, d2)
);
dotProd += dot(xValues, wValues);
}
if (${m===1}) {
dotProd +=
getX(batch, xF, xR, xC, ${h}) *
getW(wF, wR, wC, ${h}, d2);
} else if (${m===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, ${h} + 1, d2)
);
dotProd += dot(xValues, wValues);
} else if (${m===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, ${h} + 2, d2)
);
dotProd += dot(xValues, wValues);
}
}
}
}
setOutput(dotProd);
}
`}},M8=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=ga(this.outputShape.length);let s=e.padInfo.left,i=e.strideWidth,o=e.dilationWidth,l=e.filterHeight,u=e.filterWidth,p=u,c=`
int xR; int xC; int xCOffset;
vec4 wTexel; vec4 previous; vec4 final;`;for(let f=0;f<u;f++)c+=`
vec4 xTexelC${f*2};
int xTexelC${f*2}Ready;
vec4 xTexelC${f*2+1};
int xTexelC${f*2+1}Ready;
vec4 xC${f};`;c+=`
for (int r = 0; r < ${l}; r++) {
for (int d1 = 0; d1 < ${e.inChannels}; d1 += 2) {
`;for(let f=0;f<u;f++)c+=`
xTexelC${f*2} = vec4(0.0);
xTexelC${f*2}Ready = 0;
xTexelC${f*2+1} = vec4(0.0);
xTexelC${f*2+1}Ready = 0;
xC${f} = vec4(0.0);`;c+=`
xR = xRCorner + r * dilations[0];
if (xR >=0 && xR < inDims[0]) {
`;for(let f=0;f<(p+1)/2;f++){let g=f*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 y=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) + ${y};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.0);
}
xTexelC${g+1}Ready = 1;
}
`,o>1?c+=`
xCOffset -= 2;
if (xCOffset >= 0 && xCOffset < inDims[1]) {
previous = getX(batch, xR, xCOffset, d1);
xC${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);
`):y===1?c+=`
xC${g+1} = xTexelC${g};
`:c+=`
xCOffset = xC + ${y};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.0);
}
xTexelC${g+1}Ready = 1;
}
xC${g+1} = xTexelC${g+1};
`}}else g<u&&(s%2===1?(c+=`
xCOffset = xC + 1 - strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${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 m=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);
${m}
${h}
setOutput(result);
}
`}},eK=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=ga(this.outputShape.length);let{dataFormat:a}=t,n=Ra(),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 Ih(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 $8({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",m=!1,f=!1,g,y=[];if(s!=null){let x=Ih(s.shape,h);x!=null&&(s=pe({inputs:{x:s},backend:n,attrs:{shape:x}}),y.push(s))}if(r!=null){let x=Ih(r.shape,h);x!=null&&(r=pe({inputs:{x:r},backend:n,attrs:{shape:x}}),y.push(r))}if(!((c===1||d===1)&&p>I8)&&u.isPacked&&h&&u.texture!=null&&l[2]%2!==0&&v.arraysEqual(u.shape.slice(-3),l.slice(-3))){let x=l[0]*l[1]*(l[2]+1),A={dataId:e.dataId,shape:[1,x,a.inChannels],dtype:e.dtype},b=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(ep(u.shape,A.shape),()=>`packed reshape ${u.shape} to ${A.shape} isn't free`);let w=pe({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}});y.push(w);let I=kh({a:A,b:w,backend:n,transposeA:m,transposeB:f,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),T=n.texData.get(I.dataId);v.assert(T.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=b,T.shape=a.outShape,g=en({inputs:{x:I},backend:n}),g.shape=a.outShape,y.push(I)}else{let x=a.outHeight*a.outWidth,A=pe({inputs:{x:e},backend:n,attrs:{shape:h?[a.batchSize,x,a.inChannels]:[a.batchSize,a.inChannels,x]}}),b=pe({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}}),w=kh({a:h?A:b,b:h?b:A,transposeA:!h,transposeB:f,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i});g=pe({inputs:{x:w},backend:n,attrs:{shape:a.outShape}}),y.push(A),y.push(b),y.push(w)}for(let x of y)n.disposeIntermediateTensorInfo(x);return g}function P8({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,m=h==="channelsLast",f=l*u*p,g=d*c,y=[a.batchSize,f,g],x=!0,A=!1,b=[];if(s!=null){let G=Ih(s.shape,m);G!=null&&(s=pe({inputs:{x:s},backend:n,attrs:{shape:G}}),b.push(s))}if(r!=null){let G=Ih(r.shape,m);G!=null&&(r=pe({inputs:{x:r},backend:n,attrs:{shape:G}}),b.push(r))}let w=pe({inputs:{x:t},backend:n,attrs:{shape:[1,f,v.sizeFromShape(t.shape)/f]}});b.push(w);let I=new eK(y,a),T=[e.shape,[a.padInfo.top,a.padInfo.left],[a.strideHeight,a.strideWidth],[a.dilationHeight,a.dilationWidth],[a.inChannels],[a.filterWidth*a.inChannels],[a.outWidth]],N=n.runWebGLProgram(I,[e],"float32",T),M=pe({inputs:{x:N},backend:n,attrs:{shape:y}});b.push(N),b.push(M);let $=r!=null,E=s!=null,S=o==="leakyrelu",_=o?tp(o,!0):null,O=new k8(m?M.shape:w.shape,m?w.shape:M.shape,m?[a.batchSize,g,a.outChannels]:[a.batchSize,a.outChannels,g],x,A,$,_,E,S),W=m?[M,w]:[w,M];if(r&&W.push(r),E&&W.push(s),S){let G=n.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));W.push(G),b.push(G)}let P=n.runWebGLProgram(O,W,"float32"),U=pe({inputs:{x:P},backend:n,attrs:{shape:a.outShape}});b.push(P);for(let G of b)n.disposeIntermediateTensorInfo(G);return U}function tK(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=C.convertConv2DDataFormat(l),d=C.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=$8({x:r,filter:s,convInfo:d,backend:a});else if(d.strideWidth<=2&&c==="channelsLast"&&B().getBool("WEBGL_EXP_CONV")){let f=new M8(d),g=[[d.padInfo.top,d.padInfo.left],[d.strideHeight,d.strideWidth],[d.dilationHeight,d.dilationWidth],[d.inHeight,d.inWidth]];h=a.runWebGLProgram(f,[r,s],"float32",g)}else if(B().getBool("WEBGL_CONV_IM2COL"))h=P8({x:r,filter:s,convInfo:d,backend:a});else{let f=new E8(d);h=a.runWebGLProgram(f,[r,s],"float32")}let m=pe({inputs:{x:h},backend:a,attrs:{shape:d.outShape}});return a.disposeIntermediateTensorInfo(h),m}var aK={kernelName:wi,backendName:"webgl",kernelFunc:tK},nK=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;
}
${s?`float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);`:`float dyValue = getDy(b, d2, yR, yC);
float xValue = getX(b, d1, xR, xC);
dotProd += (xValue * dyValue);`}
}
}
}
setOutput(dotProd);
}
`}},rK=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,a=e.filterWidth,n=e.strideHeight,r=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=a-1-e.padInfo.left,l=s?1:2,u=s?2:3,p=s?3:1;this.userCode=`
const ivec2 pads = ivec2(${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);
}
`}},sK=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 >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yF, yR, yC, d2);
float xValue = getX(b, xF, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},iK=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,a=e.filterHeight,n=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=a-1-e.padInfo.top,u=n-1-e.padInfo.left;this.userCode=`
const ivec3 pads = ivec3(${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 < ${e.outChannels}; d2++) {
float xValue = getDy(batch, idyF, idyR, idyC, d2);
float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
}
}
}
}
setOutput(dotProd);
}
`}};function oK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:p}=n,c=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,p,i,1,o,u,!1,c),h=new nK(d);return a.runWebGLProgram(h,[r,s],"float32")}var lK={kernelName:mp,backendName:"webgl",kernelFunc:oK},uK=class{constructor(e){this.variableNames=["dy","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"strides",type:"vec2"}],this.outputShape=e.inShape,this.enableShapeUniforms=ga(this.outputShape.length);let t=e.filterHeight,a=e.filterWidth,n=t-1-e.padInfo.top,r=a-1-e.padInfo.left;this.userCode=`
const ivec2 pads = ivec2(${n}, ${r});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[3];
ivec2 dyCorner = ivec2(coords[1], coords[2]) - pads;
int dyRCorner = dyCorner.x;
int dyCCorner = dyCorner.y;
vec4 result = vec4(0.);
for (int wR = 0; wR < ${t}; wR++) {
float dyR = float(dyRCorner + wR) / strides[0];
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${t} - 1 - wR;
for (int wC = 0; wC < ${a}; wC++) {
int wCPerm = ${a} - 1 - wC;
float dyC = float(dyCCorner + wC) / strides[1];
bool idyCVal = (dyC >= 0.0) && (dyC < ${e.outWidth}.0)
&& (fract(dyC) == 0.0);
int idyC = int(dyC);
float dyC2 = float(dyCCorner + wC + 1) / strides[1];
bool idyCVal2 = (dyC2 >= 0.0) && (dyC2 < ${e.outWidth}.0)
&& (fract(dyC2) == 0.0);
int idyC2 = int(dyC2);
if (idyCVal && idyCVal2) {
for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
vec4 dySample = getDy(batch, idyR, idyC, d2);
vec4 dySample2 = (idyC / 2 == idyC2 / 2) ?
dySample : getDy(batch, idyR, idyC2, d2);
vec2 dyValue = mod(float(idyC), 2.) == 0. ?
dySample.xy : dySample.zw;
result.xy += vec2(dot(dyValue, wValue.xy),
dot(dyValue, wValue.zw));
dyValue = mod(float(idyC2), 2.) == 0. ?
dySample2.xy : dySample2.zw;
result.zw += vec2(dot(dyValue, wValue.xy),
dot(dyValue, wValue.zw));
}
} else if (idyCVal) {
for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
vec4 dySample = getDy(batch, idyR, idyC, d2);
vec2 dyValue = mod(float(idyC), 2.) == 0. ?
dySample.xy : dySample.zw;
result.xy += vec2(dot(dyValue, wValue.xy),
dot(dyValue, wValue.zw));
}
} else if (idyCVal2) {
for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
vec4 dySample = getDy(batch, idyR, idyC2, d2);
vec2 dyValue = mod(float(idyC2), 2.) == 0. ?
dySample.xy : dySample.zw;
result.zw += vec2(dot(dyValue, wValue.xy),
dot(dyValue, wValue.zw));
}
}
}
}
setOutput(result);
}
`}};function dK(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=C.convertConv2DDataFormat(u),d=C.computeConv2DInfo(i,s.shape,o,1,l,p,!1,c);if(B().getBool("WEBGL_PACK_CONV2DTRANSPOSE")&&c==="channelsLast"){let h=[[d.strideHeight,d.strideWidth]],m=new uK(d);return a.runWebGLProgram(m,[r,s],"float32",h)}else{let h=new rK(d);return a.runWebGLProgram(h,[r,s],"float32")}}var pK={kernelName:ki,backendName:"webgl",kernelFunc:dK};function cK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=C.computeConv3DInfo(r.shape,s.shape,i,l,o),p=new QX(u);return a.runWebGLProgram(p,[r,s],"float32")}var hK={kernelName:Ii,backendName:"webgl",kernelFunc:cK};function mK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=n,u=C.computeConv3DInfo(r.shape,l,i,1,o),p=new sK(u);return a.runWebGLProgram(p,[r,s],"float32")}var fK={kernelName:fu,backendName:"webgl",kernelFunc:mK};function gK(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=n,u=C.computeConv3DInfo(l,s.shape,o,1,i),p=new iK(u);return a.runWebGLProgram(p,[r,s],"float32")}var yK={kernelName:Si,backendName:"webgl",kernelFunc:gK},xK=Qu+`
return cos(x);
`,AK=`
vec4 result = cos(x);
bvec4 isNaN = isnan(x);
${il}
return result;
`,bK=tt({opSnippet:xK,packedOpSnippet:AK}),vK={kernelName:Ci,backendName:"webgl",kernelFunc:bK},wK=`
float e2x = exp(-x);
return (e2x + 1.0 / e2x) / 2.0;
`,kK=tt({opSnippet:wK}),IK={kernelName:Ti,backendName:"webgl",kernelFunc:kK},SK=class{constructor(e,t,a,n,r){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[p,c]=a;this.outputShape=[u,p,c,l];let d=n==="bilinear"?1:0,[h,m]=[`${i-1}.0`,`${o-1}.0`],[f,g,y]=p>1?[`${(i-1)/(p-1)}`,"(y2-y1) * height_ratio",`y1*${h} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${h}`],[x,A,b]=c>1?[`${(o-1)/(c-1)}`,"(x2-x1) * width_ratio",`x1*${m} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${m}`];this.userCode=`
const float height_ratio = float(${f});
const float width_ratio = float(${x});
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 = ${A};
float in_y = ${y};
if( in_y < 0.0 || in_y > ${h} ) {
setOutput(float(${r}));
return;
}
float in_x = ${b};
if( in_x < 0.0 || in_x > ${m} ) {
setOutput(float(${r}));
return;
}
vec2 sourceFracIndexCR = vec2(in_x,in_y);
if(${d} == 1) {
// Compute the four integer indices.
ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
float top = topLeft + (topRight - topLeft) * fracCR.x;
float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
float newValue = top + (bottom - top) * fracCR.y;
setOutput(newValue);
} else {
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestCR = ivec2(floor(
sourceFracIndexCR + vec2(0.5,0.5)));
float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
setOutput(newValue);
}
}
`}},CK=e=>{let{inputs:t,backend:a,attrs:n}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,p=new SK(r.shape,s.shape,o,l,u);return a.runWebGLProgram(p,[r,s,i],"float32")},TK={kernelName:Ei,backendName:"webgl",kernelFunc:CK},np;(function(e){e.Prod="*",e.Sum="+"})(np||(np={}));var L5=class{constructor(e,t,a,n){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let r=this.outputShape.length,s=this.op===np.Prod?"1.0":"0.0",i=a?s:`getX(${W5(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() {
${ft(r)} coords = getOutputCoords();
int end = ${B5(r,"coords",this.op)};
float val = ${i};
int pow2 = int(pow(2.0, index));
if (${l}) {
int idx = ${u};
${B5(r,"coords",this.op)} = idx;
val ${this.op}= getX(${W5(r,"coords",this.op)});
}
setOutput(val);
}
`}};function W5(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 ${e} is not yet supported`)}function B5(e,t,a){if(e===1)return`${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 ${e} is not yet supported`)}function _8(e,t,a,n,r,s){let i=t.shape.length,o=C.getAxesPermutation([n],i),l=t;o!=null&&(l=Ca({inputs:{x:t},backend:a,attrs:{perm:o}}));let u=C.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let p=l.shape[u],c=en({inputs:{x:l},backend:a});for(let d=0;d<=Math.ceil(Math.log2(p))-1;d++){let h=new L5(e,l.shape,!1,s),m=[[d]],f=c;c=a.runWebGLProgram(h,[c],c.dtype,m),a.disposeIntermediateTensorInfo(f)}if(r){let d=new L5(e,l.shape,r,s),h=c;c=a.runWebGLProgram(d,[c],c.dtype),a.disposeIntermediateTensorInfo(h)}if(o!=null){let d=C.getUndoAxesPermutation(o),h=Ca({inputs:{x:c},backend:a,attrs:{perm:d}});return a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(l),h}return c}function NK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return _8(np.Prod,r,a,s,i,o)}var RK={kernelName:Ni,backendName:"webgl",kernelFunc:NK};function EK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return _8(np.Sum,r,a,s,i,o)}var MK={kernelName:Ri,backendName:"webgl",kernelFunc:EK};function $K(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n;if(r.shape.length===1){let l=a.readSync(r.dataId),u=a.readSync(s.dataId),p=c8(l,u,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=a.bufferSync(r),u=a.bufferSync(s),p=_H(l,u,i,o);return a.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var PK={kernelName:gu,backendName:"webgl",kernelFunc:$K},_K=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 FK(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),m=i==="NHWC"?[o,c,d,h]:[o,h,c,d],f=new _K(m,s,i);return a.runWebGLProgram(f,[r],r.dtype)}var DK={kernelName:Mi,backendName:"webgl",kernelFunc:FK},F8=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=ga(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}
${u}
setOutput(result);
}
`}},D8=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=ga(this.outputShape.length);let s=e.outChannels/e.inChannels,i=e.padInfo.left,o=e.strideWidth,l=e.dilationWidth,u=e.filterHeight,p=e.filterWidth,c=p,d=`
int xR; int xC; int xCOffset;
vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g<p;g++)d+=`
vec4 xTexelC${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 y=g*2;if(d+=`
xC = xCCorner + ${y*l};
`,o===1){if(y<p&&(i%2===1?(d+=`
xCOffset = xC + 1;
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y}Ready == 0) {
xTexelC${y} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${y}.zw = vec2(0.0);
}
xTexelC${y}Ready = 1;
}
`,l===1&&y>0?d+=`
xC${y} = vec4(xTexelC${y-2}.zw, xTexelC${y}.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${y} = vec4(previous.zw, xTexelC${y}.xy);
} else {
xC${y} = vec4(0.0, 0.0, xTexelC${y}.xy);
}
`):d+=`
if (xC >= 0 && xC < inDims[1] && xTexelC${y}Ready == 0) {
xTexelC${y} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${y}.zw = vec2(0.0);
}
xTexelC${y}Ready = 1;
}
xC${y} = xTexelC${y};
`,y+1<p)){let x=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) + ${x};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) {
xTexelC${y+1} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${y+1}.zw = vec2(0.0);
}
xTexelC${y+1}Ready = 1;
}
`,l>1?d+=`
xCOffset -= 2;
if (xCOffset >= 0 && xCOffset < inDims[1]) {
previous = getX(batch, xR, xCOffset, d1);
xC${y+1} = vec4(previous.zw, xTexelC${y+1}.xy);
} else {
xC${y+1} = vec4(0.0, 0.0, xTexelC${y+1}.xy);
}
`:d+=`
xC${y+1} = vec4(xTexelC${y}.zw, xTexelC${y+1}.xy);
`):x===1?d+=`
xC${y+1} = xTexelC${y};
`:d+=`
xCOffset = xC + ${x};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) {
xTexelC${y+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${y+1}.zw = vec2(0.0);
}
xTexelC${y+1}Ready = 1;
}
xC${y+1} = xTexelC${y+1};
`}}else y<p&&(i%2===1?(d+=`
xCOffset = xC + 1 - strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y}Ready == 0) {
xTexelC${y} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${y}.zw = vec2(0.0);
}
xTexelC${y}Ready = 1;
}
if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${y+1}Ready == 0) {
xTexelC${y+1} = getX(batch, xR, xC + 1, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xC + 2 >= inDims[1]) {
xTexelC${y+1}.zw = vec2(0.0);
}
xTexelC${y+1}Ready = 1;
}
xC${y} = vec4(xTexelC${y}.zw, xTexelC${y+1}.zw);
`,y+1<p&&(d+=`
final = vec4(0.0);
xCOffset = xC + 1 + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1]) {
final = getX(batch, xR, xCOffset, d1);
}
xC${y+1} = vec4(xTexelC${y+1}.xy, final.xy);
`)):(d+=`
if(xC >= 0 && xC < inDims[1] && xTexelC${y}Ready == 0) {
xTexelC${y} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${y}.zw = vec2(0.0);
}
xTexelC${y}Ready = 1;
}
xCOffset = xC + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) {
xTexelC${y+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${y+1}.zw = vec2(0.);
}
xTexelC${y+1}Ready = 1;
}
xC${y} = vec4(
xTexelC${y}.xy, xTexelC${y+1}.xy);
`,y+1<p&&(d+=`
xC${y+1} = vec4(xTexelC${y}.zw, xTexelC${y+1}.zw);
`)));y<p&&(d+=`
wTexel = getW(r, ${y}, d1, q);
dotProd += xC${y} * vec4(wTexel.xz, wTexel.xz);
`,y+1<p&&(d+=`
wTexel = getW(r, ${y+1}, d1, q);
dotProd += xC${y+1} * vec4(wTexel.xz, wTexel.xz);
`))}d+=`
}
`,d+=`
}
`;let h="",m="";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}
}`,m="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=`
${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);
${f}
${m}
setOutput(result);
}
`}};function OK(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(C.eitherStridesOrDilationsAreOne(i,p),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${p}'`);let c=C.computeConv2DInfo(r.shape,s.shape,i,p,o,u,!0),d;B().getBool("WEBGL_PACK_DEPTHWISECONV")&&c.strideWidth<=2&&c.outChannels/c.inChannels===1?d=new D8(c):d=new F8(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 zK={kernelName:$i,backendName:"webgl",kernelFunc:OK},LK=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 >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
setOutput(dotProd);
}
`}},WK=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,a=e.filterWidth,n=e.strideHeight,r=e.strideWidth,s=t-1-e.padInfo.top,i=a-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
const ivec2 pads = ivec2(${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 * ${o} + dm;
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, dm);
dotProd += xValue * wValue;
}
}
}
setOutput(dotProd);
}
`}};function BK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:p}=n,c=C.computeConv2DInfo(r.shape,p,i,o,l,u,!0),d=new LK(c);return a.runWebGLProgram(d,[r,s],"float32")}var VK={kernelName:fp,backendName:"webgl",kernelFunc:BK};function UK(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:p}=n,c=C.computeConv2DInfo(p,s.shape,i,o,l,u,!0),d=new WK(c);return a.runWebGLProgram(d,[r,s],"float32")}var GK={kernelName:gp,backendName:"webgl",kernelFunc:UK},HK=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
setOutput(val);
}
`}};function jK(e){let{inputs:t,backend:a}=e,{x:n}=t,r=[...n.shape,...n.shape],s=v.sizeFromShape(n.shape),i=pe({inputs:{x:n},backend:a,attrs:{shape:[s]}}),o=new HK(s),l=a.runWebGLProgram(o,[i],i.dtype),u=pe({inputs:{x:l},backend:a,attrs:{shape:r}});return a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(l),u}var qK={kernelName:yu,backendName:"webgl",kernelFunc:jK},XK=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:a,padInfo:n,strideHeight:r,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:p,left:c}=n;this.userCode=`
const ivec2 strides = ivec2(${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 KK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=C.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),p,c=new XK(u);p=a.runWebGLProgram(c,[r,s],"float32");let d=pe({inputs:{x:p},backend:a,attrs:{shape:u.outShape}});return a.disposeIntermediateTensorInfo(p),d}var YK={kernelName:Pi,backendName:"webgl",kernelFunc:KK};function ZK(e){let{inputs:t,backend:a,attrs:n}=e,{equation:r}=n,s=t,{allDims:i,summedDims:o,idDims:l}=C.decodeEinsumEquation(r,s.length);C.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:p}=C.getEinsumComputePath(o,l),c=p.length,d=null,h=i.length,m=[];for(let f=0;f<c;++f){for(let g of p[f]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=s[g]:(A=Ca({inputs:{x:s[g]},backend:a,attrs:{perm:y}}),m.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=pe({inputs:{x:A},backend:a,attrs:{shape:b}}),m.push(A)),d===null?d=A:(d=L3({inputs:{a:A,b:d},backend:a}),m.push(d))}f<c-1&&(u[f]>=0&&(d=i0({inputs:{x:d},backend:a,attrs:{axis:u[f]-(i.length-h),keepDims:!1}}),m.push(d)),h--)}for(let f of m)f!==d&&a.disposeIntermediateTensorInfo(f);return d}var JK={kernelName:xp,backendName:"webgl",kernelFunc:ZK},QK="return (x >= 0.0) ? x : (exp(x) - 1.0);",eY=`
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;
`,tY=tt({opSnippet:QK,packedOpSnippet:eY}),aY={kernelName:Fi,backendName:"webgl",kernelFunc:tY},nY="return (b >= 0.0) ? a : a * (b + 1.0);",rY=`
vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,sY=e=>{let{inputs:t,backend:a}=e,{dy:n,y:r}=t,s=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ju(rY,n.shape,r.shape):new ri(nY,n.shape,r.shape);return a.runWebGLProgram(s,[n,r],n.dtype)},iY={kernelName:xu,backendName:"webgl",kernelFunc:sY},oY=`
return vec4(equal(a, b));
`,lY="return float(a == b);",uY=ha({opSnippet:lY,packedOpSnippet:oY,dtype:"bool",cpuKernelImpl:LH}),dY={kernelName:Oi,backendName:"webgl",kernelFunc:uY},pY=`
// Error function is calculated approximately with elementary function.
// See "Handbook of Mathematical Functions with Formulas,
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
float p = ${C.ERF_P};
float a1 = ${C.ERF_A1};
float a2 = ${C.ERF_A2};
float a3 = ${C.ERF_A3};
float a4 = ${C.ERF_A4};
float a5 = ${C.ERF_A5};
float sign = sign(x);
x = abs(x);
float t = 1.0 / (1.0 + p * x);
return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,cY=tt({opSnippet:pY}),hY={kernelName:Di,backendName:"webgl",kernelFunc:cY},mY=Qu+`
return exp(x);
`,fY=`
vec4 result = exp(x);
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : result.r;
result.g = isNaN.g ? x.g : result.g;
result.b = isNaN.b ? x.b : result.b;
result.a = isNaN.a ? x.a : result.a;
return result;
`,O8=tt({opSnippet:mY,packedOpSnippet:fY,cpuKernelImpl:WH,dtype:"float32"}),gY={kernelName:zi,backendName:"webgl",kernelFunc:O8};function B1(e){let{inputs:t,attrs:a,backend:n}=e,{dim:r}=a,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=r;return r<0&&(v.assert(-(i+1)<=r,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+r+1),o.splice(l,0,1),pe({inputs:{x:s},backend:n,attrs:{shape:o}})}var yY={kernelName:Au,backendName:"webgl",kernelFunc:B1},V5="return exp(x) - 1.0;",xY=tt({opSnippet:V5,packedOpSnippet:V5,cpuKernelImpl:BH}),AY={kernelName:Li,backendName:"webgl",kernelFunc:xY},U5=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 z8(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=pe({inputs:{x:e},backend:a,attrs:{shape:[i,s]}}),l=o.shape,u=new U5("real",l,t),p=new U5("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"),m=fs({inputs:{real:d,imag:h},backend:a});a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h);let f=pe({inputs:{x:m},backend:a,attrs:{shape:e.shape}});return a.disposeIntermediateTensorInfo(o),a.disposeIntermediateTensorInfo(m),f}function bY(e){let{inputs:t,backend:a}=e,{input:n}=t;return z8(n,!1,a)}var vY={kernelName:Ap,backendName:"webgl",kernelFunc:bY},wY=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 ec(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 wY(n,r),o=[[r]];return t.runWebGLProgram(i,[],s,o)}}var kY={kernelName:bu,backendName:"webgl",kernelFunc:ec},IY=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 < ${t}) {
outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
} else {
outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
}
setOutput(outputValue);
}
`}},SY={kernelName:Wi,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:a}=e,n=t,r=new IY(a.shape);return n.runWebGLProgram(r,[a],a.dtype)}},G5="return floor(x);",CY=tt({opSnippet:G5,packedOpSnippet:G5,cpuKernelImpl:VH}),TY={kernelName:Bi,backendName:"webgl",kernelFunc:CY},NY=`
float s = sign(a) * sign(b);
int ia = round(a);
int ib = round(b);
if (ib != 0) {
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
return float(idiv(ia, ib, s));
} else {
return NAN;
}
`,RY=`
ivec4 ia = round(a);
ivec4 ib = round(b);
bvec4 cond = notEqual(ib, ivec4(0));
ivec4 result = ivec4(0);
vec4 s = sign(a) * sign(b);
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
if (cond[0]) {
result[0] = idiv(ia[0], ib[0], s[0]);
}
if (cond[1]) {
result[1] = idiv(ia[1], ib[1], s[1]);
}
if (cond[2]) {
result[2] = idiv(ia[2], ib[2], s[2]);
}
if (cond[3]) {
result[3] = idiv(ia[3], ib[3], s[3]);
}
return vec4(result);
`,EY=ha({opSnippet:NY,packedOpSnippet:RY,dtype:"int32"}),MY={kernelName:Vi,backendName:"webgl",kernelFunc:EY},$Y=class{constructor(e){this.variableNames=["A"];let t=Ra(),[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 = ${t.texture2D}(A, uv);
float value;
if (depth == 0) {
value = values.r;
} else if (depth == 1) {
value = values.g;
} else if (depth == 2) {
value = values.b;
} else if (depth == 3) {
value = values.a;
}
setOutput(floor(value * 255.0 + 0.5));
}
`}},PY=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=Ra(),[a,n]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec4 result = vec4(0.);
for(int row=0; row<=1; row++) {
for(int col=0; col<=1; col++) {
texC = coords[1] + row;
depth = coords[2] + col;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${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;
}
`}},_Y={kernelName:Wd,backendName:"webgl",kernelFunc:FY},Fl,Q2=B().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function FY(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 f=B().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(Fl==null||f!==Q2)&&(Q2=f,Fl=document.createElement("canvas").getContext("2d",{willReadFrequently:Q2})),Fl.canvas.width=l,Fl.canvas.height=u,Fl.drawImage(r,0,0,l,u),r=Fl.canvas}let d=a.makeTensorInfo(p,"int32");a.texData.get(d.dataId).usage=mn.PIXELS,a.gpgpu.uploadPixelDataToTexture(a.getTexture(d.dataId),r);let h=B().getBool("WEBGL_PACK")?new PY(c):new $Y(c),m=a.runWebGLProgram(h,[d],"int32");return a.disposeData(d.dataId),m}function DY(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:p,dilations:c,dimRoundingMode:d,activation:h,leakyreluAlpha:m}=n,f=C.convertConv2DDataFormat(p),g=C.computeConv2DInfo(r.shape,s.shape,l,c,u,d,!1,f),y,x=[],A=i!=null,b=o!=null,w=h==="leakyrelu",I=()=>{let N=[r,s],M=($,E)=>{if(E==="NCHW"&&$.shape.length===1&&$.shape[0]!==1){let S=pe({inputs:{x:$},backend:a,attrs:{shape:[$.shape[0],1,1]}});return x.push(S),S}return $};if(A&&N.push(M(i,p)),b&&N.push(M(o,p)),w){let $=a.makeTensorInfo([],"float32",v.createScalarValue(m,"float32"));N.push($),x.push($)}return N};if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))y=$8({x:r,filter:s,convInfo:g,backend:a,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:m});else if(g.strideWidth<=2&&f==="channelsLast"&&B().getBool("WEBGL_EXP_CONV")){let N=h?tp(h,!0):null,M=new M8(g,A,N,b,w),$=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],E=I();y=a.runWebGLProgram(M,E,"float32",$)}else if(B().getBool("WEBGL_CONV_IM2COL"))y=P8({x:r,filter:s,convInfo:g,backend:a,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:m});else{let N=h?tp(h,!1):null,M=new E8(g,A,N,b,w),$=I();y=a.runWebGLProgram(M,$,"float32")}let T=pe({inputs:{x:y},backend:a,attrs:{shape:g.outShape}});return x.push(y),x.forEach(N=>a.disposeIntermediateTensorInfo(N)),T}var OY={kernelName:Jr,backendName:"webgl",kernelFunc:DY};function zY(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,m=[],f=p;f==null&&(f=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(l,f),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${f}'`);let g=C.computeConv2DInfo(r.shape,s.shape,l,f,u,c,!0),y=B().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,x=d?tp(d,y):null,A=[r,s],b=i!=null,w=o!=null,I=d==="leakyrelu";if(b&&A.push(i),w&&A.push(o),I){let $=a.makeTensorInfo([],"float32",v.createScalarValue(h,"float32"));A.push($),m.push($)}let T;y?T=new D8(g,b,x,w,I):T=new F8(g,b,x,w,I);let N=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],M=a.runWebGLProgram(T,A,"float32",N);return m.forEach($=>a.disposeIntermediateTensorInfo($)),M}var LY={kernelName:Qr,backendName:"webgl",kernelFunc:zY},WY=class{constructor(e,t,a,n){this.sliceDim=e,this.strides=t,this.paramsShape=n,this.variableNames=["x","indices"],this.outputShape=a;let r=ft(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 BY(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]=C.prepareAndValidate(n,r),d=pe({inputs:{x:r},backend:a,attrs:{shape:[u,i]}}),h=pe({inputs:{x:n},backend:a,attrs:{shape:[v.sizeFromShape(n.shape)/p,p]}});if(a.shouldExecuteOnCPU([n,r])||n.dtype==="string"){let y=a.readSync(r.dataId),x=a.bufferSync(n),A=UH(y,x,n.dtype,u,i,p,c,n.shape,o);return a.makeTensorInfo(l,n.dtype,A.values)}let m=new WY(i,c,[u,p],n.shape),f=a.runWebGLProgram(m,[h,d],h.dtype),g=pe({inputs:{x:f},backend:a,attrs:{shape:l}});return a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(f),g}var VY={kernelName:Gi,backendName:"webgl",kernelFunc:BY},UY=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let a=ft(this.rank),n=GY(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 GY(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 L8(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(B().get("DEBUG")){let x=a.readSync(s.dataId),A=r.shape[l];for(let b=0;b<x.length;++b){let w=x[b];v.assert(w<=A-1&&w>=0,()=>`GatherV2: the index value ${w} is not in [0, ${A-1}]`)}}let u=C.segment_util.collectGatherOpShapeInfo(r,s,l,o),p=v.sizeFromShape(s.shape),c=[],d=pe({inputs:{x:r},backend:a,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=pe({inputs:{x:s},backend:a,attrs:{shape:[u.batchSize,p/u.batchSize]}});c.push(d),c.push(h);let m=[u.batchSize,u.outerSize,p/u.batchSize,u.sliceSize];if(a.shouldExecuteOnCPU([r,s])||r.dtype==="string"){let x=a.bufferSync(h),A=a.bufferSync(d),b=GH(A,x,m);return c.forEach(w=>a.disposeIntermediateTensorInfo(w)),a.makeTensorInfo(u.outputShape,b.dtype,b.values)}let f=new UY(d.shape,m),g=a.runWebGLProgram(f,[d,h],d.dtype);c.push(g);let y=pe({inputs:{x:g},backend:a,attrs:{shape:u.outputShape}});return c.forEach(x=>a.disposeIntermediateTensorInfo(x)),y}var HY={kernelName:vu,backendName:"webgl",kernelFunc:L8},jY="return float(a > b);",qY=`
return vec4(greaterThan(a, b));
`,XY=ha({opSnippet:jY,packedOpSnippet:qY,cpuKernelImpl:HH,dtype:"bool"}),KY={kernelName:Hi,backendName:"webgl",kernelFunc:XY},YY="return float(a >= b);",ZY=`
return vec4(greaterThanEqual(a, b));
`,JY=ha({opSnippet:YY,packedOpSnippet:ZY,dtype:"bool",cpuKernelImpl:jH}),QY={kernelName:ji,backendName:"webgl",kernelFunc:JY};function eZ(e){let{inputs:t,backend:a}=e,{input:n}=t;return z8(n,!0,a)}var tZ={kernelName:bp,backendName:"webgl",kernelFunc:eZ},aZ="return float(!isnan(x) && !isinf(x));",nZ=tt({opSnippet:aZ,dtype:"bool"}),rZ={kernelName:Xi,backendName:"webgl",kernelFunc:nZ},sZ="return float(isinf(x));",iZ=tt({opSnippet:sZ,dtype:"bool"}),oZ={kernelName:Ki,backendName:"webgl",kernelFunc:iZ},lZ="return float(isnan(x));",uZ=tt({opSnippet:lZ,dtype:"bool"}),dZ={kernelName:Yi,backendName:"webgl",kernelFunc:uZ},pZ="return float(a < b);",cZ=`
return vec4(lessThan(a, b));
`,hZ=ha({opSnippet:pZ,packedOpSnippet:cZ,cpuKernelImpl:qH,dtype:"bool"}),mZ={kernelName:Ji,backendName:"webgl",kernelFunc:hZ},fZ="return float(a <= b);",gZ=`
return vec4(lessThanEqual(a, b));
`,yZ=ha({opSnippet:fZ,packedOpSnippet:gZ,cpuKernelImpl:XH,dtype:"bool"}),xZ={kernelName:Qi,backendName:"webgl",kernelFunc:yZ};function AZ(e){let{backend:t,attrs:a}=e,{start:n,stop:r,num:s}=a,i=KH(n,r,s);return t.makeTensorInfo([i.length],"float32",i)}var bZ={kernelName:eo,backendName:"webgl",kernelFunc:AZ},vZ=Qu+`
return x < 0.0 ? 0./0. : log(x);
`,wZ=`
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;
`,kZ=tt({opSnippet:vZ,packedOpSnippet:wZ,cpuKernelImpl:YH}),IZ={kernelName:to,backendName:"webgl",kernelFunc:kZ},SZ=Qu+`
return log(1.0 + x);
`,CZ=tt({opSnippet:SZ}),TZ={kernelName:ao,backendName:"webgl",kernelFunc:CZ},NZ="return float(a >= 1.0 && b >= 1.0);",RZ=`
return vec4(
vec4(greaterThanEqual(a, vec4(1.0))) *
vec4(greaterThanEqual(b, vec4(1.0))));
`,EZ=ha({opSnippet:NZ,packedOpSnippet:RZ,dtype:"bool"}),MZ={kernelName:no,backendName:"webgl",kernelFunc:EZ},$Z="return float(!(x >= 1.0));",PZ=tt({opSnippet:$Z}),_Z={kernelName:ro,backendName:"webgl",kernelFunc:PZ},FZ="return float(a >= 1.0 || b >= 1.0);",DZ=`
return min(
vec4(greaterThanEqual(a, vec4(1.0))) +
vec4(greaterThanEqual(b, vec4(1.0))),
vec4(1.0));
`,OZ=ha({opSnippet:FZ,packedOpSnippet:DZ,dtype:"bool"}),zZ={kernelName:so,backendName:"webgl",kernelFunc:OZ},LZ=class{constructor(e,t,a,n,r){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${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 * ${o};
setOutput(val);
}
`}},WZ=class{constructor(e,t,a,n,r){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${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);
}
`}},BZ=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n,u=B().getBool("WEBGL_PACK_NORMALIZATION")?new WZ(r.shape,s,i,o,l):new LZ(r.shape,s,i,o,l);return a.runWebGLProgram(u,[r],r.dtype)},VZ={kernelName:io,backendName:"webgl",kernelFunc:BZ},UZ=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);
}
`}},GZ=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 UZ(r.shape,o,l,u,p);return a.runWebGLProgram(c,[r,s,i],r.dtype)},HZ={kernelName:wu,backendName:"webgl",kernelFunc:GZ};function jZ(e,t,a,n){let r=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/r,i=pe({inputs:{x:e},attrs:{shape:[s,r]},backend:n}),o=ol(i,e.dtype,"max",n),l=pe({inputs:{x:o},attrs:{shape:a},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}function W8(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=C.getAxesPermutation(u,o),c=p!=null,d=a.shouldExecuteOnCPU([r]),h=r;if(c){if(d){let x=a.texData.get(h.dataId).values,A=new Array(o);for(let I=0;I<A.length;I++)A[I]=r.shape[p[I]];let b=O3(x,r.shape,r.dtype,p,A);h=a.makeTensorInfo(A,r.dtype);let w=a.texData.get(h.dataId);w.values=b}else h=s0(r,p,a);u=C.getInnerMostAxes(u.length,o)}C.assertAxesAreInnerMostDims("max",u,o);let[m,f]=C.computeOutAndReduceShapes(h.shape,u),g=m;i&&(g=C.expandShapeToKeepDim(m,l));let y;if(d){let x=a.texData.get(h.dataId).values,A=ZH(x,v.sizeFromShape(f),g,r.dtype);y=a.makeTensorInfo(g,r.dtype);let b=a.texData.get(y.dataId);b.values=A}else y=jZ(h,f,g,a);return c&&a.disposeIntermediateTensorInfo(h),y}var qZ={kernelName:oo,backendName:"webgl",kernelFunc:W8},XZ=z3+`
return max(a, b);
`,KZ=`
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);
`+il+`
return result;
`,YZ=ha({opSnippet:XZ,packedOpSnippet:KZ,cpuKernelImpl:JH}),ZZ={kernelName:lo,backendName:"webgl",kernelFunc:YZ};function JZ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;qu(r,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(C.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=C.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))return en({inputs:{x:r},backend:a});let c=new ap(p,"max",!1);return a.runWebGLProgram(c,[r],r.dtype)}var QZ={kernelName:uo,backendName:"webgl",kernelFunc:JZ};function eJ(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=C.computePool3DInfo(r.shape,s,i,p,o,u,l),d=new W3(c,"max",!1);return a.runWebGLProgram(d,[r],r.dtype)}var tJ={kernelName:ku,backendName:"webgl",kernelFunc:eJ},aJ=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 * ${s} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
setOutput(dotProd);
}
`}},nJ=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,a=e.strideHeight,n=e.strideWidth,r=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,p=o-1-e.padInfo.front,c=l-1-e.padInfo.top,d=u-1-e.padInfo.left,h=o*l*u-1;this.userCode=`
const ivec3 pads = ivec3(${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 rJ(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=C.computePool3DInfo(i.shape,o,l,c,u,p),h=new W3(d,"max",!0),m=a.runWebGLProgram(h,[i],i.dtype),f=new nJ(d),g=a.runWebGLProgram(f,[r,m],i.dtype);return a.disposeIntermediateTensorInfo(m),g}var sJ={kernelName:kp,backendName:"webgl",kernelFunc:rJ};function iJ(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s,output:i}=t,o=s;qu([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:p,dimRoundingMode:c}=n,d=C.computePool2DInfo(o.shape,l,u,1,p,c),h=!0,m=new ap(d,"max",h),f=a.runWebGLProgram(m,[o],o.dtype),g=new aJ(d),y=a.runWebGLProgram(g,[r,f],o.dtype);return a.disposeIntermediateTensorInfo(f),y}var oJ={kernelName:wp,backendName:"webgl",kernelFunc:iJ};function lJ(e,t,a,n){let r=new ap(a,"max",!1),s=n.runWebGLProgram(r,[e],"float32");r=new ap(a,"max",!0,!0,t);let i=n.runWebGLProgram(r,[e],"float32");return[s,i]}var uJ={kernelName:Iu,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(C.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let p=C.computePool2DInfo(n.shape,r,s,u,i),[c,d]=lJ(n,o,p,l);return[c,d]}};function dJ(e,t,a,n){let r=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/r,i=pe({inputs:{x:e},attrs:{shape:[s,r]},backend:n}),o=ol(i,"float32","mean",n),l=pe({inputs:{x:o},attrs:{shape:a},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}var pJ={kernelName:po,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=C.getAxesPermutation(u,o),c=p!=null,d=i.shouldExecuteOnCPU([n]),h=[],m=n;if(c){if(d){let A=i.texData.get(m.dataId).values,b=new Array(o);for(let T=0;T<b.length;T++)b[T]=n.shape[p[T]];let w=O3(A,n.shape,n.dtype,p,b);m=i.makeTensorInfo(b,n.dtype);let I=i.texData.get(m.dataId);I.values=w}else m=s0(n,p,i);h.push(m),u=C.getInnerMostAxes(u.length,o)}C.assertAxesAreInnerMostDims("sum",u,o);let[f,g]=C.computeOutAndReduceShapes(m.shape,u),y=f;r&&(y=C.expandShapeToKeepDim(f,l));let x=dJ(m,g,y,i);for(let A of h)i.disposeIntermediateTensorInfo(A);return x}};function cJ(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=C.getAxesPermutation(u,o),c=r;p!=null&&(c=Ca({inputs:{x:r},backend:a,attrs:{perm:p}}),u=C.getInnerMostAxes(u.length,r.shape.length)),C.assertAxesAreInnerMostDims("min",u,o);let[d,h]=C.computeOutAndReduceShapes(c.shape,u),m=v.sizeFromShape(h),f=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,m]}}),g=ol(f,f.dtype,"min",a),y;if(i){let x=C.expandShapeToKeepDim(d,l);y=pe({inputs:{x:g},backend:a,attrs:{shape:x}})}else y=pe({inputs:{x:g},backend:a,attrs:{shape:d}});return a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(g),p!=null&&a.disposeIntermediateTensorInfo(c),y}var hJ={kernelName:co,backendName:"webgl",kernelFunc:cJ},mJ=z3+`
return min(a, b);
`,fJ=`
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);
`+il+`
return result;
`,gJ=ha({opSnippet:mJ,packedOpSnippet:fJ,cpuKernelImpl:QH}),yJ={kernelName:ho,backendName:"webgl",kernelFunc:gJ},xJ=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=ft(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}));
}
`}},AJ=class{constructor(e,t,a){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((h,m)=>h[0]+e[m]+h[1]);let n=e.length,r=ft(n),s=t.map(h=>h[0]).join(","),i=t.map((h,m)=>h[0]+e[m]).join(","),o=ka("rc",n),l=ka("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);
}
`}},bJ=({inputs:e,backend:t,attrs:a})=>{let{x:n}=e,{paddings:r,mode:s}=a,i=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new AJ(n.shape,r,s):new xJ(n.shape,r,s);return t.runWebGLProgram(i,[n],n.dtype)},vJ={kernelName:mo,backendName:"webgl",kernelFunc:bJ},wJ=`if (b == 0.0) return NAN;
return mod(a, b);`,kJ=`
vec4 result = mod(a, b);
bvec4 isNaN = equal(b, vec4(0.0));
`+il+`
return result;
`,IJ=ha({opSnippet:wJ,packedOpSnippet:kJ}),SJ={kernelName:fo,backendName:"webgl",kernelFunc:IJ},CJ=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}));
}
`}},TJ=`
if (a == b) {
return 1.0;
};
return a / b;`,NJ=`
// 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;
`,B8=ha({opSnippet:TJ,packedOpSnippet:NJ,checkOutOfBounds:!0}),RJ={kernelName:_i,backendName:"webgl",kernelFunc:B8},H5="return a - b;",V8=ha({opSnippet:H5,packedOpSnippet:H5,supportsComplex:!0,cpuKernelImpl:bj}),EJ={kernelName:Ko,backendName:"webgl",kernelFunc:V8};function U8(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{dim:s}=n,i=v.parseAxisParam([s],r.shape),o=W8({inputs:{x:r},backend:a,attrs:{reductionIndices:i,keepDims:!1}}),l=C.expandShapeToKeepDim(o.shape,i),u=pe({inputs:{x:o},backend:a,attrs:{shape:l}}),p=V8({inputs:{a:r,b:u},backend:a}),c=O8({inputs:{x:p},backend:a}),d=i0({inputs:{x:c},backend:a,attrs:{axis:i,keepDims:!1}}),h=pe({inputs:{x:d},backend:a,attrs:{shape:l}}),m=B8({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),m}var MJ={kernelName:Ho,backendName:"webgl",kernelFunc:U8};function $J(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n,l=o?r:U8({inputs:{logits:r},backend:a,attrs:{dim:r.shape.length-1}}),u=l.shape[0],p=l.shape[1],c=new CJ(u,p,s),d=[[i]],h=a.runWebGLProgram(c,[l],"int32",d);return o||a.disposeIntermediateTensorInfo(l),h}var PJ={kernelName:go,backendName:"webgl",kernelFunc:$J},_J=Mn+`
return -x;
`,FJ=`
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 DJ(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])){let s=a.texData.get(n.dataId),[i,o]=tj(s.values,n.shape,n.dtype);return a.makeTensorInfo(o,n.dtype,i)}let r;return B().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new qr(n.shape,FJ):r=new Zn(n.shape,_J),a.runWebGLProgram(r,[n],n.dtype)}var OJ={kernelName:Su,backendName:"webgl",kernelFunc:DJ},zJ=En.nonMaxSuppressionV3Impl;function LJ(e){C.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}=zJ(u,p,i,o,l);return a.makeTensorInfo([c.length],"int32",new Int32Array(c))}var WJ={kernelName:Ao,backendName:"webgl",kernelFunc:LJ},BJ=En.nonMaxSuppressionV4Impl;function VJ(e){C.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}=BJ(p,c,i,o,l,u);return[a.makeTensorInfo([d.length],"int32",new Int32Array(d)),a.makeTensorInfo([],"int32",new Int32Array([h]))]}var UJ={kernelName:Cu,backendName:"webgl",kernelFunc:VJ},GJ=En.nonMaxSuppressionV5Impl;function HJ(e){C.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,m=l,f=u,{selectedIndices:g,selectedScores:y}=GJ(p,c,d,h,m,f);return[a.makeTensorInfo([g.length],"int32",new Int32Array(g)),a.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var jJ={kernelName:bo,backendName:"webgl",kernelFunc:HJ},qJ=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)));
}
`}},XJ=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 qJ(u,i,o,l),c=pe({inputs:{x:r},backend:a,attrs:{shape:[u]}}),d=a.runWebGLProgram(p,[c],s);a.disposeIntermediateTensorInfo(c);let h=[...r.shape,i],m=pe({inputs:{x:d},backend:a,attrs:{shape:h}});return a.disposeIntermediateTensorInfo(d),m},KJ={kernelName:vo,backendName:"webgl",kernelFunc:XJ};function Sh(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="complex64"){let r=Qp({inputs:{input:n},backend:a}),s=Sh({inputs:{x:r},backend:a}),i=o0({inputs:{input:n},backend:a}),o=Sh({inputs:{x:i},backend:a}),l=fs({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return ec({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:a})}var YJ={kernelName:Vu,backendName:"webgl",kernelFunc:Sh};function G8(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=Qp({inputs:{input:n},backend:a}),s=G8({inputs:{x:r},backend:a}),i=o0({inputs:{input:n},backend:a}),o=Sh({inputs:{x:i},backend:a}),l=fs({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return ec({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:a})}var ZJ={kernelName:Tu,backendName:"webgl",kernelFunc:G8};function JJ(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return B1({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=B1({inputs:{input:p},backend:a,attrs:{dim:r}});return o.push(c),c}),u=R8({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(p=>a.disposeIntermediateTensorInfo(p)),u}var QJ={kernelName:Nu,backendName:"webgl",kernelFunc:JJ},eQ=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=ft(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}));
}
}
`}},tQ=class{constructor(e,t,a){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((m,f)=>m[0]+e[f]+m[1]);let n=e.length,r=ft(n),s=t.map(m=>m[0]).join(","),i=t.map((m,f)=>m[0]+e[f]).join(","),o=ka("rc",n),l=ka("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 m=0,f=n===1?2:4;m<f;m++)h+=`
${c[m]}
if (${d}) {
result[${m}] = float(value);
} else {
${r} source = rc - start;
result[${m}] = 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);
}
`}},H8=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 ec({backend:a,attrs:{shape:u,value:i,dtype:r.dtype}})}let o=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new tQ(r.shape,s,i):new eQ(r.shape,s,i),l=[[i]];return a.runWebGLProgram(o,[r],r.dtype,l)},aQ={kernelName:wo,backendName:"webgl",kernelFunc:H8},nQ=`
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);
`,rQ=`
// 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);
`+il+`
return result;
`,sQ=ha({opSnippet:nQ,packedOpSnippet:rQ}),iQ={kernelName:ko,backendName:"webgl",kernelFunc:sQ};function oQ(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=C.getAxesPermutation(p,o),d=r;c!=null&&(d=Ca({inputs:{x:r},backend:a,attrs:{perm:c}}),p=C.getInnerMostAxes(p.length,o),l.push(d)),C.assertAxesAreInnerMostDims("prod",p,o);let h;if(a.shouldExecuteOnCPU([d])){let m=a.texData.get(d.dataId).values,{outVals:f,outShape:g,outDtype:y}=nj(d.shape,d.dtype,m,p);h=a.makeTensorInfo(g,y,f)}else{let[m,f]=C.computeOutAndReduceShapes(d.shape,p),g=v.sizeFromShape(f),y=pe({inputs:{x:d},backend:a,attrs:{shape:[-1,g]}}),x=_p(r.dtype),A=ol(y,x,"prod",a);h=pe({inputs:{x:A},backend:a,attrs:{shape:m}}),l.push(y),l.push(A)}if(i){l.push(h);let m=C.expandShapeToKeepDim(h.shape,u);h=pe({inputs:{x:h},backend:a,attrs:{shape:m}})}return l.forEach(m=>a.disposeIntermediateTensorInfo(m)),h}var lQ={kernelName:So,backendName:"webgl",kernelFunc:oQ};function uQ(e){let{inputs:t,backend:a,attrs:n}=e,{paramsNestedSplits:r,paramsDenseValues:s,indices:i}=t,{outputRaggedRank:o}=n,l=r.map(y=>a.readSync(y.dataId)),u=r.map(y=>y.shape),p=a.readSync(s.dataId),c=a.readSync(i.dataId),[d,h,m]=rj(l,u,p,s.shape,s.dtype,c,i.shape,o),f=d.map(y=>a.makeTensorInfo([y.length],"int32",y)),g=a.makeTensorInfo(m,s.dtype,h);return f.concat([g])}var dQ={kernelName:$h,backendName:"webgl",kernelFunc:uQ};function pQ(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]=sj(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 cQ={kernelName:Ph,backendName:"webgl",kernelFunc:pQ};function hQ(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),[m,f]=ij(u,r.shape,p,s.shape,s.dtype,c,i.shape,d,h,l);return a.makeTensorInfo(m,s.dtype,f)}var mQ={kernelName:_h,backendName:"webgl",kernelFunc:hQ},j8=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=oj(n,r,s,i);return t.makeTensorInfo([o.length],i,o)},fQ={kernelName:Ru,backendName:"webgl",kernelFunc:j8},gQ="return 1.0 / x;",yQ=tt({opSnippet:gQ}),xQ={kernelName:Co,backendName:"webgl",kernelFunc:yQ},AQ=Mn+`
return (x < 0.0) ? 0.0 : x;
`,bQ=`
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;
`,vQ=tt({opSnippet:AQ,packedOpSnippet:bQ}),wQ={kernelName:To,backendName:"webgl",kernelFunc:vQ},kQ=Mn+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,IQ=`
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;
`,SQ=tt({opSnippet:kQ,packedOpSnippet:IQ}),CQ={kernelName:Eo,backendName:"webgl",kernelFunc:SQ},TQ=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);
}
`}},NQ=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 RQ(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,p=B().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new NQ(r.shape,l,u,s,i):new TQ(r.shape,l,u,s,i);return a.runWebGLProgram(p,[r],"float32")}var EQ={kernelName:Ro,backendName:"webgl",kernelFunc:RQ},MQ=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,m=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(${m});
// 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 $Q(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=new MQ(s.shape,r.shape,i);return a.runWebGLProgram(o,[s],s.dtype)}var PQ={kernelName:$u,backendName:"webgl",kernelFunc:$Q},_Q=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);
}
`}},FQ=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 < ${a-1};
vec4 newValue = vec4(
getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);
setOutput(newValue);
}
`}};function DQ(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,p=B().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new FQ(r.shape,l,u,s,i):new _Q(r.shape,l,u,s,i);return a.runWebGLProgram(p,[r],r.dtype)}var OQ={kernelName:No,backendName:"webgl",kernelFunc:DQ},zQ=class{constructor(e,t,a){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,r]=t,[,s,i]=e,o=[a&&s>1?n-1:n,a&&i>1?r-1:r],l=[a&&s>1?s-1:s,a&&i>1?i-1:i],u=o[0]/l[0],p=o[1]/l[1],c=1/u,d=1/p,h=Math.ceil(c)*2+2,m=Math.ceil(d)*2+2;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
int r = coords[1];
int c = coords[2];
float accumulator = 0.0;
const float heightScale = float(${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(${m});
// 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),
${a} ? float(round(sourceFracCol)) :
float(floor(sourceFracCol))));
if (r == sourceNearestRow && c == sourceNearestCol) {
accumulator += getDy(b, dyR, dyC, d);
}
}
}
// End loop over dy
setOutput(accumulator);
}
`}};function LQ(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=new zQ(s.shape,r.shape,i);return a.runWebGLProgram(o,[s],s.dtype)}var WQ={kernelName:Mu,backendName:"webgl",kernelFunc:LQ},BQ=class{constructor(e,t){this.variableNames=["x"];let a=e.length;if(a>4)throw new Error(`WebGL backend: Reverse of rank-${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=ft(a);this.userCode=`
void main() {
${s} coords = getOutputCoords();
setOutput(getX(${r}));
}
`}},VQ=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-${a} tensor is not yet supported`);this.outputShape=e;let n=ka("rc",a),r=`${n[a-1]} + 1 < ${this.outputShape[a-1]}`,s=`${n[a-2]} + 1 < ${this.outputShape[a-2]}`,i=ft(a);a===1?this.userCode=`
void main(){
int rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = getChannel(getX(${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 = ${p(n.slice())};
}
}
setOutput(result);
}
`;function o(h){return c(h)}function l(h){return h[a-1]="("+h[a-1]+" + 1)",c(h)}function u(h){return h[a-2]="("+h[a-2]+" + 1)",c(h)}function p(h){return h[a-1]="("+h[a-1]+" + 1)",h[a-2]="("+h[a-2]+" + 1)",c(h)}function c(h){let m=e.map((y,x)=>d(x,h)),f=m.join(","),g=m.slice(-2).join(",");return`getChannel(getX(${f}), vec2(${g}))`}function d(h,m){return t.indexOf(h)!==-1&&e[h]!==1?`${e[h]} - ${m[h]} - 1`:`${m[h]}`}}};function UQ(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 en({inputs:{x:r},backend:a});let l=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new VQ(r.shape,o):new BQ(r.shape,o);return a.runWebGLProgram(l,[r],r.dtype)}var GQ={kernelName:Mo,backendName:"webgl",kernelFunc:UQ},HQ=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 < ${a}) {
outputValue = getImage(coords[0], coordY, coordX, coords[3]);
}
setOutput(outputValue);
}
`}},jQ={kernelName:el,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{image:n}=e,{radians:r,fillValue:s,center:i}=t,o=a,l=new HQ(n.shape,s),[u,p]=C.getImageCenter(i,n.shape[1],n.shape[2]),c=[[u,p,Math.sin(r),Math.cos(r)]];return o.runWebGLProgram(l,[n],n.dtype,c)}},qQ=`
// OpenGL ES does not support round function.
// The algorithm is based on banker's rounding.
float base = floor(x);
if ((x - base) < 0.5) {
return floor(x);
} else if ((x - base) > 0.5) {
return ceil(x);
} else {
if (mod(base, 2.0) == 0.0) {
return base;
} else {
return base + 1.0;
}
}
`,XQ=tt({opSnippet:qQ}),KQ={kernelName:$o,backendName:"webgl",kernelFunc:XQ},YQ="return inversesqrt(x);",ZQ=tt({opSnippet:YQ,cpuKernelImpl:lj}),JQ={kernelName:Po,backendName:"webgl",kernelFunc:ZQ},B3=class{constructor(e,t,a,n,r,s,i=!0,o=!1){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let l=ft(r.length),u=ft(s.length),p="";a===1?p="i":a===2&&(p="i, j");let c=`getIndices(${p})`,d="";n===1?d="i":n===2&&(d="i, coords[1]");let h=`getUpdates(${d})`,m="";o&&(m="coords[0], coords[1]");let f=`getDefaultValue(${m})`,g=t>1?"strides[j]":"strides";this.userCode=`
${l} strides = ${l}(${r});
void main() {
${u} coords = getOutputCoords();
float sum = 0.0;
bool found = false;
for (int i = 0; i < ${e}; i++) {
int flattenedIndex = 0;
for (int j = 0; j < ${t}; j++) {
int index = round(${c});
flattenedIndex += index * ${g};
}
if (flattenedIndex == coords[0]) {
sum += ${h};
found = true;
}
}
setOutput(mix(${f}, sum, float(found)));
}
`}},QQ=class{constructor(e,t,a,n,r,s,i=!0,o=!1){this.variableNames=["updates","indices","defaultValue"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=s;let l=ft(r.length),u=ft(s.length),p="";a===1?p="i":a===2&&(p="i, j");let c=`getIndices(${p})`,d="";n===1?d="i":n===2&&(d="i, coords[1]");let h=`getUpdates(${d})`,m="";o&&(m="coords[0], coords[1]");let f=`getDefaultValue(${m})`,g=t>1?"strides[j]":"strides",y=t>1?"strides[j + 1]":"strides";this.userCode=`
${l} strides = ${l}(${r});
void main() {
${u} coords = getOutputCoords();
vec4 sum = vec4(0.);
vec4 found = vec4(0.);
for (int i = 0; i < ${e}; i+=2) {
ivec2 flattenedIndex = ivec2(0);
for (int j = 0; j < ${t}; j+=2) {
ivec4 index = round(${c});
flattenedIndex += index.xz * ${g};
if (j + 1 < ${t}) {
flattenedIndex += index.yw * ${y};
}
}
if (flattenedIndex[0] == coords[0] || flattenedIndex[1] == coords[0] ||
flattenedIndex[0] == coords[0] + 1 || flattenedIndex[1] == coords[0] + 1) {
vec4 updVals = ${h};
if (flattenedIndex[0] == coords[0]) {
sum.xy += updVals.xy;
found.xy = vec2(1.);
} else if (flattenedIndex[0] == coords[0] + 1) {
sum.zw += updVals.xy;
found.zw = vec2(1.);
}
if (flattenedIndex[1] == coords[0]) {
sum.xy += updVals.zw;
found.xy = vec2(1.);
} else if (flattenedIndex[1] == coords[0] + 1) {
sum.zw += updVals.zw;
found.zw = vec2(1.);
}
}
}
setOutput(mix(${f}, sum, found));
}
`}};function eee(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}=C.calculateShapes(s,r,i),d=[c/u,u];if(c===0)return a.makeTensorInfo(i,r.dtype);let h=pe({inputs:{x:r},backend:a,attrs:{shape:[l,o]}}),m=pe({inputs:{x:s},backend:a,attrs:{shape:[l,u]}}),f=a.makeTensorInfo([],"float32",new Float32Array([0])),g;B().getBool("WEBGL_PACK")?g=new QQ(l,o,h.shape.length,m.shape.length,p,d):g=new B3(l,o,h.shape.length,m.shape.length,p,d);let y=a.runWebGLProgram(g,[m,h,f],m.dtype),x=pe({inputs:{x:y},backend:a,attrs:{shape:i}});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(y),a.disposeIntermediateTensorInfo(f),x}var tee={kernelName:_o,backendName:"webgl",kernelFunc:eee},aee=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=B().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 nee(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n,o=new aee(r.shape[0],r.shape[1],s.shape[1],i),l=[[r.shape[1]]];return a.runWebGLProgram(o,[r,s],"int32",l)}var ree={kernelName:Do,backendName:"webgl",kernelFunc:nee},see=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=ft(a);this.userCode=`
void main() {
${s} resRC = getOutputCoords();
float cVal = getC(${n});
if (cVal >= 1.0) {
setOutput(getA(${r}));
} else {
setOutput(getB(${r}));
}
}
`}};function iee(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t,i=new see(n.shape.length,r.shape,r.shape.length);return a.runWebGLProgram(i,[n,r,s],pa(r.dtype,s.dtype))}var oee={kernelName:Pu,backendName:"webgl",kernelFunc:iee},lee=`
// Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
// see: https://arxiv.org/abs/1706.02515
float scaleAlpha = ${C.SELU_SCALEALPHA};
float scale = ${C.SELU_SCALE};
return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,uee=tt({opSnippet:lee}),dee={kernelName:Oo,backendName:"webgl",kernelFunc:uee},pee=Qu+`
return 1.0 / (1.0 + exp(-1.0 * x));
`,cee=`
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;
`,hee=tt({opSnippet:pee,packedOpSnippet:cee,cpuKernelImpl:dj}),mee={kernelName:Bo,backendName:"webgl",kernelFunc:hee},fee=`
if (isnan(x)) { return 0.0; }
return sign(x);
`,gee=tt({opSnippet:fee}),yee={kernelName:Wo,backendName:"webgl",kernelFunc:gee},xee=Qu+`
return sin(x);
`,Aee=`
vec4 result = sin(x);
bvec4 isNaN = isnan(x);
${il}
return result;
`,bee=tt({opSnippet:xee,packedOpSnippet:Aee}),vee={kernelName:zo,backendName:"webgl",kernelFunc:bee},wee=`
float e2x = exp(x);
return (e2x - 1.0 / e2x) / 2.0;
`,kee=tt({opSnippet:wee}),Iee={kernelName:Lo,backendName:"webgl",kernelFunc:kee},See=`
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;
`,Cee=tt({opSnippet:See}),Tee={kernelName:Vo,backendName:"webgl",kernelFunc:Cee},Nee=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((y,x)=>y*x),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<r.shape.length;++y)l.push([0,0]);let u=[],p=H8({inputs:{x:r},backend:a,attrs:{paddings:l,constantValue:0}}),c=C.getReshaped(p.shape,s,o,!1),d=C.getPermuted(c.length,s.length,!1),h=C.getReshapedPermuted(p.shape,s,o,!1),m=pe({inputs:{x:p},backend:a,attrs:{shape:c}}),f=Ca({inputs:{x:m},backend:a,attrs:{perm:d}}),g=pe({inputs:{x:f},backend:a,attrs:{shape:h}});return u.push(p),u.push(m),u.push(f),u.forEach(y=>a.disposeIntermediateTensorInfo(y)),g},Ree={kernelName:Fu,backendName:"webgl",kernelFunc:Nee};function Eee(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:
${n.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw:
${r.shape}`);if(i.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
${i.shape}`);let o=a.readSync(n.dataId),l=a.readSync(r.dataId),u=a.readSync(s.dataId),p=a.readSync(i.dataId)[0],[c,d,h,m,f]=cj(o,n.shape,n.dtype,l,r.dtype,u,p);return[a.makeTensorInfo(d,n.dtype,c),a.makeTensorInfo([d[0]],r.dtype,h),a.makeTensorInfo([m.length],"bool",new Uint8Array(m.map(g=>Number(g)))),a.makeTensorInfo([f.length],n.dtype,new Int32Array(f))]}var Mee={kernelName:Sp,backendName:"webgl",kernelFunc:Eee};function $ee(e){let{inputs:t,backend:a}=e,{inputIndices:n,inputShape:r,newShape:s}=t;if(n.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${n.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${r.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let i=Array.from(a.readSync(r.dataId)),o=a.readSync(n.dataId),l=Array.from(a.readSync(s.dataId)),[u,p,c]=hj(o,n.shape,n.dtype,i,l);return[a.makeTensorInfo(p,n.dtype,u),a.makeTensorInfo([c.length],s.dtype,new Int32Array(c))]}var Pee={kernelName:Ou,backendName:"webgl",kernelFunc:$ee};function _ee(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
${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]=m8(i,n.shape,n.dtype,o,l,!0);return a.makeTensorInfo(p,n.dtype,u)}var Fee={kernelName:zu,backendName:"webgl",kernelFunc:_ee};function Dee(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${s.shape}`);let i=a.readSync(n.dataId),o=a.readSync(r.dataId),l=a.readSync(s.dataId),[u,p]=m8(i,n.shape,n.dtype,o,l);return a.makeTensorInfo(p,n.dtype,u)}var Oee={kernelName:Lu,backendName:"webgl",kernelFunc:Dee};function zee(e){let{inputs:t,backend:a,attrs:n}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=t,{outputShape:o}=n,{sliceRank:l,numUpdates:u,sliceSize:p,strides:c,outputSize:d}=C.calculateShapes(s,r,o),h=!1;if(s.dtype==="string"){let y=a.bufferSync(r),x=a.bufferSync(s),A=v.decodeString(a.readSync(i.dataId)[0]),b=uj(y,x,o,d,p,u,l,c,A,h);return a.makeTensorInfo(o,b.dtype,b.values)}let m=new B3(u,l,r.shape.length,s.shape.length,c,[d,1],h),f=a.runWebGLProgram(m,[s,r,i],s.dtype),g=pe({inputs:{x:f},backend:a,attrs:{shape:o}});return a.disposeIntermediateTensorInfo(f),g}var Lee={kernelName:jo,backendName:"webgl",kernelFunc:zee};function Wee(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=n,o=v.parseAxisParam(i,r.shape)[0],l=C.prepareSplitSize(r,s,o),u=r.shape.length,p=new Array(u).fill(0),c=r.shape.slice();return l.map(d=>{let h=[...c];h[o]=d;let m=ed({inputs:{x:r},backend:a,attrs:{begin:p,size:h}});return p[o]+=d,m})}var Bee={kernelName:Du,backendName:"webgl",kernelFunc:Wee},j5="return sqrt(x);",Vee=tt({opSnippet:j5,packedOpSnippet:j5,cpuKernelImpl:mj}),Uee={kernelName:Uo,backendName:"webgl",kernelFunc:Vee},Gee="return x * x;",Hee=tt({opSnippet:Gee}),jee={kernelName:Cp,backendName:"webgl",kernelFunc:Hee},q5="return (a - b) * (a - b);",qee=ha({opSnippet:q5,packedOpSnippet:q5}),Xee={kernelName:qo,backendName:"webgl",kernelFunc:qee};function Kee(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;if(r.dtype!=="string")throw new Error("Input must be of datatype string");let s=a.readSync(r.dataId),i=C.fromUint8ToStringArray(s),o=fj(i,"string",n);return a.makeTensorInfo(r.shape,"string",o)}var Yee={kernelName:Tp,backendName:"webgl",kernelFunc:Kee};function Zee({inputs:e,attrs:t,backend:a}){let{x:n}=e,r=Mn+`
return x > 0.0 ? 1.0 : float(${t.alpha});
`,s=new Zn(n.shape,r);return a.runWebGLProgram(s,[n],n.dtype)}var Jee={kernelName:ps,backendName:"webgl",kernelFunc:Zee},Qee=class{constructor(e,t,a){this.variableNames=["x"],this.outputShape=a;let n=a.length,r=ft(a.length),s=ft(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 ete(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:m,isIdentity:f,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Nt.sliceInfo(r.shape,s,i,o,l,u,p,c,d),w;if(f)w=pe({inputs:{x:r},backend:a,attrs:{shape:m}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let T=Nt.computeOutShape(x,A,b),N=ed({inputs:{x:r},backend:a,attrs:{begin:x,size:T}});w=pe({inputs:{x:N},backend:a,attrs:{shape:m}}),a.disposeIntermediateTensorInfo(N)}else if(a.shouldExecuteOnCPU([r])){let T=a.readSync(r.dataId),N=_e(r.shape,r.dtype,T),M=gj(h,N,b,x);w=a.makeTensorInfo(m,r.dtype,M.values)}else{let T=new Qee(x,b,h);w=a.runWebGLProgram(T,[r],r.dtype)}let I=pe({inputs:{x:w},backend:a,attrs:{shape:m}});return a.disposeIntermediateTensorInfo(w),I}var tte={kernelName:Xo,backendName:"webgl",kernelFunc:ete};function ate(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),[m,f]=yj(d,h,r,s,i,o,l,u);return[a.makeTensorInfo([m.length],"string",m),a.makeTensorInfo(c.shape,"int32",f)]}var nte={kernelName:Wu,backendName:"webgl",kernelFunc:ate};function rte(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]=xj(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 ste={kernelName:Np,backendName:"webgl",kernelFunc:rte};function ite(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=Aj(i,r);return a.makeTensorInfo(s.shape,"int32",o)}var ote={kernelName:Rp,backendName:"webgl",kernelFunc:ite},lte="return tan(x);",ute=tt({opSnippet:lte}),dte={kernelName:Yo,backendName:"webgl",kernelFunc:ute},pte=`
float e2x = exp(-2.0 * abs(x));
return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,cte=tt({opSnippet:pte}),hte={kernelName:Zo,backendName:"webgl",kernelFunc:cte};function mte(e){let{inputs:t,backend:a,attrs:n}=e,{tensor:r,indices:s,updates:i}=t,{}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:c}=C.calculateShapes(i,s,r.shape),d=[c/u,u];if(c===0)return a.makeTensorInfo(r.shape,s.dtype);let h=pe({inputs:{x:s},backend:a,attrs:{shape:[l,o]}}),m=pe({inputs:{x:i},backend:a,attrs:{shape:[l,u]}}),f=pe({inputs:{x:r},backend:a,attrs:{shape:d}}),g=new B3(l,o,h.shape.length,m.shape.length,p,d,!1,!0),y=a.runWebGLProgram(g,[m,h,f],f.dtype),x=pe({inputs:{x:y},backend:a,attrs:{shape:r.shape}});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(y),x}var fte={kernelName:Fo,backendName:"webgl",kernelFunc:mte},gte=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=ft(this.rank),r=yte(e);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
setOutput(getA(${r}));
}
`}};function yte(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 q8(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=_e(r.shape,r.dtype,l),p=vj(u,s);return a.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new gte(r.shape,s);return a.runWebGLProgram(i,[r],r.dtype)}var xte={kernelName:ds,backendName:"webgl",kernelFunc:q8},Ate=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));
}
}
`}},bte=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 zs(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function X5(e){let t=1;for(;t<e;)t*=2;return t}function vte(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{k:s,sorted:i}=n,o=B().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=B().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=r.shape,p=u[u.length-1];if(a.shouldExecuteOnCPU([r])||p<o||s>l){let M=a.readSync(r.dataId),[$,E]=wj(M,u,r.dtype,s,i);return[a.makeTensorInfo($.shape,$.dtype,$.values),a.makeTensorInfo(E.shape,E.dtype,E.values)]}if(s===0)return u[u.length-1]=0,[a.makeTensorInfo(u,r.dtype,[]),a.makeTensorInfo(u,"int32",[])];if(p===1)return[r,ec({attrs:{shape:u,dtype:"int32",value:0},backend:a})];let c=a.texData.get(r.dataId),d=c!==null&&c.isPacked,h=d?a.unpackTensor(r):r,m=v.sizeFromShape(u)/p,f=pe({inputs:{x:h},attrs:{shape:[m,p]},backend:a});d&&zs(a,h);let g=X5(s),y=X5(p),x=null,A=()=>x===null?[f,f]:[f,x],b=(M,$,E)=>{let S=A(),_=new Ate(E),O=[[p],[x===null?1:0],[Number.NEGATIVE_INFINITY],[M],[$]],W=x;x=a.runWebGLProgram(_,S,"int32",O),zs(a,W)};for(let M=1;M<g;M*=2){let $=M*2;for(let E=M;E>=1;E/=2)b($,E,[m,y])}for(let M=y;M>g;M/=2){let $=A(),E=new bte([m,M/2]),S=[[p],[x===null?1:0],[g]],_=x;x=a.runWebGLProgram(E,$,"int32",S),zs(a,_);let O=g/2,W=O*2;for(let P=O;P>=1;P/=2)b(W,P,x.shape)}let w=x;x=ed({inputs:{x},backend:a,attrs:{begin:0,size:[m,s]}}),zs(a,w);let I=L8({inputs:{x:f,indices:x},backend:a,attrs:{axis:1,batchDims:1}});zs(a,f);let T=u.slice(0,-1);T.push(s),w=x,x=pe({inputs:{x},attrs:{shape:T},backend:a}),zs(a,w);let N=I;return I=pe({inputs:{x:I},attrs:{shape:T},backend:a}),zs(a,N),[I,x]}var wte={kernelName:Jo,backendName:"webgl",kernelFunc:vte},kte=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 Ite(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,[m,f]=u!=null?u:[c,d],g=[p,m,f,h],y=new kte(c,d,i,o,l,g);return a.runWebGLProgram(y,[r,s],"float32")}var Ste={kernelName:Qo,backendName:"webgl",kernelFunc:Ite};function Cte(e){let{inputs:t,attrs:a,backend:n}=e,{axis:r}=a,{x:s}=t;qu(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}=kj(i,r,s.shape,s.dtype);return[n.makeTensorInfo(l,s.dtype,o),n.makeTensorInfo([u.length],"int32",u)]}var Tte={kernelName:Ep,backendName:"webgl",kernelFunc:Cte};function Nte(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 f=0;f<o;f++)f!==s&&(u[p++]=i.shape[f]);let c=[],d=new Array(o).fill(0),h=i.shape.slice();h[s]=1;let m=new Array(l);for(let f=0;f<m.length;f++){d[s]=f;let g=ed({inputs:{x:i},backend:a,attrs:{begin:d,size:h}}),y=pe({inputs:{x:g},backend:a,attrs:{shape:u}});m[f]=y,c.push(g)}return c.forEach(f=>a.disposeIntermediateTensorInfo(f)),m}var Rte={kernelName:Bu,backendName:"webgl",kernelFunc:Nte},Ete=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 Mte(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=C.getAxesPermutation([u],o),c=r;p!=null&&(c=Ca({inputs:{x:r},backend:a,attrs:{perm:p}}),l.push(c),u=C.getInnerMostAxes(1,o)[0]);let d=C.segment_util.computeOutShape(c.shape,u,i),h=v.sizeFromShape([c.shape[u]]),m=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,h]}});l.push(m);let f=_p(r.dtype),g=(b,w,I,T,N)=>{let M=b.shape[0],$=b.shape[1],E=C.segment_util.segOpComputeOptimalWindowSize($,N),S={windowSize:E,inSize:$,batchSize:M,numSegments:N},_=new Ete(S,w),O=a.compileAndRun(_,[b,I],T);if(l.push(O),O.shape[1]===N)return O;let W=j8({backend:a,attrs:{start:0,stop:N,step:1,dtype:"float32"}}),P=q8({inputs:{x:W},backend:a,attrs:{reps:[$/E]}});return l.push(W),l.push(P),g(O,w,P,T,N)},y=g(m,"unsortedSegmentSum",s,f,i),x=pe({inputs:{x:y},backend:a,attrs:{shape:d}}),A=x;if(p!=null){l.push(x);let b=C.getUndoAxesPermutation(p);A=Ca({inputs:{x:A},backend:a,attrs:{perm:b}})}return l.forEach(b=>a.disposeIntermediateTensorInfo(b)),A}var $te={kernelName:Mp,backendName:"webgl",kernelFunc:Mte},Pte=[gq,xq,vq,Iq,Cq,Rq,Mq,Pq,Oq,Lq,Vq,Hq,Xq,Jq,tX,nX,sX,uX,pX,hX,yX,IX,CX,EX,$X,zX,WX,GX,Qj,qX,JX,aK,lK,pK,hK,fK,yK,vK,IK,TK,RK,MK,PK,DK,zK,VK,GK,qK,YK,JK,aY,iY,dY,hY,gY,yY,AY,vY,kY,SY,TY,MY,_Y,OY,LY,VY,HY,KY,QY,Jj,tZ,YX,rZ,oZ,dZ,tq,mZ,xZ,bZ,IZ,TZ,MZ,_Z,zZ,VZ,HZ,qZ,ZZ,QZ,tJ,sJ,oJ,uJ,pJ,hJ,yJ,vJ,SJ,PJ,rq,OJ,WJ,UJ,jJ,_X,KJ,ZJ,QJ,aQ,iQ,nq,lQ,dQ,cQ,mQ,fQ,FX,RJ,xQ,wQ,CQ,iq,EQ,PQ,OQ,WQ,GQ,jQ,KQ,JQ,tee,ree,oee,dee,mee,yee,vee,Iee,wX,MJ,Tee,Ree,Mee,Pee,Fee,Oee,Lee,Bee,Uee,jee,Xee,Yee,Jee,tte,nte,ste,ote,EJ,hq,dte,hte,fte,xte,wte,Ste,mq,Tte,Rte,$te,YJ];for(let e of Pte)xn(e);var nt;(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"})(nt||(nt={}));var rp;(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"})(rp||(rp={}));var X8;function _te(e){X8=e.wasm.cwrap(Zr,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Fte(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,m=0;if(i!=null){let N=a.dataIdMap.get(i.dataId);if(N.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${N.shape.length}.`);m=N.id}let f=o==null?0:a.dataIdMap.get(o.dataId).id,g=rp[p];if(g==null)throw new Error(`${p} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?r.shape[2]:r.shape[1],x=u?s.shape[1]:s.shape[2],A=nl.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)),b=a.makeOutput([...A,y,x],r.dtype),w=a.dataIdMap.get(b.dataId).id,I=new Uint8Array(new Int32Array(r.shape).buffer),T=new Uint8Array(new Int32Array(s.shape).buffer);return X8(d,I,r.shape.length,h,T,s.shape.length,l,u,g,m,f,c||0,w),b}var Dte={kernelName:Zr,backendName:"wasm",setupFunc:_te,kernelFunc:Fte};function Qe(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,nt[o.dtype],p),u}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:r}}var Ote=Qe(ou),zte=Qe(oi),Lte=Qe(li);function Gt(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,m=C.assertAndGetBroadcastShape(u.shape,p.shape),f=o.makeOutput(m,h);if(v.sizeFromShape(m)===0)return f;let g=new Uint8Array(new Int32Array(u.shape).buffer),y=new Uint8Array(new Int32Array(p.shape).buffer),x=o.dataIdMap.get(f.dataId).id;return n(c,g,u.shape.length,d,y,p.shape.length,nt[u.dtype],x),f}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:s}}var Wte=!0,Bte=Gt(ls,Wte),K8;function Vte(e){K8=e.wasm.cwrap(ui,null,["array","number","number","number"])}function Ute(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 K8(s,r.length,nt[n.dtype],i),n}var Gte={kernelName:ui,backendName:"wasm",setupFunc:Vte,kernelFunc:Ute};function l0(e){let{inputs:{x:t},backend:a}=e;if(t.dtype==="string")return Ve(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 Hte={kernelName:qi,backendName:"wasm",kernelFunc:l0},Y8;function jte(e){Y8=e.wasm.cwrap(kr,null,["number","array","number","number","number","array","number"])}function os(e){let{inputs:t,backend:a,attrs:n}=e,[r,s]=Xte(t.x.shape,n.perm),i=!0;for(let m=0;m<s.length;m++)s[m]!==m&&(i=!1);let o=qte(t.x.shape,n.perm),l={dataId:t.x.dataId,shape:r,dtype:t.x.dtype};if(i){let m=l0({inputs:t,backend:a});return m.shape=o,m}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 Y8(p,h,l.shape.length,nt[l.dtype],c,d,s.length),u}function qte(e,t){let a=new Array(e.length);for(let n=0;n<a.length;n++)a[n]=e[t[n]];return a}function Xte(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 Kte={kernelName:kr,backendName:"wasm",kernelFunc:os,setupFunc:jte};function gs(e,t,a){let n=e.shape,r=e.shape.length,s=v.parseAxisParam(t,n),i=s,o=C.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=C.getInnerMostAxes(i.length,r),l=os({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 Z8;function Yte(e){Z8=e.wasm.cwrap(di,null,["number, number, number"])}function Zte(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}=gs(i,r,t);if(d){let x=t.dataIdMap.get(u.dataId).id;l=u,o=x}let h=l.shape.length;C.assertAxesAreInnerMostDims("all",p,h);let[m,f]=C.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(f),y=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;Z8(o,g,x)}if(d&&t.disposeData(u.dataId),s){let x=C.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var Jte={kernelName:di,backendName:"wasm",setupFunc:Yte,kernelFunc:Zte},J8;function Qte(e){J8=e.wasm.cwrap(pi,null,["number, number, number"])}function eae(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}=gs(i,r,t);if(d){let x=t.dataIdMap.get(u.dataId).id;l=u,o=x}let h=l.shape.length;C.assertAxesAreInnerMostDims("any",p,h);let[m,f]=C.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(f),y=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;J8(o,g,x)}if(d&&t.disposeData(u.dataId),s){let x=C.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var tae={kernelName:pi,backendName:"wasm",setupFunc:Qte,kernelFunc:eae};function Q8(e){let t;function a(r){t=r.wasm.cwrap(e,null,["number","number","number","number","number"])}function n(r){let{backend:s,inputs:i,attrs:o}=r,{axis:l}=o,{x:u}=i,p=s.dataIdMap.get(u.dataId).id,c=p,d=u,{transposed:h,axes:m,inputWasTransposed:f}=gs(u,l,s);if(f){let w=s.dataIdMap.get(h.dataId).id;w!==p&&(d=h,c=w)}let g=d.shape.slice(0,-1),y=s.makeOutput(g,"int32"),x=s.dataIdMap.get(y.dataId).id,A=v.sizeFromShape(y.shape),b=d.shape[m[0]];return t(c,nt[d.dtype],A,b,x),f&&s.disposeData(h.dataId),y}return{kernelName:e,backendName:"wasm",setupFunc:a,kernelFunc:n}}var aae=Q8(lu),nae=Q8(uu),rae=Qe(ci),sae=Qe(hi),iae=Qe(mi),oae=Gt(gi,!1),lae=Qe(fi),ew;function uae(e){ew=e.wasm.cwrap(yi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function dae(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=C.computePool2DInfo(r.shape,i,o,1,l,u),c=p.filterHeight,d=p.filterWidth,h=p.padInfo.top,m=p.padInfo.right,f=p.padInfo.bottom,g=p.padInfo.left,y=p.strideHeight,x=p.strideWidth,A=p.inChannels;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);if(p.dilationWidth!==1||p.dilationHeight!==1)throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${p.dilationHeight}, ${p.dilationWidth}].`);let b=n.makeOutput(p.outShape,"float32"),w=n.dataIdMap.get(b.dataId).id;return ew(s,r.shape[0],r.shape[1],r.shape[2],c,d,h,m,f,g,y,x,A,w),b}var pae={kernelName:yi,backendName:"wasm",setupFunc:uae,kernelFunc:dae},tw;function cae(e){tw=e.wasm.cwrap("AvgPool3D",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function hae(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n,p=C.computePool3DInfo(r.shape,s,i,1,o,l,u),c=a.makeOutput(p.outShape,r.dtype);return tw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),c}var mae={kernelName:du,backendName:"wasm",setupFunc:cae,kernelFunc:hae},aw;function fae(e){aw=e.wasm.cwrap("AvgPool3DGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function gae(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,p=C.computePool3DInfo(s.shape,i,o,1,l,u),c=a.makeOutput(s.shape,s.dtype);return aw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left,p.filterDepth,p.filterHeight,p.filterWidth),c}var yae={kernelName:pp,backendName:"wasm",setupFunc:fae,kernelFunc:gae},nw;function xae(e){nw=e.wasm.cwrap("AvgPoolGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Aae(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l}=n,u=C.computePool2DInfo(s.shape,i,o,1,l),p=a.makeOutput(s.shape,s.dtype);return nw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(p.dataId).id,u.batchSize,u.inChannels,u.inHeight,u.inWidth,u.outHeight,u.outWidth,u.strideHeight,u.strideWidth,u.dilationHeight,u.dilationWidth,u.effectiveFilterHeight,u.effectiveFilterWidth,u.padInfo.top,u.padInfo.left,u.filterHeight,u.filterWidth),p}var bae={kernelName:dp,backendName:"wasm",setupFunc:xae,kernelFunc:Aae};function La(e){let{inputs:t,attrs:a}=e,{x:n}=t,{shape:r}=a,s=v.sizeFromShape(n.shape),i=v.inferFromImplicitShape(r,s);return v.assert(s===v.sizeFromShape(i),()=>`new shape: ${i}, old shape: ${n.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(n.dataId),{dataId:n.dataId,shape:i,dtype:n.dtype}}var vae={kernelName:Eu,backendName:"wasm",kernelFunc:La},rw;function wae(e){rw=e.wasm.cwrap(xi,null,["number","array","number","number","array","number","number","number","number"])}function kae(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=r.shape.length,u=s.shape.length,p=i?r.shape[l-2]:r.shape[l-1],c=o?s.shape[u-1]:s.shape[u-2],d=i?r.shape[l-1]:r.shape[l-2],h=o?s.shape[u-2]:s.shape[u-1],m=r.shape.slice(0,-2),f=s.shape.slice(0,-2),g=v.sizeFromShape(m),y=v.sizeFromShape(f),x=nl.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)).concat([d,h]);v.assert(p===c,()=>`Error in matMul: inner shapes (${p}) and (${c}) of Tensors with shapes ${r.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let A=i?[g,p,d]:[g,d,p],b=o?[y,h,c]:[y,c,h],w=La({inputs:{x:r},backend:a,attrs:{shape:A}}),I=La({inputs:{x:s},backend:a,attrs:{shape:b}}),T=a.dataIdMap.get(w.dataId).id,N=a.dataIdMap.get(I.dataId).id,M=i?w.shape[2]:w.shape[1],$=o?I.shape[1]:I.shape[2],E=Math.max(g,y),S=a.makeOutput([E,M,$],w.dtype),_=a.dataIdMap.get(S.dataId).id,O=new Uint8Array(new Int32Array(w.shape).buffer),W=new Uint8Array(new Int32Array(I.shape).buffer);return rw(T,O,w.shape.length,N,W,I.shape.length,i,o,_),a.disposeData(w.dataId),a.disposeData(I.dataId),S.shape=x,S}var Iae={kernelName:xi,backendName:"wasm",setupFunc:wae,kernelFunc:kae};function si(e){let{inputs:{x:t},attrs:{begin:a,size:n},backend:r}=e,[s,i]=Nt.parseSliceParams(t,a,n),o=Nt.isSliceContinous(t.shape,s,i),l=r.readSync(t.dataId),u=r.makeOutput(i,t.dtype),p=v.computeStrides(t.shape),c=r.dataIdMap.get(u.dataId);if(o){let m=Nt.computeFlatOffset(s,p);return t.dtype==="string"?c.stringBytes=l.slice(m,m+v.sizeFromShape(i)):r.typedArrayFromHeap(u).set(l.subarray(m,m+v.sizeFromShape(i))),u}if(t.dtype==="string"){let m=Ah(l,s,i,t.shape,t.dtype);return c.stringBytes=m,u}let d=r.typedArrayFromHeap(u),h=t.shape.length;if(h===2)Sae(l,p[0],d,s,i);else if(h===3)Cae(l,p[0],p[1],d,s,i);else if(h===4)Tae(l,p[0],p[1],p[2],d,s,i);else{let m=Ah(l,s,i,t.shape,t.dtype);d.set(m)}return u}function Sae(e,t,a,n,r){let s=0,i=n[0],o=n[1],l=i+r[0];for(let u=i;u<l;u++){let p=u*t+o;a.set(e.subarray(p,p+r[1]),s),s+=r[1]}}function Cae(e,t,a,n,r,s){let i=0,o=r[0],l=r[1],u=r[2],p=o+s[0],c=l+s[1];for(let d=o;d<p;d++)for(let h=l;h<c;h++){let m=d*t+h*a+u;n.set(e.subarray(m,m+s[2]),i),i+=s[2]}}function Tae(e,t,a,n,r,s,i){let o=0,l=s[0],u=s[1],p=s[2],c=l+i[0],d=u+i[1],h=p+i[2],m=s[3];for(let f=l;f<c;f++)for(let g=u;g<d;g++)for(let y=p;y<h;y++){let x=f*t+g*a+y*n+m;r.set(e.subarray(x,x+i[3]),o),o+=i[3]}}var Nae={kernelName:_u,backendName:"wasm",kernelFunc:si};function Rae(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,crops:i}=n,o=s.reduce((y,x)=>y*x),l=C.getReshaped(r.shape,s,o),u=C.getPermuted(l.length,s.length),p=C.getReshapedPermuted(r.shape,s,o),c=C.getSliceBeginCoords(i,s.length),d=C.getSliceSize(p,i,s.length),h=La({inputs:{x:r},backend:a,attrs:{shape:l}}),m=os({inputs:{x:h},backend:a,attrs:{perm:u}}),f=La({inputs:{x:m},backend:a,attrs:{shape:p}}),g=si({inputs:{x:f},backend:a,attrs:{begin:c,size:d}});return a.disposeData(h.dataId),a.disposeData(m.dataId),a.disposeData(f.dataId),g}var Eae={kernelName:pu,backendName:"wasm",kernelFunc:Rae},sw;function Mae(e){sw=e.wasm.cwrap(Ai,null,["number","number","boolean","number","number","number"])}function $ae(e){let{backend:t,inputs:a,attrs:n}=e,{x:r,weights:s}=a,{size:i}=n,o=s.shape.reduce((c,d)=>c*d,1)!==0,l=r.shape.length===1?[i]:[r.shape[0],i],u=t.makeOutput(l,s.dtype);function p(c){return t.dataIdMap.get(c.dataId).id}return sw(p(r),i,o,p(s),nt[s.dtype],p(u)),u}var Pae={kernelName:Ai,backendName:"wasm",setupFunc:Mae,kernelFunc:$ae},_ae=!0,Fae=Gt(cu,_ae);function Dae(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t,s=a.typedArrayFromHeap(n),i=a.typedArrayFromHeap(r),o=C.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return a.makeOutput([o.length],"int32",void 0,new Int32Array(o))}var Oae={kernelName:hu,backendName:"wasm",kernelFunc:Dae};function ys(e){let{inputs:{x:t},attrs:{dtype:a},backend:n}=e,r=n.makeOutput(t.shape,a),s=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(r).set(s),r}var zae={kernelName:bi,backendName:"wasm",kernelFunc:ys},Lae=Qe(vi),iw;function Wae(e){iw=e.wasm.cwrap(us,null,["number","number","number","number"])}function Bae(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=n,o=a.dataIdMap.get(r.dataId).id,l=a.makeOutput(r.shape,r.dtype),u=a.dataIdMap.get(l.dataId).id;return iw(o,s,i,u),l}var Vae={kernelName:us,backendName:"wasm",setupFunc:Wae,kernelFunc:Bae};function ow(e){let{inputs:t,backend:a}=e,n=v.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=t.map(h=>h.shape);C.assertParamsConsistent(r,n);let s=C.computeOutShape(t.map(h=>h.shape),n),i=t.filter(h=>v.sizeFromShape(h.shape)>0);if(i.length===1)return l0({inputs:{x:i[0]},backend:a});let o=a.makeOutput(s,t[0].dtype);if(v.sizeFromShape(s)===0)return o;if(i[0].dtype==="string"){let h=i.map(A=>{let b=[-1,v.sizeFromShape(A.shape.slice(n))];return La({inputs:{x:A},backend:a,attrs:{shape:b}})}),m=h.map(A=>({vals:a.readSync(A.dataId),shape:A.shape}));s=C.computeOutShape(h.map(A=>A.shape),1);let f=h[0].shape[0]===1,g=m3(m,s,t[0].dtype,f),y=C.computeOutShape(i.map(A=>A.shape),n);o.shape=y;let x=a.dataIdMap.get(o.dataId);return x.stringBytes=C.fromStringArrayToUint8(g),h.forEach(A=>a.disposeData(A.dataId)),o}let l=v.sizeFromShape(i[0].shape.slice(0,n)),u=0,p=i.map(h=>{let m=v.sizeFromShape(h.shape.slice(n));return u+=m,m}),c=i.map(h=>a.typedArrayFromHeap(h)),d=a.typedArrayFromHeap(o);for(let h=0;h<l;h++){let m=h*u;for(let f=0;f<c.length;f++){let g=p[f],y=h*g,x=c[f].subarray(y,y+g);d.set(x,m),m+=g}}return o}var Uae={kernelName:mu,backendName:"wasm",kernelFunc:ow},lw;function Gae(e){lw=e.wasm.cwrap(wi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Hae(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,dataFormat:d}=a,h=C.convertConv2DDataFormat(d),m=C.computeConv2DInfo(r.shape,s.shape,l,u,p,c,!1,h),f=m.filterHeight,g=m.filterWidth,y=m.padInfo.top,x=m.padInfo.right,A=m.padInfo.bottom,b=m.padInfo.left,w=m.dilationHeight,I=m.dilationWidth,T=m.strideHeight,N=m.strideWidth,M=m.inChannels,$=m.outChannels,E=m.padInfo.type==="SAME"?1:0;if(m.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${m.dataFormat}'. Please use 'channelsLast'.`);let S=n.makeOutput(m.outShape,"float32"),_=n.dataIdMap.get(S.dataId).id;return lw(i,r.shape[0],r.shape[1],r.shape[2],o,f,g,y,x,A,b,E,w,I,T,N,M,$,_),S}var jae={kernelName:wi,backendName:"wasm",setupFunc:Gae,kernelFunc:Hae},uw;function qae(e){uw=e.wasm.cwrap(ki,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Xae(e){let{backend:t,inputs:a,attrs:n}=e,{dy:r,filter:s}=a,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,inputShape:p}=n,c=1,d=C.convertConv2DDataFormat(l),h=C.computeConv2DInfo(p,s.shape,i,c,o,u,!1,d),{batchSize:m,filterHeight:f,filterWidth:g,inChannels:y,inHeight:x,inWidth:A,outChannels:b,outHeight:w,outWidth:I,strideHeight:T,strideWidth:N}=h,M=f-1-h.padInfo.top,$=g-1-h.padInfo.left,E=h.dataFormat==="channelsLast",S=v.computeStrides(h.inShape),_=v.computeStrides(r.shape),[O,W,P]=v.computeStrides(s.shape),U=S[0],G=E?S[1]:S[2],q=E?S[2]:1,H=E?1:S[1],V=_[0],Z=E?_[1]:_[2],X=E?_[2]:1,re=E?1:_[1],ee=t.makeOutput(h.inShape,"float32"),ge=t.dataIdMap.get(ee.dataId).id,ie=t.dataIdMap.get(r.dataId).id,be=t.dataIdMap.get(s.dataId).id;return uw(ie,be,m,f,g,x,A,y,w,I,b,T,N,M,$,O,W,P,U,G,q,H,V,Z,X,re,ge),ee}var Kae={kernelName:ki,backendName:"wasm",setupFunc:qae,kernelFunc:Xae},dw;function Yae(e){dw=e.wasm.cwrap(Ii,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Zae(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n;if(r.dtype!=="float32")throw new Error(`Tensor x must have dtype float32, got ${r.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let u=C.computeConv3DInfo(r.shape,s.shape,i,l,o),p=a.makeOutput(u.outShape,r.dtype);return dw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(p.dataId).id,u.batchSize,u.inDepth,u.inHeight,u.inWidth,u.inChannels,u.outDepth,u.outHeight,u.outWidth,u.outChannels,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.filterDepth,u.filterHeight,u.filterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left),p}var Jae={kernelName:Ii,backendName:"wasm",setupFunc:Yae,kernelFunc:Zae},pw;function Qae(e){pw=e.wasm.cwrap(fu,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function ene(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=n;if(r.dtype!=="float32")throw new Error(`Tensor dy must have dtype float32, got ${r.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let u=C.computeConv3DInfo(r.shape,l,i,1,o),p=a.makeOutput(u.filterShape,s.dtype);return pw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(p.dataId).id,u.batchSize,u.inDepth,u.inHeight,u.inWidth,u.inChannels,u.outDepth,u.outHeight,u.outWidth,u.outChannels,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.filterDepth,u.filterHeight,u.filterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left),p}var tne={kernelName:fu,backendName:"wasm",setupFunc:Qae,kernelFunc:ene},cw;function ane(e){cw=e.wasm.cwrap(Si,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function nne(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=n;if(r.dtype!=="float32")throw new Error(`Tensor dy must have dtype float32, got ${r.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let u=C.computeConv3DInfo(l,s.shape,o,1,i),p=a.makeOutput(u.inShape,r.dtype);return cw(a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(p.dataId).id,u.batchSize,u.inDepth,u.inHeight,u.inWidth,u.inChannels,u.outDepth,u.outHeight,u.outWidth,u.outChannels,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.filterDepth,u.filterHeight,u.filterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left),p}var rne={kernelName:Si,backendName:"wasm",setupFunc:ane,kernelFunc:nne},sne=Qe(Ci),ine=Qe(Ti),V1;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(V1||(V1={}));var hw;function one(e){hw=e.wasm.cwrap(Ei,null,["number","number","number","number","array","number","number","number","number","number"])}function lne(e){let{backend:t,inputs:a,attrs:n}=e,{method:r,extrapolationValue:s,cropSize:i}=n,{image:o,boxes:l,boxInd:u}=a,p=l.shape[0],[c,d]=i,h=[p,c,d,o.shape[3]],m=t.dataIdMap.get(o.dataId),f;o.dtype!=="float32"&&(f=ys({backend:t,inputs:{x:o},attrs:{dtype:"float32"}}),m=t.dataIdMap.get(f.dataId));let g=m.id,y=t.dataIdMap.get(l.dataId).id,x=t.dataIdMap.get(u.dataId).id,A=t.makeOutput(h,"float32"),b=t.dataIdMap.get(A.dataId).id,w=new Uint8Array(new Int32Array(o.shape).buffer);return hw(g,y,x,p,w,c,d,V1[r],s,b),f!=null&&t.disposeData(f.dataId),A}var une={kernelName:Ei,backendName:"wasm",setupFunc:one,kernelFunc:lne},mw;function dne(e){mw=e.wasm.cwrap(Ni,null,["number","number","number","number","number","number"])}function pne(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumprod does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([s],l),p=r;u!==null&&(p=os({inputs:{x:r},attrs:{perm:u},backend:a}));let c=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumprod",[c],l);let d=a.makeOutput(p.shape,p.dtype),h=p.shape[c],m=a.dataIdMap.get(p.dataId).id,f=a.dataIdMap.get(d.dataId).id;mw(m,i?1:0,o?1:0,h,f,nt[r.dtype]);let g=d;if(u!==null){let y=C.getUndoAxesPermutation(u);g=os({inputs:{x:d},attrs:{perm:y},backend:a}),a.disposeData(p.dataId),a.disposeData(d.dataId)}return g}var cne={kernelName:Ni,backendName:"wasm",setupFunc:dne,kernelFunc:pne},fw;function hne(e){fw=e.wasm.cwrap(Ri,null,["number","number","number","number","number","number"])}function mne(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumsum does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([s],l),p=r;u!==null&&(p=os({inputs:{x:r},attrs:{perm:u},backend:a}));let c=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumsum",[c],l);let d=a.makeOutput(p.shape,p.dtype),h=p.shape[c],m=a.dataIdMap.get(p.dataId).id,f=a.dataIdMap.get(d.dataId).id;fw(m,i?1:0,o?1:0,h,f,nt[r.dtype]);let g=d;if(u!==null){let y=C.getUndoAxesPermutation(u);g=os({inputs:{x:d},attrs:{perm:y},backend:a}),a.disposeData(p.dataId),a.disposeData(d.dataId)}return g}var fne={kernelName:Ri,backendName:"wasm",setupFunc:hne,kernelFunc:mne},gw;function gne(e){gw=e.wasm.cwrap("DenseBincount",null,["number","array","number","number","boolean","number","number","boolean","number"])}function yne(e){let{backend:t,inputs:a,attrs:n}=e,{x:r,weights:s}=a,{size:i,binaryOutput:o}=n,l=s.shape.reduce((d,h)=>d*h,1)!==0,u=r.shape.length===1?[i]:[r.shape[0],i],p=t.makeOutput(u,s.dtype);function c(d){return t.dataIdMap.get(d.dataId).id}return gw(c(r),new Uint8Array(new Int32Array(r.shape).buffer),r.shape.length,i,l,c(s),nt[s.dtype],o,c(p)),p}var xne={kernelName:gu,backendName:"wasm",setupFunc:gne,kernelFunc:yne},yw;function Ane(e){yw=e.wasm.cwrap(Mi,null,["number","number","number","array","number","array","array","number","number"])}function bne(e){let{backend:t,inputs:a,attrs:n}=e,{x:r}=a,{blockSize:s,dataFormat:i}=n,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],c=l*s,d=u*s,h=p/(s*s),m=i==="NHWC"?[o,c,d,h]:[o,h,c,d],f=t.makeOutput(m,"float32"),g=t.dataIdMap.get(r.dataId).id,y=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),x=new Uint8Array(new Int32Array(m).buffer),A=new Uint8Array(new Int32Array(v.computeStrides(m)).buffer),b=t.dataIdMap.get(f.dataId).id;return yw(g,s,i==="NHWC"?1:0,y,r.shape.length-1,x,A,m.length,b),f}var vne={kernelName:Mi,backendName:"wasm",setupFunc:Ane,kernelFunc:bne},xw;function wne(e){xw=e.wasm.cwrap($i,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function kne(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=C.computeConv2DInfo(r.shape,s.shape,l,d,p,c,!0),m=h.filterHeight,f=h.filterWidth,g=h.padInfo.top,y=h.padInfo.right,x=h.padInfo.bottom,A=h.padInfo.left,b=h.dilationHeight,w=h.dilationWidth,I=h.strideHeight,T=h.strideWidth,N=h.inChannels,M=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 E=n.makeOutput(h.outShape,"float32"),S=n.dataIdMap.get(E.dataId).id;return xw(i,r.shape[0],r.shape[1],r.shape[2],o,m,f,g,y,x,A,$,b,w,I,T,N,M,S),E}var Ine={kernelName:$i,backendName:"wasm",setupFunc:wne,kernelFunc:kne},Aw;function Sne(e){Aw=e.wasm.cwrap("Diag",null,["number","number","number","number"])}function Cne(e){let{inputs:t,backend:a}=e,{x:n}=t,r=v.sizeFromShape(n.shape),s=a.makeOutput([...n.shape,...n.shape],n.dtype);return Aw(a.dataIdMap.get(n.dataId).id,nt[n.dtype],r,a.dataIdMap.get(s.dataId).id),s}var Tne={kernelName:yu,backendName:"wasm",setupFunc:Sne,kernelFunc:Cne},bw;function Nne(e){bw=e.wasm.cwrap(Pi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Rne(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n;if(r.dtype!==s.dtype)throw new Error(`Dilation2D error: x must have the same dtype as filter. Got ${r.dtype} and ${s.dtype}`);let u=C.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),p=a.makeOutput(u.outShape,r.dtype);return bw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(p.dataId).id,nt[r.dtype],u.batchSize,u.inChannels,u.inHeight,u.inWidth,u.outHeight,u.outWidth,u.strideHeight,u.strideWidth,u.dilationHeight,u.dilationWidth,u.filterHeight,u.filterWidth,u.padInfo.top,u.padInfo.left),p}var Ene={kernelName:Pi,backendName:"wasm",setupFunc:Nne,kernelFunc:Rne},vw;function Mne(e){vw=e.wasm.cwrap(Xl,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function $ne(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=n;if(r.dtype!==s.dtype||r.dtype!==i.dtype)throw new Error(`Dilation2DBackpropFilter error: x must have the same dtype as filter and dy. Got ${r.dtype}, ${s.dtype}, and ${i.dtype}`);let p=C.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),c=a.makeOutput(s.shape,s.dtype);return vw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(i.dataId).id,a.dataIdMap.get(c.dataId).id,nt[r.dtype],p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.filterHeight,p.filterWidth,p.padInfo.top,p.padInfo.left),c}var Pne={kernelName:Xl,backendName:"wasm",setupFunc:Mne,kernelFunc:$ne},ww;function _ne(e){ww=e.wasm.cwrap(ql,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Fne(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=n;if(r.dtype!==s.dtype||r.dtype!==i.dtype)throw new Error(`Dilation2DBackpropInput error: x must have the same dtype as filter and dy. Got ${r.dtype}, ${s.dtype}, and ${i.dtype}`);let p=C.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),c=a.makeOutput(r.shape,r.dtype);return ww(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(i.dataId).id,a.dataIdMap.get(c.dataId).id,nt[r.dtype],p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.filterHeight,p.filterWidth,p.padInfo.top,p.padInfo.left),c}var Dne={kernelName:ql,backendName:"wasm",setupFunc:_ne,kernelFunc:Fne},One=Qe(Fi),kw;function zne(e){kw=e.wasm.cwrap(xu,null,["number","number","number"])}function Lne(e){let{inputs:t,backend:a}=e,{dy:n,y:r}=t,s=a.makeOutput(r.shape,"float32"),i=o=>a.dataIdMap.get(o.dataId).id;return kw(i(r),i(n),i(s)),s}var Wne={kernelName:xu,backendName:"wasm",setupFunc:zne,kernelFunc:Lne},Bne=!1,Vne=Gt(Oi,Bne,"bool"),Une=Qe(Di),Gne=Qe(zi,"float32");function U1(e){let{inputs:t,attrs:a,backend:n}=e,{input:r}=t,{dim:s}=a,i=r.shape.length,o=r.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),La({inputs:{x:r},backend:n,attrs:{shape:o}})}var Hne={kernelName:Au,backendName:"wasm",kernelFunc:U1},jne=Qe(Li,"float32");function Iw(e){let{attrs:{shape:t,value:a},backend:n}=e,{attrs:{dtype:r}}=e;r=r||v.inferDtype(a);let s=n.makeOutput(t,r);return n.typedArrayFromHeap(s).fill(a),s}var qne={kernelName:bu,backendName:"wasm",kernelFunc:Iw},Sw;function Xne(e){Sw=e.wasm.cwrap(Wi,null,["number","number","number","number","number","number"])}function Kne(e){let{inputs:t,backend:a}=e,{image:n}=t,r=a.makeOutput(n.shape,n.dtype),s=a.dataIdMap.get(n.dataId).id,i=a.dataIdMap.get(r.dataId).id,[o,l,u,p]=n.shape;return Sw(s,o,l,u,p,i),r}var Yne={kernelName:Wi,backendName:"wasm",kernelFunc:Kne,setupFunc:Xne},Zne=Qe(Bi),Jne=!1,Qne=Gt(Vi,Jne),Cw;function ere(e){Cw=e.wasm.cwrap(Ui,null,["number","number","number","number","number","number","number"])}function tre(e){let{backend:t,inputs:a,attrs:n}=e,{varianceEpsilon:r}=n,{x:s,mean:i,variance:o,offset:l,scale:u}=a,p=t.dataIdMap.get(s.dataId).id,c=t.dataIdMap.get(i.dataId).id,d=t.dataIdMap.get(o.dataId).id,h=l!=null?t.dataIdMap.get(l.dataId).id:0,m=u!=null?t.dataIdMap.get(u.dataId).id:0,f=t.makeOutput(s.shape,s.dtype);if(v.sizeFromShape(s.shape)===0)return f;let g=t.dataIdMap.get(f.dataId).id;return Cw(p,c,d,h,m,r,g),f}var are={kernelName:Ui,backendName:"wasm",setupFunc:ere,kernelFunc:tre},Tw;function nre(e){Tw=e.wasm.cwrap(Jr,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function rre(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:c,dimRoundingMode:d,activation:h,leakyreluAlpha:m}=a,f=C.computeConv2DInfo(r.shape,s.shape,l,p,u,d),g=rp[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedConv2D in the wasm backend.`);let y=n.dataIdMap.get(r.dataId).id,x=n.dataIdMap.get(s.dataId).id,A=f.outChannels,b=0;if(i!=null){let X=n.dataIdMap.get(i.dataId);if(X.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${X.shape.length}.`);if(X.shape[0]!==A)throw new Error(`FusedConv2D bias shape (${X.shape}) does not match the number of output channels (${A})`);b=X.id}let w=f.filterHeight,I=f.filterWidth,T=f.padInfo.top,N=f.padInfo.right,M=f.padInfo.bottom,$=f.padInfo.left,E=f.dilationHeight,S=f.dilationWidth,_=f.strideHeight,O=f.strideWidth,W=f.inChannels,P=f.padInfo.type==="SAME"?1:0,U=f.batchSize,G=f.inHeight,q=f.inWidth;if(c!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${c}'. Please use 'NHWC'.`);let H=n.makeOutput(f.outShape,"float32"),V=n.dataIdMap.get(H.dataId).id,Z=o==null?0:n.dataIdMap.get(o.dataId).id;return Tw(y,U,G,q,x,w,I,b,T,N,M,$,P,E,S,_,O,W,A,g,Z,m||0,V),H}var sre={kernelName:Jr,backendName:"wasm",setupFunc:nre,kernelFunc:rre},Nw;function ire(e){Nw=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 ore(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:m}=a,f=C.computeConv2DInfo(r.shape,s.shape,l,p,u,d,!0),g=rp[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let y=n.dataIdMap.get(r.dataId).id,x=n.dataIdMap.get(s.dataId).id,A=f.outChannels,b=0;if(i!=null){let X=n.dataIdMap.get(i.dataId);if(X.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${X.shape.length}.`);if(X.shape[0]!==A)throw new Error(`FusedDepthwiseConv2D bias shape (${X.shape}) does not match the number of output channels (${A})`);b=X.id}let w=f.filterHeight,I=f.filterWidth,T=f.padInfo.top,N=f.padInfo.right,M=f.padInfo.bottom,$=f.padInfo.left,E=f.dilationHeight,S=f.dilationWidth,_=f.strideHeight,O=f.strideWidth,W=f.inChannels,P=f.padInfo.type==="SAME"?1:0,U=f.batchSize,G=f.inHeight,q=f.inWidth;if(c!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${c}'. Please use 'NHWC'.`);let H=n.makeOutput(f.outShape,"float32"),V=n.dataIdMap.get(H.dataId).id,Z=o==null?0:n.dataIdMap.get(o.dataId).id;return Nw(y,U,G,q,x,w,I,b,T,N,M,$,P,E,S,_,O,W,A,g,Z,m||0,V),H}var lre={kernelName:Qr,backendName:"wasm",setupFunc:ire,kernelFunc:ore},Rw;function ure(e){Rw=e.wasm.cwrap(Gi,null,["number","number","number","number","number","number","array","number"])}function dre(e){let{backend:t,inputs:a}=e,{params:n,indices:r}=a,[s,i,o,l]=s3.prepareAndValidate(n,r),u=t.makeOutput(s,n.dtype);if(i===0)return u;let p=r.shape,c=p[p.length-1],d=t.dataIdMap.get(n.dataId).id,h=t.dataIdMap.get(r.dataId).id,m=new Uint8Array(new Int32Array(l).buffer),f=t.dataIdMap.get(u.dataId).id;return Rw(d,nt[n.dtype],h,i,c,o,m,f),u}var pre={kernelName:Gi,backendName:"wasm",setupFunc:ure,kernelFunc:dre},Ew;function cre(e){Ew=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function hre(e){let{backend:t,inputs:a,attrs:n}=e,{x:r,indices:s}=a,{axis:i,batchDims:o}=n,l=v.parseAxisParam(i,r.shape)[0],u=t.readSync(s.dataId),p=r.shape[l];for(let T=0;T<u.length;++T){let N=u[T];v.assert(N<=p-1&&N>=0,()=>`GatherV2: the index value ${N} is not in [0, ${p-1}]`)}let c=C.segment_util.collectGatherOpShapeInfo(r,s,l,o),d=La({inputs:{x:r},attrs:{shape:[c.batchSize,c.outerSize,c.dimSize,c.sliceSize]},backend:t}),h=v.sizeFromShape(s.shape),m=La({inputs:{x:s},attrs:{shape:[c.batchSize,h/c.batchSize]},backend:t}),f=[c.batchSize,c.outerSize,h/c.batchSize,c.sliceSize],g=t.makeOutput(f,r.dtype);if(v.sizeFromShape(r.shape)===0)return g;let y=d.shape.length-1,x=t.dataIdMap.get(d.dataId).id,A=t.dataIdMap.get(m.dataId).id,b=t.dataIdMap.get(g.dataId).id,w=new Uint8Array(new Int32Array(v.computeStrides(d.shape)).buffer),I=new Uint8Array(new Int32Array(v.computeStrides(f)).buffer);return Ew(x,nt[r.dtype],w,y,A,c.batchSize,I,b),t.disposeData(d.dataId),t.disposeData(m.dataId),g.shape=c.outputShape,g}var mre={kernelName:vu,backendName:"wasm",setupFunc:cre,kernelFunc:hre},fre=!1,gre=Gt(Hi,fre,"bool"),yre=!1,xre=Gt(ji,yre,"bool"),Are=Qe(Xi,"bool"),bre=Qe(Ki,"bool"),vre=Qe(Yi,"bool"),Mw;function wre(e){Mw=e.wasm.cwrap(Zi,null,["number","number","number","number"])}function kre(e){let{inputs:{x:t},attrs:{alpha:a},backend:n}=e,r=n.dataIdMap.get(t.dataId).id,s=n.makeOutput(t.shape,"float32");if(v.sizeFromShape(t.shape)!==0){let i=n.dataIdMap.get(s.dataId).id;Mw(r,nt[t.dtype],a,i)}return s}var Ire={kernelName:Zi,backendName:"wasm",setupFunc:wre,kernelFunc:kre},Sre=!1,Cre=Gt(Ji,Sre,"bool"),Tre=!1,Nre=Gt(Qi,Tre,"bool"),$w;function Rre(e){$w=e.wasm.cwrap(eo,null,["number","number","number","number"])}function Ere(e){let{attrs:t,backend:a}=e,{start:n,stop:r,num:s}=t,i=Math.floor(s),o=a.makeOutput([i],"float32");return $w(a.dataIdMap.get(o.dataId).id,n,r,i),o}var Mre={kernelName:eo,backendName:"wasm",setupFunc:Rre,kernelFunc:Ere},$re=Qe(to),Pre=Qe(ao),_re=!1,Fre=Gt(no,_re,"bool"),Dre=Qe(ro),Ore=!1,zre=Gt(so,Ore,"bool"),Lre=!1,Wre=Gt(RA,Lre,"bool"),Pw;function Bre(e){Pw=e.wasm.cwrap(io,null,["number","number","number","number","number","number","number"])}function Vre(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n;if(r.dtype!=="float32")throw new Error("LRN error: x must have dtype float32");let u=a.makeOutput(r.shape,r.dtype);return Pw(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(u.dataId).id,r.shape[3],s,i,o,l),u}var Ure={kernelName:io,backendName:"wasm",setupFunc:Bre,kernelFunc:Vre},_w;function Gre(e){_w=e.wasm.cwrap(wu,null,["number","number","number","number","number","number","number","number","number"])}function Hre(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;if(r.dtype!=="float32"||s.dtype!=="float32"||i.dtype!=="float32")throw new Error("LRNGrad error: x, y, and dy must have dtype float32");let c=a.makeOutput(r.shape,r.dtype);return _w(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(i.dataId).id,a.dataIdMap.get(c.dataId).id,i.shape[3],o,l,u,p),c}var jre={kernelName:wu,backendName:"wasm",setupFunc:Gre,kernelFunc:Hre},Fw;function qre(e){Fw=e.wasm.cwrap(oo,null,["number","number","number","number"])}function Xre(e){let{backend:t,inputs:a,attrs:n}=e,{reductionIndices:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:c,inputWasTransposed:d}=gs(i,r,t);if(d){let x=t.dataIdMap.get(u.dataId).id;l=u,o=x}let h=l.shape.length;C.assertAxesAreInnerMostDims("max",p,h);let[m,f]=C.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(f),y=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;Fw(o,nt[i.dtype],g,x)}if(d&&t.disposeData(u.dataId),s){let x=C.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var Kre={kernelName:oo,backendName:"wasm",setupFunc:qre,kernelFunc:Xre},Yre=!1,Zre=Gt(lo,Yre),Dw;function Jre(e){Dw=e.wasm.cwrap(uo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Qre(e){let{inputs:t,attrs:a,backend:n}=e,r=t.x,s=n.dataIdMap.get(r.dataId).id;v.assert(r.dtype==="float32",()=>`Error in MaxPool: only float32 input is supported. Got ${r.dtype}.`);let{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=a,p=C.computePool2DInfo(r.shape,i,o,1,l,u),c=p.filterHeight,d=p.filterWidth,h=p.padInfo.top,m=p.padInfo.right,f=p.padInfo.bottom,g=p.padInfo.left,y=p.dilationHeight,x=p.dilationWidth,A=p.strideHeight,b=p.strideWidth,w=p.inChannels,I=p.outChannels;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);let T=n.makeOutput(p.outShape,"float32"),N=n.dataIdMap.get(T.dataId).id;return Dw(s,r.shape[0],r.shape[1],r.shape[2],c,d,h,m,f,g,y,x,A,b,w,I,N),T}var ese={kernelName:uo,backendName:"wasm",setupFunc:Jre,kernelFunc:Qre},Ow;function tse(e){Ow=e.wasm.cwrap("MaxPool3D",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function ase(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n,p=C.computePool3DInfo(r.shape,s,i,1,o,l,u),c=a.makeOutput(p.outShape,r.dtype);return Ow(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),c}var nse={kernelName:ku,backendName:"wasm",setupFunc:tse,kernelFunc:ase},zw;function rse(e){zw=e.wasm.cwrap("MaxPool3DGrad",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 sse(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,p=C.computePool3DInfo(s.shape,i,o,1,l,u),c=a.makeOutput(s.shape,s.dtype);return zw(a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),c}var ise={kernelName:kp,backendName:"wasm",setupFunc:rse,kernelFunc:sse},Lw;function ose(e){Lw=e.wasm.cwrap("MaxPoolGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function lse(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,p=C.computePool2DInfo(s.shape,i,o,1,l,u),c=a.makeOutput(s.shape,s.dtype);return Lw(a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.top,p.padInfo.left),c}var use={kernelName:wp,backendName:"wasm",setupFunc:ose,kernelFunc:lse},Ww;function dse(e){Ww=e.wasm.cwrap("MaxPoolWithArgmax",null,["number","number","number","number","boolean","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function pse(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,includeBatchInIndex:l}=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let u=[1,1];v.assert(C.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=C.computePool2DInfo(r.shape,s,i,[1,1],o),c=a.makeOutput(p.outShape,r.dtype),d=a.makeOutput(p.outShape,"int32");return Ww(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,a.dataIdMap.get(d.dataId).id,nt[r.dtype],l,p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.top,p.padInfo.left),[c,d]}var cse={kernelName:Iu,backendName:"wasm",setupFunc:dse,kernelFunc:pse},Bw;function hse(e){Bw=e.wasm.cwrap(po,null,["number, number, number"])}function mse(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}=gs(i,r,t),m=c;if(h){let b=t.dataIdMap.get(p.dataId).id;b!==o&&(u=p,l=b,m=C.getInnerMostAxes(m.length,u.shape.length))}C.assertAxesAreInnerMostDims("mean",m,u.shape.length);let[f,g]=C.computeOutAndReduceShapes(u.shape,m),y=v.sizeFromShape(g),x=u;u.dtype!=="float32"&&(x=ys({backend:t,inputs:{x:u},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(x.dataId).id);let A=t.makeOutput(f,"float32");if(v.sizeFromShape(u.shape)!==0){let b=t.dataIdMap.get(A.dataId).id;Bw(l,y,b)}if(h&&t.disposeData(p.dataId),s){let b=C.expandShapeToKeepDim(A.shape,d);A.shape=b}return u.dtype!=="float32"&&t.disposeData(x.dataId),A}var fse={kernelName:po,backendName:"wasm",setupFunc:hse,kernelFunc:mse},Vw;function gse(e){Vw=e.wasm.cwrap(co,null,["number","number","number","number"])}function yse(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}=gs(i,r,t);if(h){let A=t.dataIdMap.get(p.dataId).id;A!==o&&(u=p,l=A)}let m=u.shape.length;C.assertAxesAreInnerMostDims("min",c,m);let[f,g]=C.computeOutAndReduceShapes(u.shape,c),y=v.sizeFromShape(g),x=t.makeOutput(f,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;Vw(l,nt[i.dtype],y,A)}if(h&&t.disposeData(p.dataId),s){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var xse={kernelName:co,backendName:"wasm",setupFunc:gse,kernelFunc:yse},Ase=!1,bse=Gt(ho,Ase),G1;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(G1||(G1={}));var Uw;function vse(e){Uw=e.wasm.cwrap(mo,null,["number","array","number","number","array","array","number","number"])}function wse(e){let{inputs:{x:t},backend:a,attrs:{paddings:n,mode:r}}=e,s=n.map((m,f)=>m[0]+t.shape[f]+m[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(m=>m[0]),c=n.map(m=>m[1]),d=new Uint8Array(new Int32Array(p).buffer),h=new Uint8Array(new Int32Array(c).buffer);return Uw(i,u,t.shape.length,nt[t.dtype],d,h,G1[r],l),o}var kse={kernelName:mo,backendName:"wasm",kernelFunc:wse,setupFunc:vse},Gw;function Ise(e){Gw=e.wasm.cwrap(Ho,null,["number","number","number","number"])}function Hw(e){let{backend:t,inputs:{logits:a},attrs:{dim:n}}=e,r=t.dataIdMap.get(a.dataId).id,s=t.makeOutput(a.shape,a.dtype),i=t.dataIdMap.get(s.dataId).id,o=a.shape[n],l=v.sizeFromShape(a.shape)/o;return v.sizeFromShape(s.shape)===0||Gw(r,i,o,l),s}var Sse={kernelName:Ho,backendName:"wasm",setupFunc:Ise,kernelFunc:Hw},jw;function Cse(e){jw=e.wasm.cwrap(go,null,["number","number","number","number","number","number"])}function Tse(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n;if(r.dtype!=="float32")throw new Error(`Tensor logits must have dtype float32, got ${r.dtype}`);let l=o?r:Hw({inputs:{logits:r},backend:a,attrs:{dim:r.shape.length-1}}),[u,p]=l.shape,c=a.makeOutput([u,s],"int32");return jw(a.dataIdMap.get(l.dataId).id,u,p,s,i,a.dataIdMap.get(c.dataId).id),o||a.disposeData(l.dataId),c}var Nse={kernelName:go,backendName:"wasm",setupFunc:Cse,kernelFunc:Tse},Rse=Gt(fo,!0),Ese=!0,Mse=Gt(yo,Ese),$se=Qe(Su);function V3(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 qw;function Pse(e){qw=e.wasm.cwrap(Ao,"number",["number","number","number","number","number"])}function _se(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=qw(u,p,s,r,i),{pSelectedIndices:d,selectedSize:h,pSelectedScores:m,pValidOutputs:f}=V3(t,c);return t.wasm._free(m),t.wasm._free(f),t.makeOutput([h],"int32",d)}var Fse={kernelName:Ao,backendName:"wasm",setupFunc:Pse,kernelFunc:_se},Xw;function Dse(e){Xw=e.wasm.cwrap(Cu,"number",["number","number","number","number","number","bool"])}function Ose(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=Xw(p,c,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=V3(t,d);t.wasm._free(f);let y=t.makeOutput([m],"int32",h),x=t.makeOutput([],"int32",g);return[y,x]}var zse={kernelName:Cu,backendName:"wasm",setupFunc:Dse,kernelFunc:Ose},Kw;function Lse(e){Kw=e.wasm.cwrap(bo,"number",["number","number","number","number","number","number"])}function Wse(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=Kw(p,c,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=V3(t,d);t.wasm._free(g);let y=t.makeOutput([m],"int32",h),x=t.makeOutput([m],"float32",f);return[y,x]}var Bse={kernelName:bo,backendName:"wasm",setupFunc:Lse,kernelFunc:Wse},Vse=!1,Use=Gt(xo,Vse,"bool"),Yw;function Gse(e){Yw=e.wasm.cwrap(vo,null,["number","number","number","number","number"])}function Hse(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 Yw(c,i,o,l,p),u}var jse={kernelName:vo,backendName:"wasm",setupFunc:Gse,kernelFunc:Hse};function qse(e){let{inputs:{x:t},backend:a}=e,n=a.makeOutput(t.shape,t.dtype);return a.typedArrayFromHeap(n).fill(1),n}var Xse={kernelName:Tu,backendName:"wasm",kernelFunc:qse};function Kse(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return U1({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=U1({inputs:{input:p},backend:a,attrs:{dim:r}});return o.push(c),c}),u=ow({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(p=>a.disposeData(p.dataId)),u}var Yse={kernelName:Nu,backendName:"wasm",kernelFunc:Kse},Zw;function Zse(e){Zw=e.wasm.cwrap(wo,null,["number","array","number","number","array","array","number","number"])}function Jse(e){let{inputs:{x:t},backend:a,attrs:{paddings:n,constantValue:r}}=e,s=n.map((m,f)=>m[0]+t.shape[f]+m[1]);if(v.sizeFromShape(t.shape)===0)return Iw({backend:a,attrs:{shape:s,value:r,dtype:t.dtype}});let 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(m=>m[0]),c=n.map(m=>m[1]),d=new Uint8Array(new Int32Array(p).buffer),h=new Uint8Array(new Int32Array(c).buffer);return Zw(i,u,t.shape.length,nt[t.dtype],d,h,r,l),o}var Jw={kernelName:wo,backendName:"wasm",kernelFunc:Jse,setupFunc:Zse},Qse=!1,eie=Gt(ko,Qse),Qw;function tie(e){Qw=e.wasm.cwrap(Io,null,["number","number","number"])}function aie(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t,s=a.dataIdMap.get(n.dataId).id,i=a.dataIdMap.get(r.dataId).id,o=s,l=n,u=l;l.dtype!=="float32"&&(u=ys({backend:a,inputs:{x:n},attrs:{dtype:"float32"}}),o=a.dataIdMap.get(u.dataId).id);let p=a.makeOutput(n.shape,"float32"),c=a.dataIdMap.get(p.dataId).id;return Qw(o,i,c),l.dtype!=="float32"&&a.disposeData(u.dataId),p}var nie={kernelName:Io,backendName:"wasm",setupFunc:tie,kernelFunc:aie},ek;function rie(e){ek=e.wasm.cwrap(So,null,["number","number","number","number"])}function sie(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}=gs(i,r,t),m=c;if(h){let A=t.dataIdMap.get(p.dataId).id;A!==o&&(u=p,l=A,m=C.getInnerMostAxes(m.length,u.shape.length))}C.assertAxesAreInnerMostDims("prod",m,u.shape.length);let[f,g]=C.computeOutAndReduceShapes(u.shape,m),y=v.sizeFromShape(g),x=t.makeOutput(f,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;ek(l,y,nt[x.dtype],A)}if(h&&t.disposeData(p.dataId),s){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var iie={kernelName:So,backendName:"wasm",setupFunc:rie,kernelFunc:sie},oie=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=y3(n,r,s,i),l=t.makeOutput([o.length],i);return t.typedArrayFromHeap(l).set(o),l},lie={kernelName:Ru,backendName:"wasm",kernelFunc:oie},uie=!0,die=Gt(_i,uie),pie=Qe(Co),cie=Qe(To),hie=Qe(Eo),tk;function mie(e){tk=e.wasm.cwrap(Ro,null,["number","number","number","number","number","number","number","number","number","number"])}function fie(e){let{backend:t,inputs:a,attrs:n}=e,{images:r}=a,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,[p,c,d,h]=r.shape,m=[p,l,u,h],f=t.dataIdMap.get(r.dataId),g;f.dtype!=="float32"&&(g=ys({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),f=t.dataIdMap.get(g.dataId));let y=f.id,x=t.makeOutput(m,"float32");if(v.sizeFromShape(r.shape)===0)return x;let A=t.dataIdMap.get(x.dataId).id;return tk(y,p,c,d,h,l,u,s?1:0,i?1:0,A),g!=null&&t.disposeData(g.dataId),x}var gie={kernelName:Ro,backendName:"wasm",setupFunc:mie,kernelFunc:fie},ak;function yie(e){ak=e.wasm.cwrap($u,null,["number","number","number","array","array","boolean"])}function xie(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=a.makeOutput(r.shape,"float32"),l=a.dataIdMap.get(r.dataId),u;return l.dtype!=="float32"&&(u=ys({backend:a,inputs:{x:r},attrs:{dtype:"float32"}}),l=a.dataIdMap.get(u.dataId)),ak(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(o.dataId).id,new Uint8Array(new Int32Array(r.shape).buffer),new Uint8Array(new Int32Array(s.shape).buffer),i),u!=null&&a.disposeData(u.dataId),o}var Aie={kernelName:$u,backendName:"wasm",setupFunc:yie,kernelFunc:xie},nk;function bie(e){nk=e.wasm.cwrap(No,null,["number","number","number","number","number","number","number","number","number","number"])}function vie(e){let{backend:t,inputs:a,attrs:n}=e,{images:r}=a,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,[p,c,d,h]=r.shape,m=[p,l,u,h],f=t.makeOutput(m,"float32");if(v.sizeFromShape(r.shape)===0)return f;let g=t.dataIdMap.get(r.dataId),y;g.dtype!=="float32"&&(y=ys({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),g=t.dataIdMap.get(y.dataId));let x=g.id,A=t.dataIdMap.get(f.dataId).id;return nk(x,p,c,d,h,l,u,s?1:0,i?1:0,A),y!=null&&t.disposeData(y.dataId),f}var wie={kernelName:No,backendName:"wasm",setupFunc:bie,kernelFunc:vie},rk;function kie(e){rk=e.wasm.cwrap(Mu,null,["number","number","number","array","array","boolean"])}function Iie(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=a.makeOutput(r.shape,"float32"),l=a.dataIdMap.get(r.dataId),u;return l.dtype!=="float32"&&(u=ys({backend:a,inputs:{x:r},attrs:{dtype:"float32"}}),l=a.dataIdMap.get(u.dataId)),rk(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(o.dataId).id,new Uint8Array(new Int32Array(r.shape).buffer),new Uint8Array(new Int32Array(s.shape).buffer),i),u!=null&&a.disposeData(u.dataId),o}var Sie={kernelName:Mu,backendName:"wasm",setupFunc:kie,kernelFunc:Iie},sk;function Cie(e){sk=e.wasm.cwrap(Mo,null,["number","array","number","array","number","number"])}function Tie(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dims:s}=n,i=v.parseAxisParam(s,r.shape);if(r.shape.length===0)return l0({inputs:{x:r},backend:a});let o=a.makeOutput(r.shape,r.dtype),l=a.dataIdMap.get(r.dataId).id,u=a.dataIdMap.get(o.dataId).id,p=new Uint8Array(new Int32Array(i).buffer),c=new Uint8Array(new Int32Array(r.shape).buffer);sk(l,p,i.length,c,r.shape.length,u);let d=La({inputs:{x:o},attrs:{shape:r.shape},backend:a});return a.disposeData(o.dataId),d}var Nie={kernelName:Mo,backendName:"wasm",kernelFunc:Tie,setupFunc:Cie},ik;function Rie(e){ik=e.wasm.cwrap(el,null,["number","number","number","number","number","number","number","number","array","number","number"])}function Eie(e){let{inputs:t,backend:a,attrs:n}=e,{image:r}=t,{radians:s,fillValue:i,center:o}=n,l=a.makeOutput(r.shape,r.dtype),u=a.dataIdMap.get(r.dataId).id,p=a.dataIdMap.get(l.dataId).id,[c,d,h,m]=r.shape,[f,g]=C.getImageCenter(o,d,h),y=i===0,x=255,A=typeof i=="number"?[i,i,i,y?0:x]:[...i,x],b=new Uint8Array(new Int32Array(A).buffer);return ik(u,c,d,h,m,s,f,g,b,A.length,p),l}var Mie={kernelName:el,backendName:"wasm",kernelFunc:Eie,setupFunc:Rie},$ie=Qe($o),Pie=Qe(Po),ok;function _ie(e){ok=e.wasm.cwrap(_o,null,["number","number","number","number","number","number","array","number","number"])}function Fie(e){let{backend:t,inputs:a,attrs:n}=e,{indices:r,updates:s}=a,{shape:i}=n,o=t.makeOutput(i,s.dtype);if(v.sizeFromShape(i)===0)return o;let{sliceRank:l,numUpdates:u,sliceSize:p,strides:c,outputSize:d}=jh.calculateShapes(s,r,i),h=t.dataIdMap.get(r.dataId).id,m=t.dataIdMap.get(s.dataId).id,f=new Uint8Array(new Int32Array(c).buffer),g=t.dataIdMap.get(o.dataId).id;return ok(h,m,nt[s.dtype],l,u,p,f,d,g),o}var Die={kernelName:_o,backendName:"wasm",setupFunc:_ie,kernelFunc:Fie},lk;function Oie(e){lk=e.wasm.cwrap(Do,null,["number","number","number","number","number","number","bool","number"])}function zie(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n;if(r.dtype!==s.dtype)throw new Error(`SearchSorted error: sorted_sequence must have the same dtype as values. 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${n.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape
${r.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let i=t.dataIdMap.get(n.dataId).id,o=t.dataIdMap.get(r.dataId).id,l=t.dataIdMap.get(s.dataId).id,u=n.shape[0],p=v.sizeFromShape(s.shape),c=t.makeOutput([u,p],n.dtype),d=t.dataIdMap.get(c.dataId).id,h=t.makeOutput([p],s.dtype),m=t.dataIdMap.get(h.dataId).id,f=t.makeOutput([3],"int32"),g=t.dataIdMap.get(f.dataId).id;ck(i,o,l,u,d,m,g);let y=t.readSync(f.dataId),x;switch(y[0]){case 0:{x=C.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(y[1],y[2]);break}case 1:{x=C.getSparseReshapeNegativeOutputDimErrorMessage(y[1],y[2]);break}case 2:x=C.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage();break;case 3:{let A=Array.from(t.readSync(r.dataId)),b=Array.from(t.readSync(h.dataId));x=C.getSparseReshapeInputOutputMultipleErrorMessage(A,b);break}case 4:{let A=Array.from(t.readSync(r.dataId)),b=Array.from(t.readSync(h.dataId));x=C.getSparseReshapeInputOutputMismatchErrorMessage(A,b);break}default:x=""}if(t.disposeData(f.dataId),x)throw t.disposeData(c.dataId),t.disposeData(h.dataId),new Error(x);return[c,h]}var roe={kernelName:Ou,backendName:"wasm",setupFunc:aoe,kernelFunc:noe},hk;function mk(e){hk=e.wasm.cwrap("SparseSegmentReduction",null,["number","number","number","number","number","number","number","number","number"])}function fk(e,t){let{backend:a,inputs:n}=e,{data:r,indices:s,segmentIds:i}=n,o=s.shape[0],l=a.readSync(i.dataId,o-1,o)[0],u=o>0?l+1:0;if(u<0)throw new Error(C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let p=r.shape.slice();p[0]=u;let c=a.dataIdMap.get(r.dataId).id,d=a.dataIdMap.get(s.dataId).id,h=a.dataIdMap.get(i.dataId).id,m=a.makeOutput(p,r.dtype),f=a.dataIdMap.get(m.dataId).id,g=a.makeOutput([4],"int32"),y=a.dataIdMap.get(g.dataId).id;hk(c,nt[r.dtype],r.shape[0],d,h,f,y,t,0);let x=a.readSync(g.dataId),A;switch(x[0]){case 0:{A=C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage();break}case 1:{A=C.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage();break}case 2:A=C.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(x[1],x[2]);break;case 3:A=C.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(x[1],x[2],x[3]);break;default:A=""}if(a.disposeData(g.dataId),A)throw a.disposeData(m.dataId),new Error(A);return m}function soe(e){return fk(e,!0)}var ioe={kernelName:zu,backendName:"wasm",setupFunc:mk,kernelFunc:soe};function ooe(e){return fk(e,!1)}var loe={kernelName:Lu,backendName:"wasm",setupFunc:mk,kernelFunc:ooe},gk;function uoe(e){gk=e.wasm.cwrap(jo,null,["number","number","number","number","number","number","number","number","array","number","number"])}function doe(e){let{backend:t,inputs:a,attrs:n}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=a,{outputShape:o}=n,l=t.makeOutput(o,i.dtype);if(v.sizeFromShape(o)===0)return l;let{sliceRank:u,numUpdates:p,sliceSize:c,strides:d,outputSize:h}=C.calculateShapes(s,r,o),m=t.dataIdMap.get(r.dataId).id,f=t.dataIdMap.get(s.dataId).id,g=t.dataIdMap.get(i.dataId).id,y=new Uint8Array(new Int32Array(d).buffer),x=t.dataIdMap.get(l.dataId).id;return gk(m,f,s.shape.length,g,nt[i.dtype],u,p,c,y,h,x),l}var poe={kernelName:jo,backendName:"wasm",setupFunc:uoe,kernelFunc:doe};function coe(e){let{inputs:t,attrs:a,backend:n}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=a,o=v.parseAxisParam(i,r.shape)[0],l=C.prepareSplitSize(r,s,o),u=new Array(r.shape.length).fill(0),p=r.shape.slice();return l.map(c=>{let d=[...p];d[o]=c;let h=si({inputs:{x:r},attrs:{begin:u,size:d},backend:n});return u[o]+=c,h})}var hoe={kernelName:Du,backendName:"wasm",kernelFunc:coe},moe=Qe(Uo),foe=Qe(Cp),goe=!0,yoe=Gt(qo,goe),yk;function xoe(e){yk=e.wasm.cwrap(ps,null,["number","number","number","number"])}function Aoe(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 yk(i,r,nt[s.dtype],l),o}var boe={kernelName:ps,backendName:"wasm",setupFunc:xoe,kernelFunc:Aoe},xk;function voe(e){xk=e.wasm.cwrap(Xo,null,["number","array","number","array","array","array","array","array","number","number"])}function woe(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:m,isIdentity:f,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Nt.sliceInfo(r.shape,s,i,o,l,u,p,c,d),w;if(f)w=La({inputs:{x:r},backend:t,attrs:{shape:m}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let I=Nt.computeOutShape(x,A,b),T=si({inputs:{x:r},backend:t,attrs:{begin:x,size:I}});w=La({inputs:{x:T},backend:t,attrs:{shape:m}}),t.disposeData(T.dataId)}else{let I=t.makeOutput(h,"float32"),T=t.dataIdMap.get(r.dataId).id,N=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),M=new Uint8Array(new Int32Array(x).buffer),$=new Uint8Array(new Int32Array(A).buffer),E=new Uint8Array(new Int32Array(b).buffer),S=new Uint8Array(new Int32Array(h).buffer),_=new Uint8Array(new Int32Array(v.computeStrides(h)).buffer),O=t.dataIdMap.get(I.dataId).id;xk(T,N,r.shape.length,M,$,E,S,_,h.length,O),w=La({inputs:{x:I},backend:t,attrs:{shape:m}}),t.disposeData(I.dataId)}return w}var koe={kernelName:Xo,backendName:"wasm",setupFunc:voe,kernelFunc:woe};function Ioe(e){let{backend:t,inputs:a,attrs:n}=e,{data:r,dataSplits:s}=a,{separator:i,nGramWidths:o,leftPad:l,rightPad:u,padWidth:p,preserveShortSequences:c}=n,d=t.readSync(r.dataId),h=t.readSync(s.dataId),[m,f]=A3(d,h,i,o,l,u,p,c),g=t.makeOutput([m.length],"string"),y=t.dataIdMap.get(g.dataId);y.stringBytes=m;let x=t.makeOutput(s.shape,"int32");return t.typedArrayFromHeap(x).set(f),[g,x]}var Soe={kernelName:Wu,backendName:"wasm",kernelFunc:Ioe};function Coe(e){let{backend:t,inputs:a,attrs:n}=e,{input:r,delimiter:s}=a,{skipEmpty:i}=n,o=t.readSync(r.dataId),l=t.readSync(s.dataId),[u,p,c]=b3(o,l[0],i),d=p.length,h=t.makeOutput([d,2],"int32");t.typedArrayFromHeap(h).set(u);let m=t.makeOutput([d],"string"),f=t.dataIdMap.get(m.dataId);f.stringBytes=p;let g=t.makeOutput([2],"int32");return t.typedArrayFromHeap(g).set(c),[h,m,g]}var Toe={kernelName:Np,backendName:"wasm",kernelFunc:Coe};function Noe(e){let{backend:t,inputs:a,attrs:n}=e,{input:r}=a,{numBuckets:s}=n,i=t.readSync(r.dataId),o=v3(i,s),l=t.makeOutput(r.shape,"int32");return t.typedArrayFromHeap(l).set(o),l}var Roe={kernelName:Rp,backendName:"wasm",kernelFunc:Noe},Eoe=!0,Moe=Gt(Ko,Eoe),Ak;function $oe(e){Ak=e.wasm.cwrap(Go,null,["number","number","number","number"])}function Poe(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:c,originalAxes:d,inputWasTransposed:h}=gs(i,r,t),m=c;if(h){let A=t.dataIdMap.get(p.dataId).id;A!==o&&(u=p,l=A,m=C.getInnerMostAxes(m.length,u.shape.length))}C.assertAxesAreInnerMostDims("sum",m,u.shape.length);let[f,g]=C.computeOutAndReduceShapes(u.shape,m),y=v.sizeFromShape(g),x=t.makeOutput(f,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;Ak(l,y,nt[x.dtype],A)}if(h&&t.disposeData(p.dataId),s){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var _oe={kernelName:Go,backendName:"wasm",setupFunc:$oe,kernelFunc:Poe},Foe=Qe(Yo),Doe=Qe(Zo),bk;function Ooe(e){bk=e.wasm.cwrap(Fo,null,["number","number","number","number","number","number","array","number","number","number"])}function zoe(e){let{backend:t,inputs:a,attrs:n}=e,{tensor:r,indices:s,updates:i}=a,{}=n,o=t.makeOutput(r.shape,r.dtype);if(v.sizeFromShape(r.shape)===0)return o;let{sliceRank:l,numUpdates:u,sliceSize:p,strides:c,outputSize:d}=jh.calculateShapes(i,s,r.shape),h=t.dataIdMap.get(s.dataId).id,m=t.dataIdMap.get(i.dataId).id,f=t.dataIdMap.get(r.dataId).id,g=new Uint8Array(new Int32Array(c).buffer),y=t.dataIdMap.get(o.dataId).id;return bk(h,m,nt[i.dtype],l,u,p,g,d,y,f),o}var Loe={kernelName:Fo,backendName:"wasm",setupFunc:Ooe,kernelFunc:zoe},vk;function Woe(e){vk=e.wasm.cwrap(ds,null,["number","array","number","array","number","number"])}function Boe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,s=a.dataIdMap.get(r.dataId).id,{reps:i}=n,o=new Array(r.shape.length);for(let 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`)+vle,lh(t.shape),u,Cle(t.shape.length)];a.atomic||p.push(Tle(t.shape,t.dtype,a.outputComponent)),a.variableNames.forEach((h,m)=>{p.push(`${lh(e[m].shape,h)}`)});let c=e.map((h,m)=>Ile(h,t.shape,a.variableComponents?a.variableComponents[m]:a.outputComponent,a.dispatchLayout.x.length===t.shape.length)).join(`
`);p.push(c),p.push(a.getUserCode());let d=rA(a);return p.push(aA(d,a)),p.join(`
`)}function ble(e,t,a){let n=e.shaderKey;if(e.pixelsOpType!=null)return n;let r=[],s=[];t.forEach(p=>{r.push(p.shape),s.push(p.dtype)}),r.push(a.shape),s.push(a.dtype);let i=t.map(p=>C.getBroadcastDims(p.shape,a.shape)),o=t.map(p=>v.arraysEqual(p.shape,a.shape)).join("_"),l=i.map(p=>p.join("_")).join(";"),u=Ck(e)?"flatDispatch":"";return n+="_"+(e.workgroupSize?e.workgroupSize.join(","):"")+r.map(p=>p.length).join(",")+s.join(",")+e.variableNames.join(",")+l+o+u,n}var nA=`
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;
}
// 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> {
let floatToUint: vec4<u32> = bitcast<vec4<u32>>(val);
return (floatToUint & vec4<u32>(0x7fffffffu)) > vec4<u32>(0x7f800000u);
}
`,vle=`
fn isinf(val: f32) -> bool {
return abs(val) == uniforms.INFINITY;
}
`;function lh(e,t=""){let a=e.length,n=t!==""?`get${t.charAt(0).toUpperCase()+t.slice(1)}CoordsFromIndex`:"getCoordsFromIndex",r=t!==""?`${t.charAt(0).toLowerCase()+t.slice(1)}ShapeStrides`:"outShapeStrides";if(a<=1)return`fn ${n}(index : i32) -> i32 { return index; }`;let s=v.computeStrides(e),i=Pt(a),o=[];for(let u=0;u<a;u++)o.push(`d${u}`);if(s.length===1)return` fn ${n}(index : i32) -> vec2<i32> {
let d0 = index / uniforms.${r}; let d1 = index - d0 * uniforms.${r};
return vec2<i32>(d0, d1);
}`;let l;return l="var index2 = index;"+s.map((u,p)=>{let c=`let ${o[p]} = index2 / uniforms.${r}.${Sr(p)}`,d=p===s.length-1?`let ${o[p+1]} = index2 - ${o[p]} * uniforms.${r}.${Sr(p)}`:`index2 = index2 - ${o[p]} * uniforms.${r}.${Sr(p)}`;return`${c}; ${d};`}).join(""),`
fn ${n}(index : i32) -> ${i} {
${l}
return ${i}(${o.join(",")});
}
`}function wle(e,t){let a=e.name,n=e.shape.length,r=Pt(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`
fn ${s}() -> ${Xe(t)} {
return ${Xe(t)}(${a}[0]);
}
`;let l=`uniforms.${a.charAt(0).toLowerCase()+a.slice(1)}Shape`,u=`${n}D`;return n===0&&(u="1D"),`
fn ${s}(${o}) -> ${Xe(t)} {
return ${Xe(t)}(${a}[getIndexFromCoords${u}(${r}(${i.join(",")}),
${l})${t===1?"":` / ${t}`}]);
}
`}function kle(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=Pt(l);if(v.arraysEqual(e.shape,t)&&n)return`
fn ${i}Index(globalIndex : i32) -> ${Xe(a)} {
return ${Xe(a)}(${r}[globalIndex]);
}
fn ${i}Coords(coords : ${u}) -> ${Xe(a)} {
return ${Xe(a)}(${r}[${l>1?"getOutputIndexFromCoords(coords)":"coords"}${a===1?"":` / ${a}`}]);
}
`;let p=C.getBroadcastDims(e.shape,t),c=l-o,d="";if(o===0)return`
fn ${i}Index(globalIndex : i32) -> ${Xe(a)}{
return get${s}();
}
fn ${i}Coords(coords : ${u}) -> ${Xe(a)}{
return get${s}();
}
`;l<2&&p.length>=1?d="coords = 0;":d=p.map(g=>`coords.${Sr(g+c)} = 0;`).join(`
`);let h="";if(l<2&&o>0)h="coords";else if(l>1){let g=Pt(o),y=e.shape.map((x,A)=>`coords.${Sr(A+c)}`).join(", ");h=`${g}(${y})`}else h="coords";let m=`uniforms.${r.charAt(0).toLowerCase()+r.slice(1)}Shape`,f=`${o}D`;return`
fn ${i}Index(globalIndex : i32) -> ${Xe(a)} {
var coords = getCoordsFromIndex(globalIndex);
${d}
return ${Xe(a)}(${r}[getIndexFromCoords${f}(${h}, ${m})${a===1?"":` / ${a}`}]);
}
fn ${i}Coords(coordsIn : ${u}) -> ${Xe(a)} {
var coords = coordsIn;
${d}
return ${Xe(a)}(${r}[getIndexFromCoords${f}(${h}, ${m})${a===1?"":` / ${a}`}]);
}
`}function Ile(e,t,a,n){let r=wle(e,a);return e.shape.length<=t.length&&(r+=kle(e,t,a,n)),r}function Sle(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() -> ${Pt(s)}{
let globalIndex = getGlobalIndex();
return getCoordsFromIndex(globalIndex);
}
`;let o="",l=[a,n,r];for(let d=0;d<l.length;d++){let h=l[d];if(h.length!==0)if(h.length===1)o+=`let d${h[0]} = i32(globalId[${d}]);`;else{let m=gle(h,"uniforms.outShape");o+=`var index${d} = i32(globalId[${d}]);`;for(let f=0;f<m.length;f++)o+=`let d${h[f]} = index${d} / ${m[f]};`,f===m.length-1?o+=`let d${h[f+1]} = index${d} - d${h[f]} * ${m[f]};`:o+=`index${d} = index${d} - d${h[f]} * ${m[f]};`}}let u=[];for(let d=0;d<i;d++)u.push(`d${d}`);let p=Pt(i),c=`fn getOutputCoords() -> ${p} {
${o}
`;return u.length===0?c+=`return ${p}(0); }`:c+=`return ${p}(${u.join(",")}); }`,c}function Cle(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 Ck(e){return e.dispatch[1]===1&&e.dispatch[2]===1}function Hs(e,t=1){if(e==="float32")return Xe(t,"f32");if(e==="int32"||e==="bool")return Xe(t,"i32");throw new Error(`type ${e} is not supported.`)}function Tle(e,t,a){let n=e.length,r=Hs(t,a),s=`fn setOutputAtIndex(flatIndex : i32, value : ${Xe(a)}) {
result[flatIndex] = ${r}(value);
}
fn setOutputAtIndexI32(flatIndex : i32, value : ${Xe(a,"i32")}) {
result[flatIndex] = ${r}(value);
}
`;if(n>=2){let i=["d0","d1","d2","d3","d4","d5"].slice(0,n),o=Pt(n);s+=`
fn setOutputAtCoords(${i.map(l=>`${l} : i32`).join(", ")}, value : ${Xe(a)}) {
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
setOutputAtIndex(flatIndex${a===1?"":` / ${a}`}, value);
}
fn setOutputAtCoordsI32(${i.map(l=>`${l} : i32`).join(", ")}, value : ${Xe(a,"i32")}) {
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
setOutputAtIndexI32(flatIndex${a===1?"":` / ${a}`}, value);
}
`}return s}function Nle(e){let t=/(\w+)\s*:\s*vec(5|6)/g;e=e.replace(t,n=>"@align(16) "+n);let a=/vec(5|6)\s*,\s*(\w+)/g;return e=e.replace(a,(n,r,s)=>`vec${r}, @align(16) ${s}`),e}function rA(e){return!(e.dispatchLayout.hasOwnProperty("y")&&e.dispatchLayout.y.length!==0||e.dispatchLayout.hasOwnProperty("z")&&e.dispatchLayout.z.length!==0)}var Tk={};Ze(Tk,{GPUBytesPerElement:()=>q1,MatMulProgramType:()=>On,assertNotComplex:()=>q3,computeDispatch:()=>de,computeWorkPerThreadForConv2d:()=>H3,computeWorkgroupInfoForMatMul:()=>Nk,computeWorkgroupSizeForConv2d:()=>G3,flatDispatchLayout:()=>me,isWebGPUSupported:()=>j3,tilesFitEvenlyIntoShape:()=>Rle});var Xs=e=>{let t=1;for(let a=0;a<e.length;a++)t*=e[a];return t};function Rle(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 de(e,t,a=[1,1,1],n=[1,1,1]){let[r,s,i]=[Math.ceil(Xs(e.x.map(o=>t[o]))/(a[0]*n[0])),e.y?Math.ceil(Xs(e.y.map(o=>t[o]))/(a[1]*n[1])):1,e.z?Math.ceil(Xs(e.z.map(o=>t[o]))/(a[2]*n[2])):1];return[r,s,i]}function Nk(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 G3(e,t,a=!1){if(a)return[8,8,1];let n=Xs(e.x.map(s=>t[s])),r=Xs(e.y.map(s=>t[s]));return n<=4?[4,16,1]:r<=4?[16,4,1]:[16,16,1]}function H3(e,t,a=!1){if(a)return[4,4,1];let n=Xs(e.x.map(s=>t[s])),r=Xs(e.y.map(s=>t[s]));return n<=4?[1,2,1]:r<=4?[2,1,1]:[2,2,1]}function me(e){return{x:e.map((t,a)=>a)}}function q1(e){if(e==="float32"||e==="int32"||e==="bool"||e==="string")return 4;if(e==="complex64")return 8;throw new Error(`Unknown dtype ${e}`)}function j3(){return!!(typeof globalThis!="undefined"&&globalThis.navigator&&globalThis.navigator.gpu)}function q3(e,t){Array.isArray(e)||(e=[e]),e.forEach(a=>{a!=null&&v.assert(a.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGPU backend.`)})}var On;(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"})(On||(On={}));var Ele=B().getNumber("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD"),Mle=(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]},X3=class Rk extends su{nextDataId(){return Rk.nextDataId++}constructor(t,a){if(super(),this.commandQueueOwnedIds=new WeakSet,this.dispatchCountInPass=0,this.disposed=!1,this.downloadWaitMs=0,this.tensorDataPendingDisposal=[],this.queryResolveBuffer=null,this.querySet=null,this.querySetCount=2,this.stagingPendingDisposal=[],this.uniformPendingDisposal=[],this.uploadWaitMs=0,this.hasReadSyncWarned=!1,this.hasTimestampQueryWarned=!1,!j3())throw new Error("WebGPU is not supported on this device");this.pipelineCache={},this.device=t,this.queue=t.queue,this.commandEncoder=null,this.computePassEncoder=null,this.adapterInfo=new hle(a),this.supportTimestampQuery=this.device.features.has("timestamp-query"),this.thresholdToIncreaseWorkgroups=this.adapterInfo.intelGPUGeneration>=12?16:8,this.bufferManager=new mle(this.device),this.textureManager=new fle(this.device),this.tensorMap=new op(this,It()),B().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:t,format:"bgra8unorm"}),document.body.appendChild(this.dummyCanvas))}floatPrecision(){return 32}disposeData(t,a=!1){if(!this.tensorMap.has(t))return!0;let n=this.tensorMap.get(t);return a?n.refCount=0:n.refCount--,n.refCount>0?!1:(n.complexTensorInfos!=null&&(this.disposeData(n.complexTensorInfos.real.dataId),this.disposeData(n.complexTensorInfos.imag.dataId)),this.commandQueueOwnedIds.has(t)?(this.tensorDataPendingDisposal.push(t),!0):(this.releaseResource(t),this.tensorMap.delete(t),!0))}memory(){return{numBytesInGPU:this.bufferManager.numBytesUsed,numBytesAllocatedInGPU:this.bufferManager.numBytesAllocated,unreliable:!1}}releaseResource(t){let a=this.tensorMap.get(t);if(!(!a||!a.resource)){if(a.external){a.resource=null;return}a.resource instanceof GPUBuffer?this.bufferManager.releaseBuffer(a.resource):a.resource instanceof GPUTexture&&this.textureManager.releaseTexture(a.resource),a.resource=null}}refCount(t){return this.tensorMap.has(t)?this.tensorMap.get(t).refCount:0}incRef(t){let a=this.tensorMap.get(t);a.refCount++}decRef(t){if(this.tensorMap.has(t)){let a=this.tensorMap.get(t);a.refCount--}}write(t,a,n){if(n==="complex64"&&t!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let r={id:this.nextDataId()};return this.tensorMap.set(r,{dtype:n,shape:a,values:t,refCount:1}),r}move(t,a,n,r,s){if(r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.tensorMap.set(t,{dtype:r,shape:n,values:a,refCount:s})}submitQueue(){this.queue.submit([this.commandEncoder.finish()]),this.commandEncoder=null,this.dispatchCountInPass=0,this.commandQueueOwnedIds=new WeakSet,this.tensorDataPendingDisposal.forEach(t=>{this.releaseResource(t),this.tensorMap.delete(t)}),this.uniformPendingDisposal.forEach(t=>this.bufferManager.releaseBuffer(t)),this.stagingPendingDisposal.forEach(t=>this.bufferManager.releaseBuffer(t,!1)),this.tensorDataPendingDisposal=[],this.uniformPendingDisposal=[],this.stagingPendingDisposal=[]}ensureCommandEncoderReady(){this.commandEncoder||(this.commandEncoder=this.device.createCommandEncoder())}endComputePassEncoder(){this.computePassEncoder&&(this.computePassEncoder.end(),this.computePassEncoder=null)}async checkCompileCompletionAsync(){let t;try{t=await Promise.all(Object.values(this.pipelineCache))}catch(a){throw new Error(a.message)}Object.keys(this.pipelineCache).map((a,n)=>{this.pipelineCache[a]=t[n]})}async getBufferData(t){if(B().getBool("WEBGPU_ENGINE_COMPILE_ONLY"))return console.warn("The data may be invalid since WEBGPU_ENGINE_COMPILE_ONLY is true, this can only be called when WEBGPU_ENGINE_COMPILE_ONLY is false"),null;let a=t.size,n=this.bufferManager.acquireBuffer(a,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ);this.ensureCommandEncoderReady(),this.endComputePassEncoder(),this.commandEncoder.copyBufferToBuffer(t,0,n,0,a),this.submitQueue(),await n.mapAsync(GPUMapMode.READ);let r=n.getMappedRange().slice(0);return n.unmap(),n!=null&&this.bufferManager.releaseBuffer(n),B().getBool("WEBGPU_USE_PROFILE_TOOL")&&(v.assert(this.dummyContext!==void 0,()=>"Fail to get context for profiling tool"),this.dummyContext.getCurrentTexture()),r}convertAndCacheOnCPU(t,a){let n=this.tensorMap.get(t);return n.values=a,n.values}readSync(t){let a=this.tensorMap.get(t),{values:n,complexTensorInfos:r}=a;if(n!=null||a.dtype==="string")return n;if(a.dtype==="complex64"){let f=this.readSync(r.real.dataId),g=this.readSync(r.imag.dataId),y=v.convertBackendValuesAndArrayBuffer(C.mergeRealAndImagArrays(f,g).buffer,"float32");return this.convertAndCacheOnCPU(t,y),y}this.hasReadSyncWarned||(this.hasReadSyncWarned=!0,console.warn("The performance of synchronously reading data from GPU to CPU is poor on the webgpu backend, please use asynchronous APIs instead."));let s=["opaque","premultiplied"],i=a.resource,o=i.size;v.assert(o%4===0,()=>"Because there is 4 bytes for one pixel, buffer size must be multiple of 4.");let l=o/4,u=new ArrayBuffer(o),p=256,c=256,d=s.map(f=>new OffscreenCanvas(p,c)),h=new OffscreenCanvas(p,c);this.endComputePassEncoder(),d.map((f,g)=>{let y=f.getContext("webgpu");return y.configure({device:this.device,format:"bgra8unorm",usage:GPUTextureUsage.COPY_DST,alphaMode:s[g]}),y.getCurrentTexture()}).map((f,g)=>{let y=p*4,x=(N,M,$)=>{this.ensureCommandEncoderReady(),this.commandEncoder.copyBufferToTexture({buffer:i,bytesPerRow:y,offset:$},{texture:f},{width:N,height:M}),this.submitQueue();let E=h.getContext("2d",{willReadFrequently:!0});E.clearRect(0,0,N,M),E.drawImage(d[g],0,0);let S=E.getImageData(0,0,N,M).data,_=s[g],O=new Uint8ClampedArray(u,$,N*M*4);for(let W=0;W<O.length;W+=4)if(_==="premultiplied")O[W+3]=S[W+3];else{let P=S[W];O[W]=S[W+2],O[W+1]=S[W+1],O[W+2]=P}},A=Math.floor(l/(p*c)),b=p,w=c,I=0;for(let N=0;N<A;N++)x(b,w,I),I+=p*c*4;let T=l%(p*c);w=Math.floor(T/p),w>0&&(x(b,w,I),I+=w*(p*4)),b=T%p,b>0&&x(b,1,I)});let m=v.convertBackendValuesAndArrayBuffer(u,a.dtype);return this.convertAndCacheOnCPU(t,m),m}async read(t){if(!this.tensorMap.has(t))throw new Error(`Tensor ${t} was not registered!`);let a=this.tensorMap.get(t),{values:n}=a;if(n!=null)return n;let r;if(a.dtype==="complex64"){let s=await Promise.all([this.read(a.complexTensorInfos.real.dataId),this.read(a.complexTensorInfos.imag.dataId)]),i=s[0],o=s[1];r=C.mergeRealAndImagArrays(i,o)}else{let s=await this.getBufferData(a.resource);r=v.convertBackendValuesAndArrayBuffer(s,a.dtype)}return this.convertAndCacheOnCPU(t,r),r}copyBuffer(t){let a=t.size,n=t.usage,r=this.bufferManager.acquireBuffer(a,n);return this.ensureCommandEncoderReady(),this.endComputePassEncoder(),this.commandEncoder.copyBufferToBuffer(t,0,r,0,a),this.submitQueue(),r}createTensorFromGPUData(t,a,n){let r=t.buffer;if(n==="complex64")throw new Error("Cannot write to a complex64 dtype. ");let s={id:this.nextDataId()};this.tensorMap.set(s,{dtype:n,shape:a,values:null,refCount:1,external:t.zeroCopy});let i=this.tensorMap.get(s),o=q1(i.dtype)*v.sizeFromShape(i.shape);if(t.buffer.size<o)throw new Error(`GPUBuffer size(${t.buffer.size}) is smaller than tensor size(${o})!`);if((t.buffer.usage&(GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC))!==(GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC))throw new Error("GPUBuffer.usage should include GPUBufferUsage.STORAGE | GPUBufferUsage.COPY_SRC!");return t.zeroCopy!==!0&&(r=this.copyBuffer(r)),i.resource=r,It().makeTensorFromDataId(s,a,n,this)}readToGPU(t){let a=this.tensorMap.get(t),{values:n,dtype:r,shape:s,resource:i}=a;if(r==="complex64")throw new Error("Does not support reading buffer for complex64 dtype.");if(i==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 o=i,l=o.size,u=o.usage,p=this.bufferManager.acquireBuffer(l,u);this.ensureCommandEncoderReady(),this.endComputePassEncoder(),this.commandEncoder.copyBufferToBuffer(i,0,p,0,l),this.submitQueue();let c=this.makeTensorInfo(s,r),d=It().makeTensorFromTensorInfo(c),h=this.tensorMap.get(c.dataId);return h.resource=p,{tensorRef:d,buffer:p}}bufferSync(t){let a=this.readSync(t.dataId);if(t.dtype==="string")try{let n=a.map(r=>v.decodeString(r));return _e(t.shape,t.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return _e(t.shape,t.dtype,a)}async time(t){!this.supportTimestampQuery&&!this.hasTimestampQueryWarned&&(console.warn("This device doesn't support timestamp-query extension. Start Chrome browser with flag --enable-dawn-features=allow_unsafe_apis to try it again. Otherwise, zero will be shown for the kernel time when profiling mode is enabled."),this.hasTimestampQueryWarned=!0);let a=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,t();let s=v.flatten(this.activeTimers.map(u=>u.query)).filter(u=>u!=null),i=v.flatten(this.activeTimers.map(u=>u.name)).filter(u=>u!=null);this.activeTimers=a,r&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},l=await Promise.all(s);return o.kernelMs=v.sum(l),o.getExtraProfileInfo=()=>l.map((u,p)=>({name:i[p],ms:u})).map(u=>`${u.name}: ${u.ms}`).join(", "),this.uploadWaitMs=0,this.downloadWaitMs=0,o}makeTensorInfo(t,a,n){return a==="string"&&n!=null&&n.length>0&&v.isString(n[0])&&(n=n.map(r=>v.encodeString(r))),{dataId:this.write(n,t,a),shape:t,dtype:a}}tensorToBinding(t){if(!t)return null;let a=this.tensorMap.get(t.dataId).resource;return a instanceof GPUBuffer?{buffer:a}:a instanceof GPUTexture?a.createView():a}uploadToGPU(t){let a=this.tensorMap.get(t);if(a.resource!=null)return;let n=q1(a.dtype)*v.sizeFromShape(a.shape),r,s=GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST;if(a.values){if(r=this.bufferManager.acquireBuffer(n,s,!0),r.mapState==="unmapped"){let i=this.bufferManager.acquireBuffer(n,GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC,!0,!1),o=i.getMappedRange();a.dtype==="int32"||a.dtype==="bool"?new Int32Array(o).set(a.values):new Float32Array(o).set(a.values),i.unmap(),this.ensureCommandEncoderReady(),this.endComputePassEncoder(),this.commandEncoder.copyBufferToBuffer(i,0,r,0,n),this.stagingPendingDisposal.push(i)}else{let i=r.getMappedRange();a.dtype==="int32"||a.dtype==="bool"?new Int32Array(i).set(a.values):new Float32Array(i).set(a.values),r.unmap()}a.values=null}else r=this.bufferManager.acquireBuffer(n,s);a.resource=r}makeUniforms(t){let a=0,n=0,r=[],s=1;t.forEach(l=>{l.data.length===0&&(l.data=[1]);let u;switch(l.data.length){case 1:u=4;break;case 2:u=8;break;case 3:u=16;break;case 4:u=16;break;case 5:u=16;break;case 6:u=16;break;default:v.assert(!1,()=>`Unsupported ${l.data.length}D shape`)}(n===5||n===6)&&(u=16),u>s&&(s=u),a=Math.ceil(a/u)*u,n=l.data.length,r.push(a),a+=l.data.length*4}),a=Math.ceil(a/s)*s;let i=new ArrayBuffer(a);t.forEach((l,u)=>{let p=r[u];l.type==="int32"?new Int32Array(i,p,l.data.length).set(l.data):l.type==="uint32"?new Uint32Array(i,p,l.data.length).set(l.data):new Float32Array(i,p,l.data.length).set(l.data)});let o=this.bufferManager.acquireBuffer(a,GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM);return this.queue.writeBuffer(o,0,i,0,a),this.uniformPendingDisposal.push(o),{offset:0,size:a,buffer:o}}runWebGPUProgram(t,a,n,r,s){if(s||(s=this.makeTensorInfo(t.outputShape,n)),v.sizeFromShape(s.shape)===0)return this.tensorMap.get(s.dataId).values=v.getTypedArrayFromDType(s.dtype,0),s;this.uploadToGPU(s.dataId),t.dispatch=Mle(this.device,t);let i=a.map((l,u)=>{if(l.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(l.dataId),{dtype:this.tensorMap.get(l.dataId).dtype,shape:l.shape,name:t.variableNames[u]}});t.shaderKey=ble(t,i,s);let o=B().getBool("WEBGPU_ENGINE_COMPILE_ONLY");return t.shaderKey in this.pipelineCache||(this.pipelineCache[t.shaderKey]=yle(this.device,t,i,s,o)),t.pipeline=this.pipelineCache[t.shaderKey],o||this.recordAndSubmit(t,s,a,r),s}recordAndSubmit(t,a,n,r){if(t.pipeline instanceof Promise)throw new Error("Please call checkCompileCompletionAsync to ensure parallel compilation is done!");let s=[],i=[],o="int32";if(t.pixelsOpType==null){s.push({type:"float32",data:[NaN]},{type:"float32",data:[1/0]}),i=n.concat(a).map(h=>h.shape);let d="int32";i.map(h=>{s.push({type:d,data:h});let m=v.computeStrides(h);s.push({type:d,data:m})})}else{let d=v.computeStrides(a.shape);s.push({type:o,data:d})}if(t.size){let d=v.sizeFromShape(t.outputShape);s.push({type:o,data:[t.outputComponent?d/t.outputComponent:d]})}r&&(s=[...s,...r]);let l=[this.tensorToBinding(a),...n.map(d=>this.tensorToBinding(d)),this.makeUniforms(s)];n.forEach(d=>{this.commandQueueOwnedIds.add(d.dataId)}),this.commandQueueOwnedIds.add(a.dataId);let u=this.device.createBindGroup({layout:t.pipeline.getBindGroupLayout(0),entries:l.map((d,h)=>({binding:h,resource:d}))}),p=this.activeTimers!=null;this.ensureCommandEncoderReady();let c={};p&&this.supportTimestampQuery?(this.endComputePassEncoder(),this.querySet==null&&(this.querySet=this.device.createQuerySet({type:"timestamp",count:this.querySetCount})),c.timestampWrites={querySet:this.querySet,beginningOfPassWriteIndex:0,endOfPassWriteIndex:1},this.computePassEncoder=this.commandEncoder.beginComputePass(c)):this.computePassEncoder||(this.computePassEncoder=this.commandEncoder.beginComputePass(c)),this.computePassEncoder.setPipeline(t.pipeline),this.computePassEncoder.setBindGroup(0,u),this.computePassEncoder.dispatchWorkgroups(t.dispatch[0],t.dispatch[1],t.dispatch[2]),this.dispatchCountInPass++,(p||B().get("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE")<=this.dispatchCountInPass||t.pixelsOpType===nu.DRAW)&&(this.endComputePassEncoder(),p?this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime()}):this.submitQueue())}async getQueryTime(){if(!this.supportTimestampQuery)return 0;this.queryResolveBuffer==null&&(this.queryResolveBuffer=this.bufferManager.acquireBuffer(this.querySetCount*8,GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST|GPUBufferUsage.QUERY_RESOLVE)),this.commandEncoder.resolveQuerySet(this.querySet,0,this.querySetCount,this.queryResolveBuffer,0);let t=this.bufferManager.acquireBuffer(this.querySetCount*8,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST);this.commandEncoder.copyBufferToBuffer(this.queryResolveBuffer,0,t,0,this.querySetCount*8),this.submitQueue(),await t.mapAsync(GPUMapMode.READ);let a=new BigUint64Array(t.getMappedRange()),n=Number(a[1]-a[0])/1e6;return t.unmap(),this.bufferManager.releaseBuffer(t),n}shouldExecuteOnCPU(t,a=Ele){return B().getBool("WEBGPU_CPU_FORWARD")&&t.every(n=>this.tensorMap.get(n.dataId).resource==null&&v.sizeFromShape(n.shape)<a)}numDataIds(){return this.tensorMap.numDataIds()-this.tensorDataPendingDisposal.length}dispose(){this.disposed||(this.querySet!=null&&this.querySet.destroy(),this.bufferManager.dispose(),this.textureManager.dispose(),this.disposed=!0)}};X3.nextDataId=0;j3()&&al("webgpu",async()=>{let e={powerPreference:B().get("WEBGPU_USE_LOW_POWER_GPU")?"low-power":"high-performance"},t=await navigator.gpu.requestAdapter(e),a={},n=[];t.features.has("timestamp-query")&&n.push("timestamp-query"),t.features.has("bgra8unorm-storage")&&n.push(["bgra8unorm-storage"]),a.requiredFeatures=n;let r=t.limits;a.requiredLimits={maxComputeWorkgroupStorageSize:r.maxComputeWorkgroupStorageSize,maxComputeWorkgroupsPerDimension:r.maxComputeWorkgroupsPerDimension,maxStorageBufferBindingSize:r.maxStorageBufferBindingSize,maxBufferSize:r.maxBufferSize,maxComputeWorkgroupSizeX:r.maxComputeWorkgroupSizeX,maxComputeInvocationsPerWorkgroup:r.maxComputeInvocationsPerWorkgroup};let s=await t.requestDevice(a),i=await t.requestAdapterInfo();return new X3(s,i)},3);var Pe;(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.ELU_DER=5]="ELU_DER",e[e.EQUAL=6]="EQUAL",e[e.FLOOR_DIV=7]="FLOOR_DIV",e[e.GREATER=8]="GREATER",e[e.GREATER_EQUAL=9]="GREATER_EQUAL",e[e.LESS=10]="LESS",e[e.LESS_EQUAL=11]="LESS_EQUAL",e[e.LOGICAL_AND=12]="LOGICAL_AND",e[e.LOGICAL_OR=13]="LOGICAL_OR",e[e.MAX=14]="MAX",e[e.MIN=15]="MIN",e[e.MOD=16]="MOD",e[e.MUL=17]="MUL",e[e.NOT_EQUAL=18]="NOT_EQUAL",e[e.POW=19]="POW",e[e.PRELU=20]="PRELU",e[e.SQUARED_DIFFERENCE=21]="SQUARED_DIFFERENCE",e[e.SUB=22]="SUB"})(Pe||(Pe={}));var $le="let resultTemp = a + b;",Ple="let resultTemp = atan2(a, b);",_le="let resultTemp = areal * breal - aimag * bimag;",Fle="let resultTemp = areal * bimag + aimag * breal;",Dle="let resultTemp = a / b;",Ole="let resultTemp = select(a * (b + 1.0), a, b >= b - b);",zle=`
let zero = sign(a) * 0 + 0;
let one = sign(b) * 0 + 1;
let resultTemp = select(zero, one, a == b);
`,Lle=`
let remainder =
select(a % b, round(a % b), (round(a) == a) & (round(b) == b));
let quotient = (a - remainder) / b;
let resultTemp =
round(select(quotient, quotient - 1, sign(remainder) == -sign(b)));
`,Wle=`
let zero = sign(a) * 0 + 0;
let one = sign(b) * 0 + 1;
let resultTemp = select(zero, one, a > b);
`,Ble=`
let zero = sign(a) * 0 + 0;
let one = sign(b) * 0 + 1;
let resultTemp = select(zero, one, a >= b);
`,Vle=`
let zero = sign(a) * 0 + 0;
let one = sign(b) * 0 + 1;
let resultTemp = select(zero, one, a < b);
`,Ule=`
let zero = sign(a) * 0 + 0;
let one = sign(b) * 0 + 1;
let resultTemp = select(zero, one, a <= b);
`,Gle="return f32(a >= 1.0 && b >= 1.0);",Hle=`return (vec4<f32>(a >= vec4<f32>(1.0)) *
vec4<f32>(b >= vec4<f32>(1.0)));`,jle="return f32(a >= 1.0 || b >= 1.0);",qle=`return min(vec4<f32>(a >= vec4<f32>(1.0)) +
vec4<f32>(b >= vec4<f32>(1.0)), vec4<f32>(1.0));`,Xle="let resultTemp = max(a, b);",Kle="let resultTemp = min(a, b);",Yle=`
let isNaN = b == 0.;
var resultTemp = a % b;
resultTemp = select((resultTemp + b) % b, resultTemp,
(a < 0. && b < 0.) || (a >= 0. && b > 0.));
`,Zle=`
let isNaN = !vec4<bool>(b);
var resultTemp = vec4<f32>(a % b);
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];
}
`,Jle="let resultTemp = a * b;",Qle=`
var resultTemp = f32(a != b);
let valueForNaN = 1.0;
`,eue=`
var resultTemp = vec4<f32>(a != b);
let valueForNaN = 1.0;
`,tue=`
let isNaN = a < 0.0 && floor(b) < b;
if (b == 0.0) {
return 1.0;
}
var resultTemp = select(sign(a) * pow(abs(a), b), pow(abs(a), b),
round(abs(b) % 2.0) != 1.0);
`,aue=`
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);
`,nue="if (a < 0.0) { return b * a; } return a;",rue=`
let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
return (aLessThanZero * (b * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
`,sue="let resultTemp = (a - b) * (a - b);",iue="let resultTemp = a - b;";function K3(e,t){let a;do{switch(e){case Pe.ATAN2:a=Ple;break;case Pe.MAX:a=Xle;break;case Pe.MIN:a=Kle;break;case Pe.MOD:a=t?Zle:Yle;break;case Pe.NOT_EQUAL:a=t?eue:Qle;break;case Pe.POW:a=t?aue:tue;break;default:continue}let n,r,s;return t?(n="isnanVec4",r="vec4<f32>",s="vec4<bool>"):(n="isnan",r="f32",s="bool"),`
let aIsNaN = ${n}(a);
let aPostLegalization = select(a, ${r}(42), aIsNaN);
let bIsNaN = ${n}(b);
let bPostLegalization = select(b, ${r}(42), bIsNaN);
let isNaN = false;
let valueForNaN = uniforms.NAN;
{
let a = aPostLegalization;
let b = bPostLegalization;
${a}
return select(
resultTemp, ${r}(valueForNaN),
${s}(isNaN) | aIsNaN | bIsNaN);
}
`}while(!1);switch(e){case Pe.ADD:a=$le;break;case Pe.COMPLEX_MULTIPLY_IMAG:a=Fle;break;case Pe.COMPLEX_MULTIPLY_REAL:a=_le;break;case Pe.DIV:a=Dle;break;case Pe.ELU_DER:a=Ole;break;case Pe.EQUAL:a=zle;break;case Pe.FLOOR_DIV:a=Lle;break;case Pe.GREATER:a=Wle;break;case Pe.GREATER_EQUAL:a=Ble;break;case Pe.LESS:a=Vle;break;case Pe.LESS_EQUAL:a=Ule;break;case Pe.LOGICAL_AND:return t?Hle:Gle;case Pe.LOGICAL_OR:return t?qle:jle;case Pe.MUL:a=Jle;break;case Pe.PRELU:return t?rue:nue;case Pe.SQUARED_DIFFERENCE:a=sue;break;case Pe.SUB:a=iue;break;default:}return`
${a}
return resultTemp;
`}var le;(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.ROUND=27]="ROUND",e[e.RSQRT=28]="RSQRT",e[e.SELU=29]="SELU",e[e.SIGMOID=30]="SIGMOID",e[e.SIGN=31]="SIGN",e[e.SIN=32]="SIN",e[e.SINH=33]="SINH",e[e.SOFTPLUS=34]="SOFTPLUS",e[e.SQRT=35]="SQRT",e[e.SQUARE=36]="SQUARE",e[e.STEP=37]="STEP",e[e.TAN=38]="TAN",e[e.TANH=39]="TANH",e[e.TO_INT=40]="TO_INT"})(le||(le={}));var oue="return abs(a);",lue=`
if (abs(a) > 1.) {
return uniforms.NAN;
}
return acos(a);
`,uue=`
if (a < 1.) {
return uniforms.NAN;
}
return acosh(a);
`,due=`
if (abs(a) > 1.) {
return uniforms.NAN;
}
return asin(a);
`,pue="return asinh(a);",cue=`
if (isnan(a)) {
return uniforms.NAN;
}
return atan(a);
`,hue=`
if (abs(a) > 1.) {
return uniforms.NAN;
}
if (a == 1.) {
return uniforms.INFINITY;
}
if (a == -1.) {
return -uniforms.INFINITY;
}
return atanh(a);
`,mue="return ceil(a);",fue="return cos(a);",gue=`
let e2x = exp(-a);
return (e2x + 1.0 / e2x) / 2.0;
`,yue="return exp(a) - 1.0;",xue="if (a >= 0.0) { return a; } return (exp(a) - 1.0);",Aue=`
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;
`,bue=`
// Error function is calculated approximately with elementary function.
// See "Handbook of Mathematical Functions with Formulas,
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
let p = ${C.ERF_P};
let a1 = ${C.ERF_A1};
let a2 = ${C.ERF_A2};
let a3 = ${C.ERF_A3};
let a4 = ${C.ERF_A4};
let a5 = ${C.ERF_A5};
let sign = sign(a);
let absA = abs(a);
let t = 1.0 / (1.0 + p * absA);
return sign * (1.0 - (((((a5 * t + a4) * t) + a3) * t + a2) * t + a1) * t * exp(-absA * absA));
`,vue="return exp(a);",wue="return floor(a);",kue="return f32(!isnan(a) && !isinf(a));",Iue="return f32(isinf(a));",Sue="return f32(isnan(a));",Cue="return a;",Tue=`if (a < 0.0) { return uniforms.NAN; }
return log(a);`,Nue=`
if (isnan(a)) { return a; }
return log(1.0 + a);
`,Rue="return f32(!(a >= 1.0));",Eue="return -a;",Mue="if (a < 0.0) { return uniforms.alpha * a; } return a;",$ue=`
let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
return (aLessThanZero * (uniforms.alpha * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
`,Pue="return 1.0 / a;",_ue="return select(a, 0.0, a < 0.0);",Fue="return clamp(a, 0.0, 6.0);",Due="return clamp(a, vec4<f32>(0.0, 0.0, 0.0, 0.0), vec4<f32>(6.0, 6.0, 6.0, 6.0));",Oue=`
return select(a, vec4<f32>(0.0), a < vec4<f32>(0.0));
`,zue="return round(a);",Lue="return inverseSqrt(a);",Wue=`
if (a >= 0.0) {
return ${C.SELU_SCALE} * a;
} else {
return ${C.SELU_SCALEALPHA} * (exp(a) - 1.0);
}
`,Bue="return 1.0 / (1.0 + exp(-1.0 * a));",Vue="return sign(a);",Uue="return sin(a);",Gue=`
let e2x = exp(a);
return (e2x - 1.0 / e2x) / 2.0;
`,Hue=`
let epsilon = 1.1920928955078125e-7;
let threshold = log(epsilon) + 2.0;
let too_large = a > -threshold;
let too_small = a < threshold;
let exp_a = exp(a);
if (too_large) {
return a;
} else if (too_small) {
return exp_a;
} else {
return log(exp_a + 1.0);
}
`,jue="return sqrt(a);",que="return a * a;",Xue=`
if (isnan(a)) {
return a;
}
return select(uniforms.stepAlpha, 1.0, a > 0.0);
`,Kue="return tan(a);",Yue=`
let e2x = exp(-2.0 * abs(a));
return sign(a) * (1.0 - e2x) / (1.0 + e2x);
`,Zue="return f32(i32((a)));";function Ws(e,t){switch(e){case le.ABS:return oue;case le.ACOS:return lue;case le.ACOSH:return uue;case le.ASIN:return due;case le.ASINH:return pue;case le.ATAN:return cue;case le.ATANH:return hue;case le.COS:return fue;case le.COSH:return gue;case le.CEIL:return mue;case le.ELU:return t?Aue:xue;case le.ERF:return bue;case le.EXP:return vue;case le.EXPM1:return yue;case le.FLOOR:return wue;case le.IS_FINITE:return kue;case le.IS_INF:return Iue;case le.IS_NAN:return Sue;case le.LINEAR:return Cue;case le.LOG:return Tue;case le.LOG1P:return Nue;case le.LOGICAL_NOT:return Rue;case le.NEG:return Eue;case le.LEAKYRELU:return t?$ue:Mue;case le.RECIPROCAL:return Pue;case le.RELU:return t?Oue:_ue;case le.RELU6:return t?Due:Fue;case le.ROUND:return zue;case le.RSQRT:return Lue;case le.SELU:return Wue;case le.SIGMOID:return Bue;case le.SIGN:return Vue;case le.SIN:return Uue;case le.SINH:return Gue;case le.SOFTPLUS:return Hue;case le.SQRT:return jue;case le.SQUARE:return que;case le.STEP:return Xue;case le.TAN:return Kue;case le.TANH:return Yue;case le.TO_INT:return Zue;default:throw new Error(`BinaryType ${e} is not implemented!`)}}function Pr(e,t=!1,a=!1,n=3){if(e===null)return"";let r="";if(e==="linear")r=Ws(le.LINEAR);else if(e==="relu")r=Ws(le.RELU,a);else if(e==="elu")r=Ws(le.ELU,a);else if(e==="relu6")r=Ws(le.RELU6,a);else if(e==="prelu")r=K3(Pe.PRELU,a);else if(e==="sigmoid")r=Ws(le.SIGMOID,a);else if(e==="leakyrelu")r=Ws(le.LEAKYRELU,a);else throw new Error(`Activation ${e} has not been implemented for the WebGPU backend.`);let s=Xe(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 ll(e,t){return`
${e?"value = value + getBiasByOutputCoords(coords);":""}
${t?"value = activation(value, coords);":""}
`}function Ek(e,t,a=!1,n=!1,r=!1,s=1){v.assert(e&&s===1||!e,()=>`transposeA ${e} is not compatible with component size ${s}`);let i=`
${e?"value = getA(batch, col, row);":"value = getA(batch, row, col);"}
`,o=t?"value = getB(batch, col, row);":"value = getB(batch, row, col);";return`
fn mm_readA(batch: i32, row: i32, col: i32) -> ${Xe(s)} {
var value = ${Xe(s)}(0.0);
${a&&r?i:`
${e?"if(row < uniforms.dimAOuter && col < uniforms.dimInner)":"if(row < uniforms.aShape[1] && col < uniforms.aShape[2])"}
{
${i}
}
`}
return value;
}
fn mm_readB(batch: i32, row: i32, col: i32) -> ${Xe(s)} {
var value = ${Xe(s)}(0.0);
${o}
return value;
}
`}function Y3(e,t,a,n,r=!1,s=!1,i=!1,o=1){return`
${Ek(a,n,r,s,i,o)}
fn mm_write(batch: i32, row: i32, col: i32, valueIn: ${Xe(o)}) {
${r&&s?"":"if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)"}
{
var value = valueIn;
let coords = vec3<i32>(batch, row, col);
${ll(e,t)}
setOutputAtCoords(coords[0], coords[1], coords[2], value);
}
}
`}var Jue=(e,t)=>e?`
mm_Asub[inputRow][inputCol] = mm_readA(batchA,
kStart + inputRow,
globalRowStart + inputCol * ${t});
`:`
mm_Asub[inputRow][inputCol] = mm_readA(batchA,
globalRow + innerRow,
kStart + inputCol * ${t});
`,Que=(e,t,a,n)=>{if(e)return`
for (var k = 0; k < ${n}; k++) {
let BCached0 = mm_Bsub[k][tileCol];
let ACached0 = mm_Asub[k][localRow];
for (var i = 0; i < ${a}; i++) {
acc[i] = fma(BCached0, vec4<f32>(ACached0[i]), acc[i]);
}
}`;{let r="",s="";for(let i=0;i<t;i++)r+=`let BCached${i} = mm_Bsub[k * ${t} + ${i}][tileCol];`,s+=`acc[i] = fma(BCached${i}, vec4<f32>(ACached[${i}]), acc[i]);`;return`
for (var k = 0; k < ${n/t}; k++) {
${r}
for (var i = 0; i < ${a}; i++) {
let ACached = mm_Asub[tileRow + i][k];
${s}
}
}`}};function d0(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],h=e[1],m=e[0];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}>;
${ue()} {
let localRow = i32(localId.y);
let tileRow = localRow * ${h};
let tileCol = i32(localId.x);
let globalRow = i32(globalId.y) * ${h};
let globalCol = i32(globalId.x) * ${m};
let batch = ${r?"0":"i32(globalId.z)"};
let batchA = ${r||!i?"batch":"batch % uniforms.aShape[0]"};
let batchB = ${r||!i?"batch":"batch % uniforms.bShape[0]"};
let globalRowStart = i32(workgroupId.y) * ${o};
let numTiles = ${r?`${Math.ceil(s/n)}`:`(uniforms.dimInner - 1) / ${n} + 1`};
var kStart = ${r?`i32(globalId.z) * ${s}`:"0"};
var acc: array<vec4<f32>, ${h}>;
// Loop over shared dimension.
let tileRowB = localRow * ${d};
for (var t = 0; t < numTiles; t++) {
// Load one tile of A into local memory.
for (var innerRow = 0; innerRow < ${h}; innerRow++) {
let inputRow = tileRow + innerRow;
let inputCol = tileCol;
${Jue(a,c)}
}
// Load one tile of B into local memory.
for (var innerRow = 0; innerRow < ${d}; innerRow++) {
let inputRow = tileRowB + innerRow;
let inputCol = tileCol;
mm_Bsub[inputRow][inputCol] = mm_readB(batchB, kStart + inputRow, globalCol);
}
kStart = kStart + ${n};
workgroupBarrier();
// Compute acc values for a single thread.
${Que(a,c,h,n)}
workgroupBarrier();
}
for (var innerRow = 0; innerRow < ${h}; innerRow++) {
mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]);
}
}`}var sA=e=>e?`
mm_Asub[inputRow][inputCol] = mm_readA(batchA,
kStart + inputRow,
globalRowStart + inputCol);
`:`
mm_Asub[inputRow][inputCol] = mm_readA(batchA,
globalRowStart + inputRow,
kStart + inputCol);
`,ede=e=>e?"let ACached = mm_Asub[k][tileRow + innerRow];":"let ACached = mm_Asub[tileRow + innerRow][k];";function p0(e,t,a=!1,n=32,r=!1,s=32,i=!1,o=!1){let l=e[1]*t[1],u=e[0]*t[0],p=a?l:n,c=a?n:l;v.assert(c%t[1]===0&&p%t[0]===0&&n%t[1]===0,()=>`tileAHight ${c} must be divisible by workgroupSize[1]${t[1]}, tileAWidth ${p} must be divisible by workgroupSize[0]${t[0]}, tileInner ${n} must be divisible by workgroupSize[1]${t[1]}`);let d=c/t[1],h=p/t[0],m=n/t[1],f=e[1],g=e[0],y=i?`
let localRow = i32(localId.y);
let localCol = i32(localId.x);
let globalRowStart = i32(workgroupId.y) * ${l};
let globalColStart = i32(workgroupId.x) * ${u};
// Loop over shared dimension.
for (var t = 0; t < numTiles; t++) {
// Load one tile of A into local memory.
for (var inputRow = localRow; inputRow < ${c}; inputRow = inputRow + ${t[1]}) {
for (var inputCol = localCol; inputCol < ${p}; inputCol = inputCol + ${t[0]}) {
${sA(a)}
}
}
// Load one tile of B into local memory.
for (var inputRow = localRow; inputRow < ${n}; inputRow = inputRow + ${t[1]}) {
for (var inputCol = localCol; inputCol < ${u}; inputCol = inputCol + ${t[0]}) {
mm_Bsub[inputRow][inputCol] = mm_readB(batchB,
kStart + inputRow,
globalColStart + inputCol);
}
}
kStart = kStart + ${n};
workgroupBarrier();
// Compute acc values for a single thread.
var BCached : array<f32, ${g}>;
for (var k = 0; k < ${n}; k++) {
for (var inner = 0; inner < ${g}; inner++) {
BCached[inner] = mm_Bsub[k][localCol + inner * ${t[0]}];
}
for (var innerRow = 0; innerRow < ${f}; innerRow++) {
let ACached = ${a?`mm_Asub[k][localRow + innerRow * ${t[1]}];`:`mm_Asub[localRow + innerRow * ${t[1]}][k];`}
for (var innerCol = 0; innerCol < ${g}; innerCol++) {
acc[innerRow][innerCol] =
fma(ACached, BCached[innerCol], acc[innerRow][innerCol]);
}
}
}
workgroupBarrier();
}
for (var innerRow = 0; innerRow < ${f}; innerRow++) {
let gRow = globalRowStart + localRow + innerRow * ${t[1]};
for (var innerCol = 0; innerCol < ${g}; innerCol++) {
let gCol = globalColStart + localCol + innerCol * ${t[0]};
mm_write(batch, gRow, gCol, acc[innerRow][innerCol]);
}
}
`:`
let tileRow = i32(localId.y) * ${f};
let tileCol = i32(localId.x) * ${g};
let globalRow = i32(globalId.y) * ${f};
let globalCol = i32(globalId.x) * ${g};
let globalRowStart = i32(workgroupId.y) * ${l};
let tileRowA = i32(localId.y) * ${d};
let tileColA = i32(localId.x) * ${h};
let tileRowB = i32(localId.y) * ${m};
// Loop over shared dimension.
for (var t = 0; t < numTiles; t++) {
// Load one tile of A into local memory.
for (var innerRow = 0; innerRow < ${d}; innerRow++) {
for (var innerCol = 0; innerCol < ${h}; innerCol++) {
let inputRow = tileRowA + innerRow;
let inputCol = tileColA + innerCol;
${sA(a)}
}
}
// Load one tile of B into local memory.
for (var innerRow = 0; innerRow < ${m}; innerRow++) {
for (var innerCol = 0; innerCol < ${g}; innerCol++) {
let inputRow = tileRowB + innerRow;
let inputCol = tileCol + innerCol;
mm_Bsub[inputRow][inputCol] = mm_readB(batchB,
kStart + inputRow,
globalCol + innerCol);
}
}
kStart = kStart + ${n};
workgroupBarrier();
// Compute acc values for a single thread.
var BCached : array<f32, ${g}>;
for (var k = 0; k < ${n}; k++) {
for (var inner = 0; inner < ${g}; inner++) {
BCached[inner] = mm_Bsub[k][tileCol + inner];
}
for (var innerRow = 0; innerRow < ${f}; innerRow++) {
${ede(a)}
for (var innerCol = 0; innerCol < ${g}; innerCol++) {
acc[innerRow][innerCol] =
fma(ACached, BCached[innerCol], acc[innerRow][innerCol]);
}
}
}
workgroupBarrier();
}
for (var innerRow = 0; innerRow < ${f}; innerRow++) {
for (var innerCol = 0; innerCol < ${g}; innerCol++) {
mm_write(batch, globalRow + innerRow, globalCol + innerCol,
acc[innerRow][innerCol]);
}
}
`;return`
var<workgroup> mm_Asub : array<array<f32, ${p}>, ${c}>;
var<workgroup> mm_Bsub : array<array<f32, ${u}>, ${n}>;
${ue()} {
let batch = ${r?"0":"i32(globalId.z)"};
let batchA = ${r||!o?"batch":"batch % uniforms.aShape[0]"};
let batchB = ${r||!o?"batch":"batch % uniforms.bShape[0]"};
let numTiles = ${r?`${Math.ceil(s/n)}`:`(uniforms.dimInner - 1) / ${n} + 1`};
var kStart = ${r?`i32(globalId.z) * ${s}`:"0"};
var acc : array<array<f32, ${g}>, ${f}>;
// Without this initialization strange values show up in acc.
for (var innerRow = 0; innerRow < ${f}; innerRow++) {
for (var innerCol = 0; innerCol < ${g}; innerCol++) {
acc[innerRow][innerCol] = 0.0;
}
}
${y}
}
`}var tde=e=>e?`
mm_readA(batchA, colA, globalRow),
mm_readA(batchA, colA + 1, globalRow),
mm_readA(batchA, colA + 2, globalRow),
mm_readA(batchA, colA + 3, globalRow)
`:`
mm_readA(batchA, globalRow, colA),
mm_readA(batchA, globalRow, colA + 1),
mm_readA(batchA, globalRow, colA + 2),
mm_readA(batchA, globalRow, colA + 3)
`;function ade(e,t=!1){v.assert(e[1]===1&&e[2]===1,()=>`A linear work group size is required. But got ${e}.`);let a=e[0]*4;return`
var<workgroup> mm_Asub : array<vec4<f32>, ${e[0]}>;
${ue()} {
let tileCol = i32(localId.x);
let globalCol = i32(globalId.x);
let globalRow = i32(globalId.y);
let numTiles = (uniforms.dimInner - 1) / ${a} + 1;
let batch = i32(globalId.z);
let batchA = batch % uniforms.aShape[0];
let batchB = batch % uniforms.bShape[0];
// Without this initialization strange values show up in acc.
var acc = 0.0;
// Loop over shared dimension.
for (var t = 0; t < numTiles; t++) {
// Load one tile of A into local memory.
let colA = t * ${a} + tileCol * 4;
mm_Asub[tileCol] = vec4<f32>(${tde(t)});
workgroupBarrier();
// Compute acc values for a single thread.
for (var k = 0; k < ${a/4}; k++) {
let rowB = t * ${a} + k * 4;
let BCached = vec4<f32>(mm_readB(batchB, rowB, globalCol),
mm_readB(batchB, rowB + 1, globalCol),
mm_readB(batchB, rowB + 2, globalCol),
mm_readB(batchB, rowB + 3, globalCol));
let ACached = mm_Asub[k];
acc = acc + dot(ACached, BCached);
}
workgroupBarrier();
}
mm_write(batch, globalRow, globalCol, acc);
}
`}var nde=class{constructor(e,t,a=!1,n=!1,r=null,s=null,i=null,o=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=t,this.dispatchLayout={x:[2],y:[1],z:[0]};let l=a?e[1]:e[2];if(this.isVec4=(l%4===0&&!a||t[1]%4===0&&a)&&t[2]%4===0&&!n,this.outputComponent=this.isVec4?4:1,this.isVectorA=t[1]===1&&!a,!this.isVec4&&this.isVectorA)this.elementsPerThread=[1,1,1],this.workgroupSize=[32,1,1];else{let c=Nk(t[1],l,t[2],a);this.workgroupSize=c.workgroupSize,this.elementsPerThread=c.elementsPerThread}this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread);let u=r!=null,p=i!=null;u&&this.variableNames.push("bias"),p&&this.variableNames.push("preluActivationWeights"),this.sequentialAccessByThreads=o,this.transposeA=a,this.transposeB=n,this.addBias=u,this.activation=s,this.hasPreluActivationWeights=p,[this.fitAOuter,this.fitBOuter,this.fitInner]=this.getShapeFit(t[1],t[2],l),this.shaderKey=`matMulPacked_${this.elementsPerThread}_${a}_${n}_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.isVectorA}_${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`
${Pr(this.activation,this.hasPreluActivationWeights,this.isVec4)}
${Y3(this.addBias,this.activation,!1,this.transposeB,this.fitAOuter,this.fitBOuter,this.fitInner,this.isVec4?4:1)}
${this.isVec4?d0(this.elementsPerThread,this.workgroupSize,this.transposeA,this.tileInner,!1,null,!0):this.isVectorA?ade(this.workgroupSize,this.transposeA):p0(this.elementsPerThread,this.workgroupSize,this.transposeA,this.tileInner,!1,null,this.sequentialAccessByThreads,!0)}
`}};function rde(e){return`
var<workgroup> sumValues : array<f32, ${e}>;
${ue()} {
let coords = getOutputCoords();
let batch = coords[0];
let batchA = batch % uniforms.aShape[0];
let batchB = batch % uniforms.bShape[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 + ${e}) {
let dataA = mm_readA(batchA, row, k);
let dataB = mm_readB(batchB, k, col);
sum = sum + dataA * dataB;
}
sumValues[localId.x] = sum;
workgroupBarrier();
for(var currentSize = ${e/2}u; currentSize > 1u;
currentSize = currentSize / 2u) {
if (localId.x < currentSize)
{
sumValues[localId.x] = sumValues[localId.x] + sumValues[localId.x + currentSize];
}
workgroupBarrier();
}
if (localId.x == 0u) {
sum = sumValues[0] + sumValues[1];
mm_write(batch, row, col, sum);
}
}
`}var sde=class{constructor(e,t=!1,a=!1,n=null,r=null,s=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout={x:[],y:[1,2],z:[0]},this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize);let i=n!=null,o=s!=null;i&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),this.transposeA=t,this.transposeB=a,this.addBias=i,this.activation=r,this.hasPreluActivationWeights=o,this.shaderKey=`matMulReduce_${this.activation}_${t}_${a}`}getUserCode(){return`
${Pr(this.activation,this.hasPreluActivationWeights)}
${Y3(this.addBias,this.activation,this.transposeA,this.transposeB)}
${rde(this.workgroupSize[0])}
`}};function ide(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.
${ue()} {
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);
let batchA = batch % uniforms.aShape[0];
let batchB = batch % uniforms.bShape[0];
// 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(batchA, globalRow, globalColA);
var regB0 = mm_readB(batchB, globalRowB + 2 * tileRow, globalCol);
var regB1 = mm_readB(batchB, 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(batchA, globalRow, globalColA);
regB0 = mm_readB(batchB, globalRowB + 2 * tileRow, globalCol);
regB1 = mm_readB(batchB, globalRowB + 2 * tileRow + 1, globalCol);
globalColA = globalColA + ${n};
globalRowB = globalRowB + ${n};
for (var k = 0; k < ${n}; k = k + 1) {
acc = acc + mm_Asub[tileRow][k] * mm_Bsub[k][tileCol];
}
workgroupBarrier();
}
mm_write(batch, globalRow, globalCol, acc);
}
`}var ode=class{constructor(e,t,a,n=!1,r=!1,s=null,i=null,o=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[16,8,1],this.outputShape=a,this.dispatchLayout={x:[2],y:[1],z:[0]},this.dispatch=[Math.ceil(a[2]/this.workgroupSize[0]),Math.ceil(a[1]/this.workgroupSize[1]),a[0]];let l=s!=null;l&&this.variableNames.push("bias");let u=o!=null;u&&this.variableNames.push("preluActivationWeights"),this.transposeA=n,this.transposeB=r,this.addBias=l,this.activation=i,this.hasPreluActivationWeights=u,this.shaderKey=`matMulSmallOutputSize_${this.activation}_${n}_${r}`}getUserCode(){return`
${Pr(this.activation,this.hasPreluActivationWeights)}
${Y3(this.addBias,this.activation,this.transposeA,this.transposeB)}
${ide(this.workgroupSize)}
`}},lde=class{constructor(e,t,a=!1,n=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[8,8,1],this.atomic=!0,this.splitedDimInner=128,v.assert(e[0]===1,()=>"MatMulSplitKProgram only supports batch = 1."),this.outputShape=e,this.dispatchLayout={x:[2],y:[1],z:[0,3]};let r=(a&&this.outputShape[1]%4===0||!a&&t%4===0)&&this.outputShape[2]%4===0;this.elementsPerThread=[4,4,this.splitedDimInner],this.outputComponent=r?4:1,r||(this.outputShape[1]<16&&(this.elementsPerThread[1]=1),this.outputShape[2]<16&&(this.elementsPerThread[0]=1)),this.dispatch=de(this.dispatchLayout,[this.outputShape[0],this.outputShape[1],this.outputShape[2],t],this.workgroupSize,this.elementsPerThread),this.transposeA=a,this.transposeB=n,this.shaderKey=`matMulSplitK_${a}_${n}_${this.elementsPerThread}_${this.outputComponent}`}getUserCode(){let e=this.outputComponent;return`
${Ek(!1,this.transposeB,!1,!1,!1,e)}
fn mm_write(batch: i32, row : i32, col : i32, value : ${Xe(e)}) {
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.
for (var i = 0; i < ${e}; i = i + 1) {
${xs("&result[flatIndex + i]",`${e>1?"value[i]":"value"}`,"float32")}
}
}
}
${e===4?d0(this.elementsPerThread,this.workgroupSize,this.transposeA,32,!0,this.splitedDimInner):p0(this.elementsPerThread,this.workgroupSize,this.transposeA,32,!0,this.splitedDimInner)}
`}},ude=class{constructor(e,t=null,a=null,n=null){this.uniforms="",this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.addBias=t!=null,this.hasPreluActivationWeights=n!=null,this.activation=a,this.addBias&&this.variableNames.push("bias"),this.hasPreluActivationWeights&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`biasActivation_${a}`}getUserCode(){return`
${Pr(this.activation,this.hasPreluActivationWeights)}
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
var value = getXByOutputIndex(index);
${ll(this.addBias,this.activation)}
setOutputAtIndex(index, value);
}
}
`}},dde=class{constructor(e){this.variableNames=[],this.outputShape=[],this.uniforms="value : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="fill"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
setOutputAtIndex(index, uniforms.value);
}
}
`}};function Wa(e){let{backend:t,attrs:a}=e,{shape:n,value:r}=a,{dtype:s}=a;if(s=s||v.inferDtype(r),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(n));return i.fill(r),t.makeTensorInfo(n,s,i)}else{let i=new dde(n),o=[{type:"float32",data:[r]}];return t.runWebGPUProgram(i,[],s,o)}}var pde={kernelName:bu,backendName:"webgpu",kernelFunc:Wa};function ke(e){let{inputs:t,attrs:a}=e,{x:n}=t,{shape:r}=a,s=v.sizeFromShape(n.shape),i=v.inferFromImplicitShape(r,s),o=v.sizeFromShape(i);return v.assert(s===o,()=>`The new shape (${i}) has ${o} elements and the old shape (${n.shape}) has ${s} elements. The new shape and old shape must have the same number of elements.`),e.backend.incRef(n.dataId),{dataId:n.dataId,shape:i,dtype:n.dtype}}var cde={kernelName:Eu,backendName:"webgpu",kernelFunc:ke};function c0({a:e,b:t,transposeA:a,transposeB:n,backend:r,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,p=t.shape.length,c=a?e.shape[u-2]:e.shape[u-1],d=n?t.shape[p-1]:t.shape[p-2],h=a?e.shape[u-1]:e.shape[u-2],m=n?t.shape[p-2]:t.shape[p-1],f=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(f),x=v.sizeFromShape(g),A=nl.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,m]);v.assert(c===d,()=>`Error in matMul: inner shapes (${c}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${a} and transposeB=${n} must match.`);let b=a?[y,c,h]:[y,h,c],w=n?[x,m,d]:[x,d,m],I=ke({inputs:{x:e},backend:r,attrs:{shape:b}}),T=ke({inputs:{x:t},backend:r,attrs:{shape:w}}),N=[I,T],M=Math.max(y,x),$=[I,T],E=[{type:"int32",data:[h]},{type:"int32",data:[m]},{type:"int32",data:[c]}],S,_,O=[M,h,m],W=B().get("WEBGPU_MATMUL_PROGRAM_TYPE");if(W<0){let U=B().getNumber("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL"),G=U>0?U:r.thresholdToIncreaseWorkgroups,q=M*Math.ceil(h/32)*Math.ceil(m/32);q<=G||h<=8&&q<=G*2?M*h*m<=128?W=On.MatMulReduceProgram:M===1&&d>=2e3?W=On.MatMulSplitKProgram:W=On.MatMulSmallOutputSizeProgram:W=On.MatMulPackedProgram}switch(W){case On.MatMulReduceProgram:S=new sde(O,a,n,s,l,i);break;case On.MatMulSplitKProgram:{if(_=Wa({backend:r,attrs:{shape:O,value:0,dtype:e.dtype}}),S=new lde(O,d,a,n),s||l){_=r.runWebGPUProgram(S,$,e.dtype,E,_);let G=new ude(_.shape,s,l,i),q=null,H=[_];s&&H.push(s),i&&H.push(i),l==="leakyrelu"&&(q=[{type:"float32",data:[o]}],G.uniforms+=" alpha : f32,");let V=r.runWebGPUProgram(G,H,_.dtype,q);N.push(_);let Z=ke({inputs:{x:V},backend:r,attrs:{shape:A}});N.push(V);for(let X of N)r.disposeData(X.dataId);return Z}break}case On.MatMulSmallOutputSizeProgram:S=new ode(b,w,O,a,n,s,l,i);break;case On.MatMulPackedProgram:let U=r.adapterInfo.isIntel();S=new nde(b,O,a,n,s,l,i,U);break;default:throw new Error(`Unsupported MatMulProgramType ${W}.`)}s&&$.push(s),i&&$.push(i),l==="leakyrelu"&&(E.push({type:"float32",data:[o]}),S.uniforms+=" alpha : f32,"),_=r.runWebGPUProgram(S,$,e.dtype,E,_);let P=ke({inputs:{x:_},backend:r,attrs:{shape:A}});N.push(_);for(let U of N)r.disposeData(U.dataId);return P}function hde(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 c0({a:r,b:s,transposeA:l,transposeB:u,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:c,activation:p})}var mde={kernelName:Zr,backendName:"webgpu",kernelFunc:hde},iA=class{constructor(e,t,a){this.variableNames=["AReal","AImag","BReal","BImag"],this.workgroupSize=[128,1,1],this.size=!0,this.outputShape=C.assertAndGetBroadcastShape(t,a),this.dispatchLayout=me(this.outputShape),this.dispatch=de(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 {
${K3(this.op,!1)}
}
${ue("index")} {
if(index < uniforms.size) {
let areal = getARealByOutputIndex(index);
let aimag = getAImagByOutputIndex(index);
let breal = getBRealByOutputIndex(index);
let bimag = getBImagByOutputIndex(index);
setOutputAtIndex(index, binaryOpComplex(areal, aimag, breal, bimag));
}
}
`}},Th=class{constructor(e,t,a){if(this.size=!0,this.variableNames=["A","B"],this.outputShape=C.assertAndGetBroadcastShape(t,a),this.dispatchLayout=me(this.outputShape),this.op=e,this.useSharedMemoryWithA=t.length<=1&&a.length>1&&t[0]<128,this.useSharedMemoryWithB=a.length<=1&&t.length>1&&a[0]<128,this.useSharedMemoryWithA||this.useSharedMemoryWithB)this.outputComponent=1,this.variableComponents=[1,1],this.lastDimensionSize=this.useSharedMemoryWithB?a[0]:t[0],this.shaderKey=`binary_${e}_${this.lastDimensionSize}`,this.type="shared",this.workgroupSize=[256,1,1];else{let n=t.length>0&&t[t.length-1]%4===0,r=a.length>0&&a[a.length-1]%4===0;n&&r?(this.outputComponent=4,this.variableComponents=[4,4]):n&&(v.isScalarShape(a)||a[a.length-1]===1)||r&&(v.isScalarShape(t)||t[t.length-1]===1)?(this.outputComponent=4,this.variableComponents=n?[4,1]:[1,4]):(this.outputComponent=1,this.variableComponents=[1,1]),this.type="nonshared",this.shaderKey=`binary_${e}_${this.variableComponents}`,this.workgroupSize=[128,1,1]}this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.outputComponent,1,1])}getUserCode(){let e,t=this.outputComponent===4?"vec4<f32>":"f32",a=`
fn binaryOperation(a : ${t}, b : ${t}) -> ${t} {
${K3(this.op,this.outputComponent===4)}
};
`;if(this.type==="shared"){let n=this.lastDimensionSize>1?`coords[${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}>;
${ue("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}
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index * ${this.outputComponent});
let a = ${t}(getAByOutputCoords(coords));
let b = ${t}(getBByOutputCoords(coords));
setOutputAtIndex(index, binaryOperation(a, b));
}
}
`;return e}};function tn(e){let{inputs:t}=e,{x:a}=t;return e.backend.incRef(a.dataId),{dataId:a.dataId,shape:a.shape,dtype:a.dtype}}var fde={kernelName:qi,backendName:"webgpu",kernelFunc:tn};function ul(e){let{inputs:t,backend:a}=e,{real:n,imag:r}=t,s=a.makeTensorInfo(n.shape,"complex64"),i=a.tensorMap.get(s.dataId),o=tn({inputs:{x:n},backend:a}),l=tn({inputs:{x:r},backend:a});return i.complexTensorInfos={real:o,imag:l},s}var gde={kernelName:cp,backendName:"webgpu",kernelFunc:ul},td=class{constructor(e,t,a=""){this.variableNames=["A"],this.size=!0;let n=128;this.workgroupSize=[n,1,1],this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.op=t,a!==""&&(this.uniforms=a),this.shaderKey=`unary_${t}`}getUserCode(){return`
fn unaryOperation(a : f32) -> f32 {
${Ws(this.op,!1)}
}
${ue("index")} {
if (index < uniforms.size) {
let a = getAByOutputIndex(index);
setOutputAtIndex(index, unaryOperation(a));
}
}
`}};function at({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 td(s.shape,e);return i.runWebGPUProgram(l,[s],o)}}function ta({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,m;if(e!==Pe.MUL)[h,m]=[[c.complexTensorInfos.real,d.complexTensorInfos.real],[c.complexTensorInfos.imag,d.complexTensorInfos.imag]].map(g=>{let[y,x]=g,A={dataId:y.dataId,dtype:y.dtype,shape:i.shape},b={dataId:x.dataId,dtype:x.dtype,shape:o.shape},w=new Th(e,i.shape,o.shape);return l.runWebGPUProgram(w,[A,b],pa(y.dtype,x.dtype))});else{let g=new iA(Pe.COMPLEX_MULTIPLY_REAL,i.shape,o.shape),y=new iA(Pe.COMPLEX_MULTIPLY_IMAG,i.shape,o.shape),x=[{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,x,"float32"),m=l.runWebGPUProgram(y,x,"float32")}let f=ul({inputs:{real:h,imag:m},backend:l});return l.disposeData(h.dataId),l.disposeData(m.dataId),f}let u=n||pa(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"?C.fromUint8ToStringArray(c):c,m=i.dtype==="string"?C.fromUint8ToStringArray(d):d,[f,g]=t(i.shape,o.shape,h,m,u);return l.makeTensorInfo(g,u,f)}let p=new Th(e,i.shape,o.shape);return l.runWebGPUProgram(p,[i,o],u)}}var{addImpl:yde,castImpl:xde,ceilImpl:Ade,concatImpl:bde,equalImpl:vde,expImpl:wde,expm1Impl:kde,floorImpl:Ide,floorDivImpl:Sde,gatherNdImpl:Cde,gatherV2Impl:Tde,greaterEqualImpl:Nde,greaterImpl:Rde,lessEqualImpl:Ede,lessImpl:Mde,logImpl:$de,maxImpl:Pde,maximumImpl:_de,minimumImpl:Fde,multiplyImpl:Dde,negImpl:Ode,notEqualImpl:zde,prodImpl:Lde,rangeImpl:Wde,rsqrtImpl:Bde,scatterImpl:Vde,simpleAbsImpl:Ude,sliceImpl:Gde,stridedSliceImpl:Hde,stringNGramsImpl:jde,subImpl:qde,tileImpl:Xde,topKImpl:Kde,transposeImpl:Yde,uniqueImpl:pye}=t0,Zde=at({opType:le.ABS,cpuKernelImpl:Ude}),Jde={kernelName:ou,backendName:"webgpu",kernelFunc:Zde},Qde=at({opType:le.ACOS}),epe={kernelName:oi,backendName:"webgpu",kernelFunc:Qde},tpe=at({opType:le.ACOSH}),ape={kernelName:li,backendName:"webgpu",kernelFunc:tpe},npe=ta({opType:Pe.ADD,cpuKernelImpl:yde,supportsComplex:!0}),rpe={kernelName:ls,backendName:"webgpu",kernelFunc:npe},spe=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${a}`),this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.shaderKey="addN"}getUserCode(){let e=[];this.variableNames.forEach(a=>{e.push(`let v${a} = get${a}ByOutputCoords(coords);`)});let t=this.variableNames.map(a=>`v${a}`).join(" + ");return`
${ue("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 ipe(e){let{inputs:t,backend:a}=e,n=t;if(n.length===1)return tn({inputs:{x:n[0]},backend:a});let r=n.map(o=>o.dtype).reduce((o,l)=>pa(o,l)),s=n.map(o=>o.shape),i=new spe(s);return a.runWebGPUProgram(i,n,r)}var ope={kernelName:ui,backendName:"webgpu",kernelFunc:ipe},lpe=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=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[1,1,1]),this.shaderKey="transposeShared"}getUserCode(){v.assert(this.workgroupSize[0]===this.workgroupSize[1],()=>`Must be a square tile, current tile shape is ${this.workgroupSize[0]} x ${this.workgroupSize[1]}`);let e=this.workgroupSize[0];return`
var<workgroup> tile : array<array<f32, ${this.workgroupSize[0]+1}>, ${this.workgroupSize[0]}>;
${ue()} {
var x = i32(workgroupId.x) * ${e} + i32(localId.x);
var y = i32(workgroupId.y) * ${e} + 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) * ${e} + i32(localId.x);
y = i32(workgroupId.x) * ${e} + i32(localId.y);
if (x < height && y < width) {
setOutputAtIndex((y * height + x), tile[localId.x]
[localId.y]);
}
}
`}},upe=class{constructor(e,t){this.variableNames=["A"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0;let a=new Array(e.length);for(let n=0;n<a.length;n++)a[n]=e[t[n]];this.outputShape=a,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.newDim=t,this.shaderKey=`transpose_${t}`}getUserCode(){let e=Pt(this.outputShape.length),t=Mk(this.newDim);return`
${ue("index")} {
for(var i = 0; i < ${this.workPerThread}; i = i + 1) {
let flatIndex = index * ${this.workPerThread} + i;
if(flatIndex < uniforms.size) {
let coords = getCoordsFromIndex(flatIndex);
setOutputAtIndex(flatIndex, A[getIndexFromCoords${this.outputShape.length}D(
${e}(${t}), uniforms.aShape)]);
}
}
}
`}};function Mk(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let a=new Array(t);for(let n=0;n<e.length;n++)a[e[n]]=`coords.${Sr(n)}`;return a.join()}function rr(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=Yde(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 lpe(r.shape,s);return i.runWebGPUProgram(p,[r],r.dtype)}let u=new upe(r.shape,s);return i.runWebGPUProgram(u,[r],r.dtype)}var dpe={kernelName:kr,backendName:"webgpu",kernelFunc:rr},ppe=class{constructor(e,t,a){this.variableNames=["x"],this.uniforms="reduceSize : i32,",this.size=!0,this.inputShape=[e.batchSize,e.inSize];let[n]=C.computeOutAndReduceShapes(this.inputShape,[1]);this.outputShape=n.length===0?[1]:n,e.inSize>=32768&&a>=512?this.workgroupSize=[512,1,1]:e.inSize>=4096?this.workgroupSize=[256,1,1]:this.workgroupSize=[64,1,1],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,[1,1,1]),this.reduceType=t,this.shaderKey=`reduce_${t}`}getUserCode(){let e="",t="0.0",a=this.workgroupSize[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 n=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, ${a}>;
`}
fn getOffset(outputIndex : i32) -> i32 {
let outputCoords = getCoordsFromIndex(outputIndex);
let offset = ${this.outputShape.length===1?"outputCoords":"outputCoords[0]"} * uniforms.reduceSize;
return offset;
}
${ue("index")} {
let outputIndex = index / ${a};
let offset = getOffset(outputIndex);
var bestValue = ${t};
let Length = uniforms.reduceSize;
let WorkPerThread = DIV_CEIL(u32(Length), ${a}u);
for (var k = i32(localId.x); k < Length && outputIndex < uniforms.size;
k = k + ${a}) {
let candidate = f32(x[offset + k]);
${e}
}
xBestValues[localId.x] = bestValue;
workgroupBarrier();
var reduceSize = min(u32(Length), ${a}u);
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) {
${n}
}
}
`}},cpe={mean:"float32",all:"bool",any:"bool"};function dl(e,t,a,n,r){let s=e.shape.length,i=[],o=v.parseAxisParam(t,e.shape),l=o,u=C.getAxesPermutation(l,s),p=e;u!=null&&(p=rr({inputs:{x:e},attrs:{perm:u},backend:r}),l=C.getInnerMostAxes(l.length,s),i.push(p)),C.assertAxesAreInnerMostDims(n,l,s);let[c,d]=C.computeOutAndReduceShapes(p.shape,l),h=c;a&&(h=C.expandShapeToKeepDim(c,o));let m;if((n==="max"||n==="prod")&&r.shouldExecuteOnCPU([p])){let f=r.tensorMap.get(p.dataId).values;switch(n){case"max":let g=Pde(f,v.sizeFromShape(d),h,e.dtype);m=r.makeTensorInfo(h,e.dtype,g);break;case"prod":let{outVals:y,outShape:x,outDtype:A}=Lde(p.shape,p.dtype,f,l);m=r.makeTensorInfo(x,A,y);break;default:throw new Error(`${n} CPU implementation is not yet supported.`)}}else{let f=v.sizeFromShape(d),g=v.sizeFromShape(p.shape)/f,y={windowSize:f,inSize:f,batchSize:g,outSize:1},x=cpe[n]||_p(e.dtype),A=[{type:"int32",data:[f]}],b=new ppe(y,n,r.device.limits.maxComputeWorkgroupSizeX),w=r.runWebGPUProgram(b,[p],x,A);i.push(w),m=ke({inputs:{x:w},attrs:{shape:h},backend:r})}return i.forEach(f=>r.disposeData(f.dataId)),m}function hpe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return dl(r,i,s,"all",a)}var mpe={kernelName:di,backendName:"webgpu",kernelFunc:hpe};function fpe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return dl(r,i,s,"any",a)}var gpe={kernelName:pi,backendName:"webgpu",kernelFunc:fpe},$k=class{constructor(e,t,a){this.workgroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="infinityValue : f32,",this.size=!0;let n=[t];this.op=a==="min"?"<":">";let[r,s]=C.computeOutAndReduceShapes(e,n);this.outputShape=r.length===0?[1]:r,this.dispatchLayout=me(this.outputShape),v.sizeFromShape(s)<32?(this.type="plain",this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize)):(this.type="shared",this.dispatch=de(this.dispatchLayout,this.outputShape,[1,1,1])),this.inputShape=e,this.shaderKey=`argMinMax_${this.op}_${this.type}`}getUserCode(){let e=this.workgroupSize[0],t=()=>this.inputShape.length===1?"uniforms.xShape":`uniforms.xShape.${Sr(this.inputShape.length-1)}`,a=()=>{let n="";if(this.outputShape.length===1)this.inputShape.length!==1&&(n+="outputCoords,");else for(let r=0;r<this.outputShape.length;r++)n+=`outputCoords.${Sr(r)},`;return n};return this.type==="shared"?`
fn DIV_CEIL(a : u32, b : u32) -> u32 {
return ((a - 1u) / b + 1u);
}
${`
var<workgroup> xBestIndices : array<i32, ${e}>;
var<workgroup> xBestValues : array<f32, ${e}>;
`}
${ue("index")} {
let outputIndex = index / ${e};
let reduceLength = ${t()};
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 + ${e}) {
let candidate = getX(${a()} 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), ${e}u);
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]);
}
}
`:`
${ue("index")} {
if (index < uniforms.size) {
let outputCoords = getCoordsFromIndex(index);
var bestIndex = 0;
var bestValue = getX(${a()} 0);
let reduceLength = ${t()};
for (var i = 1; i < reduceLength; i++) {
let candidate = getX(${a()} i);
if (candidate ${this.op} bestValue) {
bestValue = candidate;
bestIndex = i;
}
}
setOutputAtIndexI32(index, bestIndex);
}
}
`}};function ype(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=C.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=rr({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let p=new $k(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 xpe={kernelName:lu,backendName:"webgpu",kernelFunc:ype};function Ape(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=C.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=rr({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let p=new $k(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 bpe={kernelName:uu,backendName:"webgpu",kernelFunc:Ape},vpe=at({opType:le.ASIN}),wpe={kernelName:ci,backendName:"webgpu",kernelFunc:vpe},kpe=at({opType:le.ASINH}),Ipe={kernelName:hi,backendName:"webgpu",kernelFunc:kpe},Spe=at({opType:le.ATAN}),Cpe={kernelName:mi,backendName:"webgpu",kernelFunc:Spe},Tpe=ta({opType:Pe.ATAN2}),Npe={kernelName:gi,backendName:"webgpu",kernelFunc:Tpe},Rpe=at({opType:le.ATANH}),Epe={kernelName:fi,backendName:"webgpu",kernelFunc:Rpe},Mpe=class{constructor(e){this.variableNames=["x"],this.uniforms="strides : vec2<i32>,",this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="poolWithFilterSizeEqualsOne"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords[0];
let d = coords[3];
let xRCCorner = coords.yz * uniforms.strides;
let xRCorner = xRCCorner.x;
let xCCorner = xRCCorner.y;
let value = getX(batch, xRCorner, xCCorner, d);
setOutputAtIndex(index, value);
}
}
`}},sp=class{constructor(e,t,a=!1,n=!1,r=!1){if(this.variableNames=["x"],this.uniforms="strides : vec2<i32>, pads : vec2<i32>, dilations : vec2<i32>, convDims : vec2<i32>, filterDims : vec2<i32>,",this.workgroupSize=[128,1,1],this.size=!0,t==="avg"&&a)throw new Error("Cannot compute positions for average pool.");this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.poolType=t,this.computePositions=a,this.flattenPositions=n,this.includeBatchIndex=r,this.shaderKey=`pool2D_${t}_${a}_${n}_${r}`}getUserCode(){let e;this.poolType==="avg"?e="resultValue = resultValue + value; count = count + 1.0;":this.computePositions?e=`let currMaxValue = mix(value, maxValue, maxValueFound);
if (value >= currMaxValue) {
maxValue = value;
maxValueFound = 1.0;
maxPosition = ${this.flattenPositions?this.includeBatchIndex?"((batch * uniforms.xShape[1] + xR) * uniforms.xShape[2] + xC) * uniforms.xShape[3] + d":"(xR * uniforms.xShape[2] + xC) * uniforms.xShape[3] + d":"wR * uniforms.filterDims.y + wC"};
}`:e="resultValue = max(value, resultValue);";let t="resultValue";return this.poolType==="avg"&&(t="resultValue / max(count, 1.0)"),`
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords[0];
let d = coords[3];
let xRCCorner = vec2<i32>(coords.yz) * uniforms.strides - uniforms.pads;
let xRCorner = xRCCorner.x;
let xCCorner = xRCCorner.y;
${this.computePositions?`var maxValue = 0.0;
var maxValueFound = 0.0;
var maxPosition = 0;`:`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.dilations.x) {
let xR = xRCorner + wR;
if (xR < 0 || xR >= uniforms.convDims.x) {
continue;
}
for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + uniforms.dilations.y) {
let xC = xCCorner + wC;
if (xC < 0 || xC >= uniforms.convDims.y) {
continue;
}
let value = getX(batch, xR, xC, d);
${e}
}
}
${this.computePositions?"setOutputAtIndexI32(index, maxPosition);":`setOutputAtIndex(index, ${t});`}
}
}
`}},Z3=class{constructor(e,t,a=!1,n=!1,r=!1){if(this.variableNames=["x"],this.uniforms="strides : vec3<i32>, pads : vec3<i32>, convDims : vec3<i32>, filterDims : vec3<i32>,",this.workgroupSize=[128,1,1],this.size=!0,t==="avg"&&a)throw new Error("Cannot compute positions for average pool.");this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.poolType=t,this.computePositions=a,this.flattenPositions=n,this.includeBatchIndex=r,this.shaderKey=`pool3D_${t}_${a}_${n}_${r}`}getUserCode(){let e;this.poolType==="avg"?e="resultValue += value; count += 1.0;":this.computePositions?e=`let currMaxValue = mix(value, maxValue, maxValueFound);
if (value >= currMaxValue) {
maxValue = value;
maxValueFound = 1.0;
maxPosition = ${this.flattenPositions?this.includeBatchIndex?"(((batch * uniforms.xShape.y + xD) * uniforms.xShape.z + xR) * uniforms.xShape.w + xC) * uniforms.xShape.u + ch":"((xD * uniforms.xShape.z + xR) * uniforms.xShape.w + xC) * uniforms.xShape.u + ch":"wD * uniforms.filterDims.y * uniforms.filterDims.y + wR * uniforms.filterDims.z + wC"};
}`:e="resultValue = max(value, resultValue);";let t="resultValue";return this.poolType==="avg"&&(t="resultValue / max(count, 1.0)"),`
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords.x;
let ch = coords.u;
let xCorner = vec3<i32>(coords.y, coords.z, coords.w) * uniforms.strides - uniforms.pads;
let xDCorner = xCorner.x;
let xRCorner = xCorner.y;
let xCCorner = xCorner.z;
${this.computePositions?`var maxValue = 0.0;
var maxValueFound = 0.0;
var maxPosition = 0;`:`var resultValue = ${this.poolType==="avg"?"0.0":"-1.0 / pow(10.0, -20.0)"};`}
var count = 0.0;
for (var wD = 0; wD < uniforms.filterDims.x; wD++) {
let xD = xDCorner + wD;
if (xD < 0 || xD >= uniforms.convDims.x) {
continue;
}
for (var wR = 0; wR < uniforms.filterDims.y; wR++) {
let xR = xRCorner + wR;
if (xR < 0 || xR >= uniforms.convDims.y) {
continue;
}
for (var wC = 0; wC < uniforms.filterDims.z; wC++) {
let xC = xCCorner + wC;
if (xC < 0 || xC >= uniforms.convDims.z) {
continue;
}
let value = getX(batch, xD, xR, xC, ch);
${e}
}
}
}
${this.computePositions?"setOutputAtIndexI32(index, maxPosition);":`setOutputAtIndex(index, ${t});`}
}
}
`}};function Pk(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reductionIndices:s,keepDims:i}=n;return dl(r,s,i,"max",a)}var $pe={kernelName:oo,backendName:"webgpu",kernelFunc:Pk};function _k(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return dl(r,i,s,"mean",a)}var Ppe={kernelName:po,backendName:"webgpu",kernelFunc:_k};function Fk(e,t,a,n){if(t.filterWidth===1&&t.filterHeight===1&&v.arraysEqual(t.inShape,t.outShape))return tn({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=ke({inputs:{x:e},backend:n,attrs:{shape:[e.shape[i-3]*e.shape[i-2],e.shape[i-1]]}}),l;a==="avg"?l=_k({inputs:{x:o},backend:n,attrs:{axis:0,keepDims:!1}}):(v.assert(a==="max",()=>`Invalid pool type ${a}`),l=Pk({inputs:{x:o},backend:n,attrs:{reductionIndices:0,keepDims:!1}}));let u=ke({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 Mpe(t):(a==="avg"?r=new sp(t,"avg"):(v.assert(a==="max",()=>`Invalid pool type ${a}`),r=new sp(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 _pe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=C.computePool2DInfo(r.shape,s,i,1,o,l);return Fk(r,u,"avg",a)}var Fpe={kernelName:yi,backendName:"webgpu",kernelFunc:_pe};function Dpe(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=C.computePool3DInfo(r.shape,s,i,p,o,u,l),d=new Z3(c,"avg"),h=[{type:"int32",data:[c.strideDepth,c.strideHeight,c.strideWidth]},{type:"int32",data:[c.padInfo.front,c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.inDepth,c.inHeight,c.inWidth]},{type:"int32",data:[c.effectiveFilterDepth,c.effectiveFilterHeight,c.effectiveFilterWidth]}];return a.runWebGPUProgram(d,[r],r.dtype,h)}var Ope={kernelName:du,backendName:"webgpu",kernelFunc:Dpe},zpe=class{constructor(e){this.variableNames=["dy"],this.uniforms=`strides : vec2<i32>, pads : vec2<i32>, dilations : vec2<i32>, filterDims : vec2<i32>,
outHeight : i32, outWidth : i32, avgMultiplier : f32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="avgPool2DBackprop"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords[0];
let d = coords[3];
let dyRCCorner = vec2<i32>(coords.yz) - uniforms.pads;
let dyRCorner = dyRCCorner.x;
let 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.
var dotProd = 0.0;
for (var wR = 0; wR < uniforms.filterDims[0]; wR = wR + uniforms.dilations[0]) {
let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[0]);
if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) {
continue;
}
let idyR = i32(dyR);
for (var wC = 0; wC < uniforms.filterDims[1]; wC = wC + uniforms.dilations[1]) {
let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[1]);
if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) {
continue;
}
let idyC = i32(dyC);
let dyValue = getDy(batch, idyR, idyC, d);
dotProd = dotProd + dyValue * uniforms.avgMultiplier;
}
}
setOutputAtIndex(index, dotProd);
}
}
`}},Lpe=class{constructor(e){this.variableNames=["dy"],this.uniforms=`strides : vec3<i32>, pads : vec3<i32>, filterDims : vec3<i32>,
outDepth : i32, outHeight : i32, outWidth : i32, avgMultiplier : f32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="avgPool3DBackprop"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords.x;
let ch = coords.u;
let dyCorner = vec3<i32>(coords.y, coords.z, coords.w) - uniforms.pads;
let dyDCorner = dyCorner.x;
let dyRCorner = dyCorner.y;
let 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.
var dotProd = 0.0;
for (var wD = 0; wD < uniforms.filterDims[0]; wD++) {
let dyD = f32(dyDCorner + wD) / f32(uniforms.strides[0]);
if (dyD < 0.0 || dyD >= f32(uniforms.outDepth) || fract(dyD) > 0.0) {
continue;
}
let idyD = i32(dyD);
for (var wR = 0; wR < uniforms.filterDims[1]; wR++) {
let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[1]);
if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) {
continue;
}
let idyR = i32(dyR);
for (var wC = 0; wC < uniforms.filterDims[2]; wC++) {
let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[2]);
if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) {
continue;
}
let idyC = i32(dyC);
let dyValue = getDy(batch, idyD, idyR, idyC, ch);
dotProd += dyValue * uniforms.avgMultiplier;
}
}
}
setOutputAtIndex(index, dotProd);
}
}
`}};function Wpe(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=C.computePool3DInfo(i.shape,o,l,1,u,p),d=new Lpe(c),h=1/(c.filterDepth*c.filterHeight*c.filterWidth),m=[{type:"int32",data:[c.strideDepth,c.strideHeight,c.strideWidth]},{type:"int32",data:[c.effectiveFilterDepth-1-c.padInfo.front,c.effectiveFilterHeight-1-c.padInfo.top,c.effectiveFilterWidth-1-c.padInfo.left]},{type:"int32",data:[c.effectiveFilterDepth,c.effectiveFilterHeight,c.effectiveFilterWidth]},{type:"int32",data:[c.outDepth]},{type:"int32",data:[c.outHeight]},{type:"int32",data:[c.outWidth]},{type:"float32",data:[h]}];return a.runWebGPUProgram(d,[r],i.dtype,m)}var Bpe={kernelName:pp,backendName:"webgpu",kernelFunc:Wpe};function Vpe(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s;q3([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,p=C.computePool2DInfo(i.shape,o,l,1,u),c=new zpe(p),d=1/(p.filterHeight*p.filterWidth),h=[{type:"int32",data:[p.strideHeight,p.strideWidth]},{type:"int32",data:[p.effectiveFilterHeight-1-p.padInfo.top,p.effectiveFilterWidth-1-p.padInfo.left]},{type:"int32",data:[p.dilationHeight,p.dilationWidth]},{type:"int32",data:[p.effectiveFilterHeight,p.effectiveFilterWidth]},{type:"int32",data:[p.outHeight]},{type:"int32",data:[p.outWidth]},{type:"float32",data:[d]}];return a.runWebGPUProgram(c,[r],i.dtype,h)}var Upe={kernelName:dp,backendName:"webgpu",kernelFunc:Vpe};function Gpe(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;return c0({a:r,b:s,transposeA:i,transposeB:o,backend:a})}var Hpe={kernelName:xi,backendName:"webgpu",kernelFunc:Gpe},jpe=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=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.start=e,this.uniforms=`start : ${Pt(e.length)}, `,this.shaderKey="slice"}getUserCode(){let e=Pt(this.rank),t=qpe(this.rank),a;return this.start.length===1?a=this.outputShape.map((n,r)=>"sourceLoc = uniforms.start + coords;"):a=this.outputShape.map((n,r)=>`sourceLoc.${X1[r]} = uniforms.start.${Sr(r)} + coords.${X1[r]};`),`
${ue("index")} {
if (index < uniforms.size) {
var sourceLoc : ${e};
let coords = getCoordsFromIndex(index);
${a.join(`
`)}
setOutputAtIndex(index, getSource(${t}));
}
}
`}},X1=["x","y","z","w","u","v"];function qpe(e){if(e===1)return"sourceLoc";if(e<=6)return X1.slice(0,e).map(t=>`sourceLoc.${t}`).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}function ad(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,size:i}=n,[o,l]=Nt.parseSliceParams(r,s,i);if(Nt.assertParamsValid(r,o,l),a.shouldExecuteOnCPU([r])||r.dtype==="string"){let c=a.tensorMap.get(r.dataId),d=Gde(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 jpe(o,l),p=[{type:"int32",data:o}];return a.runWebGPUProgram(u,[r],r.dtype,p)}var Xpe={kernelName:_u,backendName:"webgpu",kernelFunc:ad},Kpe=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((x,A)=>x*A),l=C.getReshaped(r.shape,s,o),u=C.getPermuted(l.length,s.length),p=C.getReshapedPermuted(r.shape,s,o),c=C.getSliceBeginCoords(i,s.length),d=C.getSliceSize(p,i,s.length),h=[],m=ke({inputs:{x:r},backend:a,attrs:{shape:l}}),f=rr({inputs:{x:m},backend:a,attrs:{perm:u}}),g=ke({inputs:{x:f},backend:a,attrs:{shape:p}}),y=ad({inputs:{x:g},backend:a,attrs:{begin:c,size:d}});return h.push(m),h.push(f),h.push(g),h.forEach(x=>a.disposeData(x.dataId)),y},Ype={kernelName:pu,backendName:"webgpu",kernelFunc:Kpe},Zpe=`
fn bincount_write(index: i32, value: f32) {
${xs("&result[index]","value","float32")}
}
`,Jpe=`
fn bincount_write(index: i32, value: f32) {
atomicStore(&result[index], bitcast<i32>(value));
}
`,Dk=class{constructor(e,t,a=!1){this.outputShape=[],this.variableNames=["x"],this.uniforms="binCountSize : i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.hasWeights=!0,this.binaryOutput=!1,this.outputShape=e,this.rank=e.length,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.binaryOutput=a,a&&(this.atomic=!1),this.hasWeights=t,this.hasWeights&&this.variableNames.push("w"),this.shaderKey=`bincount_${this.hasWeights}_${this.binaryOutput}_${this.rank}`}getUserCode(){return`
${this.binaryOutput?Jpe:Zpe}
${ue("index")} {
${this.rank===1?`if (index < uniforms.xShape) {
let indexVal = i32(getX(index));
if (indexVal < uniforms.binCountSize) {
let value = ${this.binaryOutput?1:this.hasWeights?"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?"getW(coord[0], coord[1])":"1."};
bincount_write(coord.x * uniforms.binCountSize + indexVal, value);
}
}`}
}
`}};function Qpe(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=Wa({backend:a,attrs:{shape:u,value:0,dtype:p}}),d=new Dk([o],l),h=[{type:"int32",data:[i]}],m=l?[r,s]:[r];return a.runWebGPUProgram(d,m,p,h,c)}var ece={kernelName:Ai,backendName:"webgpu",kernelFunc:Qpe},tce=class{constructor(e){this.outputShape=[],this.variableNames=["s0","s1"],this.uniforms="s0Size : i32, s1Size : i32, ",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="broadcastArgs"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
var s0 = 1.0;
var s1 = 1.0;
let indexS0 = index - uniforms.size + uniforms.s0Size;
let indexS1 = index - uniforms.size + uniforms.s1Size;
if (indexS0 >= 0) {
s0 = getS0(indexS0);
}
if (indexS1 >= 0) {
s1 = getS1(indexS1);
}
if (s0 == 1.0) {
setOutputAtIndex(index, s1);
} else if (s1 == 1.0) {
setOutputAtIndex(index, s0);
} else if (s0 != s1) {
setOutputAtIndex(index, uniforms.NAN);
} else {
setOutputAtIndex(index, s0);
}
}
}
`}};function ace(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t;if(a.shouldExecuteOnCPU([n,r])){let p=a.tensorMap.get(n.dataId),c=a.tensorMap.get(r.dataId),d=p.values,h=c.values,m=C.assertAndGetBroadcastShape(Array.from(d),Array.from(h));return a.makeTensorInfo([m.length],"int32",Int32Array.from(m))}let s=v.sizeFromShape(n.shape),i=v.sizeFromShape(r.shape),o=Math.max(s,i),l=new tce(o),u=[{type:"int32",data:[s]},{type:"int32",data:[i]}];return a.runWebGPUProgram(l,[n,r],"int32",u)}var nce={kernelName:hu,backendName:"webgpu",kernelFunc:ace},Ok=ta({opType:Pe.NOT_EQUAL,dtype:"bool",cpuKernelImpl:zde}),rce={kernelName:xo,backendName:"webgpu",kernelFunc:Ok};function tc(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.tensorMap.get(n.dataId);return tn({inputs:{x:r.complexTensorInfos.real},backend:a})}var sce={kernelName:Ip,backendName:"webgpu",kernelFunc:tc};function ice(e,t){let a=new td(e.shape,le.TO_INT),n=t.runWebGPUProgram(a,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function K1(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dtype:s}=n;if(s==="complex64"){if(r.dtype==="complex64")return tn({inputs:{x:r},backend:a});let i=yn(r.shape),o=K1({inputs:{x:r},backend:a,attrs:{dtype:"float32"}}),l=ul({inputs:{real:o,imag:i},backend:a});return i.dispose(),a.disposeData(o.dataId),l}if(r.dtype==="complex64"){let i=tc({inputs:{input:r},backend:a}),o=K1({inputs:{x:i},backend:a,attrs:{dtype:s}});return a.disposeData(i.dataId),o}if(!v.hasEncodingLoss(r.dtype,s)){let i=tn({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]=xde(i,r.shape,r.dtype,s);return a.makeTensorInfo(o,l,u)}if(s==="int32")return ice(r,a);if(s==="bool"){let i=a.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=Ok({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 oce={kernelName:bi,backendName:"webgpu",kernelFunc:K1},lce=at({opType:le.CEIL,cpuKernelImpl:Ade}),uce={kernelName:vi,backendName:"webgpu",kernelFunc:lce},dce=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workPerThread=4,this.workgroupSize=[64,1,1],this.outputComponent=4,this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.shaderKey="clipVec4"}getUserCode(){return`
${ue("index")} {
if(index < uniforms.size) {
let value = getAByOutputIndex(index);
var clampedValue = clamp(
value, vec4<f32>(uniforms.minVal), vec4<f32>(uniforms.maxVal));
clampedValue = select(clampedValue, value, isnanVec4(value));
setOutputAtIndex(index, clampedValue);
}
}
`}},pce=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=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="clip"}getUserCode(){return`
${ue("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 cce(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 dce(r.shape):o=new pce(r.shape),a.runWebGPUProgram(o,[r],r.dtype,l)}var hce={kernelName:us,backendName:"webgpu",kernelFunc:cce},mce=class{constructor(e){this.outputShape=[],this.variableNames=["real","imag"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="complexAbs"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let re = abs(getRealByOutputIndex(index));
let im = abs(getImagByOutputIndex(index));
let mx = max(re, im);
// The length function in wgsl may be not underflow-safe on some GPUs.
// So the safe solution is to ensure underflow-safety in all cases.
setOutputAtIndex(index, select(mx * length(vec2<f32>(1, min(re, im)/mx)), 0.0, mx == 0.0));
}
}
`}};function oA(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function fce(e){let{inputs:t,backend:a}=e,{x:n}=t,r=a.tensorMap.get(n.dataId),s=new mce(n.shape),i=[oA(n,r.complexTensorInfos.real),oA(n,r.complexTensorInfos.imag)];return a.runWebGPUProgram(s,i,i[0].dtype)}var gce={kernelName:hp,backendName:"webgpu",kernelFunc:fce},yce=class{constructor(e){this.uniforms="",this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=C.computeOutShape(e,1),this.variableNames=e.map((t,a)=>`T${a}`),this.dispatchLayout=me(this.outputShape),this.dispatch=de(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`
${ue("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 h0(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.tensorMap.get(n.dataId);return tn({inputs:{x:r.complexTensorInfos.imag},backend:a})}var xce={kernelName:vp,backendName:"webgpu",kernelFunc:h0};function _d(e,t,a){let n=e[0].dtype;if(n==="complex64"){let m=e.map(A=>tc({inputs:{input:A},backend:a})),f=e.map(A=>h0({inputs:{input:A},backend:a})),g=_d(m,t,a),y=_d(f,t,a),x=ul({inputs:{real:g,imag:y},backend:a});return m.forEach(A=>a.disposeData(A.dataId)),f.forEach(A=>a.disposeData(A.dataId)),a.disposeData(g.dataId),a.disposeData(y.dataId),x}let r=a.shouldExecuteOnCPU(e);if(n==="string"&&(r=!0),r){let m=e.map(w=>{let I=[-1,v.sizeFromShape(w.shape.slice(t))];return ke({inputs:{x:w},backend:a,attrs:{shape:I}})}),f=m.map(w=>({vals:a.readSync(w.dataId),shape:w.shape})),g=C.computeOutShape(m.map(w=>w.shape),1),y=m[0].shape[0]===1,x=bde(f,g,n,y),A=C.computeOutShape(e.map(w=>w.shape),t),b=a.makeTensorInfo(A,n,x);return m.forEach(w=>a.disposeData(w.dataId)),b}let s=a.device.limits.maxStorageBuffersPerShaderStage-1;if(e.length>s){let m=[];for(let g=0;g<e.length;g+=s){let y=e.slice(g,g+s);m.push(_d(y,t,a))}let f=_d(m,t,a);for(let g of m)a.disposeData(g.dataId);return f}let{tensors2D:i,outShape:o}=Ace(e,t,a),l=i.map(m=>m.shape),u=new yce(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 m=1;m<c.length;m++)c[m]=c[m-1]+l[m][1],p.push({type:"int32",data:[c[m]]})}let d=a.runWebGPUProgram(u,i,i[0].dtype,p);i.forEach(m=>a.disposeData(m.dataId));let h=ke({inputs:{x:d},backend:a,attrs:{shape:o}});return a.disposeData(d.dataId),h}function Ace(e,t,a){let n=C.computeOutShape(e.map(r=>r.shape),t);return{tensors2D:e.map(r=>ke({inputs:{x:r},backend:a,attrs:{shape:[v.sizeFromShape(r.shape.slice(0,t)),v.sizeFromShape(r.shape.slice(t))]}})),outShape:n}}function zk(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);C.assertParamsConsistent(i,s);let o=C.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?tn({inputs:{x:l[0]},backend:a}):_d(l,s,a)}var bce={kernelName:mu,backendName:"webgpu",kernelFunc:zk};function vce(e,t,a,n,r=!1,s=null,i=!1,o=4,l=4,u=4){let p=N=>{switch(N){case 1:return"resData = f32(x[xIndex]);";case 3:return"resData = vec3<f32>(x[xIndex], x[xIndex + 1], x[xIndex + 2]);";case 4:return"resData = vec4<f32>(x[xIndex / 4]);";default:throw new Error(`innerElementSize ${N} is not supported.`)}},c=N=>{switch(N){case 1:return"return f32(W[row * uniforms.wShape[3] + col]);";case 4:return"return vec4<f32>(W[(row * uniforms.wShape[3] + col) / 4]);";default:throw new Error(`innerElementSize ${N} 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);
`,m=e?"uniforms.xShape[1]":"uniforms.xShape[2]",f=e?"uniforms.xShape[2]":"uniforms.xShape[3]",g=e?"row":"col",y=e?"col":"row",x=`
let inChannels = uniforms.wShape[2];
let outWidth = ${e?"uniforms.outShape[2]":"uniforms.outShape[3]"};
let outRow = ${g} / outWidth;
let outCol = ${g} % outWidth;
let WRow = ${y} / (uniforms.filterDims[1] * inChannels);
let WCol = ${y} / inChannels % uniforms.filterDims[1];
let xRow = outRow * uniforms.strides[0] + uniforms.dilations[0] * WRow - uniforms.pads[0];
let xCol = outCol * uniforms.strides[1] + uniforms.dilations[1] * WCol - uniforms.pads[1];
let xCh = ${y} % inChannels;
var resData = ${Xe(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 < ${m} && xCol >= 0 && xCol < ${f}) {
${d}
let xIndex = getIndexFromCoords4D(coord, uniforms.xShape);
${p(o)}
}
return resData;`,A=e?t&&n?`
${x}`:`
if (row < uniforms.dimAOuter && col < uniforms.dimInner) {
${x}
}
return ${Xe(o)}(0.0);`:n&&a?`
${x}`:`
if (row < uniforms.dimInner && col < uniforms.dimBOuter) {
${x}
}
return ${Xe(o)}(0.0);`,b=`${c(l)}`,w=Xe(u),I=Xe(e?o:l),T=Xe(e?l:o);return`
${Pr(s,i,u===4,4)}
fn mm_readA(batch: i32, row : i32, col : i32) -> ${I} {
${e?A:b}
}
fn mm_readB(batch: i32, row : i32, col : i32) -> ${T} {
${e?b:A}
}
fn mm_write(batch: i32, row : i32, col : i32, valueIn : ${w}) {
if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)
{
var value = valueIn;
let outWidth = ${e?"uniforms.outShape[2]":"uniforms.outShape[3]"};
${h}
${ll(r,s)}
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
}
}`}var wce=class{constructor(e,t,a,n,r=!1,s=null,i=!1,o=!1){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, strides : vec2<i32>, dilations : vec2<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.isVec4=((e.inChannels%4===0||e.inChannels%3===0)&&this.isChannelsLast||e.outWidth%4===0&&!this.isChannelsLast)&&e.outChannels%4===0,this.dispatchLayout=this.isChannelsLast?{x:[3],y:[1,2],z:[0]}:{x:[2,3],y:[1],z:[0]},this.workgroupSize=G3(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=H3(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread),this.isVec4?(this.outputComponent=4,this.isChannelsLast&&e.inChannels%4!==0?(this.innerElementSize=3,this.variableComponents=[1,4]):(this.innerElementSize=4,this.variableComponents=[4,4]),r&&(this.variableNames.push("bias"),this.variableComponents.push(4)),i&&(this.variableNames.push("preluActivationWeights"),this.variableComponents.push(4))):(this.innerElementSize=this.elementsPerThread[0],r&&this.variableNames.push("bias"),i&&this.variableNames.push("preluActivationWeights")),this.sequentialAccessByThreads=o,this.addBias=r,this.activation=s,this.hasPreluActivationWeights=i,this.tileAOuter=this.workgroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workgroupSize[0]*this.elementsPerThread[0],this.tileInner=Math.max(this.workgroupSize[0]*this.innerElementSize,this.workgroupSize[1]),this.fitAOuter=t%this.tileAOuter===0,this.fitBOuter=a%this.tileBOuter===0,this.fitInner=n%this.tileInner===0,this.shaderKey=`conv2DMM_${this.elementsPerThread}_${this.activation}}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.innerElementSize}_${this.isChannelsLast}_${this.sequentialAccessByThreads}`}getUserCode(){let e=this.isVec4?d0(this.elementsPerThread,this.workgroupSize,!this.isChannelsLast,this.tileInner):p0(this.elementsPerThread,this.workgroupSize,!this.isChannelsLast,this.tileInner,!1,null,this.sequentialAccessByThreads),t=this.isVec4?[this.innerElementSize,4,4]:[1,1,1];return`
${vce(this.isChannelsLast,this.fitAOuter,this.fitBOuter,this.fitInner,this.addBias,this.activation,this.hasPreluActivationWeights,t[0],t[1],t[2])}
${e}
`}},kce=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms="filterDims: vec2<i32>, pads: vec2<i32>, strides: vec2<i32>, dilations: vec2<i32>,",this.workgroupSize=[4,4,8],this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.dispatchLayout=this.isChannelsLast?{x:[2],y:[1],z:[0,3]}:{x:[3],y:[2],z:[0,1]},this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.addBias=t,this.activation=a,this.hasPreluActivationWeights=n,t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`conv2dnaive_${this.activation}_${this.isChannelsLast}`}getUserCode(){return`
${Pr(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;
${ll(this.addBias,this.activation)}
setOutputAtCoords(coords.x, coords.y, coords.z, coords.w, value);
}
}
${ue("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.strides[0] + uniforms.dilations[0] * row - uniforms.pads[0];
let xCol = outCol * uniforms.strides[1] + uniforms.dilations[1] * col - uniforms.pads[1];
for (var xChannel = 0; xChannel < ${this.isChannelsLast?"uniforms.xShape[3];":"uniforms.xShape[1];"} xChannel = xChannel + 1) {
${this.isChannelsLast?"let v = readInp(batch, xRow, xCol, xChannel);":"let v = readInp(batch, xChannel, xRow, xCol);"}
let f = readFilt(row, col, xChannel, outChannel);
acc = acc + v * f;
}
}
}
writeResult(batch, outRow, outCol, outChannel, acc);
}
`}},Ice=class{constructor(e,t){this.variableNames=["x"],this.uniforms=`pads : vec2<i32>, strides : vec2<i32>, dilations : vec2<i32>, outWidth : i32, itemsPerBlockRow : i32,
inChannels : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=t,this.shaderKey=`im2col_${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`
${ue("index")} {
let coords = getCoordsFromIndex(index);
if(index < uniforms.size) {
let batch = coords[0];
let row = ${a};
let col = ${n};
let offsetY = (row / uniforms.outWidth) * uniforms.strides[0] - uniforms.pads[0];
let xRow = offsetY + uniforms.dilations[0] * (col / uniforms.itemsPerBlockRow);
var value = 0.0;
if(xRow < uniforms.xShape[${e}] && xRow >= 0) {
let offsetX = (row % uniforms.outWidth) * uniforms.strides[1] -
uniforms.pads[1];
let xCol = offsetX + uniforms.dilations[1] * ((col %
uniforms.itemsPerBlockRow) / uniforms.inChannels);
let ch = col % uniforms.inChannels;
if(xCol < uniforms.xShape[${t}] && xCol >= 0) {
value = ${r};
}
}
setOutputAtIndex(index, value);
}
}
`}};function Nh(e,t){let a=e.length;return a>=3?t?[...e.slice(0,-3),e[a-3]*e[a-2],e[a-1]]:[...e.slice(0,-3),e[a-3],e[a-2]*e[a-1]]:!t&&a===1&&e[0]>1?[e[0],1]:null}function Sce({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=a.dataFormat==="channelsLast",u=!l,p=!1,c=l&&a.filterHeight===a.inHeight&&a.filterWidth===a.inWidth&&a.padInfo.type==="VALID",d=[],h,m;if(c){let y=a.inHeight*a.inWidth*a.inChannels;h=ke({inputs:{x:e},backend:n,attrs:{shape:[1,a.batchSize,y]}}),m=ke({inputs:{x:t},backend:n,attrs:{shape:[1,y,a.outChannels]}})}else h=ke({inputs:{x:e},backend:n,attrs:{shape:l?[a.batchSize,a.inHeight*a.inWidth,a.inChannels]:[a.batchSize,a.inChannels,a.inHeight*a.inWidth]}}),m=ke({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}});if(d.push(h),d.push(m),s!=null){let y=Nh(s.shape,l);y!=null&&(s=ke({inputs:{x:s},backend:n,attrs:{shape:y}}),d.push(s))}if(r!=null){let y=Nh(r.shape,l);y!=null&&(r=ke({inputs:{x:r},backend:n,attrs:{shape:y}}),d.push(r))}let f=c0({a:l?h:m,b:l?m:h,transposeA:u,transposeB:p,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),g=ke({inputs:{x:f},backend:n,attrs:{shape:a.outShape}});d.push(f);for(let y of d)n.disposeData(y.dataId);return g}function Cce({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:p,strideWidth:c,strideHeight:d,padInfo:h,outWidth:m,outHeight:f,dilationWidth:g,dilationHeight:y,dataFormat:x}=a,A=x==="channelsLast",b=l*u*p,w=f*m,I=A?[a.batchSize,w,b]:[a.batchSize,b,w],T=new Ice(I,A),N=[{type:"int32",data:[h.top,h.left]},{type:"int32",data:[d,c]},{type:"int32",data:[y,g]},{type:"int32",data:[m]},{type:"int32",data:[p*l]},{type:"int32",data:[p]}],M=n.runWebGPUProgram(T,[e],e.dtype,N),$=[];$.push(M);let E=ke({inputs:{x:t},backend:n,attrs:{shape:[1,b,-1]}});if($.push(E),s!=null){let O=Nh(s.shape,A);O!=null&&(s=ke({inputs:{x:s},backend:n,attrs:{shape:O}}),$.push(s))}if(r!=null){let O=Nh(r.shape,A);O!=null&&(r=ke({inputs:{x:r},backend:n,attrs:{shape:O}}),$.push(r))}let S=c0({a:A?M:E,b:A?E:M,transposeA:!A,transposeB:!1,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),_=ke({inputs:{x:S},backend:n,attrs:{shape:a.outShape}});$.push(S);for(let O of $)n.disposeData(O.dataId);return _}function Lk({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=B().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 Sce({x:e,filter:t,convInfo:a,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i});let h=B().getNumber("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL"),m=h>-1?h:n.thresholdToIncreaseWorkgroups,f=a.batchSize*Math.ceil(a.outHeight*a.outWidth/32)*Math.ceil(a.outChannels/32);if(B().getBool("WEBGPU_CONV_SEPARATE_IM2COL_SHADER")||f<=m)return Cce({x:e,filter:t,convInfo:a,backend:n,bias:r,preluActivationWeights:s,leakyreluAlpha:i,activation:o});let g,y=[a.padInfo.top,a.padInfo.left],x=[{type:"int32",data:[a.filterHeight,a.filterWidth]},{type:"int32",data:[...y]},{type:"int32",data:[a.strideHeight,a.strideWidth]},{type:"int32",data:[a.dilationHeight,a.dilationWidth]}];if(d)g=new kce(a,l,o,u);else{let I=p?a.outHeight*a.outWidth:a.outChannels,T=p?a.outChannels:a.outHeight*a.outWidth,N=a.filterHeight*a.filterWidth*a.inChannels;x.push({type:"int32",data:[I]},{type:"int32",data:[T]},{type:"int32",data:[N]});let M=n.adapterInfo.isIntel();g=new wce(a,I,T,N,l,o,u,M)}let A=[],b=[e,t];l&&(!p&&r.shape.length===1&&(r=ke({inputs:{x:r},backend:n,attrs:{shape:[r.shape[0],1,1]}}),A.push(r)),b.push(r)),u&&(!p&&s.shape.length===1&&(s=ke({inputs:{x:s},backend:n,attrs:{shape:[s.shape[0],1,1]}}),A.push(s)),b.push(s)),o==="leakyrelu"&&(x.push({type:"float32",data:[i]}),g.uniforms+=" alpha : f32,");let w=n.runWebGPUProgram(g,b,e.dtype,x);for(let I of A)n.disposeData(I.dataId);return w}function Tce(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=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,s.shape,i,u,o,p,!1,c);return Lk({x:r,filter:s,convInfo:d,backend:n})}var Nce={kernelName:wi,backendName:"webgpu",kernelFunc:Tce},Rce=class{constructor(e){this.variableNames=["dy","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, strides : vec2<i32>, outBackprop : vec4<i32>,",this.workgroupSize=[64,1,1],this.size=!1,this.isVec4=!1,this.workPerThread=1,this.outputShape=e.inShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.isVec4=this.isChannelsLast&&e.outChannels%4===0&&e.inChannels%4===0,this.isVec4?(this.workPerThread=2,this.outputComponent=4,this.workgroupSize=[4,4,4],this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[4,this.workPerThread,1])):(this.size=!0,this.workPerThread=1,this.workgroupSize=[64,1,1],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize)),this.shaderKey=`conv2DDerInput_${this.isChannelsLast}_${this.isVec4}_${this.workPerThread}`}getUserCode(){let e=this.isChannelsLast?1:2,t=this.isChannelsLast?2:3,a=this.isChannelsLast?3:1,n=`
${ue()} {
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 dyCorner = vec2<i32>(r, c) - uniforms.pads;
// Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
// ? = to be determined. : = across all values in that axis.
var dotProd: array<vec4<f32>, ${this.workPerThread}>;
for (var i = 0; i < ${this.workPerThread}; i++) {
dotProd[i] = vec4<f32>(0.0);
}
for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + 1) {
let dyR = f32(dyCorner.x + wR) / f32(uniforms.strides.x);
let wRPerm = uniforms.filterDims.x - 1 - wR;
if (dyR < 0.0 || dyR >= f32(uniforms.outBackprop[1]) ||
fract(dyR) > 0.0) {
continue;
}
let idyR = i32(dyR);
for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + 1) {
let dyC = f32(dyCorner.y + wC) / f32(uniforms.strides.y);
let dyC2 = f32(dyCorner.y + 1 + wC) / f32(uniforms.strides.y);
let wCPerm = uniforms.filterDims.y - 1 - wC;
var bDyCVal = true;
var bDyCVal2 = true;
if (dyC < 0.0 || dyC >= f32(uniforms.outBackprop[2]) ||
fract(dyC) > 0.0) {
bDyCVal = false;
}
if (dyC2 < 0.0 || dyC2 >= f32(uniforms.outBackprop[2]) ||
fract(dyC2) > 0.0) {
bDyCVal2 = false;
}
let idyC = i32(dyC);
let idyC2 = i32(dyC2);
if (bDyCVal && bDyCVal2) {
let d2Length = uniforms.outBackprop[3];
for (var d2 = 0; d2 < d2Length; d2 = d2 + 4) {
let wValue0 = getW(wRPerm, wCPerm, d1, d2);
let wValue1 = getW(wRPerm, wCPerm, d1 + 1, d2);
let wValue2 = getW(wRPerm, wCPerm, d1 + 2, d2);
let wValue3 = getW(wRPerm, wCPerm, d1 + 3, d2);
var xValue = getDy(batch, idyR, idyC, d2);
let tmpval = vec4<f32>(dot(xValue, wValue0),
dot(xValue, wValue1),
dot(xValue, wValue2),
dot(xValue, wValue3));
dotProd[0] = dotProd[0] + tmpval;
xValue = getDy(batch, idyR, idyC2, d2);
dotProd[1] = dotProd[1] + vec4<f32>(dot(xValue, wValue0),
dot(xValue, wValue1),
dot(xValue, wValue2),
dot(xValue, wValue3));
}
} else if (bDyCVal) {
let d2Length = uniforms.outBackprop[3];
for (var d2 = 0; d2 < d2Length; d2 = d2 + 4) {
let wValue0 = getW(wRPerm, wCPerm, d1, d2);
let wValue1 = getW(wRPerm, wCPerm, d1 + 1, d2);
let wValue2 = getW(wRPerm, wCPerm, d1 + 2, d2);
let wValue3 = getW(wRPerm, wCPerm, d1 + 3, d2);
var xValue = getDy(batch, idyR, idyC, d2);
let tmpval = vec4<f32>(dot(xValue, wValue0),
dot(xValue, wValue1),
dot(xValue, wValue2),
dot(xValue, wValue3));
dotProd[0] = dotProd[0] + tmpval;
}
} else if (bDyCVal2) {
let d2Length = uniforms.outBackprop[3];
for (var d2 = 0; d2 < d2Length; d2 = d2 + 4) {
let wValue0 = getW(wRPerm, wCPerm, d1, d2);
let wValue1 = getW(wRPerm, wCPerm, d1 + 1, d2);
let wValue2 = getW(wRPerm, wCPerm, d1 + 2, d2);
let wValue3 = getW(wRPerm, wCPerm, d1 + 3, d2);
var xValue = getDy(batch, idyR, idyC2, d2);
let tmpval = vec4<f32>(dot(xValue, wValue0),
dot(xValue, wValue1),
dot(xValue, wValue2),
dot(xValue, wValue3));
dotProd[1] = dotProd[1] + tmpval;
}
}
}
}
for (var i = 0; i < ${this.workPerThread}; i = i + 1) {
let coords = vec4<i32>(batch, r, c + i, d1);
if (coordsInBounds4D(coords, uniforms.outShape)) {
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], dotProd[i]);
}
}
}
`;return this.isVec4?`
${n}
`:`
${ue("index")} {
if(index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords[0];
let d1 = coords[${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.strides.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.strides.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) {
let xValue = ${this.isChannelsLast?"getDy(batch, idyR, idyC, d2)":"getDy(batch, d2, idyR, idyC)"};
let wValue = getW(wRPerm, wCPerm, d1, d2);
dotProd = dotProd + xValue * wValue;
}
}
}
setOutputAtIndex(index, dotProd);
}
}
`}},Ece=class{constructor(e){this.variableNames=["x","dy"],this.uniforms="pads : vec2<i32>, strides : vec2<i32>, batchSize : i32, outHeight : i32, outWidth : i32, inHeight : i32, inWidth : i32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.filterShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",this.shaderKey=`conv2DDerFilter_${this.isChannelsLast}`}getUserCode(){return`
${ue("index")} {
if(index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let wR = coords[0];
let wC = coords[1];
let d1 = coords[2];
let d2 = coords[3];
// Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
// ? = to be determined. : = across all values in that axis.
var dotProd = 0.0;
for (var b = 0; b < uniforms.batchSize; b = b + 1) {
for (var yR = 0; yR < uniforms.outHeight; yR = yR + 1) {
let xR = wR + yR * uniforms.strides[0] - uniforms.pads[0];
if (xR < 0 || xR >= uniforms.inHeight) {
continue;
}
for (var yC = 0; yC < uniforms.outWidth; yC = yC + 1) {
let xC = wC + yC * uniforms.strides[1] - uniforms.pads[1];
if (xC < 0 || xC >= uniforms.inWidth) {
continue;
}
if (${this.isChannelsLast}) {
let dyValue = getDy(b, yR, yC, d2);
let xValue = getX(b, xR, xC, d1);
dotProd = dotProd + xValue * dyValue;
} else {
let dyValue = getDy(b, d2, yR, yC);
let xValue = getX(b, d1, xR, xC);
dotProd = dotProd + xValue * dyValue;
}
}
}
}
setOutputAtIndex(index, dotProd);
}
}
`}},Mce=class{constructor(e){this.variableNames=["x","dy"],this.uniforms=`pads : vec3<i32>, strides : vec3<i32>, batchSize : i32, outDepth : i32,
outHeight : i32, outWidth : i32, inDepth : i32, inHeight : i32, inWidth : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.filterShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="conv3DDerFilter"}getUserCode(){return`
${ue("index")} {
if(index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let wF = coords.x;
let wR = coords.y;
let wC = coords.z;
let d1 = coords.w;
let d2 = coords.u;
var dotProd = 0.0;
for (var b = 0; b < uniforms.batchSize; b++) {
for (var yF = 0; yF < uniforms.outDepth; yF++) {
let xF = wF + yF * uniforms.strides[0] - uniforms.pads[0];
if (xF < 0 || xF >= uniforms.inDepth) {
continue;
}
for (var yR = 0; yR < uniforms.outHeight; yR++) {
let xR = wR + yR * uniforms.strides[1] - uniforms.pads[1];
if (xR < 0 || xR >= uniforms.inHeight) {
continue;
}
for (var yC = 0; yC < uniforms.outWidth; yC++) {
let xC = wC + yC * uniforms.strides[2] - uniforms.pads[2];
if (xC < 0 || xC >= uniforms.inWidth) {
continue;
}
let dyValue = getDy(b, yF, yR, yC, d2);
let xValue = getX(b, xF, xR, xC, d1);
dotProd += xValue * dyValue;
}
}
}
}
setOutputAtIndex(index, dotProd);
}
}
`}},$ce=class{constructor(e){this.variableNames=["dy","W"],this.uniforms=`filterDims : vec3<i32>, pads : vec3<i32>, strides : vec3<i32>,
outDepth : i32, outHeight : i32, outWidth : i32, outChannels : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="conv3DDerInput"}getUserCode(){return`
${ue("index")} {
if(index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords.x;
let d1 = coords.u;
let dyCorner = vec3<i32>(coords.y, coords.z, coords.w) - uniforms.pads;
let dyFCorner = dyCorner.x;
let dyRCorner = dyCorner.y;
let dyCCorner = dyCorner.z;
var dotProd = 0.0;
for (var wF = 0; wF < uniforms.filterDims[0]; wF++) {
let dyF = f32(dyFCorner + wF) / f32(uniforms.strides[0]);
if (dyF < 0.0 || dyF >= f32(uniforms.outDepth) || fract(dyF) > 0.0) {
continue;
}
let idyF = i32(dyF);
let wFPerm = uniforms.filterDims[0] - 1 - wF;
for (var wR = 0; wR < uniforms.filterDims[1]; wR++) {
let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[1]);
if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) {
continue;
}
let idyR = i32(dyR);
let wRPerm = uniforms.filterDims[1] - 1 - wR;
for (var wC = 0; wC < uniforms.filterDims[2]; wC++) {
let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[2]);
if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) {
continue;
}
let idyC = i32(dyC);
let wCPerm = uniforms.filterDims[2] - 1 - wC;
for (var d2 = 0; d2 < uniforms.outChannels; d2++) {
let xValue = getDy(batch, idyF, idyR, idyC, d2);
let wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
}
}
}
}
setOutputAtIndex(index, dotProd);
}
}
`}};function Pce(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=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,p,i,1,o,u,!1,c),h=new Ece(d),m=[{type:"int32",data:[d.padInfo.top,d.padInfo.left]},{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.batchSize]},{type:"int32",data:[d.outHeight]},{type:"int32",data:[d.outWidth]},{type:"int32",data:[d.inHeight]},{type:"int32",data:[d.inWidth]}];return a.runWebGPUProgram(h,[r,s],r.dtype,m)}var _ce={kernelName:mp,backendName:"webgpu",kernelFunc:Pce};function Fce(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.strides[0]);
let xC = f32(outCol - uniforms.pads[1] + WCol) / f32(uniforms.strides[1]);
if (xR < 0.0 || xR >= f32(uniforms.outBackprop[1]) || fract(xR) > 0.0) {
return ${Xe(e)}(0.0);
}
if (xC < 0.0 || xC >= f32(uniforms.outBackprop[2]) || fract(xC) > 0.0) {
return ${Xe(e)}(0.0);
}
let coord = vec4<i32>(
batch,
i32(xR),
i32(xC),
col % uniforms.outBackprop[3]);
return x[getIndexFromCoords4D(coord, uniforms.xShape)/${e}];`}
}
return ${Xe(e)}(0.0);`;return`
fn mm_readA(batch: i32, row : i32, col : i32) -> ${Xe(e)} {
${a}
}
fn mm_readB(batch: i32, row : i32, col : i32) -> ${Xe(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 ${Xe(e)}(0.0);
}
fn mm_write(batch: i32, row : i32, col : i32, valueInput : ${Xe(e)}) {
if (row < uniforms.dimAOuter && col < uniforms.dimBOuter) {
var value = valueInput;
let outCoord = vec4<i32>(
batch,
row / uniforms.outShape[2],
row % uniforms.outShape[2],
col);
result[getIndexFromCoords4D(outCoord, uniforms.outShape)/${e}] = value;
}
}`}var Dce=class{constructor(e){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, strides : 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=G3(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=H3(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread),this.isVec4&&(this.outputComponent=4,this.variableComponents=[4,1]),this.shaderKey=`conv2DDerInputMM_${this.isVec4}_${this.elementsPerThread}`}getUserCode(){let e=this.isVec4?d0(this.elementsPerThread,this.workgroupSize):p0(this.elementsPerThread,this.workgroupSize);return`
${Fce(this.isVec4?4:1)}
${e}
`}};function Oce(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=C.convertConv2DDataFormat(u),d=C.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]}],m;if(B().getBool("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE")||d.dataFormat!=="channelsLast")m=new Rce(d);else{m=new Dce(d);let f=d.inHeight*d.inWidth,g=d.inChannels,y=d.filterHeight*d.filterWidth*d.outChannels;h.push({type:"uint32",data:[f]},{type:"uint32",data:[g]},{type:"uint32",data:[y]})}return a.runWebGPUProgram(m,[r,s],"float32",h)}var zce={kernelName:ki,backendName:"webgpu",kernelFunc:Oce},Lce=class{constructor(e){this.variableNames=["x","W"],this.uniforms="filterDims: vec3<i32>, pads: vec3<i32>, strides: vec3<i32>, dilations: vec3<i32>,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="conv3dnaive"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getOutputCoords();
let batch = coords.x;
let d2 = coords.u;
let xFRCCorner = vec3<i32>(coords.y, coords.z, coords.w) * uniforms.strides - uniforms.pads;
let xFCorner = xFRCCorner.x;
let xRCorner = xFRCCorner.y;
let xCCorner = xFRCCorner.z;
let inputDepthNearestVec4 = (uniforms.xShape.u / 4) * 4;
let inputDepthVec4Remainder = uniforms.xShape.u % 4;
var dotProd = 0.0;
for (var wF = 0; wF < uniforms.filterDims[0]; wF++) {
let xF = xFCorner + wF * uniforms.dilations[0];
if (xF < 0 || xF >= uniforms.xShape.y) {
continue;
}
for (var wR = 0; wR < uniforms.filterDims[1]; wR++) {
let xR = xRCorner + wR * uniforms.dilations[1];
if (xR < 0 || xR >= uniforms.xShape.z) {
continue;
}
for (var wC = 0; wC < uniforms.filterDims[2]; wC++) {
let xC = xCCorner + wC * uniforms.dilations[2];
if (xC < 0 || xC >= uniforms.xShape.w) {
continue;
}
for (var d1 = 0; d1 < inputDepthNearestVec4; d1 += 4) {
let xValues = vec4<f32>(
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)
);
let wValues = vec4<f32>(
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 (inputDepthVec4Remainder == 1) {
dotProd += getX(batch, xF, xR, xC, inputDepthNearestVec4) *
getW(wF, wR, wC, inputDepthNearestVec4, d2);
} else if (inputDepthVec4Remainder == 2) {
let xValues = vec2<f32>(
getX(batch, xF, xR, xC, inputDepthNearestVec4),
getX(batch, xF, xR, xC, inputDepthNearestVec4 + 1)
);
let wValues = vec2<f32>(
getW(wF, wR, wC, inputDepthNearestVec4, d2),
getW(wF, wR, wC, inputDepthNearestVec4 + 1, d2)
);
dotProd += dot(xValues, wValues);
} else if (inputDepthVec4Remainder == 3) {
let xValues = vec3<f32>(
getX(batch, xF, xR, xC, inputDepthNearestVec4),
getX(batch, xF, xR, xC, inputDepthNearestVec4 + 1),
getX(batch, xF, xR, xC, inputDepthNearestVec4 + 2)
);
let wValues = vec3<f32>(
getW(wF, wR, wC, inputDepthNearestVec4, d2),
getW(wF, wR, wC, inputDepthNearestVec4 + 1, d2),
getW(wF, wR, wC, inputDepthNearestVec4 + 2, d2)
);
dotProd += dot(xValues, wValues);
}
}
}
}
setOutputAtIndex(index, dotProd);
}
}`}};function Wce(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=C.computeConv3DInfo(r.shape,s.shape,i,l,o),p=[u.padInfo.front,u.padInfo.top,u.padInfo.left],c=[{type:"int32",data:[u.filterDepth,u.filterHeight,u.filterWidth]},{type:"int32",data:[...p]},{type:"int32",data:[u.strideDepth,u.strideHeight,u.strideWidth]},{type:"int32",data:[u.dilationDepth,u.dilationHeight,u.dilationWidth]}],d=new Lce(u),h=pa(r.dtype,s.dtype);return a.runWebGPUProgram(d,[r,s],h,c)}var Bce={kernelName:Ii,backendName:"webgpu",kernelFunc:Wce};function Vce(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=n,u=C.computeConv3DInfo(r.shape,l,i,1,o),p=new Mce(u),c=[{type:"int32",data:[u.padInfo.front,u.padInfo.top,u.padInfo.left]},{type:"int32",data:[u.strideDepth,u.strideHeight,u.strideWidth]},{type:"int32",data:[u.batchSize]},{type:"int32",data:[u.outDepth]},{type:"int32",data:[u.outHeight]},{type:"int32",data:[u.outWidth]},{type:"int32",data:[u.inDepth]},{type:"int32",data:[u.inHeight]},{type:"int32",data:[u.inWidth]}];return a.runWebGPUProgram(p,[r,s],s.dtype,c)}var Uce={kernelName:fu,backendName:"webgpu",kernelFunc:Vce};function Gce(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{strides:i,pad:o,inputShape:l}=n,u=C.computeConv3DInfo(l,s.shape,i,1,o),p=new $ce(u),c=[{type:"int32",data:[u.filterDepth,u.filterHeight,u.filterWidth]},{type:"int32",data:[u.filterDepth-1-u.padInfo.front,u.filterHeight-1-u.padInfo.top,u.filterWidth-1-u.padInfo.left]},{type:"int32",data:[u.strideDepth,u.strideHeight,u.strideWidth]},{type:"int32",data:[u.outDepth]},{type:"int32",data:[u.outHeight]},{type:"int32",data:[u.outWidth]},{type:"int32",data:[u.outChannels]}];return a.runWebGPUProgram(p,[r,s],r.dtype,c)}var Hce={kernelName:Si,backendName:"webgpu",kernelFunc:Gce},jce=at({opType:le.COS}),qce={kernelName:Ci,backendName:"webgpu",kernelFunc:jce},Xce=at({opType:le.COSH}),Kce={kernelName:Ti,backendName:"webgpu",kernelFunc:Xce},Yce=class{constructor(e,t,a,n){this.variableNames=["Image","Boxes","BoxInd"],this.uniforms="extrapolationValue : f32,",this.workgroupSize=[64,1,1],this.size=!0;let[r]=t;this.outputShape=[r,a[0],a[1],e],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.methodId=n==="bilinear"?1:0,this.cropHeightBiggerThan1=this.outputShape[1]>1,this.cropWidthBiggerThan1=this.outputShape[2]>1,this.shaderKey=`cropAndResize_${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`
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let height_ratio = f32(${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);
}
}
}
`}},Zce=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 Yce(r.shape[3],s.shape,o,l),c=[{type:"float32",data:[u]}];return a.runWebGPUProgram(p,[r,s,i],"float32",c)},Jce={kernelName:Ei,backendName:"webgpu",kernelFunc:Zce},ip;(function(e){e.Prod="*",e.Sum="+"})(ip||(ip={}));var lA=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=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.exclusive=a,this.reverse=n,this.op=e,this.shaderKey=`cum_${this.op}_${this.exclusive}_${this.reverse}`}getUserCode(){let e=this.outputShape.length,t=this.op===ip.Prod?"1.0":"0.0",a=this.exclusive?t:`getX(${uA(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"),`
${ue("index")} {
if (index < uniforms.size) {
var coords = getCoordsFromIndex(index);
let end = ${dA(e,"coords",this.op)};
var val = ${a};
let pow2 = i32(pow(2.0, uniforms.index));
if (${r}) {
let idx = ${s};
${dA(e,"coords",this.op)} = idx;
val ${this.op}= getX(${uA(e,"coords",this.op)});
}
setOutputAtIndex(index, val);
}
}
`}};function uA(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 ${e} is not yet supported`)}function dA(e,t,a){if(e===1)return`${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 ${e} is not yet supported`)}function Wk(e,t,a,n,r,s){let i=t.shape.length,o=C.getAxesPermutation([n],i),l=t;o!=null&&(l=rr({inputs:{x:t},backend:a,attrs:{perm:o}}));let u=C.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGPU cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let p=l.shape[u],c=tn({inputs:{x:l},backend:a});for(let d=0;d<=Math.ceil(Math.log2(p))-1;d++){let h=new lA(e,l.shape,!1,s),m=c,f=[{type:"float32",data:[d]}];c=a.runWebGPUProgram(h,[c],c.dtype,f),a.disposeData(m.dataId)}if(r){let d=new lA(e,l.shape,r,s),h=c,m=[{type:"float32",data:[0]}];c=a.runWebGPUProgram(d,[c],c.dtype,m),a.disposeData(h.dataId)}if(o!=null){let d=C.getUndoAxesPermutation(o),h=rr({inputs:{x:c},backend:a,attrs:{perm:d}});return a.disposeData(c.dataId),a.disposeData(l.dataId),h}return c}function Qce(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return Wk(ip.Prod,r,a,s,i,o)}var ehe={kernelName:Ni,backendName:"webgpu",kernelFunc:Qce};function the(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return Wk(ip.Sum,r,a,s,i,o)}var ahe={kernelName:Ri,backendName:"webgpu",kernelFunc:the};function nhe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n,l=r.shape.length===1,u=v.sizeFromShape(s.shape)>0,p=s.dtype,c=l?[r.shape[0]]:[r.shape[0],r.shape[1]],d=l?[i]:[r.shape[0],i],h=Wa({backend:a,attrs:{shape:d,value:0,dtype:p}}),m=new Dk(c,u,o),f=[{type:"int32",data:[i]}],g=u?[r,s]:[r];return a.runWebGPUProgram(m,g,p,f,h)}var rhe={kernelName:gu,backendName:"webgpu",kernelFunc:nhe},she=class{constructor(e,t){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.uniforms="blockSize : i32,",this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`depthToSpace_${t}`,this.dataFormat=t}getUserCode(){return`
${ue("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 = ${this.getInputSamplingString()};
setOutputAtIndex(index, rlt);
}
}`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?"uniforms.outShape[3]":"uniforms.outShape[1]"}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function ihe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockSize:s,dataFormat:i}=n,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],c=l*s,d=u*s,h=p/(s*s),m=i==="NHWC"?[o,c,d,h]:[o,h,c,d],f=[{type:"int32",data:[s]}],g=new she(m,i);return a.runWebGPUProgram(g,[r],r.dtype,f)}var ohe={kernelName:Mi,backendName:"webgpu",kernelFunc:ihe},lhe=class{constructor(e,t,a,n=!1,r=null,s=!1){this.variableNames=["x","W"],this.uniforms="pads : vec2<i32>, inDims : vec2<i32>,",this.workgroupSize=[16,16,1],this.outputShape=e,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),n&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),this.addBias=n,this.activation=r,this.hasPreluActivation=s,this.filterHeight=t,this.filterWidth=a,this.shaderKey=`depthwiseNCHW_${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`
${Pr(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;
}
${ue()} {
let coords = getOutputCoords();
let batch = coords[0];
let xRCCorner = vec2<i32>(coords.zw) - uniforms.pads;
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);
}
}
${ll(this.addBias,this.activation)}
if (coordsInBounds4D(coords, uniforms.outShape)) {
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
}
}
`}},Bk=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms="pads : vec2<i32>, inDims : vec2<i32>, virtualWidth : i32,",this.workgroupSize=[64,1,1],this.workPerThread=4,this.outputComponent=4,this.outputShape=e.outShape,this.virtualWidth=Math.ceil(this.outputShape[2]/this.workPerThread)*this.workPerThread;let r=[this.outputShape[0],this.outputShape[1],this.virtualWidth,this.outputShape[3]];this.dispatchLayout=me(r),this.dispatch=de(this.dispatchLayout,r,this.workgroupSize,[this.outputComponent*this.workPerThread,1,1]),v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=a,this.hasPreluActivation=n,this.shaderKey=`depthwiseVec4_${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,t=this.convInfo.strideHeight,a=this.convInfo.strideWidth;return`
${Pr(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;
}
${ue("index")} {
let width0 = uniforms.outShape[3] / ${this.outputComponent};
let d1 = (index % width0) * ${this.outputComponent};
var index1 = index / width0;
let width1 = uniforms.virtualWidth / ${this.workPerThread};
let c = (index1 % width1) * ${this.workPerThread};
index1 = index1 / width1;
let r = index1 % uniforms.outShape[1];
let batch = index1 / uniforms.outShape[1];
let xRCCorner = vec2<i32>(r, c) * vec2<i32>(${t}, ${a}) - uniforms.pads;
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 * ${a} + 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];
${ll(this.addBias,this.activation)}
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
}
}
}
`}},Vk=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms=`pads : vec2<i32>, inDims : vec2<i32>, filterHeight : i32,
filterWidth : i32, strides : vec2<i32>, dilations : vec2<i32>,`,this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=a,this.hasPreluActivation=n,this.shaderKey=`depthwise_${this.activation}_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?"getX(batch, xR, xC, d1);":"getX(batch, d1, xR, xC);";return`
${Pr(this.activation,this.hasPreluActivation,!1,4)}
${ue("index")} {
if (index < uniforms.size) {
let coords = getOutputCoords();
let batch = coords[0];
let xRCCorner = vec2<i32>(coords.${this.isChannelsLast?"yz":"zw"}) * uniforms.strides - uniforms.pads;
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.dilations[0];
let inputColEnd = inputColStart + uniforms.filterWidth *
uniforms.dilations[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.dilations[0];
for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {
let xC = inputColStart + wC * uniforms.dilations[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.dilations[0];
if (xR < 0 || xR >= uniforms.inDims[0]) {
continue;
}
for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {
let xC = inputColStart + wC * uniforms.dilations[1];
if (xC < 0 || xC >= uniforms.inDims[1]) {
continue;
}
let xVal = ${e};
let wVal = getW(wR, wC, d1, q);
value = value + xVal * wVal;
}
}
}
${ll(this.addBias,this.activation)}
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
}
}
`}};function uhe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:p}=n,c=C.convertConv2DDataFormat(l),d=u;d==null&&(d=[1,1]);let h=C.computeConv2DInfo(r.shape,s.shape,i,d,o,p,!0,c),m=[{type:"int32",data:[h.padInfo.top,h.padInfo.left]},{type:"int32",data:[h.inHeight,h.inWidth]}],f=h.dataFormat==="channelsLast",g;return!f&&h.inHeight>16&&h.inWidth>16&&h.strideHeight===1&&h.strideWidth===1&&h.dilationWidth===1&&h.dilationHeight===1&&h.inChannels===h.outChannels?g=new lhe(h.outShape,h.filterHeight,h.filterWidth):f&&h.outHeight>4&&h.outWidth>4&&h.strideWidth<=2&&h.inChannels===h.outChannels&&h.dilationHeight===1&&h.dilationWidth===1&&h.inChannels%4===0?(g=new Bk(h),m.push({type:"int32",data:[g.virtualWidth]})):(g=new Vk(h),m.push({type:"int32",data:[h.filterHeight]},{type:"int32",data:[h.filterWidth]},{type:"int32",data:[h.strideHeight,h.strideWidth]},{type:"int32",data:[h.dilationHeight,h.dilationWidth]})),a.runWebGPUProgram(g,[r,s],r.dtype,m)}var dhe={kernelName:$i,backendName:"webgpu",kernelFunc:uhe},phe=class{constructor(e){this.variableNames=["x","dy"],this.uniforms=`strides : vec2<i32>, pads : vec2<i32>, filterDims : vec2<i32>, outHeight : i32,
outWidth : i32, inHeight : i32, inWidth : i32, batchSize : i32, channelMul : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.filterShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="depthwise_conv2d_backprop_filter"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let wR = coords[0];
let wC = coords[1];
let d1 = coords[2];
let dm = coords[3];
let d2 = d1 * uniforms.channelMul + dm;
var dotProd = 0.0;
for (var b = 0; b < uniforms.batchSize; b++) {
for (var yR = 0; yR < uniforms.outHeight; yR++) {
let xR = wR + yR * uniforms.strides[0] - uniforms.pads[0];
if (xR < 0 || xR >= uniforms.inHeight) {
continue;
}
for (var yC = 0; yC < uniforms.outWidth; yC++) {
let xC = wC + yC * uniforms.strides[1] - uniforms.pads[1];
if (xC < 0 || xC >= uniforms.inWidth) {
continue;
}
let dyValue = getDy(b, yR, yC, d2);
let xValue = getX(b, xR, xC, d1);
dotProd += xValue * dyValue;
}
}
}
setOutputAtIndex(index, dotProd);
}
}
`}},che=class{constructor(e){this.variableNames=["dy","W"],this.uniforms=`strides : vec2<i32>, pads : vec2<i32>, filterDims : vec2<i32>,
outHeight : i32, outWidth : i32, channelMul : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="depthwise_conv2d_backprop_input"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords[0];
let d1 = coords[3];
let dyCorner = coords.yz - uniforms.pads;
let dyRCorner = dyCorner.x;
let dyCCorner = dyCorner.y;
var dotProd = 0.0;
for (var wR = 0; wR < uniforms.filterDims[0]; wR++) {
let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[0]);
if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) {
continue;
}
let idyR = i32(dyR);
let wRPerm = uniforms.filterDims[0] - 1 - wR;
for (var wC = 0; wC < uniforms.filterDims[1]; wC++) {
let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[1]);
if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) {
continue;
}
let idyC = i32(dyC);
let wCPerm = uniforms.filterDims[1] - 1 - wC;
for (var dm = 0; dm < uniforms.channelMul; dm++) {
let d2 = d1 * uniforms.channelMul + dm;
let xValue = getDy(batch, idyR, idyC, d2);
let wValue = getW(wRPerm, wCPerm, d1, dm);
dotProd += xValue * wValue;
}
}
}
setOutputAtIndex(index, dotProd);
}
}
`}};function hhe(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=C.computeConv2DInfo(r.shape,p,i,o,l,u,!0),d=new phe(c),h=[{type:"int32",data:[c.strideHeight,c.strideWidth]},{type:"int32",data:[c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.filterHeight,c.filterWidth]},{type:"int32",data:[c.outHeight]},{type:"int32",data:[c.outWidth]},{type:"int32",data:[c.inHeight]},{type:"int32",data:[c.inWidth]},{type:"int32",data:[c.batchSize]},{type:"int32",data:[c.outChannels/c.inChannels]}];return a.runWebGPUProgram(d,[r,s],"float32",h)}var mhe={kernelName:fp,backendName:"webgpu",kernelFunc:hhe};function fhe(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=C.computeConv2DInfo(p,s.shape,i,o,l,u,!0),d=new che(c),h=[{type:"int32",data:[c.strideHeight,c.strideWidth]},{type:"int32",data:[c.filterHeight-1-c.padInfo.top,c.filterWidth-1-c.padInfo.left]},{type:"int32",data:[c.filterHeight,c.filterWidth]},{type:"int32",data:[c.outHeight]},{type:"int32",data:[c.outWidth]},{type:"int32",data:[c.outChannels/c.inChannels]}];return a.runWebGPUProgram(d,[r,s],r.dtype,h)}var ghe={kernelName:gp,backendName:"webgpu",kernelFunc:fhe},yhe=class{constructor(e){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e,e],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="diag"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getOutputCoords();
let value = select(0.0, getX(coords[0]), coords[0] == coords[1]);
setOutputAtIndex(index, value);
}
}
`}};function xhe(e){let{inputs:t,backend:a}=e,{x:n}=t,r=[...n.shape,...n.shape],s=v.sizeFromShape(n.shape),i=ke({inputs:{x:n},backend:a,attrs:{shape:[s]}}),o=new yhe(s),l=a.runWebGPUProgram(o,[i],i.dtype),u=ke({inputs:{x:l},backend:a,attrs:{shape:r}});return a.disposeData(i.dataId),a.disposeData(l.dataId),u}var Ahe={kernelName:yu,backendName:"webgpu",kernelFunc:xhe},bhe=class{constructor(e){this.variableNames=["x","w"],this.uniforms="filterDims: vec2<i32>, pads: vec2<i32>, strides: vec2<i32>, dilations: vec2<i32>",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="dilation2d"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let neg_infinity = -3.4e38;
let coords = getOutputCoords();
let batch = coords.x;
let d1 = coords.w;
let outTopLeftCorner = coords.yz * uniforms.strides - uniforms.pads;
let hBeg = outTopLeftCorner.x;
let wBeg = outTopLeftCorner.y;
var curVal = neg_infinity;
for (var h = 0; h < uniforms.filterDims[0]; h = h + 1) {
let hIn = hBeg + h * uniforms.dilations[0];
if (hIn >= 0 && hIn < uniforms.xShape[1]) {
for (var w = 0; w < uniforms.filterDims[1]; w = w + 1) {
let wIn = wBeg + w * uniforms.dilations[1];
if (wIn >= 0 && wIn < uniforms.xShape[2]) {
let val = getX(batch, hIn, wIn, d1) + getW(h, w, d1);
if (val > curVal) {
curVal = val;
}
}
}
}
}
setOutputAtIndex(index, curVal);
}
}
`}};function vhe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=C.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),p=[u.padInfo.top,u.padInfo.left],c=[{type:"int32",data:[u.filterHeight,u.filterWidth]},{type:"int32",data:[...p]},{type:"int32",data:[u.strideHeight,u.strideWidth]},{type:"int32",data:[u.dilationHeight,u.dilationWidth]}],d=new bhe(u);return a.runWebGPUProgram(d,[r,s],r.dtype,c)}var whe={kernelName:Pi,backendName:"webgpu",kernelFunc:vhe},khe=class{constructor(e,t){if(this.variableNames=["x","w","dy"],this.uniforms="filterDims: vec2<i32>, pads: vec2<i32>, strides: vec2<i32>, dilations: vec2<i32>, dySize: i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=e.inShape,this.dispatchLayout=me(e.outShape),this.dispatch=de(this.dispatchLayout,e.outShape,this.workgroupSize),t!=="float32"&&t!=="int32")throw new Error(`Dilation2DBackpropInput only supports float32 and int32
types, does not support ${t} type.`);this.type=t,this.shaderKey="dilation2DBackpropInput"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.dySize) {
let coords = getDyCoordsFromIndex(index);
let b = coords[0];
let r = coords[1];
let c = coords[2];
let d = coords[3];
let dyCorner = vec2<i32>(r, c) * uniforms.strides - uniforms.pads;
var curVal = -3.4e38; // neg_infinity
var xRMax = 0;
var xCMax = 0;
// In the case of multiple argmax branches, we only back-propagate
// along the last branch, i.e., the one with largest value of
// 'wR * uniforms.filterDims[1] + wC', similarly to the max-pooling
// backward routines.
for (var wR = 0; wR < uniforms.filterDims[0]; wR++) {
let xR = dyCorner.x + wR * uniforms.dilations[0];
if (xR >= 0 && xR < uniforms.xShape[1]) {
for (var wC = 0; wC < uniforms.filterDims[1]; wC++) {
let xC = dyCorner.y + wC * uniforms.dilations[1];
if (xC >= 0 && xC < uniforms.xShape[2]) {
let val = getX(b, xR, xC, d) + getW(wR, wC, d);
if (val > curVal) {
curVal = val;
xRMax = xR;
xCMax = xC;
}
}
}
}
}
let flatIndexIn = d + uniforms.xShape[3] *
(xCMax + uniforms.xShape[2] * (xRMax + uniforms.xShape[1] * b));
let value = getDy(b, r, c, d);
${xs("&result[flatIndexIn]","value",this.type)}
}
}
`}},Ihe=class{constructor(e,t,a){if(this.variableNames=["x","w","dy"],this.uniforms="filterDims: vec2<i32>, pads: vec2<i32>, strides: vec2<i32>, dilations: vec2<i32>, dySize: i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=e.filterShape,this.dispatchLayout=me(e.outShape),this.dispatch=de(this.dispatchLayout,e.outShape,this.workgroupSize),a!=="float32"&&a!=="int32")throw new Error(`Dilation2DBackpropFilter only supports float32 and int32
types, does not support ${a} type.`);this.type=a,this.shaderKey="dilation2DBackpropFilter"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.dySize) {
let coords = getDyCoordsFromIndex(index);
let b = coords[0];
let r = coords[1];
let c = coords[2];
let d = coords[3];
let dyCorner = vec2<i32>(r, c) * uniforms.strides - uniforms.pads;
var curVal = -3.4e38; // neg_infinity
var wRMax = 0;
var wCMax = 0;
// In the case of multiple argmax branches, we only back-propagate
// along the last branch, i.e., the one with largest value of
// 'wR * uniforms.filterDims[1] + wC', similarly to the max-pooling
// backward routines.
for (var wR = 0; wR < uniforms.filterDims[0]; wR++) {
let xR = dyCorner.x + wR * uniforms.dilations[0];
if (xR >= 0 && xR < uniforms.xShape[1]) {
for (var wC = 0; wC < uniforms.filterDims[1]; wC++) {
let xC = dyCorner.y + wC * uniforms.dilations[1];
if (xC >= 0 && xC < uniforms.xShape[2]) {
let val = getX(b, xR, xC, d) + getW(wR, wC, d);
if (val > curVal) {
curVal = val;
wRMax = wR;
wCMax = wC;
}
}
}
}
}
let flatIndexIn = d + uniforms.wShape[2] * (wCMax + wRMax * uniforms.wShape[1]);
let value = getDy(b, r, c, d);
${xs("&result[flatIndexIn]","value",this.type)}
}
}
`}};function She(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=n,p=C.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),c=s.dtype,d=new Ihe(p,s.shape,c),h=[{type:"int32",data:[p.filterHeight,p.filterWidth]},{type:"int32",data:[p.padInfo.top,p.padInfo.left]},{type:"int32",data:[p.strideHeight,p.strideWidth]},{type:"int32",data:[p.dilationHeight,p.dilationWidth]},{type:"int32",data:[v.sizeFromShape(p.outShape)]}],m=Wa({backend:a,attrs:{shape:s.shape,value:0,dtype:c}});return a.runWebGPUProgram(d,[r,s,i],c,h,m)}var Che={kernelName:Xl,backendName:"webgpu",kernelFunc:She};function The(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=n,p=C.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),c=r.dtype,d=new khe(p,c),h=[{type:"int32",data:[p.filterHeight,p.filterWidth]},{type:"int32",data:[p.padInfo.top,p.padInfo.left]},{type:"int32",data:[p.strideHeight,p.strideWidth]},{type:"int32",data:[p.dilationHeight,p.dilationWidth]},{type:"int32",data:[v.sizeFromShape(p.outShape)]}],m=Wa({backend:a,attrs:{shape:p.inShape,value:0,dtype:c}});return a.runWebGPUProgram(d,[r,s,i],c,h,m)}var Nhe={kernelName:ql,backendName:"webgpu",kernelFunc:The},Rhe=class{constructor(e,t,a){this.variableNames=["Image"],this.uniforms="alpha: f32,",this.workgroupSize=[64,1,1],this.pixelsOpType=nu.DRAW,this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.type=t,this.textureFormat=a,this.shaderKey=`draw_${t}_${a}`}getUserCode(){let e,t=this.type==="float32"?"value":"value / 255.0";return e=`
if (uniforms.numChannels == 1) {
rgba[0] = ${t};
rgba[1] = ${t};
rgba[2] = ${t};
} else {
rgba[d] = ${t};
}`,`
@group(0) @binding(0) var outImage : texture_storage_2d<${this.textureFormat}, write>;
${ue("index")} {
if (index < uniforms.size) {
var rgba = vec4<f32>(0.0, 0.0, 0.0, uniforms.alpha);
for (var d = 0; d < uniforms.numChannels; d = d + 1) {
let value = f32(inBuf[index * uniforms.numChannels + d]);
${e}
}
rgba.x = rgba.x * rgba.w;
rgba.y = rgba.y * rgba.w;
rgba.z = rgba.z * rgba.w;
let coords = getCoordsFromIndex(index);
textureStore(outImage, vec2<i32>(coords.yx), rgba);
}
}
`}};function Ehe(e){let{inputs:t,backend:a,attrs:n}=e,{image:r}=t,{canvas:s,options:i}=n,[o,l]=r.shape.slice(0,2),{imageOptions:u}=i||{},p=(u==null?void 0:u.alpha)||1,c=a.device.features.has("bgra8unorm-storage")?"bgra8unorm":"rgba8unorm",d=[o,l],h=new Rhe(d,r.dtype,c);s.width=l,s.height=o;let m="webgpu",f=s.getContext(m),g;f||(g=new OffscreenCanvas(l,o),f=g.getContext(m));let y=r.shape.length===3?r.shape[2]:1;f.configure({device:a.device,format:c,usage:GPUTextureUsage.STORAGE_BINDING,alphaMode:"premultiplied"});let x="int32",A=a.makeTensorInfo(d,x),b=a.tensorMap.get(A.dataId);b.resource=f.getCurrentTexture(),b.external=!0;let w=[{type:"uint32",data:[y]},{type:"float32",data:[p]}];if(a.runWebGPUProgram(h,[r],x,w,A),g){let I=s.getContext("2d");if(!I)throw new Error("Please make sure this canvas has only been used for 2d or webgpu context!");I.drawImage(g,0,0)}return a.disposeData(A.dataId),r}var Mhe={kernelName:yp,backendName:"webgpu",kernelFunc:Ehe},Uk=ta({opType:Pe.MUL,cpuKernelImpl:Dde,supportsComplex:!0}),$he={kernelName:yo,backendName:"webgpu",kernelFunc:Uk};function Gk(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return dl(r,s,i,"sum",a)}var Phe={kernelName:Go,backendName:"webgpu",kernelFunc:Gk};function _he(e){let{inputs:t,backend:a,attrs:n}=e,{equation:r}=n,s=t,{allDims:i,summedDims:o,idDims:l}=C.decodeEinsumEquation(r,s.length);C.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:p}=C.getEinsumComputePath(o,l),c=p.length,d=null,h=i.length,m=[];for(let f=0;f<c;++f){for(let g of p[f]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=s[g]:(A=rr({inputs:{x:s[g]},backend:a,attrs:{perm:y}}),m.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=ke({inputs:{x:A},backend:a,attrs:{shape:b}}),m.push(A)),d===null?d=A:(d=Uk({inputs:{a:A,b:d},backend:a}),m.push(d))}f<c-1&&(u[f]>=0&&(d=Gk({inputs:{x:d},backend:a,attrs:{axis:u[f]-(i.length-h),keepDims:!1}}),m.push(d)),h--)}for(let f of m)f!==d&&a.disposeData(f.dataId);return d}var Fhe={kernelName:xp,backendName:"webgpu",kernelFunc:_he},Dhe=at({opType:le.ELU}),Ohe={kernelName:Fi,backendName:"webgpu",kernelFunc:Dhe},zhe=e=>{let{inputs:t,backend:a}=e,{dy:n,y:r}=t,s=new Th(Pe.ELU_DER,n.shape,r.shape);return a.runWebGPUProgram(s,[n,r],n.dtype)},Lhe={kernelName:xu,backendName:"webgpu",kernelFunc:zhe},Whe=ta({opType:Pe.EQUAL,dtype:"bool",cpuKernelImpl:vde}),Bhe={kernelName:Oi,backendName:"webgpu",kernelFunc:Whe},Vhe=at({opType:le.ERF}),Uhe={kernelName:Di,backendName:"webgpu",kernelFunc:Vhe},Ghe=at({opType:le.EXP,cpuKernelImpl:wde,dtype:"float32"}),Hhe={kernelName:zi,backendName:"webgpu",kernelFunc:Ghe};function Y1(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)}, ${i}]`),l=i+r+1),o.splice(l,0,1),ke({inputs:{x:s},backend:n,attrs:{shape:o}})}var jhe={kernelName:Au,backendName:"webgpu",kernelFunc:Y1},qhe=at({opType:le.EXPM1,cpuKernelImpl:kde}),Xhe={kernelName:Li,backendName:"webgpu",kernelFunc:qhe},pA=class{constructor(e,t){this.variableNames=["real","imag"],this.outputShape=[],this.uniforms="exponentMultiplier : f32, denominator: f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.component=e,this.shaderKey=`fft_${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;
}
${ue("index")} {
if (index < uniforms.size) {
let coords = getOutputCoords();
setOutputAtIndex(index, mulMatDFT(coords[0], coords[1]));
}
}
`}};function Hk(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=ke({inputs:{x:e},backend:a,attrs:{shape:[i,s]}});o.push(l);let u=l.shape,p=new pA("real",u),c=new pA("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,m=t?u[1]:1,f=[{type:"float32",data:[h]},{type:"float32",data:[m]}],g=a.runWebGPUProgram(p,d,"float32",f);o.push(g);let y=a.runWebGPUProgram(c,d,"float32",f);o.push(y);let x=ul({inputs:{real:g,imag:y},backend:a});o.push(x);let A=ke({inputs:{x},backend:a,attrs:{shape:e.shape}});return o.forEach(b=>a.disposeData(b.dataId)),A}function Khe(e){let{inputs:t,backend:a}=e,{input:n}=t;return Hk(n,!1,a)}var Yhe={kernelName:Ap,backendName:"webgpu",kernelFunc:Khe},Zhe=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="flipLeftRight"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let coordX = uniforms.xShape[2] - coords[2] - 1;
let outputValue = getX(coords[0], coords[1], coordX, coords[3]);
setOutputAtIndex(index, outputValue);
}
}
`}},Jhe={kernelName:Wi,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{image:a}=e,n=t,r=new Zhe(a.shape);return n.runWebGPUProgram(r,[a],a.dtype)}},Qhe=at({opType:le.FLOOR,cpuKernelImpl:Ide}),e0e={kernelName:Bi,backendName:"webgpu",kernelFunc:Qhe},t0e=ta({opType:Pe.FLOOR_DIV,cpuKernelImpl:Sde,dtype:"int32"}),a0e={kernelName:Vi,backendName:"webgpu",kernelFunc:t0e},n0e=class{constructor(e,t,a=!1){this.pixelsOpType=nu.FROM_PIXELS,this.outputShape=[0],this.variableNames=[],this.workgroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[t,1,1]),this.importVideo=a,this.shaderKey=`fromPixels_${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>"};
${ue("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]));
}
}
}
`}},r0e={kernelName:Wd,backendName:"webgpu",kernelFunc:s0e},Dl,e1=B().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function s0e(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=B().getBool("WEBGPU_IMPORT_EXTERNAL_TEXTURE")&&i,m=i||o;if(u||l||m){let x;if(h)x=a.device.importExternalTexture({source:r});else{if(m){let S=B().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(Dl==null||S!==e1)&&(e1=S,Dl=document.createElement("canvas").getContext("2d",{willReadFrequently:e1})),Dl.canvas.width=p,Dl.canvas.height=c,Dl.drawImage(r,0,0,p,c),r=Dl.canvas}let $=GPUTextureUsage.COPY_DST|GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING,E=a.textureManager.acquireTexture(d[1],d[0],"rgba8unorm",$);a.queue.copyExternalImageToTexture({source:r},{texture:E},[d[1],d[0]]),x=E}let A=v.sizeFromShape(d),b=v.computeStrides(d),w=new n0e(d,s,h),I=[{type:"uint32",data:[A]},{type:"uint32",data:[s]},{type:"uint32",data:[...b]}],T=a.makeTensorInfo([c,p],"int32"),N=a.tensorMap.get(T.dataId);N.resource=x;let M=a.runWebGPUProgram(w,[T],"int32",I);return a.disposeData(T.dataId),M}let f=r.data,g=f;if(s!=null&&s!==4){g=new Uint8Array(r.width*r.height*s);let x=f.length,A=0;for(let b=0;b<x;b++)b%4<s&&(g[A++]=f[b])}let y=a.makeTensorInfo(d,"int32",new Int32Array(g));return a.uploadToGPU(y.dataId),y}var i0e=class{constructor(e,t,a,n,r){this.uniforms="varianceEpsilon : f32,",this.workgroupSize=[128,1,1],this.size=!0,this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,a),this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),n!=null&&(C.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset")),r!=null&&(C.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)"),`
${ue("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)));
}
}
`}},o0e={kernelName:Ui,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 i0e(n.shape,i.shape,o.shape,c,d),m=[{type:"float32",data:[l]}];return u.runWebGPUProgram(h,p,n.dtype,m)}};function l0e(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:m}=n,f=C.convertConv2DDataFormat(p),g=C.computeConv2DInfo(r.shape,s.shape,l,c,u,d,!1,f);return Lk({x:r,filter:s,convInfo:g,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:m,activation:h})}var u0e={kernelName:Jr,backendName:"webgpu",kernelFunc:l0e};function d0e(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,m=p;m==null&&(m=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let f=C.computeConv2DInfo(r.shape,s.shape,l,m,u,c,!0),g=[r,s],y=i!=null,x=o!=null;y&&g.push(i),x&&g.push(o);let A=[{type:"int32",data:[f.padInfo.top,f.padInfo.left]},{type:"int32",data:[f.inHeight,f.inWidth]}],b;return f.outHeight>4&&f.outWidth>4&&f.strideWidth<=2&&f.inChannels===f.outChannels&&f.dilationHeight===1&&f.dilationWidth===1&&f.inChannels%4===0?(b=new Bk(f,y,d,x),A.push({type:"int32",data:[b.virtualWidth]})):(b=new Vk(f,y,d,x),A.push({type:"int32",data:[f.filterHeight]},{type:"int32",data:[f.filterWidth]},{type:"int32",data:[f.strideHeight,f.strideWidth]},{type:"int32",data:[f.dilationHeight,f.dilationWidth]})),d==="leakyrelu"&&(A.push({type:"float32",data:[h]}),b.uniforms+=" alpha : f32,"),a.runWebGPUProgram(b,g,"float32",A)}var p0e={kernelName:Qr,backendName:"webgpu",kernelFunc:d0e},c0e=class{constructor(e,t){this.variableNames=["A","indices"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`gathernd_${e}`,this.sliceDim=e,this.uniforms=`sliceDim : i32, strides : ${Pt(e)},`}getUserCode(){let e;return this.sliceDim>1?e="uniforms.strides[j]":e="uniforms.strides",`
${ue("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 h0e(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]=C.prepareAndValidate(n,r),d=ke({inputs:{x:r},backend:a,attrs:{shape:[u,i]}}),h=ke({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),b=Cde(x,A,n.dtype,u,i,p,c,n.shape,o);return a.makeTensorInfo(l,n.dtype,b.values)}let m=new c0e(i,[u,p]),f=[{type:"int32",data:[i]},{type:"int32",data:c}],g=a.runWebGPUProgram(m,[h,d],h.dtype,f),y=ke({inputs:{x:g},backend:a,attrs:{shape:l}});return a.disposeData(d.dataId),a.disposeData(h.dataId),a.disposeData(g.dataId),y}var m0e={kernelName:Gi,backendName:"webgpu",kernelFunc:h0e},f0e=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=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="gather"}getUserCode(){let e=g0e(this.aShape);return`
${ue("index")} {
if (index < uniforms.size) {
let resRC = getCoordsFromIndex(index);
let indexZ = i32(getIndices(resRC.x, resRC.z));
let inBounds = select(0.0, 1.0, indexZ >= 0 && indexZ < uniforms.aShape[2]);
setOutputAtIndex(index, inBounds * getA(${e}));
}
}
`}};function g0e(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 jk(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=C.segment_util.collectGatherOpShapeInfo(r,s,l,o),p=v.sizeFromShape(s.shape),c=[],d=ke({inputs:{x:r},backend:a,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=ke({inputs:{x:s},backend:a,attrs:{shape:[u.batchSize,p/u.batchSize]}});c.push(d),c.push(h);let m=[u.batchSize,u.outerSize,p/u.batchSize,u.sliceSize];if(a.shouldExecuteOnCPU([r,s])){let x=a.tensorMap.get(h.dataId).values,A=_e(h.shape,h.dtype,x),b=a.tensorMap.get(d.dataId).values,w=_e(d.shape,d.dtype,b),I=Tde(w,A,m);return c.forEach(T=>a.disposeData(T.dataId)),a.makeTensorInfo(u.outputShape,I.dtype,I.values)}let f=new f0e(d.shape,m),g=a.runWebGPUProgram(f,[d,h],d.dtype);c.push(g);let y=ke({inputs:{x:g},backend:a,attrs:{shape:u.outputShape}});return c.forEach(x=>a.disposeData(x.dataId)),y}var y0e={kernelName:vu,backendName:"webgpu",kernelFunc:jk},x0e=ta({opType:Pe.GREATER,cpuKernelImpl:Rde,dtype:"bool"}),A0e={kernelName:Hi,backendName:"webgpu",kernelFunc:x0e},b0e=ta({opType:Pe.GREATER_EQUAL,dtype:"bool",cpuKernelImpl:Nde}),v0e={kernelName:ji,backendName:"webgpu",kernelFunc:b0e};function w0e(e){let{inputs:t,backend:a}=e,{input:n}=t;return Hk(n,!0,a)}var k0e={kernelName:bp,backendName:"webgpu",kernelFunc:w0e},I0e=at({opType:le.IS_FINITE,dtype:"bool"}),S0e={kernelName:Xi,backendName:"webgpu",kernelFunc:I0e},C0e=at({opType:le.IS_INF,dtype:"bool"}),T0e={kernelName:Ki,backendName:"webgpu",kernelFunc:C0e},N0e=at({opType:le.IS_NAN,dtype:"bool"}),R0e={kernelName:Yi,backendName:"webgpu",kernelFunc:N0e};function E0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{alpha:s}=n,i=[{type:"float32",data:[s]}],o=new td(r.shape,le.LEAKYRELU,"alpha : f32,");return a.runWebGPUProgram(o,[r],"float32",i)}var M0e={kernelName:Zi,backendName:"webgpu",kernelFunc:E0e},$0e=ta({opType:Pe.LESS,dtype:"bool",cpuKernelImpl:Mde}),P0e={kernelName:Ji,backendName:"webgpu",kernelFunc:$0e},_0e=ta({opType:Pe.LESS_EQUAL,dtype:"bool",cpuKernelImpl:Ede}),F0e={kernelName:Qi,backendName:"webgpu",kernelFunc:_0e},D0e=class{constructor(e){this.variableNames=[],this.outputShape=[],this.uniforms="start : f32, step : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="linSpace"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
setOutputAtIndex(index, uniforms.start + f32(index) * uniforms.step);
}
}
`}};function O0e(e){let{backend:t,attrs:a}=e,{start:n,stop:r,num:s}=a,i=(r-n)/(s-1),o=new D0e(s),l=[{type:"float32",data:[n]},{type:"float32",data:[i]}];return t.runWebGPUProgram(o,[],"float32",l)}var z0e={kernelName:eo,backendName:"webgpu",kernelFunc:O0e},L0e=at({opType:le.LOG,cpuKernelImpl:$de}),W0e={kernelName:to,backendName:"webgpu",kernelFunc:L0e},B0e=at({opType:le.LOG1P}),V0e={kernelName:ao,backendName:"webgpu",kernelFunc:B0e},U0e=ta({opType:Pe.LOGICAL_AND,dtype:"bool"}),G0e={kernelName:no,backendName:"webgpu",kernelFunc:U0e},H0e=at({opType:le.LOGICAL_NOT}),j0e={kernelName:ro,backendName:"webgpu",kernelFunc:H0e},q0e=ta({opType:Pe.LOGICAL_OR}),X0e={kernelName:so,backendName:"webgpu",kernelFunc:q0e},qk=`
var powValue = 0.0;
let basis = uniforms.bias + uniforms.alpha * sum;
if (uniforms.beta == 0.5) {
powValue = inverseSqrt(basis);
} else if (uniforms.beta == 1.0) {
powValue = 1.0 / basis;
} else {
powValue = exp(log(basis) * (-uniforms.beta));
}
`,K0e=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.uniforms="radius : i32, bias : f32, alpha : f32, beta : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="lrn"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getOutputCoords();
let b = coords[0];
let r = coords[1];
let c = coords[2];
let d = coords[3];
let x = getX(b, r, c, d);
var sum = 0.0;
for (var i = -uniforms.radius; i <= uniforms.radius; i = i + 1) {
let idx = d + i;
if (idx >= 0 && idx < uniforms.xShape[3]) {
let z = getX(b, r, c, idx);
sum = sum + z * z;
}
}
${qk}
setOutputAtIndex(index, x * powValue);
}
}
`}},Y0e=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.uniforms="radius : i32, bias : f32, alpha : f32, beta : f32,",this.workgroupSize=[256,1,1],this.maxAllowRadius=16,v.assert(t<=this.maxAllowRadius,()=>`Radius must be less than or equal to ${this.maxAllowRadius}, current radius is ${t}`),this.outputShape=e,this.elementsPerWorkgroup=this.workgroupSize[0]-2*this.maxAllowRadius,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=de(this.dispatchLayout,this.outputShape,[this.elementsPerWorkgroup,this.workgroupSize[1],this.workgroupSize[2]]),this.shaderKey="lrn_shared"}getUserCode(){return`
var <workgroup>lrnSub: array<f32, ${this.workgroupSize[0]}>;
const elementsPerWorkgroup = ${this.elementsPerWorkgroup};
const maxAllowRadius = ${this.maxAllowRadius};
${ue()} {
let localDepth = i32(localId.x);
let workgroupDepth = i32(workgroupId.x) * elementsPerWorkgroup;
let xDepth = workgroupDepth + localDepth - maxAllowRadius;
let b = i32(globalId.z) / uniforms.xShape[1];
let r = i32(globalId.z) - b * uniforms.xShape[1];
let c = i32(globalId.y);
let d = workgroupDepth + localDepth;
var x = 0.0;
if (xDepth >= 0 && xDepth < uniforms.xShape[3]) {
x = getX(b, r, c, xDepth);
}
lrnSub[localDepth] = x;
workgroupBarrier();
if (localDepth < elementsPerWorkgroup && d < uniforms.outShape[3]) {
var sum = 0.0;
let index = localDepth + maxAllowRadius;
for (var i = -uniforms.radius; i <= uniforms.radius; i = i + 1) {
let z = lrnSub[index + i];
sum = sum + z * z;
}
${qk}
setOutputAtCoords(b, r, c, d, lrnSub[index] * powValue);
}
} `}};function Z0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n,u;s>16?u=new K0e(r.shape):u=new Y0e(r.shape,s);let p=[{type:"int32",data:[s]},{type:"float32",data:[i]},{type:"float32",data:[o]},{type:"float32",data:[l]}];return a.runWebGPUProgram(u,[r],r.dtype,p)}var J0e={kernelName:io,backendName:"webgpu",kernelFunc:Z0e},Q0e=class{constructor(e){this.outputShape=[],this.variableNames=["inputImage","outputImage","dy"],this.uniforms="depthRadius : i32, bias : f32, alpha : f32, beta : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="lrn_grad"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getOutputCoords();
let b = coords[0];
let r = coords[1];
let c = coords[2];
let MIN_DEPTH_BEGIN = 0;
let MAX_DEPTH_END = uniforms.outShape[3];
var result = 0.0;
for (var d = MIN_DEPTH_BEGIN; d < MAX_DEPTH_END; d++) {
let depthBegin = max(MIN_DEPTH_BEGIN, d - uniforms.depthRadius);
let depthEnd = min(MAX_DEPTH_END, d + uniforms.depthRadius + 1);
var norm = 0.0;
for (var 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 = uniforms.alpha * norm + uniforms.bias;
for (var k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; k++) {
if (k < depthBegin) {
continue;
} else if (k >= depthBegin && k < depthEnd) {
var dyi = -2.0 * uniforms.alpha * uniforms.beta
* getInputImage(b, r, c, k) * getOutputImage(b, r, c, d) / norm;
if (k == d) {
dyi += pow(norm, -1.0 * uniforms.beta);
}
if (k == coords[3]) {
dyi *= getDy(b, r, c, d);
result += dyi;
}
} else {
break;
}
}
}
setOutputAtIndex(index, result);
}
}
`}};function eme(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 Q0e(r.shape),d=[{type:"int32",data:[o]},{type:"float32",data:[l]},{type:"float32",data:[u]},{type:"float32",data:[p]}];return a.runWebGPUProgram(c,[r,s,i],r.dtype,d)}var tme={kernelName:wu,backendName:"webgpu",kernelFunc:eme},ame=ta({opType:Pe.MAX,cpuKernelImpl:_de}),nme={kernelName:lo,backendName:"webgpu",kernelFunc:ame};function rme(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=C.computePool2DInfo(r.shape,s,i,1,o,l);return Fk(r,u,"max",a)}var sme={kernelName:uo,backendName:"webgpu",kernelFunc:rme};function ime(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=C.computePool3DInfo(r.shape,s,i,p,o,u,l),d=new Z3(c,"max"),h=[{type:"int32",data:[c.strideDepth,c.strideHeight,c.strideWidth]},{type:"int32",data:[c.padInfo.front,c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.inDepth,c.inHeight,c.inWidth]},{type:"int32",data:[c.effectiveFilterDepth,c.effectiveFilterHeight,c.effectiveFilterWidth]}];return a.runWebGPUProgram(d,[r],r.dtype,h)}var ome={kernelName:ku,backendName:"webgpu",kernelFunc:ime},lme=class{constructor(e){this.variableNames=["dy","maxPos"],this.uniforms=`strides : vec2<i32>, pads : vec2<i32>, dilations : vec2<i32>, filterDims : vec2<i32>,
outHeight : i32, outWidth : i32`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="maxPool2DBackprop"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords[0];
let d = coords[3];
let dyRCCorner = vec2<i32>(coords.yz) - uniforms.pads;
let dyRCorner = dyRCCorner.x;
let 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.
var dotProd = 0.0;
let lastIndex = uniforms.filterDims[0] * uniforms.filterDims[1] - 1;
for (var wR = 0; wR < uniforms.filterDims[0]; wR += uniforms.dilations[0]) {
let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[0]);
if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) {
continue;
}
let idyR = i32(dyR);
for (var wC = 0; wC < uniforms.filterDims[1]; wC += uniforms.dilations[1]) {
let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[1]);
if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) {
continue;
}
let idyC = i32(dyC);
let dyValue = getDy(batch, idyR, idyC, d);
let maxPosValue = lastIndex - i32(getMaxPos(batch, idyR, idyC, d));
// Get the current value, check it against the value from the
// position matrix.
let curPosValue = wR * uniforms.filterDims[1] + wC;
let mask = select(0.0, 1.0, maxPosValue == curPosValue);
dotProd += dyValue * mask;
}
}
setOutputAtIndex(index, dotProd);
}
}
`}},ume=class{constructor(e){this.variableNames=["dy","maxPos"],this.uniforms=`strides : vec3<i32>, pads : vec3<i32>, filterDims : vec3<i32>,
outDepth : i32, outHeight : i32, outWidth : i32`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="maxPool3DBackprop"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords.x;
let ch = coords.u;
let dyCorner = vec3<i32>(coords.y, coords.z, coords.w) - uniforms.pads;
let dyDCorner = dyCorner.x;
let dyRCorner = dyCorner.y;
let 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.
var dotProd = 0.0;
let lastIndex = uniforms.filterDims[0] * uniforms.filterDims[1] * uniforms.filterDims[2] - 1;
for (var wD = 0; wD < uniforms.filterDims[0]; wD++) {
let dyD = f32(dyDCorner + wD) / f32(uniforms.strides[0]);
if (dyD < 0.0 || dyD >= f32(uniforms.outDepth) || fract(dyD) > 0.0) {
continue;
}
let idyD = i32(dyD);
for (var wR = 0; wR < uniforms.filterDims[1]; wR++) {
let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[1]);
if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) {
continue;
}
let idyR = i32(dyR);
for (var wC = 0; wC < uniforms.filterDims[2]; wC++) {
let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[2]);
if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) {
continue;
}
let idyC = i32(dyC);
let dyValue = getDy(batch, idyD, idyR, idyC, ch);
let maxPosValue = lastIndex - i32(getMaxPos(batch, idyD, idyR, idyC, ch));
// Get the current value, check it against the value from the
// position matrix.
let curPosValue = wD * uniforms.filterDims[1] * uniforms.filterDims[2] + wR * uniforms.filterDims[2] + wC;
let mask = select(0.0, 1.0, maxPosValue == curPosValue);
dotProd += dyValue * mask;
}
}
}
setOutputAtIndex(index, dotProd);
}
}
`}};function dme(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=C.computePool3DInfo(i.shape,o,l,c,u,p),h=new Z3(d,"max",!0),m=[{type:"int32",data:[d.strideDepth,d.strideHeight,d.strideWidth]},{type:"int32",data:[d.padInfo.front,d.padInfo.top,d.padInfo.left]},{type:"int32",data:[d.inDepth,d.inHeight,d.inWidth]},{type:"int32",data:[d.effectiveFilterDepth,d.effectiveFilterHeight,d.effectiveFilterWidth]}],f=a.runWebGPUProgram(h,[i],"int32",m),g=new ume(d);m=[{type:"int32",data:[d.strideDepth,d.strideHeight,d.strideWidth]},{type:"int32",data:[d.effectiveFilterDepth-1-d.padInfo.front,d.effectiveFilterHeight-1-d.padInfo.top,d.effectiveFilterWidth-1-d.padInfo.left]},{type:"int32",data:[d.effectiveFilterDepth,d.effectiveFilterHeight,d.effectiveFilterWidth]},{type:"int32",data:[d.outDepth]},{type:"int32",data:[d.outHeight]},{type:"int32",data:[d.outWidth]}];let y=a.runWebGPUProgram(g,[r,f],i.dtype,m);return a.disposeData(f.dataId),y}var pme={kernelName:kp,backendName:"webgpu",kernelFunc:dme};function cme(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s,output:i}=t,o=s;q3([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:p,dimRoundingMode:c}=n,d=C.computePool2DInfo(o.shape,l,u,1,p,c),h=new sp(d,"max",!0),m=[{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.padInfo.top,d.padInfo.left]},{type:"int32",data:[d.dilationHeight,d.dilationWidth]},{type:"int32",data:[d.inHeight,d.inWidth]},{type:"int32",data:[d.effectiveFilterHeight,d.effectiveFilterWidth]}],f=a.runWebGPUProgram(h,[o],"int32",m),g=new lme(d);m=[{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.effectiveFilterHeight-1-d.padInfo.top,d.effectiveFilterWidth-1-d.padInfo.left]},{type:"int32",data:[d.dilationHeight,d.dilationWidth]},{type:"int32",data:[d.effectiveFilterHeight,d.effectiveFilterWidth]},{type:"int32",data:[d.outHeight]},{type:"int32",data:[d.outWidth]}];let y=a.runWebGPUProgram(g,[r,f],o.dtype,m);return a.disposeData(f.dataId),y}var hme={kernelName:wp,backendName:"webgpu",kernelFunc:cme};function mme(e){let{inputs:t,backend:a,attrs:n}=e,{filterSize:r,strides:s,pad:i,includeBatchInIndex:o}=n,{x:l}=t;v.assert(l.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${l.shape.length}.`);let u=[1,1];v.assert(C.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let p=C.computePool2DInfo(l.shape,r,s,u,i),c=[{type:"int32",data:[p.strideHeight,p.strideWidth]},{type:"int32",data:[p.padInfo.top,p.padInfo.left]},{type:"int32",data:[p.dilationHeight,p.dilationWidth]},{type:"int32",data:[p.inHeight,p.inWidth]},{type:"int32",data:[p.effectiveFilterHeight,p.effectiveFilterWidth]}],d=new sp(p,"max",!1),h=a.runWebGPUProgram(d,[l],l.dtype,c);d=new sp(p,"max",!0,!0,o);let m=a.runWebGPUProgram(d,[l],"int32",c);return[h,m]}var fme={kernelName:Iu,backendName:"webgpu",kernelFunc:mme};function gme(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return dl(r,s,i,"min",a)}var yme={kernelName:co,backendName:"webgpu",kernelFunc:gme},xme=ta({opType:Pe.MIN,cpuKernelImpl:Fde}),Ame={kernelName:ho,backendName:"webgpu",kernelFunc:xme},bme=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=me(this.outputShape),this.dispatch=de(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=Pt(e),o=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
${ue("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}));
}
}
`}},vme={kernelName:mo,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 bme(n.shape,r,s);return i.runWebGPUProgram(l,[n],n.dtype,o)}},wme=ta({opType:Pe.MOD}),kme={kernelName:fo,backendName:"webgpu",kernelFunc:wme},Ime=class{constructor(e,t){this.variableNames=["probs"],this.outputShape=[],this.uniforms="seed : f32, numOutcomes: i32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e,t],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="multinomial"}getUserCode(){return`
//Based on the work of Dave Hoskins
//https://www.shadertoy.com/view/4djSRW
fn random (seed : f32, resultUV : vec2<f32>) -> f32 {
let HASHSCALE1 = 443.8975;
let p = resultUV * seed;
var p3 = fract(vec3<f32>(p.xyx) * HASHSCALE1);
p3 = p3 + dot(p3, p3.yzx + 19.19);
return fract((p3.x + p3.y) * p3.z);
}
${ue("index")} {
if (index < uniforms.size) {
let coords = getOutputCoords();
let batch = coords[0];
let resUV = vec2<f32>(f32(coords[1]) / f32(uniforms.outShape[1]),
f32(coords[0]) / f32(uniforms.outShape[0]));
let r = random(uniforms.seed, resUV);
var cdf = 0.0;
for (var i = 0; i < uniforms.numOutcomes - 1; i = i + 1) {
cdf = cdf + getProbs(batch, i);
if (r < cdf) {
setOutputAtIndexI32(index, i);
return;
}
}
// If no other event happened, last event happened.
setOutputAtIndexI32(index, uniforms.numOutcomes - 1);
}
}
`}},Sme=class{constructor(e){this.variableNames=["logits"],this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=[this.outputShape[0],1,1],this.outputShape[1]>=4096?this.workgroupSize=[256,1,1]:this.workgroupSize=[64,1,1],this.shaderKey="softmax"}getUserCode(){return`
var<workgroup> buf : array<f32, ${this.workgroupSize[0]}>;
var<workgroup> rowMaxShared : f32;
var<workgroup> rowSumShared : f32;
const blockSize = ${this.workgroupSize[0]};
${ue("index")} {
let row = index / blockSize;
let tid = i32(localId.x);
let cols = uniforms.outShape[1];
var threadMax = -3.402823e+38f;
for (var col = tid; col < cols; col += blockSize) {
let value = getLogits(row, col);
threadMax = max(threadMax, value);
}
if (tid < cols) {
buf[tid] = threadMax;
}
workgroupBarrier();
var reduceSize = min(cols, blockSize);
for (var currSize = reduceSize >> 1; currSize > 0; currSize = reduceSize >> 1) {
reduceSize = currSize + (reduceSize & 1);
if (tid < currSize) {
buf[tid] = max(buf[tid], buf[tid + reduceSize]);
}
workgroupBarrier();
}
if (tid == 0) {
rowMaxShared = buf[0];
}
workgroupBarrier();
var threadSum = 0.0;
for (var col = tid; col < cols; col += blockSize) {
let subExp = exp(getLogits(row, col) - rowMaxShared);
threadSum += subExp;
}
buf[tid] = threadSum;
workgroupBarrier();
for (var currSize = blockSize >> 1; currSize > 0; currSize = currSize >> 1) {
if (tid < currSize) {
buf[tid] = buf[tid] + buf[tid + currSize];
}
workgroupBarrier();
}
if (tid == 0) {
rowSumShared = buf[0];
}
workgroupBarrier();
for (var col = tid; col < cols; col += blockSize) {
let value = exp(getLogits(row, col) - rowMaxShared) / rowSumShared;
setOutputAtCoords(row, col, value);
}
}
`}};function Xk(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{dim:s}=n,i=ke({inputs:{x:r},backend:a,attrs:{shape:[v.sizeFromShape(r.shape)/r.shape[s],r.shape[s]]}}),o=new Sme(i.shape),l=a.runWebGPUProgram(o,[i],r.dtype),u=ke({inputs:{x:l},backend:a,attrs:{shape:r.shape}});return a.disposeData(i.dataId),a.disposeData(l.dataId),u}var Cme={kernelName:Ho,backendName:"webgpu",kernelFunc:Xk};function Tme(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n,l=o?r:Xk({inputs:{logits:r},backend:a,attrs:{dim:r.shape.length-1}}),u=l.shape[0],p=l.shape[1],c=new Ime(u,s),d=[{type:"float32",data:[i]},{type:"int32",data:[p]}],h=a.runWebGPUProgram(c,[l],"int32",d);return o||a.disposeData(l.dataId),h}var Nme={kernelName:go,backendName:"webgpu",kernelFunc:Tme};function Rme(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])){let s=a.tensorMap.get(n.dataId),[i,o]=Ode(s.values,n.shape,n.dtype);return a.makeTensorInfo(o,n.dtype,i)}let r=new td(n.shape,le.NEG);return a.runWebGPUProgram(r,[n],n.dtype)}var Eme={kernelName:Su,backendName:"webgpu",kernelFunc:Rme};function Mme(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}=En.nonMaxSuppressionV3Impl(u,p,i,o,l);return a.makeTensorInfo([c.length],"int32",new Int32Array(c))}var $me={kernelName:Ao,backendName:"webgpu",kernelFunc:Mme};function Pme(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,m=l,f=u,{selectedIndices:g,selectedScores:y}=En.nonMaxSuppressionV5Impl(p,c,d,h,m,f);return[a.makeTensorInfo([g.length],"int32",new Int32Array(g)),a.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var _me={kernelName:bo,backendName:"webgpu",kernelFunc:Pme},Fme=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=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="onehot"}getUserCode(){return`
${ue("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 Dme(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 Fme(u,i),c=ke({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 m=[...r.shape,i],f=ke({inputs:{x:h},backend:a,attrs:{shape:m}});return a.disposeData(h.dataId),f}var Ome={kernelName:vo,backendName:"webgpu",kernelFunc:Dme};function Rh(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="complex64"){let r=tc({inputs:{input:n},backend:a}),s=Rh({inputs:{x:r},backend:a}),i=h0({inputs:{input:n},backend:a}),o=Rh({inputs:{x:i},backend:a}),l=ul({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 Wa({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:a})}var zme={kernelName:Vu,backendName:"webgpu",kernelFunc:Rh};function Kk(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=tc({inputs:{input:n},backend:a}),s=Kk({inputs:{x:r},backend:a}),i=h0({inputs:{input:n},backend:a}),o=Rh({inputs:{x:i},backend:a}),l=ul({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 Wa({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:a})}var Lme={kernelName:Tu,backendName:"webgpu",kernelFunc:Kk};function Wme(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return Y1({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=Y1({inputs:{input:p},backend:a,attrs:{dim:r}});return o.push(c),c}),u=zk({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(p=>a.disposeData(p.dataId)),u}var Bme={kernelName:Nu,backendName:"webgpu",kernelFunc:Wme};function Yk(e,t=!1){let a=e.length,n=Pt(a),r=e.map((c,d)=>`uniforms.pad${d}[0]`).join(","),s=e.map((c,d)=>`uniforms.pad${d}[0] + uniforms.xShape${a>1?`[${d}]`:""}`).join(","),i=a>1?`${n}(${r})`:`${r}`,o=a>1?`${n}(${s})`:`${s}`,l=a>1?"any(paddedCoords < start)":"paddedCoords < start",u=a>1?"any(paddedCoords >= end)":"paddedCoords >= end",p=a>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,a):"coords";return`
let start = ${i};
let end = ${o};
if (${l} || ${u}) {
setOutputAtIndex(index, ${t?0:"uniforms.constantValue"});
} else {
let coords = paddedCoords - start;
setOutputAtIndex(index, getX(${p}));
}
`}var Vme=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=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),t.map((a,n)=>{this.uniforms+=` pad${n} : vec2<i32>,`}),this.xShape=e,this.shaderKey="pad"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let paddedCoords = getCoordsFromIndex(index);
${Yk(this.xShape)}
}
}
`}},Ume=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 tn({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 Wa({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 Vme(r.shape,s);return a.runWebGPUProgram(l,[r],r.dtype,o)},Gme={kernelName:wo,backendName:"webgpu",kernelFunc:Ume},Hme=ta({opType:Pe.POW}),jme={kernelName:ko,backendName:"webgpu",kernelFunc:Hme};function qme(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t,s=new Th(Pe.PRELU,n.shape,r.shape);return a.runWebGPUProgram(s,[n,r],"float32")}var Xme={kernelName:Io,backendName:"webgpu",kernelFunc:qme};function Kme(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return dl(r,s,i,"prod",a)}var Yme={kernelName:So,backendName:"webgpu",kernelFunc:Kme},Zme=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=Wde(n,r,s,i);return t.makeTensorInfo([o.length],i,o)},Jme={kernelName:Ru,backendName:"webgpu",kernelFunc:Zme},Qme=ta({opType:Pe.DIV}),efe={kernelName:_i,backendName:"webgpu",kernelFunc:Qme},tfe=at({opType:le.RECIPROCAL}),afe={kernelName:Co,backendName:"webgpu",kernelFunc:tfe},nfe=at({opType:le.RELU}),rfe={kernelName:To,backendName:"webgpu",kernelFunc:nfe},sfe=at({opType:le.RELU6}),ife={kernelName:Eo,backendName:"webgpu",kernelFunc:sfe},ofe=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=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="resizeBilinear"}getUserCode(){return`
${ue("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 lfe(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 ofe(r.shape,l,u);return a.runWebGPUProgram(h,[r],"float32",d)}var ufe={kernelName:Ro,backendName:"webgpu",kernelFunc:lfe},dfe=class{constructor(e,t){this.variableNames=["dy"],this.uniforms=`effectiveXSize : vec2<i32>, effectiveYSize : vec2<i32>, heightScale : f32, widthScale : f32,
invHeightScale : f32, invWidthScale : f32, winHeight : i32, winWidth : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.alignCorners=t,this.shaderKey=`resizeBilinearBackprop_${t}`}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getOutputCoords();
let b = coords[0];
let d = coords[3];
let r = coords[1];
let c = coords[2];
var accumulator = 0.0;
// Compute bounds for where in dy we will look
let startRLerp = floor(f32(r) * uniforms.invHeightScale);
let startDyR = i32(startRLerp - f32(uniforms.winHeight / 2));
let startCLerp = floor(f32(c) * uniforms.invWidthScale);
let startDyC = i32(startCLerp - f32(uniforms.winWidth / 2));
// Loop over dy
for (var dyROffset = 0; dyROffset < uniforms.winHeight; dyROffset++) {
let dyR = startDyR + dyROffset;
// Guard against the window exceeding the bounds of dy
if (dyR < 0 || dyR >= uniforms.dyShape[1]) {
continue;
}
for (var dyCOffset = 0; dyCOffset < uniforms.winWidth; dyCOffset++) {
let dyC = startDyC + dyCOffset;
// Guard against the window exceeding the bounds of dy
if (dyC < 0 || dyC >= uniforms.dyShape[2]) {
continue;
}
let dxR = f32(dyR) * uniforms.heightScale;
let topDxRIndex = i32(floor(dxR));
let bottomDxRIndex = i32(min(ceil(dxR), f32(uniforms.outShape[1] - 1)));
let dxRLerp = dxR - f32(topDxRIndex);
let inverseDxRLerp = 1.0 - dxRLerp;
let dxC = f32(dyC) * uniforms.widthScale;
let leftDxCIndex = i32(floor(dxC));
let rightDxCIndex = i32(min(ceil(dxC), f32(uniforms.outShape[2] - 1)));
let dxCLerp = dxC - f32(leftDxCIndex);
let 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
setOutputAtIndex(index, accumulator);
}
}
`}};function pfe(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,[,o,l]=r.shape,[,u,p]=s.shape,c=[i&&u>1?o-1:o,i&&p>1?l-1:l],d=[i&&u>1?u-1:u,i&&p>1?p-1:p],h=c[0]/d[0],m=c[1]/d[1],f=1/h,g=1/m,y=Math.ceil(f)*2+2,x=Math.ceil(g)*2+2,A=new dfe(r.shape,i),b=[{type:"int32",data:c},{type:"int32",data:d},{type:"float32",data:[h]},{type:"float32",data:[m]},{type:"float32",data:[f]},{type:"float32",data:[g]},{type:"int32",data:[y]},{type:"int32",data:[x]}];return a.runWebGPUProgram(A,[s],s.dtype,b)}var cfe={kernelName:$u,backendName:"webgpu",kernelFunc:pfe},hfe=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=me(this.outputShape),this.dispatch=de(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",`
${ue("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 = ${e};
// Compute the coordinators of nearest neighbor point.
let inputShapeRC = vec2<f32>(f32(uniforms.xShape.y), f32(uniforms.xShape.z));
let sourceNearestRC = vec2<i32>(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + uniforms.roundBase)));
let newValue = getX(b, sourceNearestRC.x, sourceNearestRC.y, d);
setOutputAtIndex(index, newValue);
}
}
`}};function mfe(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,p=s&&l>1?1:0,c=s&&u>1?1:0,d=[{type:"float32",data:[p,c]},{type:"float32",data:[s?.5:0]}],h=new hfe(r.shape,l,u,i);return a.runWebGPUProgram(h,[r],r.dtype,d)}var ffe={kernelName:No,backendName:"webgpu",kernelFunc:mfe},gfe=class{constructor(e,t){this.variableNames=["dy"],this.uniforms=`effectiveXSize : vec2<i32>, effectiveYSize : vec2<i32>, invHeightScale : f32, invWidthScale : f32,
winHeight : i32, winWidth : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.alignCorners=t,this.shaderKey=`resizeNearestNeigborBackprop_${t}`}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let coords = getOutputCoords();
let b = coords[0];
let d = coords[3];
let r = coords[1];
let c = coords[2];
var accumulator = 0.0;
// Compute bounds for where in dy we will look
let startRLerp = floor(f32(r) * uniforms.invHeightScale);
let startDyR = i32(floor(startRLerp - f32(uniforms.winHeight / 2)));
let startCLerp = floor(f32(c) * uniforms.invWidthScale);
let startDyC = i32(floor(startCLerp - f32(uniforms.winWidth / 2)));
// Loop over dy
for (var dyROffset = 0; dyROffset < uniforms.winHeight; dyROffset++) {
let dyR = startDyR + dyROffset;
// Guard against the window exceeding the bounds of dy
if (dyR < 0 || dyR >= uniforms.dyShape[1]) {
continue;
}
for (var dyCOffset = 0; dyCOffset < uniforms.winWidth; dyCOffset++) {
let dyC = startDyC + dyCOffset;
// Guard against the window exceeding the bounds of dy
if (dyC < 0 || dyC >= uniforms.dyShape[2]) {
continue;
}
let sourceFracRow = f32(uniforms.effectiveXSize[0]) *
(f32(dyR) / f32(uniforms.effectiveYSize[0]));
let sourceFracCol = f32(uniforms.effectiveXSize[1]) *
(f32(dyC) / f32(uniforms.effectiveYSize[1]));
let sourceNearestRow =
i32(min(f32(uniforms.outShape[1] - 1),
${this.alignCorners?"floor(sourceFracRow + 0.5)":"floor(sourceFracRow)"}));
let sourceNearestCol =
i32(min(f32(uniforms.outShape[2] - 1),
${this.alignCorners?"floor(sourceFracCol + 0.5)":"floor(sourceFracCol)"}));
if (r == sourceNearestRow && c == sourceNearestCol) {
accumulator += getDy(b, dyR, dyC, d);
}
}
}
// End loop over dy
setOutputAtIndex(index, accumulator);
}
}
`}};function yfe(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,[,o,l]=r.shape,[,u,p]=s.shape,c=[i&&u>1?o-1:o,i&&p>1?l-1:l],d=[i&&u>1?u-1:u,i&&p>1?p-1:p],h=c[0]/d[0],m=c[1]/d[1],f=1/h,g=1/m,y=Math.ceil(f)*2+2,x=Math.ceil(g)*2+2,A=new gfe(r.shape,i),b=[{type:"int32",data:c},{type:"int32",data:d},{type:"float32",data:[f]},{type:"float32",data:[g]},{type:"int32",data:[y]},{type:"int32",data:[x]}];return a.runWebGPUProgram(A,[s],s.dtype,b)}var xfe={kernelName:Mu,backendName:"webgpu",kernelFunc:yfe},Afe=class{constructor(e){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(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;
}
${ue("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 bfe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dims:s}=n,i=r.shape.length;if(i===0)return tn({inputs:{x:r},backend:a});let o=r.shape,l=[1,1,1,1];o.forEach((g,y)=>{let x=y+4-i;l[x]=g});let u=v.parseAxisParam(s,r.shape),p=[0,0,0,0];u.forEach(g=>{let y=g+4-i;p[y]=1});let c=[{type:"int32",data:p}],d=ke({inputs:{x:r},backend:a,attrs:{shape:l}}),h=new Afe(l),m=a.runWebGPUProgram(h,[d],d.dtype,c);a.disposeData(d.dataId);let f=ke({inputs:{x:m},backend:a,attrs:{shape:o}});return a.disposeData(m.dataId),f}var vfe={kernelName:Mo,backendName:"webgpu",kernelFunc:bfe},wfe=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(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`
${ue("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));
${this.fillSnippet}
if(coordX >= 0 && coordX < uniforms.xShape[2] && coordY >= 0 &&
coordY < uniforms.xShape[1]) {
outputValue = getX(coords[0], coordY, coordX, coords[3]);
}
setOutputAtIndex(index, outputValue);
}
}
`}},kfe={kernelName:el,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{image:n}=e,{radians:r,fillValue:s,center:i}=t,o=a,l=new wfe(n.shape,s),[u,p]=C.getImageCenter(i,n.shape[1],n.shape[2]),c=[{type:"float32",data:[u]},{type:"float32",data:[p]},{type:"float32",data:[Math.sin(r)]},{type:"float32",data:[Math.cos(r)]}];return typeof s=="number"?c.push({type:"float32",data:[Number.parseFloat(s.toFixed(2))]}):c.push({type:"float32",data:s}),o.runWebGPUProgram(l,[n],n.dtype,c)}},Ife=at({opType:le.ROUND}),Sfe={kernelName:$o,backendName:"webgpu",kernelFunc:Ife},Cfe=at({opType:le.RSQRT,cpuKernelImpl:Bde}),Tfe={kernelName:Po,backendName:"webgpu",kernelFunc:Cfe},zd=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=me(e),this.dispatch=de(this.dispatchLayout,e,this.workgroupSize),this.sliceDimGreaterThanOne=t>1,this.shaderKey=`scatter_${a}_${n}_${this.sliceDimGreaterThanOne}_${i}_${o}_${r.length}`;let l=Pt(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(${Array.from({length:this.updatesRank},(i,o)=>`coords[${o}]`).join(", ")})`;return`
${r}
${ue("index")} {
if (index < uniforms.updatesSize) {
let coords = getUpdatesCoordsFromFlatIndex(index);
var flattenedIndex = 0;
for (var j = 0; j < uniforms.sliceDim; j = j + 1) {
let indexInside = i32(round(${t}));
flattenedIndex = flattenedIndex + indexInside * ${a};
}
let updateValue =
${Hs(this.type)}(${s});
let flatIndex = getOutputIndexFromCoords(${n});
${this.sumDupeIndices?xs("&result[flatIndex]","updateValue",this.type):"atomicStore(&result[flatIndex], bitcast<i32>(updateValue));"}
}
}`}};function Nfe(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r,updates:s}=t,{shape:i}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:c}=C.calculateShapes(s,r,i),d=[c/u,u];if(c===0)return a.makeTensorInfo(i,r.dtype);let h=ke({inputs:{x:r},backend:a,attrs:{shape:[l,o]}}),m=ke({inputs:{x:s},backend:a,attrs:{shape:[l,u]}}),f=m.dtype,g=Wa({backend:a,attrs:{shape:d,value:0,dtype:f}}),y=v.sizeFromShape(m.shape),x=[{type:"int32",data:[o]},{type:"int32",data:p},{type:"int32",data:[y]}],A=new zd(m.shape,o,h.shape.length,m.shape.length,p,d,f),b=a.runWebGPUProgram(A,[m,h],f,x,g),w=ke({inputs:{x:b},backend:a,attrs:{shape:i}});return a.disposeData(h.dataId),a.disposeData(m.dataId),a.disposeData(b.dataId),w}var Rfe={kernelName:_o,backendName:"webgpu",kernelFunc:Nfe},Efe=class{constructor(e,t){this.outputShape=[],this.variableNames=["sortedSequence","values"],this.uniforms="numInputs : i32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.side=t,this.shaderKey=`search_sorted_${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;
}
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let value = getValuesByOutputIndex(index);
setOutputAtIndexI32(index, findBound(coords[0], value));
}
}
`}};function Mfe(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n,o=new Efe([s.shape[0],s.shape[1]],i),l=[{type:"int32",data:[r.shape[1]]}];return a.runWebGPUProgram(o,[r,s],"int32",l)}var $fe={kernelName:Do,backendName:"webgpu",kernelFunc:Mfe},Pfe=class{constructor(e,t,a){this.variableNames=["c","a","b"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=me(this.outputShape),this.dispatch=de(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`
${ue("index")} {
if (index < uniforms.size) {
let resRC = getCoordsFromIndex(index);
let cVal = getC(${e});
if (cVal >= 1.0) {
setOutputAtIndex(index, getA(${t}));
} else {
setOutputAtIndex(index, getB(${t}));
}
}
}
`}};function _fe(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t,i=new Pfe(n.shape.length,r.shape,r.shape.length);return a.runWebGPUProgram(i,[n,r,s],pa(r.dtype,s.dtype))}var Ffe={kernelName:Pu,backendName:"webgpu",kernelFunc:_fe},Dfe=at({opType:le.SELU}),Ofe={kernelName:Oo,backendName:"webgpu",kernelFunc:Dfe},zfe=at({opType:le.SIGMOID}),Lfe={kernelName:Bo,backendName:"webgpu",kernelFunc:zfe},Wfe=at({opType:le.SIGN}),Bfe={kernelName:Wo,backendName:"webgpu",kernelFunc:Wfe},Vfe=at({opType:le.SIN}),Ufe={kernelName:zo,backendName:"webgpu",kernelFunc:Vfe},Gfe=at({opType:le.SINH}),Hfe={kernelName:Lo,backendName:"webgpu",kernelFunc:Gfe},jfe=at({opType:le.SOFTPLUS}),qfe={kernelName:Vo,backendName:"webgpu",kernelFunc:jfe},Xfe=class{constructor(e,t,a,n,r,s){this.variableNames=["x"],this.outputShape=[],this.uniforms="",this.workgroupSize=[64,1,1],this.size=!0;let i=new Array(n.length);for(let o=0;o<i.length;o++)i[o]=n[r[o]];this.outputShape=i,this.newDim=r,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.xShape=e,this.paddedXShape=t,this.uniforms+=`reshapedPaddedXShape : ${Pt(n.length)}, paddedXShapeStrides : ${Pt(s)}, `,a.map((o,l)=>{this.uniforms+=` pad${l} : vec2<i32>,`}),this.shaderKey=`spaceToBatchND_${r}`}getUserCode(){let e=Pt(this.outputShape.length),t=Mk(this.newDim);return`
${lh(this.paddedXShape,"PaddedX")}
${ue("index")} {
if(index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let switchedIndex = getIndexFromCoords${this.outputShape.length}D(${e}(${t}), uniforms.reshapedPaddedXShape);
let paddedCoords = getPaddedXCoordsFromIndex(switchedIndex);
${Yk(this.xShape,!0)}
}
}
`}},Kfe=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=l.map((x,A)=>x[0]+r.shape[A]+x[1]),p=C.getReshaped(u,s,o,!1),c=C.getPermuted(p.length,s.length,!1),d=C.getReshapedPermuted(u,s,o,!1),h=v.computeStrides(u),m=new Xfe(r.shape,u,l,p,c,h.length),f=[{type:"int32",data:p},{type:"int32",data:h}];l.map(x=>f.push({type:"int32",data:[x[0],x[1]]}));let g=a.runWebGPUProgram(m,[r],r.dtype,f),y=ke({inputs:{x:g},backend:a,attrs:{shape:d}});return a.disposeData(g.dataId),y},Yfe={kernelName:Fu,backendName:"webgpu",kernelFunc:Kfe},Zfe=class{constructor(e,t,a){this.variableNames=["input","indices","segmentIds"],this.outputShape=[],this.uniforms="segmentSize : i32, sparseSize : i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=e,this.type=a,this.dispatchLayout=me([t]),this.dispatch=de(this.dispatchLayout,[t],this.workgroupSize),this.shaderKey="sparseSegmentSum"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.sparseSize) {
let indexInSegmentIds = index / uniforms.segmentSize;
let indexInSegment = index % uniforms.segmentSize;
let indexInInput = indices[indexInSegmentIds];
let segmentId = segmentIds[indexInSegmentIds];
let value = input[indexInInput * uniforms.segmentSize + indexInSegment];
let outIndex = segmentId * uniforms.segmentSize + indexInSegment;
${xs("&result[outIndex]","value",this.type)}
}
}
`}},Jfe=class{constructor(e,t){this.variableNames=["segmentIds"],this.outputShape=[],this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=[e],this.dispatchLayout=me(t),this.dispatch=de(this.dispatchLayout,t,this.workgroupSize),this.shaderKey="sparseSegmentIdCountProgram"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.segmentIdsShape) {
let segmentId = segmentIds[index];
${xs("&result[segmentId]","1","int32")}
}
}
`}},Qfe=class{constructor(e,t){this.variableNames=["segmentSum","sameSegmentIdCount"],this.outputShape=[],this.uniforms="segmentSize : i32",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.type=t,this.dispatchLayout=me(e),this.dispatch=de(this.dispatchLayout,e,this.workgroupSize),this.shaderKey="sparseSegmentMean"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.size) {
let segmentId = index / uniforms.segmentSize;
let count = sameSegmentIdCount[segmentId];
if (count != 0) {
${this.type==="float32"?"setOutputAtIndex(index, segmentSum[index] / f32(count));":"setOutputAtIndexI32(index, segmentSum[index] / count);"}
}
}
}
`}};function Zk(e,t,a,n=!1,r){let s=v.sizeFromShape(e.shape)/e.shape[0],i=e.dtype,o=v.sizeFromShape(t.shape),l=r.readSync(a.dataId),u=o>0?l[o-1]+1:0,p,c=e.shape.slice();c[0]=u;let d=o*s,h=Wa({backend:r,attrs:{shape:c,value:0,dtype:i}});p=new Zfe(c,d,i);let m=[{type:"int32",data:[s]},{type:"int32",data:[d]}],f=r.runWebGPUProgram(p,[e,t,a],i,m,h);if(n)return f;let g=Wa({backend:r,attrs:{shape:[u],value:0,dtype:"int32"}});p=new Jfe(u,a.shape);let y=r.runWebGPUProgram(p,[a],"int32",null,g),x=Wa({backend:r,attrs:{shape:c,value:0,dtype:i}});p=new Qfe(c,i),m=[{type:"int32",data:[s]}];let A=r.runWebGPUProgram(p,[f,y],i,m,x);return r.disposeData(f.dataId),r.disposeData(y.dataId),A}function e2e(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;return Zk(n,r,s,!1,a)}var t2e={kernelName:zu,backendName:"webgpu",kernelFunc:e2e};function a2e(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;return Zk(n,r,s,!0,a)}var n2e={kernelName:Lu,backendName:"webgpu",kernelFunc:a2e},r2e=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=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.rank=this.outputShape.length,this.shaderKey="tile"}getUserCode(){let e=s2e(this.rank,"uniforms.");return`
${ue("index")} {
if (index < uniforms.size) {
let resRC = getCoordsFromIndex(index);
setOutputAtIndex(index, getA(${e}));
}
}
`}};function s2e(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 J3(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=_e(r.shape,r.dtype,l),p=Xde(u,s);return a.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new r2e(r.shape,s);return a.runWebGPUProgram(i,[r],r.dtype)}var i2e={kernelName:ds,backendName:"webgpu",kernelFunc:J3};function o2e(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}=C.calculateShapes(s,r,o),h=!1;if(s.dtype==="string"){let N=a.bufferSync(r),M=a.bufferSync(s),$=v.decodeString(a.readSync(i.dataId)[0]),E=Vde(N,M,o,d,p,u,l,c,$,h);return a.makeTensorInfo(o,E.dtype,E.values)}let m=[d/p,p],f=ke({inputs:{x:r},backend:a,attrs:{shape:[u,l]}}),g=s.shape.length?ke({inputs:{x:s},backend:a,attrs:{shape:[u,p]}}):tn({inputs:{x:s},backend:a}),y=g.dtype,x=a.makeTensorInfo([],y,v.makeZerosTypedArray(1,y)),A=ke({inputs:{x:i},backend:a,attrs:{shape:Array(m.length).fill(1)}}),b=J3({inputs:{x:A},backend:a,attrs:{reps:m}}),w=v.sizeFromShape([u,p]),I=[{type:"int32",data:[l]},{type:"int32",data:c},{type:"int32",data:[w]}];switch(u){case 0:break;case 1:{let N=new zd([u,p],l,f.shape.length,g.shape.length,c,m,y,h);a.runWebGPUProgram(N,[g,f],y,I,b)}break;default:{let N=new zd([u,p],l,f.shape.length,x.shape.length,c,m,y,h);a.runWebGPUProgram(N,[x,f],y,I,b)}{let N=new zd([u,p],l,f.shape.length,g.shape.length,c,m,y);a.runWebGPUProgram(N,[g,f],y,I,b)}}let T=ke({inputs:{x:b},backend:a,attrs:{shape:o}});return a.disposeData(f.dataId),a.disposeData(g.dataId),a.disposeData(A.dataId),a.disposeData(x.dataId),a.disposeData(b.dataId),T}var l2e={kernelName:jo,backendName:"webgpu",kernelFunc:o2e};function u2e(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=C.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 m=ad({inputs:{x:r},backend:a,attrs:{begin:p,size:h}});return p[o]+=d,m})}var d2e={kernelName:Du,backendName:"webgpu",kernelFunc:u2e},p2e=at({opType:le.SQRT}),c2e={kernelName:Uo,backendName:"webgpu",kernelFunc:p2e},h2e={kernelName:Cp,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{x:a}=e,n=t,r=new td(a.shape,le.SQUARE);return n.runWebGPUProgram(r,[a],a.dtype)}},m2e=ta({opType:Pe.SQUARED_DIFFERENCE}),f2e={kernelName:qo,backendName:"webgpu",kernelFunc:m2e};function g2e({inputs:e,attrs:t,backend:a}){let{x:n}=e,r=new td(n.shape,le.STEP,"stepAlpha : f32,"),s=[{type:"float32",data:[t.alpha]}];return a.runWebGPUProgram(r,[n],n.dtype,s)}var y2e={kernelName:ps,backendName:"webgpu",kernelFunc:g2e},x2e=class{constructor(e){this.variableNames=["x"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]);let t=Pt(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`
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
setOutputAtIndex(index, getX(${t}));
}
}
`}};function A2e(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:m,isIdentity:f,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Nt.sliceInfo(r.shape,s,i,o,l,u,p,c,d),w;if(f)w=ke({inputs:{x:r},backend:a,attrs:{shape:m}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let I=Nt.computeOutShape(x,A,b),T=ad({inputs:{x:r},backend:a,attrs:{begin:x,size:I}});w=ke({inputs:{x:T},backend:a,attrs:{shape:m}}),a.disposeData(T.dataId)}else if(a.shouldExecuteOnCPU([r])){let I=a.readSync(r.dataId),T=_e(r.shape,r.dtype,I),N=Hde(h,T,b,x);w=a.makeTensorInfo(m,r.dtype,N.values)}else{let I=new x2e(h),T=[{type:"int32",data:x},{type:"int32",data:b}],N=a.runWebGPUProgram(I,[r],r.dtype,T);w=ke({inputs:{x:N},backend:a,attrs:{shape:m}}),a.disposeData(N.dataId)}return w}var b2e={kernelName:Xo,backendName:"webgpu",kernelFunc:A2e};function v2e(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),[m,f]=jde(d,h,r,s,i,o,l,u);return[a.makeTensorInfo([m.length],"string",m),a.makeTensorInfo(c.shape,"int32",f)]}var w2e={kernelName:Wu,backendName:"webgpu",kernelFunc:v2e},k2e=ta({opType:Pe.SUB,cpuKernelImpl:qde,supportsComplex:!0}),I2e={kernelName:Ko,backendName:"webgpu",kernelFunc:k2e},S2e=at({opType:le.TAN}),C2e={kernelName:Yo,backendName:"webgpu",kernelFunc:S2e},T2e=at({opType:le.TANH}),N2e={kernelName:Zo,backendName:"webgpu",kernelFunc:T2e};function R2e(e){let{inputs:t,backend:a,attrs:n}=e,{tensor:r,indices:s,updates:i}=t,{}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:c}=C.calculateShapes(i,s,r.shape),d=[c/u,u];if(c===0)return a.makeTensorInfo(r.shape,s.dtype);let h=[],m=ke({inputs:{x:s},backend:a,attrs:{shape:[l,o]}});h.push(m);let f=ke({inputs:{x:i},backend:a,attrs:{shape:[l,u]}});h.push(f);let g=ke({inputs:{x:r},backend:a,attrs:{shape:d}});h.push(g);let y=J3({inputs:{x:g},backend:a,attrs:{reps:Array(d.length).fill(1)}}),x=new zd([l,u],o,m.shape.length,f.shape.length,p,d,r.dtype,!1),A=v.sizeFromShape([l,u]),b=[{type:"int32",data:[o]},{type:"int32",data:p},{type:"int32",data:[A]}],w=a.runWebGPUProgram(x,[f,m],g.dtype,b,y);h.push(w);let I=ke({inputs:{x:w},backend:a,attrs:{shape:r.shape}});return h.forEach(T=>a.disposeData(T.dataId)),I}var E2e={kernelName:Fo,backendName:"webgpu",kernelFunc:R2e},M2e=class{constructor(e){this.variableNames=["x","indices"],this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms=`inputSize : i32, firstPass : i32, negativeInf : f32,
dir : i32, inc : i32,`,this.shaderKey="swap"}getUserCode(){return`
${ue("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));
}
}
}
`}},$2e=class{constructor(e){this.variableNames=["x","indices"],this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms="inputSize : i32, firstPass : i32, k : i32,",this.shaderKey="merge"}getUserCode(){return`
${ue("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 Ol(e,t){t!==null&&e.disposeData(t.dataId)}function cA(e){let t=1;for(;t<e;)t*=2;return t}function P2e(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,I]=Kde(b,o,r.dtype,s,i);return[a.makeTensorInfo(w.shape,w.dtype,w.values),a.makeTensorInfo(I.shape,I.dtype,I.values)]}if(s===0)return o[o.length-1]=0,[a.makeTensorInfo(o,r.dtype,[]),a.makeTensorInfo(o,"int32",[])];if(l===1)return[r,Wa({attrs:{shape:o,dtype:"int32",value:0},backend:a})];let u=v.sizeFromShape(o)/l,p=ke({inputs:{x:r},attrs:{shape:[u,l]},backend:a}),c=cA(s),d=cA(l),h=null,m=()=>h===null?[p,p]:[p,h],f=(b,w,I)=>{let T=m(),N=new M2e(I),M=[{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(N,T,"int32",M),Ol(a,$)};for(let b=1;b<c;b*=2){let w=b*2;for(let I=b;I>=1;I/=2)f(w,I,[u,d])}for(let b=d;b>c;b/=2){let w=m(),I=new $2e([u,b/2]),T=[{type:"int32",data:[l]},{type:"int32",data:[h===null?1:0]},{type:"int32",data:[c]}],N=h;h=a.runWebGPUProgram(I,w,"int32",T),Ol(a,N);let M=c/2,$=M*2;for(let E=M;E>=1;E/=2)f($,E,h.shape)}let g=h;h=ad({inputs:{x:h},backend:a,attrs:{begin:0,size:[u,s]}}),Ol(a,g);let y=jk({inputs:{x:p,indices:h},backend:a,attrs:{axis:1,batchDims:1}});Ol(a,p);let x=o.slice(0,-1);x.push(s),g=h,h=ke({inputs:{x:h},attrs:{shape:x},backend:a}),Ol(a,g);let A=y;return y=ke({inputs:{x:y},attrs:{shape:x},backend:a}),Ol(a,A),[y,h]}var _2e={kernelName:Jo,backendName:"webgpu",kernelFunc:P2e},F2e=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=me(this.outputShape),this.dispatch=de(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;
}
${ue("index")} {
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
var outputValue : f32;
let batch = coords[0];
let x = coords[2];
let y = coords[1];
let channel = coords[3];
let xf = f32(x);
let yf = f32(y);
let a1 = getTransforms(batch, 0);
let a2 = getTransforms(batch, 1);
let a3 = getTransforms(batch, 2);
let b1 = getTransforms(batch, 3);
let b2 = getTransforms(batch, 4);
let b3 = getTransforms(batch, 5);
let c1 = getTransforms(batch, 6);
let c2 = getTransforms(batch, 7);
let projection = c1 * xf + c2 * yf + 1.0;
if (projection == 0.0) {
outputValue = uniforms.fillValue;
} else {
let inX = (a1 * xf + a2 * yf + a3) / projection;
let inY = (b1 * xf + b2 * yf + b3) / projection;
let mapX = mapCoord(inX, f32(uniforms.imageShape[2]));
let mapY = mapCoord(inY, f32(uniforms.imageShape[1]));
if (uniforms.interpolationModeId == 1) {
let coordY = i32(round(mapY));
let coordX = i32(round(mapX));
outputValue = readWithFillValue(batch, coordY, coordX,
channel);
} else {
let yFloor = floor(mapY);
let xFloor = floor(mapX);
let yCeil = yFloor + 1.0;
let xCeil = xFloor + 1.0;
let valueYFloor = (xCeil - mapX) *
readWithFillValue(batch, i32(yFloor), i32(xFloor), channel) +
(mapX - xFloor) *
readWithFillValue(batch, i32(yFloor), i32(xCeil), channel);
let valueYCeil = (xCeil - mapX) *
readWithFillValue(batch, i32(yCeil), i32(xFloor), channel) +
(mapX - xFloor) *
readWithFillValue(batch, i32(yCeil), i32(xCeil), channel);
outputValue = (yCeil - mapY) * valueYFloor +
(mapY - yFloor) * valueYCeil;
}
}
setOutputAtIndex(index, outputValue);
}
}
`}};function D2e(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,[m,f]=u!=null?u:[c,d],g=[p,m,f,h],y=new F2e(g),x=i==="nearest"?1:2,A;switch(o){case"constant":A=1;break;case"reflect":A=2;break;case"wrap":A=3;break;case"nearest":A=4;break;default:A=1;break}let b=[{type:"int32",data:[x]},{type:"int32",data:[A]},{type:"float32",data:[l]}];return a.runWebGPUProgram(y,[r,s],"float32",b)}var O2e={kernelName:Qo,backendName:"webgpu",kernelFunc:D2e};function z2e(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 f=0;f<o;f++)f!==s&&(u[p++]=i.shape[f]);let c=[],d=new Array(o).fill(0),h=i.shape.slice();h[s]=1;let m=new Array(l);for(let f=0;f<m.length;f++){d[s]=f;let g=ad({inputs:{x:i},backend:a,attrs:{begin:d,size:h}}),y=ke({inputs:{x:g},backend:a,attrs:{shape:u}});m[f]=y,c.push(g)}return c.forEach(f=>a.disposeData(f.dataId)),m}var L2e={kernelName:Bu,backendName:"webgpu",kernelFunc:z2e},W2e=class{constructor(e,t,a){if(this.outputShape=[],this.variableNames=["x","segmentIds"],this.uniforms="numSegments : i32, xSize: i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=t,this.dispatchLayout=me(e),this.dispatch=de(this.dispatchLayout,e,this.workgroupSize),a!=="float32"&&a!=="int32")throw new Error(`UnsortedSegmentSum only supports float32 and int32
types, does not support ${a} type.`);this.type=a,this.shaderKey="unsortedSegmentSum"}getUserCode(){return`
${ue("index")} {
if (index < uniforms.xSize) {
let coords = getXCoordsFromIndex(index);
let b = coords[0];
let inCol = coords[1];
let segmentId = i32(getSegmentIds(inCol));
if (segmentId >= 0) {
let flatIndex = b * uniforms.numSegments + segmentId % uniforms.numSegments;
let value = getX(b, inCol);
${xs("&result[flatIndex]","value",this.type)}
}
}
}
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precision highp float;
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 e9=`
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];
}
`,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[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;
}
`,a9=`
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);
}
`,n9=`
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;
}
`,r9=`
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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wge=[[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]],kge=[[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]],Ige=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],Sge=[[474,475],[475,476],[476,477],[477,474]],Cge=[[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]],Tge=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],Nge=[[469,470],[470,471],[471,472],[472,469]],Rge=[[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 bs(e){let t=e.map(a=>a[0]);return t.push(e[e.length-1][1]),t}var Ege={lips:bs(wge),leftEye:bs(kge),leftEyebrow:bs(Ige),leftIris:bs(Sge),rightEye:bs(Cge),rightEyebrow:bs(Tge),rightIris:bs(Nge),faceOval:bs(Rge)},Mge=Object.entries(Ege).map(([e,t])=>t.map(a=>[a,e])).flat(),Ube=new Map(Mge),uc=[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],gl=[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],yl=[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417];var rt;function $ge(e,t){var n,r,s,i,o,l,u,p,c;if(!rt.drawLabels||((n=rt.faceLabels)==null?void 0:n.length)===0)return;let a=rt.faceLabels.slice();if(a=ut(a,"[id]",e.id.toFixed(0)),e.score&&(a=ut(a,"[score]",100*e.score)),e.gender&&(a=ut(a,"[gender]",e.gender)),e.genderScore&&(a=ut(a,"[genderScore]",100*e.genderScore)),e.age&&(a=ut(a,"[age]",e.age)),e.distance&&(a=ut(a,"[distance]",100*e.distance)),e.real&&(a=ut(a,"[real]",100*e.real)),e.live&&(a=ut(a,"[live]",100*e.live)),e.emotion&&e.emotion.length>0){let d=e.emotion.map(h=>`${Math.trunc(100*h.score)}% ${h.emotion}`);d.length>3&&(d.length=3),a=ut(a,"[emotions]",d.join(" "))}(s=(r=e.rotation)==null?void 0:r.angle)!=null&&s.roll&&(a=ut(a,"[roll]",cl(e.rotation.angle.roll))),(o=(i=e.rotation)==null?void 0:i.angle)!=null&&o.yaw&&(a=ut(a,"[yaw]",cl(e.rotation.angle.yaw))),(u=(l=e.rotation)==null?void 0:l.angle)!=null&&u.pitch&&(a=ut(a,"[pitch]",cl(e.rotation.angle.pitch))),(c=(p=e.rotation)==null?void 0:p.gaze)!=null&&c.bearing&&(a=ut(a,"[gaze]",cl(e.rotation.gaze.bearing))),wn(t,a,e.box[0],e.box[1],rt)}function Pge(e,t){var a,n,r,s;if((a=e.annotations)!=null&&a.leftEyeIris&&((n=e.annotations)!=null&&n.leftEyeIris[0])){t.strokeStyle=rt.useDepth?"rgba(255, 200, 255, 0.3)":rt.color,t.beginPath();let i=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,o=Math.abs(e.annotations.leftEyeIris[4][1]-e.annotations.leftEyeIris[2][1])/2;t.ellipse(e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1],i,o,0,0,2*Math.PI),t.stroke(),rt.fillPolygons&&(t.fillStyle=rt.useDepth?"rgba(255, 255, 200, 0.3)":rt.color,t.fill())}if((r=e.annotations)!=null&&r.rightEyeIris&&((s=e.annotations)!=null&&s.rightEyeIris[0])){t.strokeStyle=rt.useDepth?"rgba(255, 200, 255, 0.3)":rt.color,t.beginPath();let i=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,o=Math.abs(e.annotations.rightEyeIris[4][1]-e.annotations.rightEyeIris[2][1])/2;t.ellipse(e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1],i,o,0,0,2*Math.PI),t.stroke(),rt.fillPolygons&&(t.fillStyle=rt.useDepth?"rgba(255, 255, 200, 0.3)":rt.color,t.fill())}}function _ge(e,t){var a;if(rt.drawGaze&&((a=e.rotation)!=null&&a.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let n=e.box[0]+e.box[2]/2-e.box[3]*cl(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*cl(e.rotation.angle.pitch)/90,s=new Path2D(`
M ${e.box[0]+e.box[2]/2} ${e.box[1]}
C
${n} ${e.box[1]},
${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},
${e.box[0]+e.box[2]} ${e.box[1]+e.box[3]/2}
`);t.stroke(i),t.stroke(s)}}function Fge(e,t){var a;if(rt.drawGaze&&((a=e.rotation)!=null&&a.gaze.strength)&&e.rotation.gaze.bearing&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let n=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];oy(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[n[0],n[1]],4);let r=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];oy(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[r[0],r[1]],4)}}function Dge(e,t){if(rt.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let a=0;a<fl.length/3;a++){let n=[fl[a*3+0],fl[a*3+1],fl[a*3+2]].map(r=>e.mesh[r]);iy(t,n,rt)}Pge(e,t)}}function Oge(e,t){if(rt.drawPoints)if((e==null?void 0:e.mesh.length)>=468)for(let a=0;a<e.mesh.length;a++)lr(t,e.mesh[a][0],e.mesh[a][1],e.mesh[a][2],rt),rt.drawAttention&&(uc.includes(a)&&lr(t,e.mesh[a][0],e.mesh[a][1],e.mesh[a][2]+127,rt),gl.includes(a)&&lr(t,e.mesh[a][0],e.mesh[a][1],e.mesh[a][2]-127,rt),yl.includes(a)&&lr(t,e.mesh[a][0],e.mesh[a][1],e.mesh[a][2]-127,rt));else for(let[a,n]of Object.entries((e==null?void 0:e.annotations)||{})){if(!(n!=null&&n[0]))continue;let r=n[0];lr(t,r[0],r[1],0,rt),rt.drawLabels&&wn(t,a,r[0],r[1],rt)}}function zge(e,t){rt.drawBoxes&&ur(t,e.box[0],e.box[1],e.box[2],e.box[3],rt)}function v0(e,t,a){if(rt=Et(Ft,a),!t||!e)return;let n=vn(e);if(n){n.font=rt.font,n.strokeStyle=rt.color,n.fillStyle=rt.color;for(let r of t)zge(r,n),$ge(r,n),r.mesh&&r.mesh.length>0&&(Oge(r,n),Dge(r,n),_ge(r,n),Fge(r,n))}}function w0(e,t,a){var s,i;let n=Et(Ft,a);if(!t||!e)return;let r=vn(e);if(r){r.lineJoin="round";for(let o=0;o<t.length;o++){if(r.strokeStyle=n.color,r.fillStyle=n.color,r.lineWidth=n.lineWidth,r.font=n.font,n.drawBoxes&&t[o].box&&t[o].box.length===4&&(ur(r,t[o].box[0],t[o].box[1],t[o].box[2],t[o].box[3],n),n.drawLabels&&((s=n.bodyLabels)==null?void 0:s.length)>0)){let l=n.bodyLabels.slice();l=ut(l,"[id]",t[o].id.toFixed(0)),l=ut(l,"[score]",100*t[o].score),wn(r,l,t[o].box[0],t[o].box[1],n)}if(n.drawPoints&&t[o].keypoints)for(let l=0;l<t[o].keypoints.length;l++)!t[o].keypoints[l].score||t[o].keypoints[l].score===0||(r.fillStyle=hl(t[o].keypoints[l].position[2],n),lr(r,t[o].keypoints[l].position[0],t[o].keypoints[l].position[1],0,n));if(n.drawLabels&&((i=n.bodyPartLabels)==null?void 0:i.length)>0&&t[o].keypoints){r.font=n.font;for(let l of t[o].keypoints){if(!l.score||l.score===0)continue;let u=n.bodyPartLabels.slice();u=ut(u,"[label]",l.part),u=ut(u,"[score]",100*l.score),wn(r,u,l.position[0],l.position[1],n)}}if(n.drawPolygons&&t[o].keypoints&&t[o].annotations)for(let l of Object.values(t[o].annotations))for(let u of l)h9(r,u,n)}}}function k0(e,t,a){var s,i;let n=Et(Ft,a);if(!t||!e)return;let r=vn(e);if(r){r.lineJoin="round",r.font=n.font;for(let o of t){if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,ur(r,o.box[0],o.box[1],o.box[2],o.box[3],n),n.drawLabels&&((s=n.handLabels)==null?void 0:s.length)>0){let l=n.handLabels.slice();l=ut(l,"[id]",o.id.toFixed(0)),l=ut(l,"[label]",o.label),l=ut(l,"[score]",100*o.score),wn(r,l,o.box[0],o.box[1],n)}r.stroke()}if(n.drawPoints&&o.keypoints&&o.keypoints.length>0)for(let l of o.keypoints)r.fillStyle=hl(l[2],n),lr(r,l[0],l[1],0,n);if(n.drawLabels&&o.annotations&&((i=n.fingerLabels)==null?void 0:i.length)>0)for(let[l,u]of Object.entries(o.annotations)){let p=n.fingerLabels.slice();p=ut(p,"[label]",l),wn(r,p,u[u.length-1][0],u[u.length-1][1],n)}if(n.drawPolygons&&o.annotations){let l=u=>{if(!(!u||u.length===0||!u[0]))for(let p=0;p<u.length;p++){r.beginPath();let c=u[p][2]||0;r.strokeStyle=hl(p*c,n),r.moveTo(u[p>0?p-1:0][0],u[p>0?p-1:0][1]),r.lineTo(u[p][0],u[p][1]),r.stroke()}};r.lineWidth=n.lineWidth,l(o.annotations.index),l(o.annotations.middle),l(o.annotations.ring),l(o.annotations.pinky),l(o.annotations.thumb)}}}}function I0(e,t,a){var s;let n=Et(Ft,a);if(!t||!e)return;let r=vn(e);if(r){r.lineJoin="round",r.font=n.font;for(let i of t)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,ur(r,i.box[0],i.box[1],i.box[2],i.box[3],n),n.drawLabels&&((s=n.objectLabels)==null?void 0:s.length)>0){let o=n.objectLabels.slice();o=ut(o,"[id]",i.id.toFixed(0)),o=ut(o,"[label]",i.label),o=ut(o,"[score]",100*i.score),wn(r,o,i.box[0],i.box[1],n)}r.stroke()}}}function S0(e,t,a){var r;let n=Et(Ft,a);if(!(!t||!e)&&n.drawGestures&&((r=n.gestureLabels)==null?void 0:r.length)>0){let s=vn(e);if(!s)return;s.font=n.font,s.fillStyle=n.color;let i=1;for(let o=0;o<t.length;o++){let[l,u]=Object.entries(t[o]);if(u.length>1&&u[1].length>0){let p=l[1]>0?`#${l[1]}`:"",c=n.gestureLabels.slice();c=ut(c,"[where]",l[0]),c=ut(c,"[who]",p),c=ut(c,"[what]",u[1]),wn(s,c,8,2+i*n.lineHeight,n),i+=1}}}}var vs={face:`face
confidence: [score]%
[gender] [genderScore]%
age: [age] years
distance: [distance]cm
real: [real]%
live: [live]%
[emotions]
roll: [roll]\xB0 yaw:[yaw]\xB0 pitch:[pitch]\xB0
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py=ne.perfadd?py+Math.round(ae()-n):Math.round(ae()-n),t.performance.draw=py,s}function cy(){Ft.faceLabels=vs.face,Ft.bodyLabels=vs.body,Ft.bodyPartLabels=vs.bodyPart,Ft.handLabels=vs.hand,Ft.fingerLabels=vs.finger,Ft.objectLabels=vs.object,Ft.gestureLabels=vs.gesture}var T0={};xr(T0,{connected:()=>my,kpt:()=>hy});var hy=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPinky","rightPinky","leftIndex","rightIndex","leftThumb","rightThumb","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","bodyCenter","bodyTop","leftPalm","leftHand","rightPalm","rightHand"],my={shoulders:["leftShoulder","rightShoulder"],hips:["rightHip","leftHip"],mouth:["leftMouth","rightMouth"],leftLegUpper:["leftHip","leftKnee"],leftLegLower:["leftKnee","leftAnkle"],leftFoot:["leftAnkle","leftHeel","leftFoot"],leftTorso:["leftShoulder","leftHip"],leftArmUpper:["leftShoulder","leftElbow"],leftArmLower:["leftElbow","leftWrist"],leftHand:["leftWrist","leftPalm"],leftHandPinky:["leftPalm","leftPinky"],leftHandIndex:["leftPalm","leftIndex"],leftHandThumb:["leftPalm","leftThumb"],leftEyeOutline:["leftEyeInside","leftEyeOutside"],rightLegUpper:["rightHip","rightKnee"],rightLegLower:["rightKnee","rightAnkle"],rightFoot:["rightAnkle","rightHeel","rightFoot"],rightTorso:["rightShoulder","rightHip"],rightArmUpper:["rightShoulder","rightElbow"],rightArmLower:["rightElbow","rightWrist"],rightHand:["rightWrist","rightPalm"],rightHandPinky:["rightPalm","rightPinky"],rightHandIndex:["rightPalm","rightIndex"],rightHandThumb:["rightPalm","rightThumb"],rightEyeOutline:["rightEyeInside","rightEyeOutside"]};var kn,xl=224,g9,Vge=5,N0=[8,16,32,32,32];function Uge(){let e=[],t=0;for(;t<Vge;){let a=0,n=t;for(;n<N0.length&&N0[n]===N0[t];)a+=2,n++;let r=N0[t],s=Math.ceil(xl/r),i=Math.ceil(xl/r);for(let o=0;o<s;++o)for(let l=0;l<i;++l)for(let u=0;u<a;++u)e.push({x:(l+.5)/i,y:(o+.5)/s});t=n}g9={x:Bt(e.map(a=>a.x)),y:Bt(e.map(a=>a.y))}}async function y9(e){if(ne.initial&&(kn=null),!kn&&e.body.detector&&e.body.detector.modelPath){kn=await $e(e.body.detector.modelPath);let t=kn!=null&&kn.executor?Object.values(kn.modelSignature.inputs):void 0;xl=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0}else e.debug&&kn&&K("cached model:",kn.modelUrl);return Uge(),kn}var f9=[5,5];function Gge(e,t){return De(()=>{let a=Sa(e,12,1),n=Oe(a[0]),r=Oe(a[1]),s=Oe(a[2]),i=Oe(a[3]);n=we(ve(n,xl),t.x),r=we(ve(r,xl),t.y),s=te(ve(s,xl),f9[0]),i=te(ve(i,xl),f9[1]);let o=xe(n,ve(s,2)),l=xe(r,ve(i,2)),u=we(o,s),p=we(l,i);return ca([o,l,u,p],1)})}async function Hge(e,t,a,n){var u,p;let r=[],s={};s.boxes=Gge(e,g9),s.scores=za(t),s.nms=await fe.nonMaxSuppressionAsync(s.boxes,s.scores,1,((u=a.body.detector)==null?void 0:u.minConfidence)||.1,((p=a.body.detector)==null?void 0:p.iouThreshold)||.1);let i=await s.nms.data(),o=await s.scores.data(),l=await s.boxes.array();for(let c of Array.from(i)){let d=o[c],h=l[c],m=[Math.round(h[0]*n[0]),Math.round(h[1]*n[1]),Math.round(h[2]*n[0]),Math.round(h[3]*n[1])],f={score:d,boxRaw:h,box:m};r.push(f)}return Object.keys(s).forEach(c=>J(s[c])),r}async function x9(e,t,a){let n={};n.res=kn==null?void 0:kn.execute(e,["Identity"]),n.logitsRaw=Fe(n.res,[0,0,0],[1,-1,1]),n.boxesRaw=Fe(n.res,[0,0,1],[1,-1,-1]),n.logits=Oe(n.logitsRaw),n.boxes=Oe(n.boxesRaw);let r=await Hge(n.boxes,n.logits,t,a);return Object.keys(n).forEach(s=>J(n[s])),r}function ws(e,t=[1,1]){let a=[e.map(o=>o[0]),e.map(o=>o[1])],n=[Math.min(...a[0]),Math.min(...a[1])],r=[Math.max(...a[0]),Math.max(...a[1])],s=[n[0],n[1],r[0]-n[0],r[1]-n[1]],i=[s[0]/t[0],s[1]/t[1],s[2]/t[0],s[3]/t[1]];return{box:s,boxRaw:i}}function A9(e,t=[1,1]){let a=[e.map(u=>u[0]),e.map(u=>u[1])],n=[Math.min(...a[0]),Math.min(...a[1])],r=[Math.max(...a[0]),Math.max(...a[1])],s=[(n[0]+r[0])/2,(n[1]+r[1])/2],i=Math.max(s[0]-n[0],s[1]-n[1],-s[0]+r[0],-s[1]+r[1]),o=[Math.trunc(s[0]-i),Math.trunc(s[1]-i),Math.trunc(2*i),Math.trunc(2*i)],l=[o[0]/t[0],o[1]/t[1],o[2]/t[0],o[3]/t[1]];return{box:o,boxRaw:l}}function R0(e,t){let a=[e[2]*t,e[3]*t];return[e[0]-(a[0]-e[2])/2,e[1]-(a[1]-e[3])/2,a[0],a[1]]}var Ua,gy=256,fy=Number.MAX_SAFE_INTEGER,jge={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},M0=[],ks=[[0,0],[0,0],[0,0],[0,0]],b9=0,v9=e=>1-1/(1+Math.exp(e)),k9=e=>y9(e);async function I9(e){if(ne.initial&&(Ua=null),Ua)e.debug&&K("cached model:",Ua.modelUrl);else{Ua=await $e(e.body.modelPath);let t=Ua!=null&&Ua.executor?Object.values(Ua.modelSignature.inputs):void 0;gy=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0}return Ua}function w9(e,t,a){var s,i;let n={};if(!((s=e==null?void 0:e.shape)!=null&&s[1])||!((i=e==null?void 0:e.shape)!=null&&i[2]))return e;let r;if(a&&(n.cropped=fe.cropAndResize(e,[a],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let o=[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],l=[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0];ks=[[0,0],o,l,[0,0]],n.pad=Rn(n.cropped||e,ks),n.resize=fe.resizeBilinear(n.pad,[t,t]),r=ve(n.resize,ze.tf255)}else e.shape[1]!==t?(n.resize=fe.resizeBilinear(n.cropped||e,[t,t]),r=ve(n.resize,ze.tf255)):r=ve(n.cropped||e,ze.tf255);return Object.keys(n).forEach(o=>J(n[o])),r}function qge(e,t,a){for(let n of e)n.position=[Math.trunc(n.position[0]*(t[0]+ks[2][0]+ks[2][1])/t[0]-ks[2][0]),Math.trunc(n.position[1]*(t[1]+ks[1][0]+ks[1][1])/t[1]-ks[1][0]),n.position[2]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1],2*n.position[2]/(t[0]+t[1])];if(a){let n=a[2]-a[0],r=a[3]-a[1];for(let s of e)s.positionRaw=[s.positionRaw[0]/r+a[1],s.positionRaw[1]/n+a[0],s.positionRaw[2]],s.position=[Math.trunc(s.positionRaw[0]*t[0]),Math.trunc(s.positionRaw[1]*t[1]),s.positionRaw[2]]}return e}function Xge(e){let t=e.find(o=>o.part==="leftPalm"),a=e.find(o=>o.part==="leftWrist"),n=e.find(o=>o.part==="leftIndex");t.position[2]=((a.position[2]||0)+(n.position[2]||0))/2;let r=e.find(o=>o.part==="rightPalm"),s=e.find(o=>o.part==="rightWrist"),i=e.find(o=>o.part==="rightIndex");r.position[2]=((s.position[2]||0)+(i.position[2]||0))/2}async function Kge(e,t,a){if(!(Ua!=null&&Ua.executor))return null;let n={};[n.ld,n.segmentation,n.heatmap,n.world,n.poseflag]=Ua==null?void 0:Ua.execute(e,jge.landmarks);let r=(await n.poseflag.data())[0],s=await n.ld.data(),i=await n.world.data();Object.keys(n).forEach(m=>J(n[m]));let o=[],l=5;for(let m=0;m<s.length/l;m++){let f=v9(s[l*m+3]),g=v9(s[l*m+4]),y=Math.trunc(100*f*g*r)/100,x=[s[l*m+0]/gy,s[l*m+1]/gy,s[l*m+2]+0],A=[Math.trunc(a[0]*x[0]),Math.trunc(a[1]*x[1]),x[2]],b=[i[l*m+0],i[l*m+1],i[l*m+2]+0];o.push({part:hy[m],positionRaw:x,position:A,distance:b,score:y})}if(r<(t.body.minConfidence||0))return null;Xge(o);let u=qge(o,a),p=u.map(m=>m.position),c=ws(p,[a[0],a[1]]),d={};for(let[m,f]of Object.entries(my)){let g=[];for(let y=0;y<f.length-1;y++){let x=u.find(b=>b.part===f[y]),A=u.find(b=>b.part===f[y+1]);x&&A&&g.push([x.position,A.position])}d[m]=g}return{id:0,score:Math.trunc(100*r)/100,box:c.box,boxRaw:c.boxRaw,keypoints:u,annotations:d}}async function yy(e,t){var s,i,o;let a=[e.shape[2]||0,e.shape[1]||0],n=(t.body.skipTime||0)>ae()-b9,r=fy<(t.body.skipFrames||0);if(t.skipAllowed&&n&&r&&M0!==null)fy++;else{let l=[];if((i=(s=t.body)==null?void 0:s.detector)!=null&&i.enabled){let u=w9(e,224);l=await x9(u,t,a),J(u)}else l=[{box:[0,0,0,0],boxRaw:[0,0,1,1],score:0}];for(let u=0;u<l.length;u++){let p=w9(e,256,(o=l[u])==null?void 0:o.boxRaw);M0.length=0;let c=await Kge(p,t,a);J(p),c&&(c.id=u,M0.push(c))}b9=ae(),fy=0}return M0}var rd=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking 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Iy(e,t){if(!(Mt!=null&&Mt.executor)||!(Mt!=null&&Mt.inputs[0].shape))return[];let a=(t.body.skipTime||0)>ae()-R9,n=ky<(t.body.skipFrames||0);return t.skipAllowed&&a&&n&&Object.keys(Ma.keypoints).length>0?(ky++,[Ma]):(ky=0,new Promise(async r=>{let s=De(()=>{var m,f;let c=fe.resizeBilinear(e,[((m=Mt==null?void 0:Mt.inputs[0].shape)==null?void 0:m[2])||0,((f=Mt==null?void 0:Mt.inputs[0].shape)==null?void 0:f[1])||0],!1),d=te(c,ze.tf2);return xe(d,ze.tf1)}),i;if(t.body.enabled&&(i=Mt==null?void 0:Mt.execute(s)),R9=ae(),J(s),i){Ma.keypoints.length=0;let c=Oe(i);J(i);let d=Na(c,2);J(c);for(let h=0;h<d.length;h++){let[m,f,g]=await 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t={};t.boxStarts=Fe(e,[0,1],[-1,2]),t.centers=we(t.boxStarts,z0),t.boxSizes=Fe(e,[0,3],[-1,2]),t.boxSizesNormalized=ve(t.boxSizes,id),t.centersNormalized=ve(t.centers,id),t.halfBoxSize=ve(t.boxSizesNormalized,ze.tf2),t.starts=xe(t.centersNormalized,t.halfBoxSize),t.ends=we(t.centersNormalized,t.halfBoxSize),t.startNormalized=te(t.starts,id),t.endNormalized=te(t.ends,id);let a=Uu([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>J(t[n])),a}async function G9(e,t){var u,p,c,d,h,m,f,g,y;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let a={},n=[0,0],r=[1,1];if((p=(u=t==null?void 0:t.face)==null?void 0:u.detector)!=null&&p.square){let x=Math.max(e.shape[2],e.shape[1]);n=[Math.floor((x-e.shape[2])/2),Math.floor((x-e.shape[1])/2)],a.padded=Rn(e,[[0,0],[n[1],n[1]],[n[0],n[0]],[0,0]]),r=[e.shape[2]/x,e.shape[1]/x],n=[n[0]/dr,n[1]/dr]}else a.padded=e.clone();a.resized=fe.resizeBilinear(a.padded,[dr,dr]),a.div=ve(a.resized,ze.tf127),a.normalized=xe(a.div,ze.tf1);let s=Un==null?void 0:Un.execute(a.normalized);if(Array.isArray(s)&&s.length>2){let x=s.sort((A,b)=>A.size-b.size);a.concat384=lt([x[0],x[2]],2),a.concat512=lt([x[1],x[3]],2),a.concat=lt([a.concat512,a.concat384],1),a.batch=Oe(a.concat,[0])}else Array.isArray(s)?a.batch=Oe(s[0]):a.batch=Oe(s);J(s),a.boxes=r3e(a.batch),a.logits=Fe(a.batch,[0,0],[-1,1]),a.sigmoid=za(a.logits),a.scores=Oe(a.sigmoid),a.nms=await fe.nonMaxSuppressionAsync(a.boxes,a.scores,((c=t.face.detector)==null?void 0:c.maxDetected)||0,((d=t.face.detector)==null?void 0:d.iouThreshold)||0,((h=t.face.detector)==null?void 0:h.minConfidence)||0);let i=await a.nms.array(),o=[],l=await a.scores.data();for(let x=0;x<i.length;x++){let A=l[i[x]];if(A>(((m=t.face.detector)==null?void 0:m.minConfidence)||0)){let b={};b.bbox=Fe(a.boxes,[i[x],0],[1,-1]),b.slice=Fe(a.batch,[i[x],B9-1],[1,-1]),b.squeeze=Oe(b.slice),b.landmarks=Q(b.squeeze,[B9,-1]);let w=await b.bbox.data(),I=[w[0]*r[0]-n[0],w[1]*r[1]-n[1],w[2]*r[0]-n[0],w[3]*r[1]-n[1]],T={startPoint:[I[0],I[1]],endPoint:[I[2],I[3]],landmarks:await b.landmarks.array(),confidence:A};b.anchor=Fe(z0,[i[x],0],[1,2]);let N=await b.anchor.data(),M=_9(T,[(e.shape[2]||0)/dr,(e.shape[1]||0)/dr],N),$=D0(M,((f=t.face.detector)==null?void 0:f.scale)||1.4),E=O0($);E.size[0]>(((g=t.face.detector)==null?void 0:g.minSize)||0)&&E.size[1]>(((y=t.face.detector)==null?void 0:y.minSize)||0)&&o.push(E),Object.keys(b).forEach(S=>J(b[S]))}}return Object.keys(a).forEach(x=>J(a[x])),o}var nn,Is=0,Ny=Pn.leftEyeLower0,Ry=Pn.rightEyeLower0,od={leftBounds:[Ny[0],Ny[Ny.length-1]],rightBounds:[Ry[0],Ry[Ry.length-1]]},ld={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function K9(e){var t,a;return ne.initial&&(nn=null),nn?e.debug&&K("cached 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n=e[Pn[`${a}EyeUpper0`][ld.upperCenter]][2],r=e[Pn[`${a}EyeLower0`][ld.lowerCenter]][2],s=(n+r)/2;return t.map((i,o)=>{let l=s;return o===2?l=n:o===4&&(l=r),[i[0],i[1],l]})};async function Y9(e,t,a,n){var T,N;if(!(nn!=null&&nn.executor))return e;let{box:r,boxSize:s,crop:i}=j9(e,t,od.leftBounds[0],od.leftBounds[1],a,!0,((T=n.face.iris)==null?void 0:T.scale)||2.3),{box:o,boxSize:l,crop:u}=j9(e,t,od.rightBounds[0],od.rightBounds[1],a,!0,((N=n.face.iris)==null?void 0:N.scale)||2.3),p=lt([i,u]);J(i),J(u);let c=nn.execute(p);J(p);let d=await c.data();J(c);let h=d.slice(0,ld.numCoordinates*3),{rawCoords:m,iris:f}=q9(h,r,s,!0),g=d.slice(ld.numCoordinates*3),{rawCoords:y,iris:x}=q9(g,o,l,!1),A=s3e(e);Math.abs(A)<30?(L0(e,m,"left",null),L0(e,y,"right",null)):A<1?L0(e,m,"left",["EyeUpper0","EyeLower0"]):L0(e,y,"right",["EyeUpper0","EyeLower0"]);let b=X9(e,f,"left"),w=X9(e,x,"right");return e.concat(b).concat(w)}async function J9(e,t){var s,i,o,l,u,p,c,d,h,m;let a={lips:await((i=(s=t.filter(f=>f.size===160))==null?void 0:s[0])==null?void 0:i.data()),irisL:await((l=(o=t.filter(f=>f.size===10))==null?void 0:o[0])==null?void 0:l.data()),eyeL:await((p=(u=t.filter(f=>f.size===142))==null?void 0:u[0])==null?void 0:p.data()),irisR:await((d=(c=t.filter(f=>f.size===10))==null?void 0:c[1])==null?void 0:d.data()),eyeR:await((m=(h=t.filter(f=>f.size===142))==null?void 0:h[1])==null?void 0:m.data())};for(let f of Object.values(a))if(!f)return e;let n=gl.reduce((f,g)=>f+=e[g][2],0)/gl.length;for(let f=0;f<a.irisL.length/2;f++)e.push([a.irisL[2*f+0],a.irisL[2*f+1],n]);let r=yl.reduce((f,g)=>f+=e[g][2],0)/yl.length;for(let f=0;f<a.irisR.length/2;f++)e.push([a.irisR[2*f+0],a.irisR[2*f+1],r]);for(let f=0;f<a.eyeL.length/2;f++)e[gl[f]]=[a.eyeL[2*f+0],a.eyeL[2*f+1],e[gl[f]][2]];for(let f=0;f<a.eyeR.length/2;f++)e[yl[f]]=[a.eyeR[2*f+0],a.eyeR[2*f+1],e[yl[f]][2]];for(let f=0;f<a.lips.length/2;f++)e[uc[f]]=[a.lips[2*f+0],a.lips[2*f+1],e[uc[f]][2]];return e}var pr={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},Ct=null,dc=0;async function Q9(e,t){var l,u,p,c,d,h,m,f,g,y;let a=(((l=t.face.detector)==null?void 0:l.skipTime)||0)>ae()-pr.timestamp,n=pr.skipped<(((u=t.face.detector)==null?void 0:u.skipFrames)||0);!t.skipAllowed||!a||!n||pr.boxes.length===0?(pr.boxes=await G9(e,t),pr.timestamp=ae(),pr.skipped=0):pr.skipped++;let r=[],s=[],i=0,o=dc;for(let x=0;x<pr.boxes.length;x++){let A=pr.boxes[x],b=0,w,I={id:i++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,size:[0,0],annotations:{}};if([b,w,I.tensor]=L9((p=t.face.detector)==null?void 0:p.rotation,A,e,(c=t.face.mesh)!=null&&c.enabled?dc:V9()),t.filter.equalization){let T=I.tensor?await m0(I.tensor):void 0;J(I.tensor),T&&(I.tensor=T)}if(I.boxScore=Math.round(100*A.confidence)/100,!((d=t.face.mesh)!=null&&d.enabled)||!(Ct!=null&&Ct.executor)){I.box=_0(A,e),I.boxRaw=F0(A,e),I.score=I.boxScore,I.size=A.size,I.mesh=A.landmarks,I.meshRaw=I.mesh.map(T=>[T[0]/(e.shape[2]||0),T[1]/(e.shape[1]||0),(T[2]||0)/o]);for(let T of Object.keys(ml))I.annotations[T]=[I.mesh[ml[T]]]}else if(!Ct)t.debug&&K("face mesh detection requested, but model is not loaded");else{if((h=t.face.attention)!=null&&h.enabled&&!ne.kernels.includes("atan2"))return t.face.attention.enabled=!1,J(I.tensor),r;let T=Ct.execute(I.tensor),M=await T.find($=>$.shape[$.shape.length-1]===1).data();if(I.faceScore=Math.round(100*M[0])/100,I.faceScore<(((m=t.face.detector)==null?void 0:m.minConfidence)||1)){if(A.confidence=I.faceScore,t.face.mesh.keepInvalid){I.box=_0(A,e),I.boxRaw=F0(A,e),I.size=A.size,I.score=I.boxScore,I.mesh=A.landmarks,I.meshRaw=I.mesh.map($=>[$[0]/(e.shape[2]||1),$[1]/(e.shape[1]||1),($[2]||0)/o]);for(let $ of Object.keys(ml))I.annotations[$]=[I.mesh[ml[$]]]}}else{let $=T.find(O=>O.shape[O.shape.length-1]===1404),E=Q($,[-1,3]),S=await E.array();J(E),(f=t.face.attention)!=null&&f.enabled?S=await J9(S,T):(g=t.face.iris)!=null&&g.enabled&&(S=await Y9(S,I.tensor,dc,t)),I.mesh=z9(S,A,b,w,dc),I.meshRaw=I.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(Pn))I.annotations[O]=Pn[O].map(W=>I.mesh[W]);I.score=I.faceScore;let _={...W9(I.mesh,A),confidence:A.confidence,landmarks:A.landmarks,size:A.size};I.box=_0(_,e),I.boxRaw=F0(_,e),I.size=_.size,s.push(_)}J(T)}I.score>(((y=t.face.detector)==null?void 0:y.minConfidence)||1)?r.push(I):J(I.tensor)}return pr.boxes=s,r}async function eI(e){var t,a,n,r,s,i;return ne.initial&&(Ct=null),(t=e.face.attention)!=null&&t.enabled&&(Ct!=null&&Ct.signature)&&Object.keys(((a=Ct==null?void 0:Ct.signature)==null?void 0:a.outputs)||{}).length<6&&(Ct=null),Ct?e.debug&&K("cached 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Promise(async l=>{var p,c,d;let u=[];if((p=t.face.emotion)!=null&&p.enabled){let h={},m=ra!=null&&ra.inputs[0].shape?ra.inputs[0].shape[2]:0;if(((c=t.face.emotion)==null?void 0:c.crop)>0){let g=(d=t.face.emotion)==null?void 0:d.crop,y=[[g,g,1-g,1-g]];h.resize=fe.cropAndResize(e,y,[0],[m,m])}else h.resize=fe.resizeBilinear(e,[m,m],!1);Py?(h.mul=te(h.resize,255),h.normalize=xe(h.mul,[103.939,116.779,123.68]),h.emotion=ra==null?void 0:ra.execute(h.normalize)):(h.channels=te(h.resize,ze.rgb),h.grayscale=ot(h.channels,3,!0),h.grayscaleSub=xe(h.grayscale,ze.tf05),h.grayscaleMul=te(h.grayscaleSub,ze.tf2),h.emotion=ra==null?void 0:ra.execute(h.grayscaleMul)),rI=ae();let f=await h.emotion.data();for(let g=0;g<f.length;g++)f[g]>(t.face.emotion.minConfidence||0)&&u.push({score:Math.min(.99,Math.trunc(100*f[g])/100),emotion:$y[g]});u.sort((g,y)=>y.score-g.score),Object.keys(h).forEach(g=>J(h[g]))}W0[a]=u,nI=n,l(u)}))}var sa,Ss=[],oI=0,lI=0,Fy=Number.MAX_SAFE_INTEGER;async function uI(e){var 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_n,Vy=[],d3e=["white","black","asian","indian","other"],p3e=[15,23,28,35.5,45.5,55.5,65],bI=0,vI=0,Uy=Number.MAX_SAFE_INTEGER;async function wI(e){var t;return ne.initial&&(_n=null),_n?e.debug&&K("cached model:",_n.modelUrl):_n=await $e((t=e.face.gear)==null?void 0:t.modelPath),_n}async function Gy(e,t,a,n){var i,o;if(!_n)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=Uy<(((i=t.face.gear)==null?void 0:i.skipFrames)||0),s=(((o=t.face.gear)==null?void 0:o.skipTime)||0)>ae()-vI;return t.skipAllowed&&s&&r&&bI===n&&Vy[a]?(Uy++,Vy[a]):(Uy=0,new Promise(async l=>{var y,x,A,b;if(!(_n!=null&&_n.inputs[0].shape))return;let u={},p=[[0,.1,.9,.9]];if(((y=t.face.gear)==null?void 0:y.crop)>0){let w=(x=t.face.gear)==null?void 0:x.crop;p=[[w,w,1-w,1-w]]}u.resize=fe.cropAndResize(e,p,[0],[_n.inputs[0].shape[2],_n.inputs[0].shape[1]]);let c={age:0,gender:"unknown",genderScore:0,race:[]};(A=t.face.gear)!=null&&A.enabled&&([u.age,u.gender,u.race]=_n.execute(u.resize,["age_output","gender_output","race_output"]));let d=await u.gender.data();c.gender=d[0]>d[1]?"male":"female",c.genderScore=Math.round(100*(d[0]>d[1]?d[0]:d[1]))/100;let h=await u.race.data();for(let w=0;w<h.length;w++)h[w]>(((b=t.face.gear)==null?void 0:b.minConfidence)||.2)&&c.race.push({score:Math.round(100*h[w])/100,race:d3e[w]});c.race.sort((w,I)=>I.score-w.score);let f=Array.from(await u.age.data()).map((w,I)=>[p3e[I],w]).sort((w,I)=>I[1]-w[1]),g=f[0][0];for(let w=1;w<f.length;w++)g+=f[w][1]*(f[w][0]-g);c.age=Math.round(10*g)/10,Object.keys(u).forEach(w=>J(u[w])),Vy[a]=c,bI=n,vI=ae(),l(c)}))}var $a,U0=[],II=0,SI=0,Hy=Number.MAX_SAFE_INTEGER;async function CI(e){return ne.initial&&($a=null),$a?e.debug&&K("cached model:",$a.modelUrl):$a=await $e(e.face.ssrnet.modelPathAge),$a}async function jy(e,t,a,n){var i,o,l,u;if(!$a)return{age:0};let r=Hy<(((i=t.face.ssrnet)==null?void 0:i.skipFrames)||0),s=(((o=t.face.ssrnet)==null?void 0:o.skipTime)||0)>ae()-SI;return t.skipAllowed&&r&&s&&II===n&&((l=U0[a])!=null&&l.age)&&((u=U0[a])==null?void 0:u.age)>0?(Hy++,U0[a]):(Hy=0,new Promise(async p=>{var h,m,f;if(!($a!=null&&$a.inputs)||!$a.inputs[0]||!$a.inputs[0].shape)return;let c={};if(((h=t.face.ssrnet)==null?void 0:h.crop)>0){let g=(m=t.face.ssrnet)==null?void 0:m.crop,y=[[g,g,1-g,1-g]];c.resize=fe.cropAndResize(e,y,[0],[$a.inputs[0].shape[2],$a.inputs[0].shape[1]])}else c.resize=fe.resizeBilinear(e,[$a.inputs[0].shape[2],$a.inputs[0].shape[1]],!1);c.enhance=te(c.resize,ze.tf255);let d={age:0};if((f=t.face.ssrnet)!=null&&f.enabled&&(c.age=$a.execute(c.enhance)),c.age){let g=await c.age.data();d.age=Math.trunc(10*g[0])/10}Object.keys(c).forEach(g=>J(c[g])),U0[a]=d,II=n,SI=ae(),p(d)}))}var xa,G0=[],NI=0,RI=0,qy=Number.MAX_SAFE_INTEGER,Xy=[.2989,.587,.114];async function EI(e){var t;return ne.initial&&(xa=null),xa?e.debug&&K("cached 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c3e=e=>{let t=(c,d)=>Math.atan2(c[1]-d[1],c[0]-d[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let a=[0,-.1],n=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),s=r?e.mesh[473]:e.mesh[468],i=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],o=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],l=[(i[0]-s[0])/o[0]-a[0],n*(s[1]-i[1])/o[1]-a[1]],u=Math.sqrt(l[0]*l[0]+l[1]*l[1]);return u=Math.min(u,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],l)+Math.PI/2)%Math.PI,strength:u}},VI=(e,t)=>{let a=f=>{let g=Math.sqrt(f[0]*f[0]+f[1]*f[1]+f[2]*f[2]);return f[0]/=g,f[1]/=g,f[2]/=g,f},n=(f,g)=>{let y=f[0]-g[0],x=f[1]-g[1],A=f[2]-g[2];return[y,x,A]},r=(f,g)=>{let y=f[1]*g[2]-f[2]*g[1],x=f[2]*g[0]-f[0]*g[2],A=f[0]*g[1]-f[1]*g[0];return[y,x,A]},s=f=>{let[g,y,x,A,b,w,I,T,N]=f,M,$,E;if(A<1)if(A>-1){let 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j0(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function pc(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function rS(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 fe.cropAndResize(t,s,[0],a)}function sS(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 q0(e,t=1.5){let a=pc(e),n=j0(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 X0(e){let t=pc(e),a=j0(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 w3e(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function iS(e,t){let a=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return w3e(a)}var aS=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function Ms(e,t){let a=0;for(let n=0;n<e.length;n++)a+=e[n]*t[n];return a}function k3e(e,t){let a=[];for(let n=0;n<e.length;n++)a.push(e[n][t]);return a}function nS(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(Ms(e[r],k3e(t,s)))}return a}function nx(e,t){let a=Math.cos(e),n=Math.sin(e),r=[[a,-n,0],[n,a,0],[0,0,1]],s=aS(t[0],t[1]),i=nS(s,r),o=aS(-t[0],-t[1]);return nS(i,o)}function oS(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],a=[e[0][2],e[1][2]],n=[-Ms(t[0],a),-Ms(t[1],a)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]}function rx(e,t){return[Ms(e,t[0]),Ms(e,t[1])]}var 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Object.keys(a).forEach(r=>J(a[r])),n}normalizeLandmarks(t,a){let n={};n.reshape=Q(t,[-1,7,2]),n.div=ve(n.reshape,this.inputSizeTensor),n.landmarks=we(n.div,this.anchors[a]?this.anchors[a]:0);let r=te(n.landmarks,this.inputSizeTensor);return Object.keys(n).forEach(s=>J(n[s])),r}async predict(t,a){var o;let n={};n.resize=fe.resizeBilinear(t,[this.inputSize,this.inputSize]),n.div=ve(n.resize,ze.tf127),n.image=xe(n.div,ze.tf1),n.batched=this.model.execute(n.image),n.predictions=Oe(n.batched),n.slice=Fe(n.predictions,[0,0],[-1,1]),n.sigmoid=za(n.slice),n.scores=Oe(n.sigmoid);let r=await n.scores.data();n.boxes=Fe(n.predictions,[0,1],[-1,4]),n.norm=this.normalizeBoxes(n.boxes),n.nms=await fe.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=Fe(n.norm,[l,0],[1,-1]),u.slice=Fe(n.predictions,[l,5],[1,14]),u.norm=this.normalizeLandmarks(u.slice,l),u.palmLandmarks=Q(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(),m={startPoint:c,endPoint:d,palmLandmarks:h,confidence:r[l]},f=sS(m,[(t.shape[2]||1)/this.inputSize,(t.shape[1]||0)/this.inputSize]);i.push(f),Object.keys(u).forEach(g=>J(u[g]))}return Object.keys(n).forEach(l=>J(n[l])),i}};var C3e=5,dS=1.65,pS=[0,5,9,13,17,1,2],T3e=0,N3e=2,cS=0,Y0=class{constructor(t,a){he(this,"handDetector");he(this,"handPoseModel");he(this,"inputSize");he(this,"storedBoxes");he(this,"skipped");he(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=>rx([...s,1],a)),r=this.calculateLandmarksBoundingBox(n);return q0(X0(r),C3e)}getBoxForHandLandmarks(t){let a=this.calculateLandmarksBoundingBox(t),n=q0(X0(a),dS);n.palmLandmarks=[];for(let r=0;r<pS.length;r++)n.palmLandmarks.push(t[pS[r]].slice(0,2));return n}transformRawCoords(t,a,n,r){let s=j0(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=nx(n,[0,0]),u=o.map(h=>[...rx(h,l),h[2]]),p=oS(r),c=[...pc(a),1],d=[Ms(c,p[0]),Ms(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)>ae()-cS,i=this.skipped<(a.hand.skipFrames||0);a.skipAllowed&&s&&i?this.skipped++:(r=await this.handDetector.predict(t,a),this.skipped=0),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?iS(u.palmLandmarks[T3e],u.palmLandmarks[N3e]):0,c=pc(u),d=[c[0]/t.shape[2],c[1]/t.shape[1]],h=a.hand.rotation&&ne.kernels.includes("rotatewithoffset")?fe.rotateWithOffset(t,p,0,d):t.clone(),m=nx(-p,c),f=n?this.getBoxForPalmLandmarks(u.palmLandmarks,m):u,g=rS(f,h,[this.inputSize,this.inputSize]),y=ve(g,ze.tf255);J(g),J(h);let[x,A]=this.handPoseModel.execute(y);cS=ae(),J(y);let b=(await x.data())[0];if(J(x),b>=a.hand.minConfidence/4){let w=Q(A,[-1,3]),I=await w.array();J(A),J(w);let T=this.transformRawCoords(I,f,p,m),N=this.getBoxForHandLandmarks(T);this.storedBoxes[l]={...N,confidence:b};let M={landmarks:T,confidence:b,boxConfidence:u.confidence,fingerConfidence:b,box:{topLeft:N.startPoint,bottomRight:N.endPoint}};o.push(M)}else this.storedBoxes[l]=null;J(A)}else{let p=q0(X0(u),dS),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 hS={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]},Il,Sl,sx;function E3e(){let e=Il?new K0(Il):void 0;e&&Sl&&(sx=new Y0(e,Sl))}async function ix(e,t){sx||E3e();let a=await sx.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(hS))s[p]=hS[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=H0(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 mS(e){var t;return ne.initial&&(Il=null),Il?e.debug&&K("cached model:",Il.modelUrl):Il=await $e((t=e.hand.detector)==null?void 0:t.modelPath),Il}async function fS(e){var t;return ne.initial&&(Sl=null),Sl?e.debug&&K("cached model:",Sl.modelUrl):Sl=await $e((t=e.hand.skeleton)==null?void 0:t.modelPath),Sl}var Ot=[null,null],M3e=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],$s=[[0,0],[0,0]],$3e=["hand","fist","pinch","point","face","tip","pinchtip"],yS=4,xS=1.6,P3e=512,_3e=1.4,Z0=Number.MAX_SAFE_INTEGER,ox=0,Dr=[0,0],Dt={boxes:[],hands:[]},AS={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 bS(e){var t;if(ne.initial&&(Ot[0]=null),Ot[0])e.debug&&K("cached model:",Ot[0].modelUrl);else{b0(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),Ot[0]=await $e((t=e.hand.detector)==null?void 0:t.modelPath);let a=Ot[0].executor?Object.values(Ot[0].modelSignature.inputs):void 0;$s[0][0]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[1].size):0,$s[0][1]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[2].size):0}return Ot[0]}async function vS(e){var t;if(ne.initial&&(Ot[1]=null),Ot[1])e.debug&&K("cached model:",Ot[1].modelUrl);else{Ot[1]=await $e((t=e.hand.skeleton)==null?void 0:t.modelPath);let a=Ot[1].executor?Object.values(Ot[1].modelSignature.inputs):void 0;$s[1][0]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[1].size):0,$s[1][1]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[2].size):0}return Ot[1]}async function F3e(e,t){let a=[];if(!e||!Ot[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,P3e),i=Math.round(s*r/8)*8;n.resize=fe.resizeBilinear(e,[s,i]),n.cast=Ue(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await Ot[0].executeAsync(n.cast,M3e),n.boxes=Oe(n.rawBoxes,[0,2]),n.scores=Oe(n.rawScores,[0]);let o=Na(n.scores,1);J(o[yS]),o.splice(yS,1),n.filtered=ca(o,1),J(o),n.max=fa(n.filtered,1),n.argmax=sr(n.filtered,1);let l=0;n.nms=await fe.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=Fe(n.boxes,d,1),m=await h.data();J(h);let f=[m[1],m[0],m[3]-m[1],m[2]-m[0]],g=R0(f,_3e),y=[Math.trunc(f[0]*Dr[0]),Math.trunc(f[1]*Dr[1]),Math.trunc(f[2]*Dr[0]),Math.trunc(f[3]*Dr[1])],x=p[d],A=$3e[c[d]],b={id:l++,score:x,box:y,boxRaw:g,label:A};a.push(b)}return Object.keys(n).forEach(d=>J(n[d])),a.sort((d,h)=>h.score-d.score),a.length>(t.hand.maxDetected||1)&&(a.length=t.hand.maxDetected||1),a}async function lx(e,t,a){let n={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&Ot[1]&&a.hand.landmarks&&t.score>(a.hand.minConfidence||0)){let r={},s=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=fe.cropAndResize(e,[s],[0],[$s[1][0],$s[1][1]],"bilinear"),r.div=ve(r.crop,ze.tf255),[r.score,r.keypoints]=Ot[1].execute(r.div,["Identity_1","Identity"]);let i=(await r.score.data())[0],o=(100-Math.trunc(100/(1+Math.exp(i))))/100;if(o>=(a.hand.minConfidence||0)){n.fingerScore=o,r.reshaped=Q(r.keypoints,[-1,3]);let p=(await r.reshaped.array()).map(c=>[c[0]/$s[1][1],c[1]/$s[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=>[Dr[0]*(c[0]+t.boxRaw[0]),Dr[1]*(c[1]+t.boxRaw[1]),c[2]||0]),n.landmarks=H0(n.keypoints);for(let c of Object.keys(AS))n.annotations[c]=AS[c].map(d=>n.landmarks&&n.keypoints[d]?n.keypoints[d]:null)}Object.keys(r).forEach(l=>J(r[l]))}return n}async function ux(e,t){var r,s;if(!((r=Ot[0])!=null&&r.executor)||!((s=Ot[1])!=null&&s.executor)||!Ot[0].inputs[0].shape||!Ot[1].inputs[0].shape)return[];Dr=[e.shape[2]||0,e.shape[1]||0],Z0++;let a=(t.hand.skipTime||0)>ae()-ox,n=Z0<(t.hand.skipFrames||0);return t.skipAllowed&&a&&n?Dt.hands:new Promise(async i=>{let o=3*(t.hand.skipTime||0)>ae()-ox,l=Z0<3*(t.hand.skipFrames||0);t.skipAllowed&&Dt.hands.length===t.hand.maxDetected?Dt.hands=await Promise.all(Dt.boxes.map(p=>lx(e,p,t))):t.skipAllowed&&o&&l&&Dt.hands.length>0?Dt.hands=await Promise.all(Dt.boxes.map(p=>lx(e,p,t))):(Dt.boxes=await F3e(e,t),ox=ae(),Dt.hands=await Promise.all(Dt.boxes.map(p=>lx(e,p,t))),Z0=0);let u=[...Dt.boxes];if(Dt.boxes.length=0,t.cacheSensitivity>0)for(let p=0;p<Dt.hands.length;p++){let c=A9(Dt.hands[p].keypoints,Dr);if(c.box[2]/(e.shape[2]||1)>.05&&c.box[3]/(e.shape[1]||1)>.05&&Dt.hands[p].fingerScore&&Dt.hands[p].fingerScore>(t.hand.minConfidence||0)){let d=R0(c.box,xS),h=R0(c.boxRaw,xS);Dt.boxes.push({...u[p],box:d,boxRaw:h})}}for(let p=0;p<Dt.hands.length;p++){let c=ws(Dt.hands[p].keypoints,Dr);Dt.hands[p].box=c.box,Dt.hands[p].boxRaw=c.boxRaw}i(Dt.hands)})}var cr=(e=null)=>({face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,width:0,height:0,error:e});var cc={};xr(cc,{connected:()=>Q0,horizontal:()=>dx,kpt:()=>J0,relative:()=>cx,vertical:()=>px});var J0=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],dx=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],px=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],cx=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],Q0={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var Ae=cr(),hx=0;function kS(e,t){var i,o,l,u,p,c,d,h,m,f,g,y,x,A,b,w,I,T,N,M,$,E,S,_,O,W;let a=ae();if(!e)return cr();let n=Date.now()-e.timestamp,r=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(Ae.canvas=e.canvas),e.error&&(Ae.error=e.error),!Ae.body||e.body.length!==Ae.body.length)Ae.body=JSON.parse(JSON.stringify(e.body));else for(let P=0;P<e.body.length;P++){let U=e.body[P].box.map((Z,X)=>((r-1)*Ae.body[P].box[X]+Z)/r),G=e.body[P].boxRaw.map((Z,X)=>((r-1)*Ae.body[P].boxRaw[X]+Z)/r),q=e.body[P].keypoints.map((Z,X)=>{var re,ee,ge,ie,be,Ce,Re,Le,qe;return{score:Z.score,part:Z.part,position:[Ae.body[P].keypoints[X]?((r-1)*(Ae.body[P].keypoints[X].position[0]||0)+(Z.position[0]||0))/r:Z.position[0],Ae.body[P].keypoints[X]?((r-1)*(Ae.body[P].keypoints[X].position[1]||0)+(Z.position[1]||0))/r:Z.position[1],Ae.body[P].keypoints[X]?((r-1)*(Ae.body[P].keypoints[X].position[2]||0)+(Z.position[2]||0))/r:Z.position[2]],positionRaw:[Ae.body[P].keypoints[X]?((r-1)*(Ae.body[P].keypoints[X].positionRaw[0]||0)+(Z.positionRaw[0]||0))/r:Z.positionRaw[0],Ae.body[P].keypoints[X]?((r-1)*(Ae.body[P].keypoints[X].positionRaw[1]||0)+(Z.positionRaw[1]||0))/r:Z.positionRaw[1],Ae.body[P].keypoints[X]?((r-1)*(Ae.body[P].keypoints[X].positionRaw[2]||0)+(Z.positionRaw[2]||0))/r:Z.positionRaw[2]],distance:[Ae.body[P].keypoints[X]?((r-1)*(((re=Ae.body[P].keypoints[X].distance)==null?void 0:re[0])||0)+(((ee=Z.distance)==null?void 0:ee[0])||0))/r:(ge=Z.distance)==null?void 0:ge[0],Ae.body[P].keypoints[X]?((r-1)*(((ie=Ae.body[P].keypoints[X].distance)==null?void 0:ie[1])||0)+(((be=Z.distance)==null?void 0:be[1])||0))/r:(Ce=Z.distance)==null?void 0:Ce[1],Ae.body[P].keypoints[X]?((r-1)*(((Re=Ae.body[P].keypoints[X].distance)==null?void 0:Re[2])||0)+(((Le=Z.distance)==null?void 0:Le[2])||0))/r:(qe=Z.distance)==null?void 0:qe[2]]}}),H={},V={connected:{}};(i=t.body.modelPath)!=null&&i.includes("efficientpose")?V=$0:(o=t.body.modelPath)!=null&&o.includes("blazepose")?V=T0:(l=t.body.modelPath)!=null&&l.includes("movenet")&&(V=cc);for(let[Z,X]of Object.entries(V.connected)){let re=[];for(let ee=0;ee<X.length-1;ee++){let ge=q.find(be=>be.part===X[ee]),ie=q.find(be=>be.part===X[ee+1]);ge&&ie&&re.push([ge.position,ie.position])}H[Z]=re}Ae.body[P]={...e.body[P],box:U,boxRaw:G,keypoints:q,annotations:H}}if(!Ae.hand||e.hand.length!==Ae.hand.length)Ae.hand=JSON.parse(JSON.stringify(e.hand));else for(let P=0;P<e.hand.length;P++){let U=e.hand[P].box.map((V,Z)=>((r-1)*Ae.hand[P].box[Z]+V)/r),G=e.hand[P].boxRaw.map((V,Z)=>((r-1)*Ae.hand[P].boxRaw[Z]+V)/r);Ae.hand[P].keypoints.length!==e.hand[P].keypoints.length&&(Ae.hand[P].keypoints=e.hand[P].keypoints);let q=e.hand[P].keypoints&&e.hand[P].keypoints.length>0?e.hand[P].keypoints.map((V,Z)=>V.map((X,re)=>((r-1)*(Ae.hand[P].keypoints[Z][re]||1)+(X||0))/r)):[],H={};if(Object.keys(Ae.hand[P].annotations).length!==Object.keys(e.hand[P].annotations).length)Ae.hand[P].annotations=e.hand[P].annotations,H=Ae.hand[P].annotations;else if(e.hand[P].annotations)for(let V of Object.keys(e.hand[P].annotations))H[V]=(c=(p=(u=e.hand[P])==null?void 0:u.annotations)==null?void 0:p[V])!=null&&c[0]?e.hand[P].annotations[V].map((Z,X)=>Z.map((re,ee)=>((r-1)*Ae.hand[P].annotations[V][X][ee]+re)/r)):null;Ae.hand[P]={...e.hand[P],box:U,boxRaw:G,keypoints:q,annotations:H}}if(!Ae.face||e.face.length!==Ae.face.length)Ae.face=JSON.parse(JSON.stringify(e.face));else for(let P=0;P<e.face.length;P++){let U=e.face[P].box.map((H,V)=>((r-1)*Ae.face[P].box[V]+H)/r),G=e.face[P].boxRaw.map((H,V)=>((r-1)*Ae.face[P].boxRaw[V]+H)/r),q=e.face[P].annotations;if(Object.keys(Ae.face[P].annotations).length!==Object.keys(e.face[P].annotations).length)Ae.face[P].annotations=e.face[P].annotations,q=Ae.face[P].annotations;else if(e.face[P].annotations)for(let H of Object.keys(e.face[P].annotations))q[H]=(m=(h=(d=e.face[P])==null?void 0:d.annotations)==null?void 0:h[H])!=null&&m[0]?e.face[P].annotations[H].map((V,Z)=>V.map((X,re)=>((r-1)*Ae.face[P].annotations[H][Z][re]+X)/r)):null;if(e.face[P].rotation){let H={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};H.matrix=(f=e.face[P].rotation)==null?void 0:f.matrix,H.angle={roll:((r-1)*(((y=(g=Ae.face[P].rotation)==null?void 0:g.angle)==null?void 0:y.roll)||0)+(((A=(x=e.face[P].rotation)==null?void 0:x.angle)==null?void 0:A.roll)||0))/r,yaw:((r-1)*(((w=(b=Ae.face[P].rotation)==null?void 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a={};a.resize=fe.resizeBilinear(e,[Aa.inputs[0].shape?Aa.inputs[0].shape[1]:0,Aa.inputs[0].shape?Aa.inputs[0].shape[2]:0],!1),a.norm=ve(a.resize,ze.tf255),a.res=Aa.execute(a.norm),a.squeeze=Oe(a.res,[0]),[a.bgRaw,a.fgRaw]=Na(a.squeeze,2),a.fg=Uh(a.fgRaw),a.mul=te(a.fg,ze.tf255),a.expand=Wt(a.mul,2),a.output=fe.resizeBilinear(a.expand,[e.shape[1]||0,e.shape[2]||0]);let n;switch(t.segmentation.mode||"default"){case"default":a.input=Oe(e),a.concat=lt([a.input,a.output],-1),n=Ue(a.concat,"int32");break;case"alpha":n=Ue(a.output,"int32");break;default:n=Ve(0)}return Object.keys(a).forEach(s=>J(a[s])),n}var em={};xr(em,{distance:()=>fx,find:()=>z3e,similarity:()=>O3e});function fx(e,t,a={order:2,multiplier:25}){if(!e||!e)return Number.MAX_SAFE_INTEGER;let n=0;for(let s=0;s<e.length;s++){let i=!a.order||a.order===2?e[s]-t[s]:Math.abs(e[s]-t[s]);n+=!a.order||a.order===2?i*i:i**a.order}return Math.round(100*(a.multiplier||20)*n)/100}var CS=(e,t,a,n)=>{if(e===0)return 1;let s=(1-(t===2?Math.sqrt(e):e**(1/t))/100-a)/(n-a);return Math.round(100*Math.max(Math.min(s,1),0))/100};function O3e(e,t,a={order:2,multiplier:25,min:.2,max:.8}){let n=fx(e,t,a);return CS(n,a.order||2,a.min||0,a.max||1)}function z3e(e,t,a={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let n=Number.MAX_SAFE_INTEGER,r=-1;for(let i=0;i<t.length;i++){let o=t[i].length===e.length?fx(e,t[i],a):Number.MAX_SAFE_INTEGER;if(o<n&&(n=o,r=i),n<(a.threshold||0))break}let s=CS(n,a.order||2,a.min||0,a.max||1);return{index:r,distance:n,similarity:s}}var Ex={};xr(Ex,{Models:()=>fc,validateModel:()=>om});var TS=.005,on={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function gx(e){for(let t of dx){let a=e.keypoints.findIndex(r=>r.part===t[0]),n=e.keypoints.findIndex(r=>r.part===t[1]);if(e.keypoints[a]&&e.keypoints[n]&&e.keypoints[a].position[0]<e.keypoints[n].position[0]){let r=e.keypoints[a];e.keypoints[a]=e.keypoints[n],e.keypoints[n]=r}}for(let t of px){let a=e.keypoints.findIndex(r=>r&&r.part===t[0]),n=e.keypoints.findIndex(r=>r&&r.part===t[1]);e.keypoints[a]&&e.keypoints[n]&&e.keypoints[a].position[1]<e.keypoints[n].position[1]&&e.keypoints.splice(a,1)}for(let[t,a]of cx){let n=e.keypoints.findIndex(u=>u&&u.part===t[0]),r=e.keypoints.findIndex(u=>u&&u.part===t[1]),s=e.keypoints.findIndex(u=>u&&u.part===a[0]),i=e.keypoints.findIndex(u=>u&&u.part===a[1]);if(!e.keypoints[s]||!e.keypoints[i])continue;let o=e.keypoints[n]?[Math.abs(e.keypoints[s].position[0]-e.keypoints[n].position[0]),Math.abs(e.keypoints[i].position[0]-e.keypoints[n].position[0])]:[0,0],l=e.keypoints[r]?[Math.abs(e.keypoints[i].position[0]-e.keypoints[r].position[0]),Math.abs(e.keypoints[s].position[0]-e.keypoints[r].position[0])]:[0,0];if(o[0]>o[1]||l[0]>l[1]){let u=e.keypoints[n];e.keypoints[n]=e.keypoints[r],e.keypoints[r]=u}}}function NS(e){for(let t=0;t<e.length;t++)if(e[t]&&on.keypoints[t]){let a=[Math.abs(e[t].positionRaw[0]-on.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-on.keypoints[t].positionRaw[1])];a[0]<TS&&a[1]<TS?e[t]=on.keypoints[t]:on.keypoints[t]=e[t]}else on.keypoints[t]=e[t];return e}function RS(e,t){var r,s;let a={};if(!((r=e==null?void 0:e.shape)!=null&&r[1])||!((s=e==null?void 0:e.shape)!=null&&s[2]))return 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gx(u),i.push(u),i}function B3e(e,t,a){let n=[];for(let r=0;r<e[0].length;r++){let s=e[0][r],i=Math.round(100*s[55])/100;if(i>t.body.minConfidence){let o=[];for(let d=0;d<17;d++){let h=s[3*d+2];if(h>t.body.minConfidence){let m=[s[3*d+1],s[3*d+0]];o.push({part:J0[d],score:Math.round(100*h)/100,positionRaw:m,position:[Math.round((a.shape[2]||0)*m[0]),Math.round((a.shape[1]||0)*m[1])]})}}let l=[s[52],s[51],s[54]-s[52],s[53]-s[51]],u=[Math.trunc(l[0]*(a.shape[2]||0)),Math.trunc(l[1]*(a.shape[1]||0)),Math.trunc(l[2]*(a.shape[2]||0)),Math.trunc(l[3]*(a.shape[1]||0))],p={};for(let[d,h]of Object.entries(Q0)){let m=[];for(let f=0;f<h.length-1;f++){let g=o.find(x=>x.part===h[f]),y=o.find(x=>x.part===h[f+1]);g&&y&&g.score>(t.body.minConfidence||0)&&y.score>(t.body.minConfidence||0)&&m.push([g.position,y.position])}p[d]=m}let c={id:r,score:i,box:u,boxRaw:l,keypoints:[...o],annotations:p};gx(c),n.push(c)}}return n.sort((r,s)=>s.score-r.score),n.length>t.body.maxDetected&&(n.length=t.body.maxDetected),n}async function xx(e,t){var r;if(!(jt!=null&&jt.executor)||!((r=jt==null?void 0:jt.inputs)!=null&&r[0].shape))return[];t.skipAllowed||(Cl.boxes.length=0),yx++;let a=(t.body.skipTime||0)>ae()-Cl.last,n=yx<(t.body.skipFrames||0);return t.skipAllowed&&a&&n?Cl.bodies:new Promise(async s=>{let i={};yx=0,i.input=RS(e,tm),i.res=jt==null?void 0:jt.execute(i.input),Cl.last=ae();let o=await i.res.array();Cl.bodies=i.res.shape[2]===17?W3e(o,t,e):B3e(o,t,e);for(let l of Cl.bodies)ES(l,[e.shape[2]||1,e.shape[1]||1]),NS(l.keypoints);Object.keys(i).forEach(l=>J(i[l])),s(Cl.bodies)})}var Fn,am=[],PS=0,Ax=Number.MAX_SAFE_INTEGER,rm=0,nm=2.5;async function _S(e){if(!Fn||ne.initial){Fn=await $e(e.object.modelPath);let t=Fn!=null&&Fn.executor?Object.values(Fn.modelSignature.inputs):void 0;rm=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):416}else e.debug&&K("cached model:",Fn.modelUrl);return Fn}async function V3e(e,t,a){var u,p;let n=0,r=[],s=rm;for(let c of[1,2,4]){let d=c*13,h=Oe(e.find(A=>A.shape[1]===d**2&&(A.shape[2]||0)===rd.length)),m=await h.array(),f=Oe(e.find(A=>A.shape[1]===d**2&&(A.shape[2]||0)<rd.length)),g=Q(f,[-1,4,(((u=f.shape)==null?void 0:u[1])||0)/4]),y=sr(g,2),x=await y.array();for(let A=0;A<h.shape[0];A++)for(let b=0;b<(((p=h.shape)==null?void 0:p[1])||0);b++){let w=m[A][b];if(w>(a.object.minConfidence||0)&&b!==61){let I=(.5+Math.trunc(A%d))/d,T=(.5+Math.trunc(A/d))/d,N=x[A].map(P=>P*(d/c/s)),[M,$]=[I-nm/c*N[0],T-nm/c*N[1]],[E,S]=[I+nm/c*N[2]-M,T+nm/c*N[3]-$],_=[M,$,E,S];_=_.map(P=>Math.max(0,Math.min(P,1)));let O=[_[0]*t[0],_[1]*t[1],_[2]*t[0],_[3]*t[1]],W={id:n++,score:Math.round(100*w)/100,class:b+1,label:rd[b].label,box:O.map(P=>Math.trunc(P)),boxRaw:_};r.push(W)}}J([h,f,g,y])}let i=r.map(c=>[c.boxRaw[1],c.boxRaw[0],c.boxRaw[3],c.boxRaw[2]]),o=r.map(c=>c.score),l=[];if(i&&i.length>0){let c=await 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mc=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],U3e=mc.length,hc=mc.reduce((e,t,a)=>(e[t]=a,e),{}),G3e=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],B6e=G3e.map(([e,t])=>[hc[e],hc[t]]),DS=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function 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2Q==`;async function nye(e){let t=(r,s="application/octet-stream")=>fetch(`data:${s};base64,${r}`).then(i=>i.blob()),a,n;switch(e.config.warmup){case"face":a=await t(lm);break;case"body":case"full":a=await t(um);break;default:a=null}if(a){let r=await createImageBitmap(a);n=await e.detect(r,e.config),r.close()}return n}async function rye(e){return new Promise(t=>{let a;switch(e.config.warmup){case"face":a="data:image/jpeg;base64,"+lm;break;case"full":case"body":a="data:image/jpeg;base64,"+um;break;default:a=""}let n;if(typeof Image!="undefined")n=new Image;else if(ne.Image)n=new ne.Image;else{t(void 0);return}n.onload=async()=>{let r=$n(n.naturalWidth,n.naturalHeight);if(!r)K("Warmup: Canvas not found"),t(void 0);else{let s=r.getContext("2d");s&&s.drawImage(n,0,0);let i=await e.image(r,!0),o=i.tensor?await e.detect(i.tensor,e.config):void 0;t(o)}},a?n.src=a:t(void 0)})}async function sye(e){let t=r=>Buffer.from(r,"base64"),a;e.config.warmup==="face"?a=t(lm):a=t(um);let n;if("node"in Ke&&Qt()==="tensorflow"){let r=Q3.decodeJpeg(a),s=Wt(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 iye(e){let t;return typeof createImageBitmap=="function"?t=await nye(e):typeof Image!="undefined"||ne.Canvas!==void 0?t=await rye(e):t=await sye(e),t}async function oye(e){var o,l,u,p;if(!B().flagRegistry.ENGINE_COMPILE_ONLY)return;let t=Qt(),a=Vn();if(t!=="webgl"&&t!=="humangl"||!(a!=null&&a.checkCompileCompletion))return;B().set("ENGINE_COMPILE_ONLY",!0);let n=It().state.numTensors,r=[];for(let[c,d]of Object.entries(e.models.models)){if(!d)continue;let h=d!=null&&d.modelSignature&&((l=(o=d==null?void 0:d.inputs)==null?void 0:o[0])!=null&&l.shape)?[...d.inputs[0].shape]:[1,64,64,3],m=d!=null&&d.modelSignature&&((p=(u=d==null?void 0:d.inputs)==null?void 0:u[0])!=null&&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 f=yn(h,m);try{let g=d.execute(f);r.push(c),Array.isArray(g)?g.forEach(y=>J(y)):J(g)}catch(g){e.config.debug&&K("compile fail model:",c)}J(f)}let s=await a.checkCompileCompletionAsync();a.getUniformLocations(),e.config.debug&&K("compile pass:",{models:r,kernels:s.length}),B().set("ENGINE_COMPILE_ONLY",!1);let i=It().state.numTensors;i-n>0&&K("tensor leak:",i-n)}async function ZS(e,t){await oc(e,!1);let a=ae();return e.state="warmup",t&&(e.config=Et(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?cr():new Promise(async n=>{await e.models.load(),await tl(),await oye(e);let r=await iye(e),s=ae();e.config.debug&&K("warmup",e.config.warmup,Math.round(s-a),"ms"),e.emit("warmup"),n(r)})}var md,gc,yc,dm,Ps,Mx=class{constructor(t){he(this,"version");he(this,"config");he(this,"result");he(this,"state");he(this,"process");he(this,"tf");he(this,"env",ne);he(this,"draw",C0);he(this,"match",em);he(this,"models");he(this,"events");he(this,"faceTriangulation");he(this,"faceUVMap");he(this,"performance");Xn(this,md);Xn(this,gc);Xn(this,yc);he(this,"analyze",(...t)=>{if(!qa(this,gc))return;let a=this.tf.engine().state.numTensors,n=qa(this,md);Ar(this,md,a);let r=a-n;r!==0&&K(...t,r)});Xn(this,dm,t=>{if(!qa(this,yc))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof yt))return"input must be a tensor";try{this.tf.getBackend()}catch(a){return"backend not loaded"}return null});he(this,"webcam",new A0);he(this,"emit",t=>{var a;(a=this.events)!=null&&a.dispatchEvent&&this.events.dispatchEvent(new Event(t))});Xn(this,Ps,{});let a=(ac.tfjs||i3).replace(/-(.*)/,"");pl.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${a}/dist/`,pl.modelBasePath=ne.browser?"../models/":"file://models/",this.version=sy,Object.defineProperty(this,"version",{value:sy}),this.config=JSON.parse(JSON.stringify(pl)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=Et(this.config,t)),l9(this.config),this.tf=Ke,this.state="idle",Ar(this,md,0),Ar(this,gc,!1),Ar(this,yc,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new fc(this),cy(),this.result=cr(),this.process={tensor:null,canvas:null},this.faceTriangulation=tI,this.faceUVMap=aI,om(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(pl)),this.config.backend=t,ny(),ne.initial=!0}validate(t){let a=ey(pl,t||this.config);return a.length===0&&(this.config=Et(this.config,t)),a}now(){return ae()}image(t,a=!1){return y0(t,this.config,a)}async segmentation(t,a){var s,i,o;if(a&&(this.config=Et(this.config,a)),!this.config.segmentation.enabled)return null;let n=await y0(t,this.config);if(!n.tensor)return null;let r=null;return(s=this.config.segmentation.modelPath)!=null&&s.includes("rvm")&&(r=await jS(n.tensor,this.config)),(i=this.config.segmentation.modelPath)!=null&&i.includes("meet")&&(r=await IS(n.tensor,this.config)),(o=this.config.segmentation.modelPath)!=null&&o.includes("selfie")&&(r=await XS(n.tensor,this.config)),J(n.tensor),r}compare(t,a){return o9(this.config,t,a)}async init(){await oc(this,!0),await this.tf.ready(),ny()}async load(t){this.state="load";let a=ae(),n=Object.values(this.models.models).filter(i=>i).length;t&&(this.config=Et(this.config,t)),this.env.initial&&(await oc(this,!1)||K("error: backend check failed"),await tl(),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(ae()-a);s>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+s:s)}next(t=this.result){return kS(t,this.config)}async warmup(t){let a=ae(),n=await ZS(this,t),r=ae();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,y,x,A,b,w,I,T,N,M,$,E,S,_,O,W,P,U,G,q,H;this.state="config";let r;this.config=Et(this.config,a),this.state="check";let s=qa(this,dm).call(this,t);s&&(K(s,t),this.emit("error"),n(cr(s)));let i=ae();await this.load(),r=ae(),this.state="image";let o=await y0(t,this.config);if(this.process=o,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(ae()-r):Math.trunc(ae()-r),this.analyze("Get Image:"),!o.tensor){this.config.debug&&K("could not convert input to tensor"),this.emit("error"),n(cr("could not convert input to tensor"));return}this.emit("image"),r=ae(),this.config.skipAllowed=await i9(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(ae()-r):Math.trunc(ae()-r),this.analyze("Check Changed:");let l=[],u=[],p=[],c=[];this.state="detect:face",this.config.async?(l=this.config.face.enabled?ex(this,o.tensor):[],this.performance.face&&delete this.performance.face):(r=ae(),l=this.config.face.enabled?await ex(this,o.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(ae()-r):Math.trunc(ae()-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?Et(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?Sx(o.tensor,d):[]:(y=this.config.body.modelPath)!=null&&y.includes("blazepose")?u=this.config.body.enabled?yy(o.tensor,d):[]:(x=this.config.body.modelPath)!=null&&x.includes("efficientpose")?u=this.config.body.enabled?Iy(o.tensor,d):[]:(A=this.config.body.modelPath)!=null&&A.includes("movenet")&&(u=this.config.body.enabled?xx(o.tensor,d):[]),this.performance.body&&delete this.performance.body):(r=ae(),(b=this.config.body.modelPath)!=null&&b.includes("posenet")?u=this.config.body.enabled?await Sx(o.tensor,d):[]:(w=this.config.body.modelPath)!=null&&w.includes("blazepose")?u=this.config.body.enabled?await yy(o.tensor,d):[]:(I=this.config.body.modelPath)!=null&&I.includes("efficientpose")?u=this.config.body.enabled?await Iy(o.tensor,d):[]:(T=this.config.body.modelPath)!=null&&T.includes("movenet")&&(u=this.config.body.enabled?await xx(o.tensor,d):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let h=this.config.hand.maxDetected===-1?Et(this.config,{hand:{maxDetected:this.config.face.enabled?2*l.length:1}}):this.config;this.config.async?((M=(N=this.config.hand.detector)==null?void 0:N.modelPath)!=null&&M.includes("handdetect")?p=this.config.hand.enabled?ix(o.tensor,h):[]:(E=($=this.config.hand.detector)==null?void 0:$.modelPath)!=null&&E.includes("handtrack")&&(p=this.config.hand.enabled?ux(o.tensor,h):[]),this.performance.hand&&delete this.performance.hand):(r=ae(),(_=(S=this.config.hand.detector)==null?void 0:S.modelPath)!=null&&_.includes("handdetect")?p=this.config.hand.enabled?await ix(o.tensor,h):[]:(W=(O=this.config.hand.detector)==null?void 0:O.modelPath)!=null&&W.includes("handtrack")&&(p=this.config.hand.enabled?await ux(o.tensor,h):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((P=this.config.object.modelPath)!=null&&P.includes("nanodet")?c=this.config.object.enabled?bx(o.tensor,this.config):[]:(U=this.config.object.modelPath)!=null&&U.includes("centernet")&&(c=this.config.object.enabled?by(o.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=ae(),(G=this.config.object.modelPath)!=null&&G.includes("nanodet")?c=this.config.object.enabled?await bx(o.tensor,this.config):[]:(q=this.config.object.modelPath)!=null&&q.includes("centernet")&&(c=this.config.object.enabled?await by(o.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([l,u,p,c]=await Promise.all([l,u,p,c])),this.state="detect:gesture";let m=[];this.config.gesture.enabled&&(r=ae(),m=[...QI(l),...JI(u),...tS(p),...eS(l)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(ae()-i):Math.trunc(ae()-i);let f=((H=this.process.tensor)==null?void 0:H.shape)||[0,0,0,0];this.result={face:l,body:u,hand:p,gesture:m,object:c,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,width:f[2],height:f[1],get persons(){return YS(l,u,p,m,f)}},J(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?(qa(this,Ps)[t.id]||(this.config.debug&&K("video start",t.id),qa(this,Ps)[t.id]=!0),!t.paused&&qa(this,Ps)[t.id]&&t.readyState>=2&&await this.detect(t),n>0&&await this.sleep(n),qa(this,Ps)[t.id]&&requestAnimationFrame(()=>this.video(t,a,n))):(this.config.debug&&K("video stop",t.id),qa(this,Ps)[t.id]=!1)}};md=new WeakMap,gc=new WeakMap,yc=new WeakMap,dm=new WeakMap,Ps=new WeakMap;return DC(uye);})();
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